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Archive for the ‘Translational Effectiveness’ Category


The Fred Conrad Koch Lifetime Achievement Award—the Society’s highest honor—recognizes the lifetime achievements and exceptional contributions of an individual to the field of endocrinology

Curator: Larry H. Bernstein, MD, FCAP

 

Series E. 2; 7.3

 

lifetime achievements and exceptional contributions of an individual to the field of endocrinology

  • 2015

Andrzej Bartke, MS, PhD

Southern Illinois University School of Medicine

  • 2014

George P. Chrousos, MD

Athens University Medical School, Aghia Sophia Children’s Hospital

  • 2013

Michael O. Thorner, MBBS, DSc

University of Virginia

  • 2012

Samuel Refetoff, MD

University of Chicago

  • 2011

Pierre Chambon, MD

Institut de Génétique et de Biologie Moléculaire et Cellulaire

  • 2010

Kathryn B. Horwitz, PhD

University of Colorado at Denver – Anschutz Medical Campus

  • 2009
  1. Larry Jameson, MD, PhD

Northwestern University Medical School

  • 2008
  1. Reed Larsen, MD, FACP, FRCP

Harvard Medical School, Brigham and Women’s Hospital

  • 2007

John D. Baxter, MD

University of California – San Francisco

  • 2006

Gerald M. Reaven, MD

Joslin Diabetes Center, Boston

  • 2005

William F. Crowley, Jr., MD

Massachusetts General Hospital

  • 2004

Patricia K. Donahoe, MD

Massachusetts General Hospital – Harvard Medical School

  • 2003

Maria I. New, MD

New York Presbyterian Hospital, Cornell Medical School

 

 

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Treatments for Lymphomas and Leukemias

Curator and Editor: Larry H. Bernstein, MD, FCAP

 

2.4.4 Treatments for leukemia by type

2.4.4.1 Acute Lymphocytic Leukemias

Treatment of Acute Lymphoblastic Leukemia

Ching-Hon Pu, and William E. Evans
N Engl J Med Jan 12, 2006; 354:166-178
http://dx.doi.org:/10.1056/NEJMra052603

Although the overall cure rate of acute lymphoblastic leukemia (ALL) in children is about 80 percent, affected adults fare less well. This review considers recent advances in the treatment of ALL, emphasizing issues that need to be addressed if treatment outcome is to improve further.

Acute Lymphoblastic Leukemia

Ching-Hon Pui, Mary V. Relling, and James R. Downing
N Engl J Med Apr 8, 2004; 350:1535-1548
http://dx.doi.org:/10.1056/NEJMra023001

This comprehensive survey emphasizes how recent advances in the knowledge of molecular mechanisms involved in acute lymphoblastic leukemia have influenced diagnosis, prognosis, and treatment.

Gene-Expression Patterns in Drug-Resistant Acute Lymphoblastic Leukemia Cells and Response to Treatment

Amy Holleman, Meyling H. Cheok, Monique L. den Boer, et al.
N Engl J Med 2004; 351:533-42

Childhood acute lymphoblastic leukemia (ALL) is curable with chemotherapy in approximately 80 percent of patients. However, the cause of treatment failure in the remaining 20 percent of patients is largely unknown.

Methods We tested leukemia cells from 173 children for sensitivity in vitro to prednisolone, vincristine, asparaginase, and daunorubicin. The cells were then subjected to an assessment of gene expression with the use of 14,500 probe sets to identify differentially expressed genes in drug-sensitive and drug-resistant ALL. Gene-expression patterns that differed according to sensitivity or resistance to the four drugs were compared with treatment outcome in the original 173 patients and an independent cohort of 98 children treated with the same drugs at another institution.

Results We identified sets of differentially expressed genes in B-lineage ALL that were sensitive or resistant to prednisolone (33 genes), vincristine (40 genes), asparaginase (35 genes), or daunorubicin (20 genes). A combined gene-expression score of resistance to the four drugs, as compared with sensitivity to the four, was significantly and independently related to treatment outcome in a multivariate analysis (hazard ratio for relapse, 3.0; P=0.027). Results were confirmed in an independent population of patients treated with the same medications (hazard ratio for relapse, 11.85; P=0.019). Of the 124 genes identified, 121 have not previously been associated with resistance to the four drugs we tested.

Conclusions  Differential expression of a relatively small number of genes is associated with drug resistance and treatment outcome in childhood ALL.

Leukemias Treatment & Management

Author: Lihteh Wu, MD; Chief Editor: Hampton Roy Sr
http://emedicine.medscape.com/article/1201870-treatment

The treatment of leukemia is in constant flux, evolving and changing rapidly over the past few years. Most treatment protocols use systemic chemotherapy with or without radiotherapy. The basic strategy is to eliminate all detectable disease by using cytotoxic agents. To attain this goal, 3 phases are typically used, as follows: remission induction phase, consolidation phase, and maintenance therapy phase.

Chemotherapeutic agents are chosen that interfere with cell division. Tumor cells usually divide more rapidly than host cells, making them more vulnerable to the effects of chemotherapy. Primary treatment will be under the direction of a medical oncologist, radiation oncologist, and primary care physician. Although a general treatment plan will be outlined, the ophthalmologist does not prescribe or manage such treatment.

  • The initial treatment of ALL uses various combinations of vincristine, prednisone, and L-asparaginase until a complete remission is obtained.
  • Maintenance therapy with mercaptopurine is continued for 2-3 years following remission.
  • Use of intrathecal methotrexate with or without cranial irradiation to cover the CNS varies from facility to facility.
  • Daunorubicin, cytarabine, and thioguanine currently are used to obtain induction and remission of AML.
  • Maintenance therapy for 8 months may lengthen remission. Once relapse has occurred, AML generally is curable only by bone marrow transplantation.
  • Presently, treatment of CLL is palliative.
  • CML is characterized by a leukocytosis greater than 100,000 cells. Emergent treatment with leukopheresis sometimes is necessary when leukostastic complications are present. Otherwise, busulfan or hydroxyurea may control WBC counts. During the chronic phase, treatment is palliative.
  • When CML converts to the blastic phase, approximately one third of cases behave as ALL and respond to treatment with vincristine and prednisone. The remaining two thirds resemble AML but respond poorly to AML therapy.
  • Allogeneic bone marrow transplant is the only curative therapy for CML. However, it carries a high early mortality rate.
  • Leukemic retinopathy usually is not treated directly. As the hematological parameters normalize with systemic treatment, many of the ophthalmic signs resolve. There are reports that leukopheresis for hyperviscosity also may alleviate intraocular manifestations.
  • When definite intraocular leukemic infiltrates fail to respond to systemic chemotherapy, direct radiation therapy is recommended.
  • Relapse, manifested by anterior segment involvement, should be treated by radiation. In certain cases, subconjunctival chemotherapeutic agents have been injected.
  • Optic nerve head infiltration in patients with ALL is an emergency and requires prompt radiation therapy to try to salvage some vision.

Treatments and drugs

http://www.mayoclinic.org/diseases-conditions/leukemia/basics/
treatment/con-20024914

Common treatments used to fight leukemia include:

  • Chemotherapy. Chemotherapy is the major form of treatment for leukemia. This drug treatment uses chemicals to kill leukemia cells.

Depending on the type of leukemia you have, you may receive a single drug or a combination of drugs. These drugs may come in a pill form, or they may be injected directly into a vein.

  • Biological therapy. Biological therapy works by using treatments that help your immune system recognize and attack leukemia cells.
  • Targeted therapy. Targeted therapy uses drugs that attack specific vulnerabilities within your cancer cells.

For example, the drug imatinib (Gleevec) stops the action of a protein within the leukemia cells of people with chronic myelogenous leukemia. This can help control the disease.

  • Radiation therapy. Radiation therapy uses X-rays or other high-energy beams to damage leukemia cells and stop their growth. During radiation therapy, you lie on a table while a large machine moves around you, directing the radiation to precise points on your body.

You may receive radiation in one specific area of your body where there is a collection of leukemia cells, or you may receive radiation over your whole body. Radiation therapy may be used to prepare for a stem cell transplant.

  • Stem cell transplant. A stem cell transplant is a procedure to replace your diseased bone marrow with healthy bone marrow.

Before a stem cell transplant, you receive high doses of chemotherapy or radiation therapy to destroy your diseased bone marrow. Then you receive an infusion of blood-forming stem cells that help to rebuild your bone marrow.

You may receive stem cells from a donor, or in some cases you may be able to use your own stem cells. A stem cell transplant is very similar to a bone marrow transplant.

2.4.4.2 Acute Myeloid Leukemia

New treatment approaches in acute myeloid leukemia: review of recent clinical studies.

Norsworthy K1Luznik LGojo I.
Rev Recent Clin Trials. 2012 Aug; 7(3):224-37.
http://www.ncbi.nlm.nih.gov/pubmed/22540908

Standard chemotherapy can cure only a fraction (30-40%) of younger and very few older patients with acute myeloid leukemia (AML). While conventional allografting can extend the cure rates, its application remains limited mostly to younger patients and those in remission. Limited efficacy of current therapies and improved understanding of the disease biology provided a spur for clinical trials examining novel agents and therapeutic strategies in AML. Clinical studies with novel chemotherapeutics, antibodies, different signal transduction inhibitors, and epigenetic modulators demonstrated their clinical activity; however, it remains unclear how to successfully integrate novel agents either alone or in combination with chemotherapy into the overall therapeutic schema for AML. Further studies are needed to examine their role in relation to standard chemotherapy and their applicability to select patient populations based on recognition of unique disease and patient characteristics, including the development of predictive biomarkers of response. With increasing use of nonmyeloablative or reduced intensity conditioning and alternative graft sources such as haploidentical donors and cord blood transplants, the benefits of allografting may extend to a broader patient population, including older AML patients and those lacking a HLA-matched donor. We will review here recent clinical studies that examined novel pharmacologic and immunologic approaches to AML therapy.

Novel approaches to the treatment of acute myeloid leukemia.

Roboz GJ1
Hematology Am Soc Hematol Educ Program. 2011:43-50.
http://dx.doi.org:/10.1182/asheducation-2011.1.43.

Approximately 12 000 adults are diagnosed with acute myeloid leukemia (AML) in the United States annually, the majority of whom die from their disease. The mainstay of initial treatment, cytosine arabinoside (ara-C) combined with an anthracycline, was developed nearly 40 years ago and remains the worldwide standard of care. Advances in genomics technologies have identified AML as a genetically heterogeneous disease, and many patients can now be categorized into clinicopathologic subgroups on the basis of their underlying molecular genetic defects. It is hoped that enhanced specificity of diagnostic classification will result in more effective application of targeted agents and the ability to create individualized treatment strategies. This review describes the current treatment standards for induction, consolidation, and stem cell transplantation; special considerations in the management of older AML patients; novel agents; emerging data on the detection and management of minimal residual disease (MRD); and strategies to improve the design and implementation of AML clinical trials.

Age ≥ 60 years has consistently been identified as an independent adverse prognostic factor in AML, and there are very few long-term survivors in this age group.5 Poor outcomes in elderly AML patients have been attributed to both host- and disease-related factors, including medical comorbidities, physical frailty, increased incidence of antecedent myelodysplastic syndrome and myeloproliferative disorders, and higher frequency of adverse cytogenetics.28 Older patients with multiple poor-risk factors have a high probability of early death and little chance of long-term disease-free survival with standard chemotherapy. In a retrospective analysis of 998 older patients treated with intensive induction at the M.D. Anderson Cancer Center, multivariate analysis identified age ≥ 75 years, unfavorable karyotype, poor performance status, creatinine > 1.3 mg/dL, duration of antecedent hematologic disorder > 6 months, and treatment outside a laminar airflow room as adverse prognostic indicators.29 Patients with 3 or more of these factors had expected complete remission rates of < 20%, 8-week mortality > 50%, and 1-year survival < 10%. The Medical Research Council (MRC) identified cytogenetics, WBC count at diagnosis, age, and de novo versus secondary disease as critical factors influencing survival in > 2000 older patients with AML, but cautioned in their conclusions that less objective factors, such as clinical assessment of “fitness” for chemotherapy, may be equally important in making treatment decisions in this patient population.30 It is hoped that data from comprehensive geriatric assessments of functional status, cognition, mood, quality of life, and other measures obtained during ongoing cooperative group trials will improve our ability to predict how older patients will tolerate treatment.

Current treatment of acute myeloid leukemia.

Roboz GJ1.
Curr Opin Oncol. 2012 Nov; 24(6):711-9.
http://dx.doi.org:/10.1097/CCO.0b013e328358f62d.

The objectives of this review are to discuss standard and investigational nontransplant treatment strategies for acute myeloid leukemia (AML), excluding acute promyelocytic leukemia.

RECENT FINDINGS: Most adults with AML die from their disease. The standard treatment paradigm for AML is remission induction chemotherapy with an anthracycline/cytarabine combination, followed by either consolidation chemotherapy or allogeneic stem cell transplantation, depending on the patient’s ability to tolerate intensive treatment and the likelihood of cure with chemotherapy alone. Although this approach has changed little in the last three decades, increased understanding of the pathogenesis of AML and improvements in molecular genomic technologies are leading to novel drug targets and the development of personalized, risk-adapted treatment strategies. Recent findings related to prognostically relevant and potentially ‘druggable’ molecular targets are reviewed.

SUMMARY: At the present time, AML remains a devastating and mostly incurable disease, but the combination of optimized chemotherapeutics and molecularly targeted agents holds significant promise for the future.

Adult Acute Myeloid Leukemia Treatment (PDQ®)
http://www.cancer.gov/cancertopics/pdq/treatment/adultAML/healthprofessional/page9

About This PDQ Summary

This summary is reviewed regularly and updated as necessary by the PDQ Adult Treatment Editorial Board, which is editorially independent of the National Cancer Institute (NCI). The summary reflects an independent review of the literature and does not represent a policy statement of NCI or the National Institutes of Health (NIH).

Board members review recently published articles each month to determine whether an article should:

  • be discussed at a meeting,
  • be cited with text, or
  • replace or update an existing article that is already cited.

Treatment Option Overview for AML

Successful treatment of acute myeloid leukemia (AML) requires the control of bone marrow and systemic disease and specific treatment of central nervous system (CNS) disease, if present. The cornerstone of this strategy includes systemically administered combination chemotherapy. Because only 5% of patients with AML develop CNS disease, prophylactic treatment is not indicated.[13]

Treatment is divided into two phases: remission induction (to attain remission) and postremission (to maintain remission). Maintenance therapy for AML was previously administered for several years but is not included in most current treatment clinical trials in the United States, other than for acute promyelocytic leukemia. (Refer to the Adult Acute Myeloid Leukemia in Remission section of this summary for more information.) Other studies have used more intensive postremission therapy administered for a shorter duration of time after which treatment is discontinued.[4] Postremission therapy appears to be effective when given immediately after remission is achieved.[4]

Since myelosuppression is an anticipated consequence of both the leukemia and its treatment with chemotherapy, patients must be closely monitored during therapy. Facilities must be available for hematologic support with multiple blood fractions including platelet transfusions and for the treatment of related infectious complications.[5] Randomized trials have shown similar outcomes for patients who received prophylactic platelet transfusions at a level of 10,000/mm3 rather than 20,000/mm3.[6] The incidence of platelet alloimmunization was similar among groups randomly assigned to receive pooled platelet concentrates from random donors; filtered, pooled platelet concentrates from random donors; ultraviolet B-irradiated, pooled platelet concentrates from random donors; or filtered platelets obtained by apheresis from single random donors.[7] Colony-stimulating factors, for example, granulocyte colony–stimulating factor (G-CSF) and granulocyte-macrophage colony–stimulating factor (GM-CSF), have been studied in an effort to shorten the period of granulocytopenia associated with leukemia treatment.[8] If used, these agents are administered after completion of induction therapy. GM-CSF was shown to improve survival in a randomized trial of AML in patients aged 55 to 70 years (median survival was 10.6 months vs. 4.8 months). In this Eastern Cooperative Oncology Group (ECOG) (EST-1490) trial, patients were randomly assigned to receive GM-CSF or placebo following demonstration of leukemic clearance of the bone marrow;[9] however, GM-CSF did not show benefit in a separate similar randomized trial in patients older than 60 years.[10] In the latter study, clearance of the marrow was not required before initiating cytokine therapy. In a Southwest Oncology Group (NCT00023777) randomized trial of G-CSF given following induction therapy to patients older than 65 years, complete response was higher in patients who received G-CSF because of a decreased incidence of primary leukemic resistance. Growth factor administration did not impact on mortality or on survival.[11,12] Because the majority of randomized clinical trials have not shown an impact of growth factors on survival, their use is not routinely recommended in the remission induction setting.

The administration of GM-CSF or other myeloid growth factors before and during induction therapy, to augment the effects of cytotoxic therapy through the recruitment of leukemic blasts into cell cycle (growth factor priming), has been an area of active clinical research. Evidence from randomized studies of GM-CSF priming have come to opposite conclusions. A randomized study of GM-CSF priming during conventional induction and postremission therapy showed no difference in outcomes between patients who received GM-CSF and those who did not receive growth factor priming.[13,14][Level of evidence: 1iiA] In contrast, a similar randomized placebo-controlled study of GM-CSF priming in patients with AML aged 55 to 75 years showed improved disease-free survival (DFS) in the group receiving GM-CSF (median DFS for patients who achieved complete remission was 23 months vs. 11 months; 2-year DFS was 48% vs. 21%), with a trend towards improvement in overall survival (2-year survival was 39% vs. 27%, = .082) for patients aged 55 to 64 years.[15][Level of evidence: 1iiDii]

References

  1. Kebriaei P, Champlin R, deLima M, et al.: Management of acute leukemias. In: DeVita VT Jr, Lawrence TS, Rosenberg SA: Cancer: Principles and Practice of Oncology. 9th ed. Philadelphia, Pa: Lippincott Williams & Wilkins, 2011, pp 1928-54.
  2. Wiernik PH: Diagnosis and treatment of acute nonlymphocytic leukemia. In: Wiernik PH, Canellos GP, Dutcher JP, et al., eds.: Neoplastic Diseases of the Blood. 3rd ed. New York, NY: Churchill Livingstone, 1996, pp 283-302.
  3. Morrison FS, Kopecky KJ, Head DR, et al.: Late intensification with POMP chemotherapy prolongs survival in acute myelogenous leukemia–results of a Southwest Oncology Group study of rubidazone versus adriamycin for remission induction, prophylactic intrathecal therapy, late intensification, and levamisole maintenance. Leukemia 6 (7): 708-14, 1992. [PUBMED Abstract]
  4. Cassileth PA, Lynch E, Hines JD, et al.: Varying intensity of postremission therapy in acute myeloid leukemia. Blood 79 (8): 1924-30, 1992. [PUBMED Abstract]
  5. Supportive Care. In: Wiernik PH, Canellos GP, Dutcher JP, et al., eds.: Neoplastic Diseases of the Blood. 3rd ed. New York, NY: Churchill Livingstone, 1996, pp 779-967.
  6. Rebulla P, Finazzi G, Marangoni F, et al.: The threshold for prophylactic platelet transfusions in adults with acute myeloid leukemia. Gruppo Italiano Malattie Ematologiche Maligne dell’Adulto. N Engl J Med 337 (26): 1870-5, 1997. [PUBMED Abstract]
  7. Leukocyte reduction and ultraviolet B irradiation of platelets to prevent alloimmunization and refractoriness to platelet transfusions. The Trial to Reduce Alloimmunization to Platelets Study Group. N Engl J Med 337 (26): 1861-9, 1997. [PUBMED Abstract]
  8. Geller RB: Use of cytokines in the treatment of acute myelocytic leukemia: a critical review. J Clin Oncol 14 (4): 1371-82, 1996. [PUBMED Abstract]
  9. Rowe JM, Andersen JW, Mazza JJ, et al.: A randomized placebo-controlled phase III study of granulocyte-macrophage colony-stimulating factor in adult patients (> 55 to 70 years of age) with acute myelogenous leukemia: a study of the Eastern Cooperative Oncology Group (E1490). Blood 86 (2): 457-62, 1995. [PUBMED Abstract]
  10. Stone RM, Berg DT, George SL, et al.: Granulocyte-macrophage colony-stimulating factor after initial chemotherapy for elderly patients with primary acute myelogenous leukemia. Cancer and Leukemia Group B. N Engl J Med 332 (25): 1671-7, 1995. [PUBMED Abstract]
  11. Dombret H, Chastang C, Fenaux P, et al.: A controlled study of recombinant human granulocyte colony-stimulating factor in elderly patients after treatment for acute myelogenous leukemia. AML Cooperative Study Group. N Engl J Med 332 (25): 1678-83, 1995. [PUBMED Abstract]
  12. Godwin JE, Kopecky KJ, Head DR, et al.: A double-blind placebo-controlled trial of granulocyte colony-stimulating factor in elderly patients with previously untreated acute myeloid leukemia: a Southwest oncology group study (9031). Blood 91 (10): 3607-15, 1998. [PUBMED Abstract]
  13. Buchner T, Hiddemann W, Wormann B, et al.: GM-CSF multiple course priming and long-term administration in newly diagnosed AML: hematologic and therapeutic effects. [Abstract] Blood 84 (10 Suppl 1): A-95, 27a, 1994.
  14. Löwenberg B, Boogaerts MA, Daenen SM, et al.: Value of different modalities of granulocyte-macrophage colony-stimulating factor applied during or after induction therapy of acute myeloid leukemia. J Clin Oncol 15 (12): 3496-506, 1997. [PUBMED Abstract]
  15. Witz F, Sadoun A, Perrin MC, et al.: A placebo-controlled study of recombinant human granulocyte-macrophage colony-stimulating factor administered during and after induction treatment for de novo acute myelogenous leukemia in elderly patients. Groupe Ouest Est Leucémies Aiguës Myéloblastiques (GOELAM). Blood 91 (8): 2722-30, 1998. [PUBMED Abstract]

2.4.4.3 Treatment for CML

Chronic Myelogenous Leukemia Treatment (PDQ®)

http://www.cancer.gov/cancertopics/pdq/treatment/CML/Patient/page4

Treatment Option Overview

Key Points for This Section

There are different types of treatment for patients with chronic myelogenous leukemia.

Six types of standard treatment are used:

  1. Targeted therapy
  2. Chemotherapy
  3. Biologic therapy
  4. High-dose chemotherapy with stem cell transplant
  5. Donor lymphocyte infusion (DLI)
  6. Surgery

New types of treatment are being tested in clinical trials.

Patients may want to think about taking part in a clinical trial.

Patients can enter clinical trials before, during, or after starting their cancer treatment.

Follow-up tests may be needed.

There are different types of treatment for patients with chronic myelogenous leukemia.

Different types of treatment are available for patients with chronic myelogenous leukemia (CML). Some treatments are standard (the currently used treatment), and some are being tested in clinical trials. A treatment clinical trial is a research study meant to help improve current treatments or obtain information about new treatments for patients with cancer. When clinical trials show that a new treatment is better than the standard treatment, the new treatment may become the standard treatment. Patients may want to think about taking part in a clinical trial. Some clinical trials are open only to patients who have not started treatment.

Six types of standard treatment are used:

Targeted therapy

Targeted therapy is a type of treatment that uses drugs or other substances to identify and attack specific cancer cells without harming normal cells. Tyrosine kinase inhibitors are targeted therapy drugs used to treat chronic myelogenous leukemia.

Imatinib mesylate, nilotinib, dasatinib, and ponatinib are tyrosine kinase inhibitors that are used to treat CML.

See Drugs Approved for Chronic Myelogenous Leukemia for more information.

Chemotherapy

Chemotherapy is a cancer treatment that uses drugs to stop the growth of cancer cells, either by killing the cells or by stopping them from dividing. When chemotherapy is taken by mouth or injected into a vein or muscle, the drugs enter the bloodstream and can reach cancer cells throughout the body (systemic chemotherapy). When chemotherapy is placed directly into the cerebrospinal fluid, an organ, or a body cavity such as the abdomen, the drugs mainly affect cancer cells in those areas (regional chemotherapy). The way the chemotherapy is given depends on the type and stage of the cancer being treated.

See Drugs Approved for Chronic Myelogenous Leukemia for more information.

Biologic therapy

Biologic therapy is a treatment that uses the patient’s immune system to fight cancer. Substances made by the body or made in a laboratory are used to boost, direct, or restore the body’s natural defenses against cancer. This type of cancer treatment is also called biotherapy or immunotherapy.

See Drugs Approved for Chronic Myelogenous Leukemia for more information.

High-dose chemotherapy with stem cell transplant

High-dose chemotherapy with stem cell transplant is a method of giving high doses of chemotherapy and replacing blood-forming cells destroyed by the cancer treatment. Stem cells (immature blood cells) are removed from the blood or bone marrow of the patient or a donor and are frozen and stored. After the chemotherapy is completed, the stored stem cells are thawed and given back to the patient through an infusion. These reinfused stem cells grow into (and restore) the body’s blood cells.

See Drugs Approved for Chronic Myelogenous Leukemia for more information.

Donor lymphocyte infusion (DLI)

Donor lymphocyte infusion (DLI) is a cancer treatment that may be used after stem cell transplant.Lymphocytes (a type of white blood cell) from the stem cell transplant donor are removed from the donor’s blood and may be frozen for storage. The donor’s lymphocytes are thawed if they were frozen and then given to the patient through one or more infusions. The lymphocytes see the patient’s cancer cells as not belonging to the body and attack them.

Surgery

Splenectomy

What`s new in chronic myeloid leukemia research and treatment?

http://www.cancer.org/cancer/leukemia-chronicmyeloidcml/detailedguide/leukemia-chronic-myeloid-myelogenous-new-research

Combining the targeted drugs with other treatments

Imatinib and other drugs that target the BCR-ABL protein have proven to be very effective, but by themselves these drugs don’t help everyone. Studies are now in progress to see if combining these drugs with other treatments, such as chemotherapy, interferon, or cancer vaccines (see below) might be better than either one alone. One study showed that giving interferon with imatinib worked better than giving imatinib alone. The 2 drugs together had more side effects, though. It is also not clear if this combination is better than treatment with other tyrosine kinase inhibitors (TKIs), such as dasatinib and nilotinib. A study going on now is looking at combing interferon with nilotinib.

Other studies are looking at combining other drugs, such as cyclosporine or hydroxychloroquine, with a TKI.

New drugs for CML

Because researchers now know the main cause of CML (the BCR-ABL gene and its protein), they have been able to develop many new drugs that might work against it.

In some cases, CML cells develop a change in the BCR-ABL oncogene known as a T315I mutation, which makes them resistant to many of the current targeted therapies (imatinib, dasatinib, and nilotinib). Ponatinib is the only TKI that can work against T315I mutant cells. More drugs aimed at this mutation are now being tested.

Other drugs called farnesyl transferase inhibitors, such as lonafarnib and tipifarnib, seem to have some activity against CML and patients may respond when these drugs are combined with imatinib. These drugs are being studied further.

Other drugs being studied in CML include the histone deacetylase inhibitor panobinostat and the proteasome inhibitor bortezomib (Velcade).

Several vaccines are now being studied for use against CML.

2.4.4.4. Chronic Lymphocytic Leukemia

Chronic Lymphocytic Leukemia Treatment (PDQ®)

General Information About Chronic Lymphocytic Leukemia

Key Points for This Section

  1. Chronic lymphocytic leukemia is a type of cancer in which the bone marrow makes too many lymphocytes (a type of white blood cell).
  2. Leukemia may affect red blood cells, white blood cells, and platelets.
  3. Older age can affect the risk of developing chronic lymphocytic leukemia.
  4. Signs and symptoms of chronic lymphocytic leukemia include swollen lymph nodes and tiredness.
  5. Tests that examine the blood, bone marrow, and lymph nodes are used to detect (find) and diagnose chronic lymphocytic leukemia.
  6. Certain factors affect treatment options and prognosis (chance of recovery).
  7. Chronic lymphocytic leukemia is a type of cancer in which the bone marrow makes too many lymphocytes (a type of white blood cell).

Chronic lymphocytic leukemia (also called CLL) is a blood and bone marrow disease that usually gets worse slowly. CLL is one of the most common types of leukemia in adults. It often occurs during or after middle age; it rarely occurs in children.

http://www.cancer.gov/images/cdr/live/CDR755927-750.jpg

Anatomy of the bone; drawing shows spongy bone, red marrow, and yellow marrow. A cross section of the bone shows compact bone and blood vessels in the bone marrow. Also shown are red blood cells, white blood cells, platelets, and a blood stem cell.

Anatomy of the bone. The bone is made up of compact bone, spongy bone, and bone marrow. Compact bone makes up the outer layer of the bone. Spongy bone is found mostly at the ends of bones and contains red marrow. Bone marrow is found in the center of most bones and has many blood vessels. There are two types of bone marrow: red and yellow. Red marrow contains blood stem cells that can become red blood cells, white blood cells, or platelets. Yellow marrow is made mostly of fat.

Leukemia may affect red blood cells, white blood cells, and platelets.

Normally, the body makes blood stem cells (immature cells) that become mature blood cells over time. A blood stem cell may become a myeloid stem cell or a lymphoid stem cell.

A myeloid stem cell becomes one of three types of mature blood cells:

  1. Red blood cells that carry oxygen and other substances to all tissues of the body.
  2. White blood cells that fight infection and disease.
  3. Platelets that form blood clots to stop bleeding.

A lymphoid stem cell becomes a lymphoblast cell and then one of three types of lymphocytes (white blood cells):

  1. B lymphocytes that make antibodies to help fight infection.
  2. T lymphocytes that help B lymphocytes make antibodies to fight infection.
  3. Natural killer cells that attack cancer cells and viruses.
Blood cell development. CDR526538-750

Blood cell development. CDR526538-750

http://www.cancer.gov/images/cdr/live/CDR526538-750.jpg

Blood cell development; drawing shows the steps a blood stem cell goes through to become a red blood cell, platelet, or white blood cell. A myeloid stem cell becomes a red blood cell, a platelet, or a myeloblast, which then becomes a granulocyte (the types of granulocytes are eosinophils, basophils, and neutrophils). A lymphoid stem cell becomes a lymphoblast and then becomes a B-lymphocyte, T-lymphocyte, or natural killer cell.

Blood cell development. A blood stem cell goes through several steps to become a red blood cell, platelet, or white blood cell.

In CLL, too many blood stem cells become abnormal lymphocytes and do not become healthy white blood cells. The abnormal lymphocytes may also be called leukemia cells. The lymphocytes are not able to fight infection very well. Also, as the number of lymphocytes increases in the blood and bone marrow, there is less room for healthy white blood cells, red blood cells, and platelets. This may cause infection, anemia, and easy bleeding.

This summary is about chronic lymphocytic leukemia. See the following PDQ summaries for more information about leukemia:

  • Adult Acute Lymphoblastic Leukemia Treatment.
  • Childhood Acute Lymphoblastic Leukemia Treatment.
  • Adult Acute Myeloid Leukemia Treatment.
  • Childhood Acute Myeloid Leukemia/Other Myeloid Malignancies Treatment.
  • Chronic Myelogenous Leukemia Treatment.
  • Hairy Cell Leukemia Treatment

Older age can affect the risk of developing chronic lymphocytic leukemia.

Anything that increases your risk of getting a disease is called a risk factor. Having a risk factor does not mean that you will get cancer; not having risk factors doesn’t mean that you will not get cancer. Talk with your doctor if you think you may be at risk. Risk factors for CLL include the following:

  • Being middle-aged or older, male, or white.
  • A family history of CLL or cancer of the lymph system.
  • Having relatives who are Russian Jews or Eastern European Jews.

Signs and symptoms of chronic lymphocytic leukemia include swollen lymph nodes and tiredness.

Usually CLL does not cause any signs or symptoms and is found during a routine blood test. Signs and symptoms may be caused by CLL or by other conditions. Check with your doctor if you have any of the following:

  • Painless swelling of the lymph nodes in the neck, underarm, stomach, or groin.
  • Feeling very tired.
  • Pain or fullness below the ribs.
  • Fever and infection.
  • Weight loss for no known reason.

Tests that examine the blood, bone marrow, and lymph nodes are used to detect (find) and diagnose chronic lymphocytic leukemia.

The following tests and procedures may be used:

Physical exam and history : An exam of the body to check general signs of health, including checking for signs of disease, such as lumps or anything else that seems unusual. A history of the patient’s health habits and past illnesses and treatments will also be taken.

  • Complete blood count (CBC) with differential : A procedure in which a sample of blood is drawn and checked for the following:
  • The number of red blood cells and platelets.
  • The number and type of white blood cells.
  • The amount of hemoglobin (the protein that carries oxygen) in the red blood cells.
  • The portion of the blood sample made up of red blood cells.

Results from the Phase 3 Resonate™ Trial

Significantly improved progression free survival (PFS) vs ofatumumab in patients with previously treated CLL

  • Patients taking IMBRUVICA® had a 78% statistically significant reduction in the risk of disease progression or death compared with patients who received ofatumumab1
  • In patients with previously treated del 17p CLL, median PFS was not yet reached with IMBRUVICA® vs 5.8 months with ofatumumab (HR 0.25; 95% CI: 0.14, 0.45)1

Significantly prolonged overall survival (OS) with IMBRUVICA® vs ofatumumab in patients with previously treated CLL

  • In patients with previously treated CLL, those taking IMBRUVICA® had a 57% statistically significant reduction in the risk of death compared with those who received ofatumumab (HR 0.43; 95% CI: 0.24, 0.79; P<0.05)1

Typical treatment of chronic lymphocytic leukemia

http://www.cancer.org/cancer/leukemia-chroniclymphocyticcll/detailedguide/leukemia-chronic-lymphocytic-treating-treatment-by-risk-group

Treatment options for chronic lymphocytic leukemia (CLL) vary greatly, depending on the person’s age, the disease risk group, and the reason for treating (for example, which symptoms it is causing). Many people live a long time with CLL, but in general it is very difficult to cure, and early treatment hasn’t been shown to help people live longer. Because of this and because treatment can cause side effects, doctors often advise waiting until the disease is progressing or bothersome symptoms appear, before starting treatment.

If treatment is needed, factors that should be taken into account include the patient’s age, general health, and prognostic factors such as the presence of chromosome 17 or chromosome 11 deletions or high levels of ZAP-70 and CD38.

Initial treatment

Patients who might not be able to tolerate the side effects of strong chemotherapy (chemo), are often treated with chlorambucil alone or with a monoclonal antibody targeting CD20 like rituximab (Rituxan) or obinutuzumab (Gazyva). Other options include rituximab alone or a corticosteroid like prednisione.

In stronger and healthier patients, there are many options for treatment. Commonly used treatments include:

  • FCR: fludarabine (Fludara), cyclophosphamide (Cytoxan), and rituximab
  • Bendamustine (sometimes with rituximab)
  • FR: fludarabine and rituximab
  • CVP: cyclophosphamide, vincristine, and prednisone (sometimes with rituximab)
  • CHOP: cyclophosphamide, doxorubicin, vincristine (Oncovin), and prednisone
  • Chlorambucil combined with prednisone, rituximab, obinutuzumab, or ofatumumab
  • PCR: pentostatin (Nipent), cyclophosphamide, and rituximab
  • Alemtuzumab (Campath)
  • Fludarabine (alone)

Other drugs or combinations of drugs may also be also used.

If the only problem is an enlarged spleen or swollen lymph nodes in one region of the body, localized treatment with low-dose radiation therapy may be used. Splenectomy (surgery to remove the spleen) is another option if the enlarged spleen is causing symptoms.

Sometimes very high numbers of leukemia cells in the blood cause problems with normal circulation. This is calledleukostasis. Chemo may not lower the number of cells until a few days after the first dose, so before the chemo is given, some of the cells may be removed from the blood with a procedure called leukapheresis. This treatment lowers blood counts right away. The effect lasts only for a short time, but it may help until the chemo has a chance to work. Leukapheresis is also sometimes used before chemo if there are very high numbers of leukemia cells (even when they aren’t causing problems) to prevent tumor lysis syndrome (this was discussed in the chemotherapy section).

Some people who have very high-risk disease (based on prognostic factors) may be referred for possible stem cell transplant (SCT) early in treatment.

Second-line treatment of CLL

If the initial treatment is no longer working or the disease comes back, another type of treatment may help. If the initial response to the treatment lasted a long time (usually at least a few years), the same treatment can often be used again. If the initial response wasn’t long-lasting, using the same treatment again isn’t as likely to be helpful. The options will depend on what the first-line treatment was and how well it worked, as well as the person’s health.

Many of the drugs and combinations listed above may be options as second-line treatments. For many people who have already had fludarabine, alemtuzumab seems to be helpful as second-line treatment, but it carries an increased risk of infections. Other purine analog drugs, such as pentostatin or cladribine (2-CdA), may also be tried. Newer drugs such as ofatumumab, ibrutinib (Imbruvica), and idelalisib (Zydelig) may be other options.

If the leukemia responds, stem cell transplant may be an option for some patients.

Some people may have a good response to first-line treatment (such as fludarabine) but may still have some evidence of a small number of leukemia cells in the blood, bone marrow, or lymph nodes. This is known as minimal residual disease. CLL can’t be cured, so doctors aren’t sure if further treatment right away will be helpful. Some small studies have shown that alemtuzumab can sometimes help get rid of these remaining cells, but it’s not yet clear if this improves survival.

Treating complications of CLL

One of the most serious complications of CLL is a change (transformation) of the leukemia to a high-grade or aggressive type of non-Hodgkin lymphoma called diffuse large cell lymphoma. This happens in about 5% of CLL cases, and is known as Richter syndrome. Treatment is often the same as it would be for lymphoma (see our document called Non-Hodgkin Lymphoma for more information), and may include stem cell transplant, as these cases are often hard to treat.

Less often, CLL may transform to prolymphocytic leukemia. As with Richter syndrome, these cases can be hard to treat. Some studies have suggested that certain drugs such as cladribine (2-CdA) and alemtuzumab may be helpful.

In rare cases, patients with CLL may have their leukemia transform into acute lymphocytic leukemia (ALL). If this happens, treatment is likely to be similar to that used for patients with ALL (see our document called Leukemia: Acute Lymphocytic).

Acute myeloid leukemia (AML) is another rare complication in patients who have been treated for CLL. Drugs such as chlorambucil and cyclophosphamide can damage the DNA of blood-forming cells. These damaged cells may go on to become cancerous, leading to AML, which is very aggressive and often hard to treat (see our document calledLeukemia: Acute Myeloid).

CLL can cause problems with low blood counts and infections. Treatment of these problems were discussed in the section “Supportive care in chronic lymphocytic leukemia.”

2.4.4.5  Lymphoma treatment

Overview

http://www.emedicinehealth.com/lymphoma/page8_em.htm#lymphoma_treatment

The most widely used therapies are combinations of chemotherapy and radiation therapy.

  • Biological therapy, which targets key features of the lymphoma cells, is used in many cases nowadays.

The goal of medical therapy in lymphoma is complete remission. This means that all signs of the disease have disappeared after treatment. Remission is not the same as cure. In remission, one may still have lymphoma cells in the body, but they are undetectable and cause no symptoms.

  • When in remission, the lymphoma may come back. This is called recurrence.
  • The duration of remission depends on the type, stage, and grade of the lymphoma. A remission may last a few months, a few years, or may continue throughout one’s life.
  • Remission that lasts a long time is called durable remission, and this is the goal of therapy.
  • The duration of remission is a good indicator of the aggressiveness of the lymphoma and of the prognosis. A longer remission generally indicates a better prognosis.

Remission can also be partial. This means that the tumor shrinks after treatment to less than half its size before treatment.

The following terms are used to describe the lymphoma’s response to treatment:

  • Improvement: The lymphoma shrinks but is still greater than half its original size.
  • Stable disease: The lymphoma stays the same.
  • Progression: The lymphoma worsens during treatment.
  • Refractory disease: The lymphoma is resistant to treatment.

The following terms to refer to therapy:

  • Induction therapy is designed to induce a remission.
  • If this treatment does not induce a complete remission, new or different therapy will be initiated. This is usually referred to as salvage therapy.
  • Once in remission, one may be given yet another treatment to prevent recurrence. This is called maintenance therapy.

Chemotherapy

Many different types of chemotherapy may be used for Hodgkin lymphoma. The most commonly used combination of drugs in the United States is called ABVD. Another combination of drugs, known as BEACOPP, is now widely used in Europe and is being used more often in the United States. There are other combinations that are less commonly used and not listed here. The drugs that make up these two more common combinations of chemotherapy are listed below.

ABVD: Doxorubicin (Adriamycin), bleomycin (Blenoxane), vinblastine (Velban, Velsar), and dacarbazine (DTIC-Dome). ABVD chemotherapy is usually given every two weeks for two to eight months.

BEACOPP: Bleomycin, etoposide (Toposar, VePesid), doxorubicin, cyclophosphamide (Cytoxan, Neosar), vincristine (Vincasar PFS, Oncovin), procarbazine (Matulane), and prednisone (multiple brand names). There are several different treatment schedules, but different drugs are usually given every two weeks.

The type of chemotherapy, number of cycles of chemotherapy, and the additional use of radiation therapy are based on the stage of the Hodgkin lymphoma and the type and number of prognostic factors.

Adult Non-Hodgkin Lymphoma Treatment (PDQ®)

http://www.cancer.gov/cancertopics/pdq/treatment/adult-non-hodgkins/Patient/page1

Key Points for This Section

Adult non-Hodgkin Lymphoma is a disease in which malignant (cancer) cells form in the lymph system.

Because lymph tissue is found throughout the body, adult non-Hodgkin lymphoma can begin in almost any part of the body. Cancer can spread to the liver and many other organs and tissues.

Non-Hodgkin lymphoma in pregnant women is the same as the disease in nonpregnant women of childbearing age. However, treatment is different for pregnant women. This summary includes information on the treatment of non-Hodgkin lymphoma during pregnancy

Non-Hodgkin lymphoma can occur in both adults and children. Treatment for children, however, is different than treatment for adults. (See the PDQ summary on Childhood Non-Hodgkin Lymphoma Treatment for more information.)

There are many different types of lymphoma.

Lymphomas are divided into two general types: Hodgkin lymphoma and non-Hodgkin lymphoma. This summary is about the treatment of adult non-Hodgkin lymphoma. For information about other types of lymphoma, see the following PDQ summaries:

Age, gender, and a weakened immune system can affect the risk of adult non-Hodgkin lymphoma.

If cancer is found, the following tests may be done to study the cancer cells:

  • Immunohistochemistry : A test that uses antibodies to check for certain antigens in a sample of tissue. The antibody is usually linked to a radioactive substance or a dye that causes the tissue to light up under a microscope. This type of test may be used to tell the difference between different types of cancer.
  • Cytogenetic analysis : A laboratory test in which cells in a sample of tissue are viewed under a microscope to look for certain changes in the chromosomes.
  • Immunophenotyping : A process used to identify cells, based on the types of antigens ormarkers on the surface of the cell. This process is used to diagnose specific types of leukemia and lymphoma by comparing the cancer cells to normal cells of the immune system.

Certain factors affect prognosis (chance of recovery) and treatment options.

The prognosis (chance of recovery) and treatment options depend on the following:

  • The stage of the cancer.
  • The type of non-Hodgkin lymphoma.
  • The amount of lactate dehydrogenase (LDH) in the blood.
  • The amount of beta-2-microglobulin in the blood (for Waldenström macroglobulinemia).
  • The patient’s age and general health.
  • Whether the lymphoma has just been diagnosed or has recurred (come back).

Stages of adult non-Hodgkin lymphoma may include E and S.

Adult non-Hodgkin lymphoma may be described as follows:

E: “E” stands for extranodal and means the cancer is found in an area or organ other than the lymph nodes or has spread to tissues beyond, but near, the major lymphatic areas.

S: “S” stands for spleen and means the cancer is found in the spleen.

Stage I adult non-Hodgkin lymphoma is divided into stage I and stage IE.

  • Stage I: Cancer is found in one lymphatic area (lymph node group, tonsils and nearby tissue, thymus, or spleen).
  • Stage IE: Cancer is found in one organ or area outside the lymph nodes.

Stage II adult non-Hodgkin lymphoma is divided into stage II and stage IIE.

  • Stage II: Cancer is found in two or more lymph node groups either above or below the diaphragm (the thin muscle below the lungs that helps breathing and separates the chest from the abdomen).
  • Stage IIE: Cancer is found in one or more lymph node groups either above or below the diaphragm. Cancer is also found outside the lymph nodes in one organ or area on the same side of the diaphragm as the affected lymph nodes.

Stage III adult non-Hodgkin lymphoma is divided into stage III, stage IIIE, stage IIIS, and stage IIIE+S.

  • Stage III: Cancer is found in lymph node groups above and below the diaphragm (the thin muscle below the lungs that helps breathing and separates the chest from the abdomen).
  • Stage IIIE: Cancer is found in lymph node groups above and below the diaphragm and outside the lymph nodes in a nearby organ or area.
  • Stage IIIS: Cancer is found in lymph node groups above and below the diaphragm, and in the spleen.
  • Stage IIIE+S: Cancer is found in lymph node groups above and below the diaphragm, outside the lymph nodes in a nearby organ or area, and in the spleen.

In stage IV adult non-Hodgkin lymphoma, the cancer:

  • is found throughout one or more organs that are not part of a lymphatic area (lymph node group, tonsils and nearby tissue, thymus, or spleen), and may be in lymph nodes near those organs; or
  • is found in one organ that is not part of a lymphatic area and has spread to organs or lymph nodes far away from that organ; or
  • is found in the liver, bone marrow, cerebrospinal fluid (CSF), or lungs (other than cancer that has spread to the lungs from nearby areas).

Adult non-Hodgkin lymphomas are also described based on how fast they grow and where the affected lymph nodes are in the body.  Indolent & aggressive.

The treatment plan depends mainly on the following:

  • The type of non-Hodgkin’s lymphoma
  • Its stage (where the lymphoma is found)
  • How quickly the cancer is growing
  • The patient’s age
  • Whether the patient has other health problems
  • If there are symptoms present such as fever and night sweats (see above)

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Diet and Exercise

Writer and Curator: Larry H. Bernstein, MD, FCAP 

 

Introduction

In the last several decades there has been a transformation in the diet of Americans, and much debate about obesity, type 2 diabetes mellitus, hyperlipidemia, and the transformation of medical practice to a greater emphasis on preventive medicine. This occurs at a time that the Western countries are experiencing a large portion of the obesity epidemic, which actually diverts attention from a larger share of malnutrition in parts of Africa, Asia, and to a greater extent in India. This does not mean that obesity or malnutrition is exclusively in any parts of the world. But there is a factor at play that involves social factors, poverty, education, cognition, anxiety, and eating behaviors, food preferences and food balance, and activities of daily living. The epidemic of obesity also involves the development of serious long term health problems, such as, type 2 diabetes mellitus, sarcopenia, fracture risk, pulmonary disease, sleep apnea in particular, and cardiovascular and stroke risk. Nevertheless, this generation of Western society is also experiencing a longer life span than its predecessors. In this article I shall explore the published work on diet and exercise.

 

‘‘Go4Life’’ exercise counseling, accelerometer feedback, and activity levels in older people

Warren G. Thompson, CL Kuhle, GA Koepp, SK McCrady-Spitzer, JA Levine
Archives of Gerontology and Geriatrics 58 (2014) 314–319
http://dx.doi.org/10.1016/j.archger.2014.01.004

Older people are more sedentary than other age groups. We sought to determine if providing an accelerometer with feedback about activity and counseling older subjects using Go4Life educational material would increase activity levels. Participants were recruited from independent living areas within assisted living facilities and the general public in the Rochester, MN area. 49 persons aged 65–95(79.5 + 7.0 years) who were ambulatory but sedentary and overweight participated in this randomized controlled crossover trial for one year. After a baseline period of 2 weeks, group 1 received an accelerometer and counseling using Go4Life educational material (www.Go4Life.nia.nih.gov) for 24 weeks and accelerometer alone for the next 24 weeks. Group 2 had no intervention for the first 24 weeks and then received an accelerometer and Go4Life based counseling for 24 weeks. There were no significant baseline differences between the two groups. The intervention was not associated with a significant change inactivity, body weight, % body fat, or blood parameters (p > 0.05). Older (80–93) subjects were less active than younger (65–79) subjects (p = 0.003). Over the course of the 48 week study, an increase in activity level was associated with a decline in % body fat (p = 0.008). Increasing activity levels benefits older patients. However, providing an accelerometer and a Go4Life based exercise counseling program did not result in a 15% improvement in activity levels in this elderly population. Alternate approaches to exercise counseling may be needed in elderly people of this age range.

It is generally recommended that older adults be moderately or vigorously active for 150 min each week. A systematic review demonstrated that only 20–60% of older people are achieving this goal. These studies determined adherence to physical activity recommendations by questionnaire. Using NHANES data, it has been demonstrated that older people meet activity recommendations 62% of the time using a self-report questionnaire compared to 9.6% of the time when measured by accelerometry. Thus, objective measures suggest that older people are falling even more short of the goal than previously thought. Most studies have measured moderate and vigorous activity. However, light activity or NEAT (non-exercise activity thermogenesis) also has an important effect on health. For example, increased energy expenditure was associated with lower mortality in community-dwelling older adults. More than half of the extra energy expenditure in the high energy expenditure group came from non-exercise (light) activity. In addition to reduced total mortality, increased light and moderate activity has been associated with better cognitive function, reduced fracture rate (Gregg et al., 1998), less cardiovascular disease, and weight loss in older people. A meta-analysis of middle-aged and older adults has demonstrated greater all-cause mortality with increased sitting time. Thus, any strategy which can increase activity (whether light or more vigorous) has the potential to save lives and improve quality of life for older adults. A variety of devices have been used to measure physical activity.

A tri-axial accelerometer measures movement in three dimensions. Studies comparing tri-axial accelerometers with uniaxial accelerometers and pedometers demonstrate that only certain tri-axial accelerometers provide a reliable assessment of energy expenditure. This is usually due to failure to detect light activity. Since light activity accounts for a substantial portion of older people’s energy expenditure, measuring activity with a questionnaire or measuring steps with a pedometer do not provide an accurate reflection of activity in older people.

A recent review concluded that there is only weak evidence that physical activity can be improved. Since increasing both light and moderate activity benefit older people, studies demonstrating that physical activity can be improved are urgently needed. Since accelerometry is the best way to accurately assess light activity, we performed a study to determine if an activity counseling program and using an accelerometer which gives feedback on physical activity, can result in an increase in light and moderate activity in older people. We also sought to determine whether counseling and accelerometer feedback would result in weight loss, change in % body fat, glucose, hemoglobin A1c, insulin, and fasting lipid profile.

The main results of the study are both the experimental and control group lost weight (about 1 kg) at 6months (p = 0.04 and 0.02, respectively). The experimental group was less active at 6 months but not significantly while the control group was significantly less active at 6 months (p = 0.006) than at baseline. The experimental group had a modest decline in cholesterol (p = 0.03) and an improvement in Get Up & go time (p = 0.03) while the control group had a slight improvement in HgbA1c (p = 0.01). However, the main finding of the study was that there were no differences between the two groups on any of these variables. Thus, providing this group of older participants with an accelerometer and Go4Life based counseling resulted in no increase in physical activity, weight loss or change in glucose, lipids, blood pressure, or body fat. There were no differences within either group or between groups from 6 to 12 months on any of the variables (data not shown). While age was correlated with baseline activity, it did not affect activity change indicating that younger participants did not respond to the program better than older participants. Performance on the Get Up and Go test and season of the year did not influence the change in activity. There were no differences in physical activity levels at 3 or 9 months.

There was a significant correlation (r = -0.38, p = 0.006) between change in activity and change in body fat over the course of the study. Those subjects (whether in the experimental or control group) who increased their activity over the course of the year were likely to have a decline in % body fat over the year while those whose activity declined were likely to have increased %body fat. There was no correlation between change in activity and any of the other parameters including weight and waist circumference (data not shown).

Older adults are the fastest growing segment of the population in the US, but few meet the minimum recommended 30 min of moderate activity on 5 days or more per week (Centers for Disease Control and Prevention, 2002). Our study found that within the geriatric population, activity declines as people age. We saw a 2.4% decline per year cross-sectionally. This finding agrees with a recent cohort study (Bachman et al., 2014). In that study, the annual decline accelerated with increasing age. Thus, there is a need to increase activity particularly in the oldest age groups. The United States Preventive Services Task Force concluded that the evidence that counseling improves physical activity is weak (Moyer and US Preventive Services Task Force, 2012). The American Heart Association reached similar conclusions (Artinian et al., 2010). Thus, new ways of counseling older patients to counter the natural decline in activity with age are urgently needed.

Applying health behavior theory to multiple behavior change: Considerations and approaches

Seth M. Noar, Melissa Chabot, Rick S. Zimmerman
Preventive Medicine 46 (2008) 275–280
http://dx.doi.org:/10.1016/j.ypmed.2007.08.001

Background.There has been a dearth of theorizing in the area of multiple behavior change. The purpose of the current article was to examine how health behavior theory might be applied to the growing research terrain of multiple behavior change. Methods. Three approaches to applying health behavior theory to multiple behavior change are advanced, including searching the literature for potential examples of such applications. Results. These three approaches to multiple behavior change include

(1) a behavior change principles approach;

(2) a global health/behavioral category approach, and

(3) a multiple behavioral approach.

Each approach is discussed and explicated and examples from this emerging literature are provided. Conclusions. Further study in this area has the potential to broaden our understanding of multiple behaviors and multiple behavior change. Implications for additional theory-testing and application of theory to interventions are discussed.

Many of the leading causes of death in the United States are behavior-related and thus preventable. While a number of health behaviors are a concern individually, increasingly the impact of multiple behavioral risks is being appreciated. As newer initiatives funded by the National Institutes of Health and Robert Wood Johnson Foundation begin to stimulate research in this important area, a critical question emerges: How can we understand multiple health behavior change from a theoretical standpoint? While multiple behavior change interventions are beginning to be developed and evaluated, to date there have been few efforts to garner a theory-based understanding of the process of multiple health behavior change. Given that so little theoretical work currently exists in this area, our main purpose is to advance the conversation on how health behavior theory can help us to achieve a greater understanding of multiple behavior change. The approaches discussed have implications for both theory-testing as well as intervention design.

A critical question that must be asked, is whether there is a common set of principles of health behavior change that transcend individual health behaviors. This is an area where much data already exists, as health behavior theories have been tested across numerous health behaviors.The integration of findings from studies across diverse behavioral areas, is not what it could be. Godin and Kok (1996) reviewed studies of the TPB applied to numerous health-related behaviors. Across seven categories of health behaviors, they found TPB components to offer similar prediction of intention but inconsistent prediction of behavior.They concluded that the nature of differing health behaviors may require additional constructs to be added to the TPB, such as actual (versus perceived) behavioral control. Prochaska et al. (1994) examined decisional balance across stages of change for 12 health-related behaviors. Similar patterns were found across nearly all of these health behaviors, with the “pros” of changing generally increasing across the stages, the “cons” decreasing, and a pro/con crossover occurring in the contemplation or preparation stages of change. Prochaska et al. (1994) concluded that clear commonalties exist across these differing health behaviors which were examined in differing samples. Finally, Rosen (2000) examined change processes from the TTM across six behavioral categories, examining whether the trajectory of change processes is similar or different across stages of change in those health areas. He found that for smoking cessation, cognitive change processes were used more in earlier stages of change than behavioral processes, while for physical activity and dietary change, both categories of change processes increased together.

A second approach is the following: Rather than applying theoretical concepts to specific behaviors, such concepts might be applied at the general or global level. A general orientation toward health may not lead directly to specific health behaviors, but it may increase the chances of particular health-related attitudes, which may in turn lead to specific health behaviors. In fact, although Ajzen and Timko (1986) found general health attitudes to be poor predictors of behavior, such attitudes were significantly related to specific health attitudes and perceived behavioral control over specific behaviors. It is likely that when we consider multiple behaviors that we may discover an entire network of health attitudes and beliefs that are interrelated. In fact, studies of single behaviors essentially take those behaviors out of the multi-attitude and multi-behavioral context in which they are embedded. For instance, although attitudes toward walking may be a better predictor of walking behavior than attitudes toward physical activity, walking behavior is part of a larger “physical activity” behavioral category. While predicting that particular behavior may be best served by the specific measure, the larger category is both relevant and of interest. Thus, it may be that there are higher order constructs to be understood here.

A third approach is a multiple behavioral approach, or one which focuses on the linkages among health behaviors. It shares some similarities to the approach just described. Here the focus is more strictly on how particular  interventions were superior to comparison groups for 21 of 41 (51%) studies (3 physical activity, 7 diet, 11 weight loss/physical activity and diet). Twenty-four studies had indeterminate results, and in four studies the comparison conditions outperformed eHealth interventions. Conclusions: Published studies of eHealth interventions for physical activity and dietary behavior change are in their infancy. Results indicated mixed findings related to the effectiveness of eHealth interventions. Interventions that feature interactive technologies need to be refined and more rigorously evaluated to fully determine their potential as tools to facilitate health behavior change.

 

A prospective evaluation of the Transtheoretical Model of Change applied to exercise in young people 

Patrick Callaghan, Elizabeth Khalil, Ioannis Morres
Intl J Nursing Studies 47 (2010) 3–12
http://dx.doi.org:/10.1016/j.ijnurstu.2009.06.013

Objectives:To investigate the utility of the Transtheoretical Model of Change in predicting exercise in young people. Design: A prospective study: assessments were done at baseline and follow-up 6 months later. Method: Using stratified random sampling 1055 Chinese high school pupils living in Hong Kong, 533 of who were followed up at 6 months, completed measures of stage of change (SCQ), self-efficacy (SEQ), perceptions of the pros and cons of exercising (DBQ) and processes of change (PCQ). Data were analyzed using one-way ANOVA, repeated measures ANOVA and independent sample t tests.
Results:The utility of the TTM to predict exercise in this population is not strong; increases in self-efficacy and decisional balance discriminated between those remaining active at baseline and follow-up, but not in changing from an inactive (e.g.,Precontemplation or Contemplation) to an active state (e.g.,Maintenance) as one would anticipate given the staging algorithm of the TTM.
Conclusion:The TTM is a modest predictor of future stage of change for exercise in young Chinese people. Where there is evidence that TTM variables may shape movement over time, self-efficacy, pros and behavioral processes of change appear to be the strongest predictors

 

A retrospective study on changes in residents’ physical activities, social interactions, and neighborhood cohesion after moving to a walkable community

Xuemei Zhu,Chia-Yuan Yu, Chanam Lee, Zhipeng Lu, George Mann
Preventive Medicine 69 (2014) S93–S97
http://dx.doi.org/10.1016/j.ypmed.2014.08.013

Objective. This study is to examine changes in residents’ physical activities, social interactions, andneighbor-hood cohesion after they moved to a walkable community in Austin, Texas.
Methods. Retrospective surveys (N=449) were administered in 2013–2014 to collect pre-and post-move data about the outcome variables and relevant personal, social, and physical environmental factors. Walkability of each resident’s pre-move community was measured using the Walk Score. T tests were used to examine the pre–post move differences in the outcomes in the whole sample and across subgroups with different physical activity levels, neighborhood conditions, and neighborhood preferences before the move. Results. After the move, total physical activity increased significantly in the whole sample and all subgroups except those who were previously sufficiently active; lived in communities with high walkability, social interactions, or neighborhood cohesion; or had moderate preference for walkable neighborhoods. Walking in the community increased in the whole sample and all subgroups except those who were previously sufficiently active, moved from high-walkability communities, or had little to no preference for walkable neighborhoods. Social interactions and neighborhood cohesion increased significantly after the move in the whole sample and all subgroups.
Conclusion.This study explored potential health benefits of a walkable community in promoting physically and socially active lifestyles, especially for populations at higher risk of obesity. The initial result is promising, suggesting the need for more work to further examine the relationships between health and community design using pre–post assessments.

 

Application of the transtheoretical model to identify psychological constructs influencing exercise behavior: A questionnaire survey

Young-Ho Kim
Intl J Nursing Studies 44 (2007) 936–944
http://dx.doi.org:/10.1016/j.ijnurstu.2006.03.008

Background: Current research on exercise behavior has largely been attempted to identify the relationship between psychological attributes and the initiation or adherence of exercise behavior based on psychological theories. A limited data are available on the psychological predictors of exercise behavior in public health. Objectives: The present study examined the theorized association of TTM of behavior change constructs by stage of change for exercise behavior. Methods: A total of 228 college students selected from 2 universities in Seoul were surveyed. Four Korean-version questionnaires were used to identify the stage of exercise behavior and psychological attributes of adolescents. Data were analyzed by frequency analysis, MANOVA, correlation analysis, and discriminant function analysis.
Results: Multivariate F-test indicated that behavioral and cognitive processes of change, exercise efficacy, and pros differentiated participants across the stages of exercise behavior. Furthermore, exercise behavior was significantly correlated with the TTM constructs, and that overall classification accuracy across the stages of change was 61.0%. Conclusions:The present study supports the internal and external validity of the Transtheoretical Model for explaining exercise behavior. As this study highlights, dissemination must increase awareness but also influences perceptions regarding theoretically based and practically important exercise strategies for public health professionals.

 

 

Does more education lead to better health habits? Evidence from the school reforms in Australia?

Jinhu Li, Nattavudh Powdthavee
Social Science & Medicine 127 (2015) 83-91
http://dx.doi.org/10.1016/j.socscimed.2014.07.021

The current study provides new empirical evidence on the causal effect of education on health-related behaviors by exploiting historical changes in the compulsory schooling laws in Australia. Since World War II, Australian states increased the minimum school leaving age from 14 to 15 in different years. Using differences in the laws regarding minimum school leaving age across different cohorts and across different states as a source of exogenous variation in education, we show that more education improves people’s diets and their tendency to engage in more regular exercise and drinking moderately, but not necessarily their tendency to avoid smoking and to engage in more preventive health checks. The improvements in health behaviors are also reflected in the estimated positive effect of education on some health outcomes. Our results are robust to alternative measures of education and different estimation methods.

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Neonatal Pathophysiology


Neonatal Pathophysiology

Writer and Curator: Larry H. Bernstein, MD, FCAP 

 

Introduction

This curation deals with a large and specialized branch of medicine that grew since the mid 20th century in concert with the developments in genetics and as a result of a growing population, with large urban populations, increasing problems of premature deliveries.  The problems of prematurity grew very preterm to very low birth weight babies with special problems.  While there were nurseries, the need for intensive care nurseries became evident in the 1960s, and the need for perinatal care of pregnant mothers also grew as a result of metabolic problems of the mother, intrauterine positioning of the fetus, and increasing numbers of teen age pregnancies as well as nutritional problems of the mother.  There was also a period when the manufacturers of nutritional products displaced the customary use of breast feeding, which was consequential.  This discussion is quite comprehensive, as it involves a consideration of the heart, the lungs, the brain, and the liver, to a large extent, and also the kidneys and skeletal development.

It is possible to outline, with a proportionate emphasis based on frequency and severity, this as follows:

  1. Genetic and metabolic diseases
  2. Nervous system
  3. Cardiovascular
  4. Pulmonary
  5. Skeletal – bone and muscle
  6. Hematological
  7. Liver
  8. Esophagus, stomach, and intestines
  9. Kidneys
  10. Immune system

Fetal Development

Gestation is the period of time between conception and birth when a baby grows and develops inside the mother’s womb. Because it’s impossible to know exactly when conception occurs, gestational age is measured from the first day of the mother’s last menstrual cycle to the current date. It is measured in weeks. A normal gestation lasts anywhere from 37 to 41 weeks.

Week 5 is the start of the “embryonic period.” This is when all the baby’s major systems and structures develop. The embryo’s cells multiply and start to take on specific functions. This is called differentiation. Blood cells, kidney cells, and nerve cells all develop. The embryo grows rapidly, and the baby’s external features begin to form.

Week 6-9:   Brain forms into five different areas. Some cranial nerves are visible. Eyes and ears begin to form. Tissue grows that will the baby’s spine and other bones. Baby’s heart continues to grow and now beats at a regular rhythm. Blood pumps through the main vessels. Your baby’s brain continues to grow. The lungs start to form. Limbs look like paddles. Essential organs begin to grow.

Weeks 11-18: Limbs extended. Baby makes sucking motion. Movement of limbs. Liver and pancreas produce secretions. Muscle and bones developing.

Week 19-21: Baby can hear. Mom feels baby – and quickening.

http://www.nlm.nih.gov/medlineplus/ency/article/002398.htm

fetal-development

fetal-development

https://polination.files.wordpress.com/2014/02/abortion-new-research-into-fetal-development.jpg

Inherited Metabolic Disorders

The original cause of most genetic metabolic disorders is a gene mutation that occurred many, many generations ago. The gene mutation is passed along through the generations, ensuring its preservation.

Each inherited metabolic disorder is quite rare in the general population. Considered all together, inherited metabolic disorders may affect about 1 in 1,000 to 2,500 newborns. In certain ethnic populations, such as Ashkenazi Jews (Jews of central and eastern European ancestry), the rate of inherited metabolic disorders is higher.

Hundreds of inherited metabolic disorders have been identified, and new ones continue to be discovered. Some of the more common and important genetic metabolic disorders include:

Lysosomal storage disorders : Lysosomes are spaces inside cells that break down waste products of metabolism. Various enzyme deficiencies inside lysosomes can result in buildup of toxic substances, causing metabolic disorders including:

  • Hurler syndrome (abnormal bone structure and developmental delay)
  • Niemann-Pick disease (babies develop liver enlargement, difficulty feeding, and nerve damage)
  • Tay-Sachs disease (progressive weakness in a months-old child, progressing to severe nerve damage; the child usually lives only until age 4 or 5)
  • Gauchers disease and others

Galactosemia: Impaired breakdown of the sugar galactose leads to jaundice, vomiting, and liver enlargement after breast or formula feeding by a newborn.

Maple syrup urine disease: Deficiency of an enzyme called BCKD causes buildup of amino acids in the body. Nerve damage results, and the urine smells like syrup.

Phenylketonuria (PKU): Deficiency of the enzyme PAH results in high levels of phenylalanine in the blood. Mental retardation results if the condition is not recognized.

Glycogen storage diseases: Problems with sugar storage lead to low blood sugar levels, muscle pain, and weakness.

Metal metabolism disorders: Levels of trace metals in the blood are controlled by special proteins. Inherited metabolic disorders can result in protein malfunction and toxic accumulation of metal in the body:

Wilson disease (toxic copper levels accumulate in the liver, brain, and other organs)

Hemochromatosis (the intestines absorb excessive iron, which builds up in the liver, pancreas, joints, and heart, causing damage)

Organic acidemias: methylmalonic acidemia and propionic acidemia.

Urea cycle disorders: ornithine transcarbamylase deficiency and citrullinemia

Hemoglobinopathies – thalassemias, sickle cell disease

Red cell enzyme disorders – glucose-6-phosphate dehydrogenase, pyruvate kinase

This list is by no means complete.

http://www.webmd.com/a-to-z-guides/inherited-metabolic-disorder-types-and-treatments

New variations in the galactose-1-phosphate uridyltransferase (GALT) gene

Clinical and molecular spectra in galactosemic patients from neonatal screening in northeastern Italy: Structural and functional characterization of new variations in the galactose-1-phosphate uridyltransferase (GALT) gene

E Viggiano, A Marabotti, AP Burlina, C Cazzorla, MR D’Apice, et al.
Gene 559 (2015) 112–118
http://dx.doi.org/10.1016/j.gene.2015.01.013
Galactosemia (OMIM 230400) is a rare autosomal recessive inherited disorder caused by deficiency of galactose-1-phosphate uridyltransferase (GALT; OMIM 606999) activity. The incidence of galactosemia is 1 in 30,000–60,000, with a prevalence of 1 in 47,000 in the white population. Neonates with galactosemia can present acute symptoms, such as severe hepatic and renal failure, cataract and sepsis after milk introduction. Dietary restriction of galactose determines the clinical improvement in these patients. However, despite early diagnosis by neonatal screening and dietary treatment, a high percentage of patients develop long-term complications such as cognitive disability, speech problems, neurological and/or movement disorders and, in females, ovarian dysfunction.

With the benefit of early diagnosis by neonatal screening and early therapy, the acute presentation of classical galactosemia can be prevented. The objectives of the current study were to report our experience with a group of galactosemic patients identified through the neonatal screening programs in northeastern Italy during the last 30 years.

No neonatal deaths due to galactosemia complications occurred after the introduction of the neonatal screening program. However, despite the early diagnosis and dietary treatment, the patients with classical galactosemia showed one or more long-term complications.

A total of 18 different variations in the GALT gene were found in the patient cohort: 12 missense, 2 frameshift, 1 nonsense, 1 deletion, 1 silent variation, and 1 intronic. Six (p.R33P, p.G83V, p.P244S, p.L267R, p.L267V, p.E271D) were new variations. The most common variation was p.Q188R (12 alleles, 31.5%), followed by p.K285N (6 alleles, 15.7%) and p.N314D (6 alleles, 15.7%). The other variations comprised 1 or 2 alleles. In the patients carrying a new mutation, the biochemical analysis of GALT activity in erythrocytes showed an activity of < 1%. In silico analysis (SIFT, PolyPhen-2 and the computational analysis on the static protein structure) showed potentially damaging effects of the six new variations on the GALT protein, thus expanding the genetic spectrum of GALT variations in Italy. The study emphasizes the difficulty in establishing a genotype–phenotype correlation in classical galactosemia and underlines the importance of molecular diagnostic testing prior to making any treatment.

Diagnosis and Management of Hereditary Hemochromatosis

Reena J. Salgia, Kimberly Brown
Clin Liver Dis 19 (2015) 187–198
http://dx.doi.org/10.1016/j.cld.2014.09.011

Hereditary hemochromatosis (HH) is a diagnosis most commonly made in patients with elevated iron indices (transferrin saturation and ferritin), and HFE genetic mutation testing showing C282Y homozygosity.

The HFE mutation is believed to result in clinical iron overload through altering hepcidin levels resulting in increased iron absorption.

The most common clinical complications of HH include cirrhosis, diabetes, nonischemic cardiomyopathy, and hepatocellular carcinoma.

Liver biopsy should be performed in patients with HH if the liver enzymes are elevated or serum ferritin is greater than 1000 mg/L. This is useful to determine the degree of iron overload and stage the fibrosis.

Treatment of HH with clinical iron overload involves a combination of phlebotomy and/or chelation therapy. Liver transplantation should be considered for patients with HH-related decompensated cirrhosis.

Health economic evaluation of plasma oxysterol screening in the diagnosis of Niemann–Pick Type C disease among intellectually disabled using discrete event simulation

CDM van Karnebeek, Tima Mohammadi, Nicole Tsaod, Graham Sinclair, et al.
Molecular Genetics and Metabolism 114 (2015) 226–232
http://dx.doi.org/10.1016/j.ymgme.2014.07.004

Background: Recently a less invasive method of screening and diagnosing Niemann–Pick C (NP-C) disease has emerged. This approach involves the use of a metabolic screening test (oxysterol assay) instead of the current practice of clinical assessment of patients suspected of NP-C (review of medical history, family history and clinical examination for the signs and symptoms). Our objective is to compare costs and outcomes of plasma oxysterol screening versus current practice in diagnosis of NP-C disease among intellectually disabled (ID) patients using decision-analytic methods.
Methods: A discrete event simulation model was conducted to follow ID patients through the diagnosis and treatment of NP-C, forecast the costs and effectiveness for a cohort of ID patients and compare the outcomes and costs in two different arms of the model: plasma oxysterol screening and routine diagnosis procedure (anno 2013) over 5 years of follow up. Data from published sources and clinical trials were used in simulation model. Unit costs and quality-adjusted life-years (QALYs) were discounted at a 3% annual rate in the base case analysis. Deterministic and probabilistic sensitivity analyses were conducted.
Results: The outcomes of the base case model showed that using plasma oxysterol screening for diagnosis of NP-C disease among ID patients is a dominant strategy. It would result in lower total cost and would slightly improve patients’ quality of life. The average amount of cost saving was $3642 CAD and the incremental QALYs per each individual ID patient in oxysterol screening arm versus current practice of diagnosis NP-C was 0.0022 QALYs. Results of sensitivity analysis demonstrated robustness of the outcomes over the wide range of changes in model inputs.
Conclusion: Whilst acknowledging the limitations of this study, we conclude that screening ID children and adolescents with oxysterol tests compared to current practice for the diagnosis of NP-C is a dominant strategy with clinical and economic benefits. The less costly, more sensitive and specific oxysterol test has potential to save costs to the healthcare system while improving patients’ quality of life and may be considered as a routine tool in the NP-C diagnosis armamentarium for ID. Further research is needed to elucidate its effectiveness in patients presenting characteristics other than ID in childhood and adolescence.

Neurological and Behavioral Disorders

Estrogen receptor signaling during vertebrate development

Maria Bondesson, Ruixin Hao, Chin-Yo Lin, Cecilia Williams, Jan-Åke Gustafsson
Biochimica et Biophysica Acta 1849 (2015) 142–151
http://dx.doi.org/10.1016/j.bbagrm.2014.06.005

Estrogen receptors are expressed and their cognate ligands produced in all vertebrates, indicative of important and conserved functions. Through evolution estrogen has been involved in controlling reproduction, affectingboth the development of reproductive organs and reproductive behavior. This review broadly describes the synthesis of estrogens and the expression patterns of aromatase and the estrogen receptors, in relation to estrogen functions in the developing fetus and child. We focus on the role of estrogens for the development of reproductive tissues, as well as non-reproductive effects on the developing brain. We collate data from human, rodent, bird and fish studies and highlight common and species-specific effects of estrogen signaling on fetal development. Morphological malformations originating from perturbed estrogen signaling in estrogen receptor and aromatase knockout mice are discussed, as well as the clinical manifestations of rare estrogen receptor alpha and aromatase gene mutations in humans. This article is part of a Special Issue entitled: Nuclear receptors in animal development.

 

Memory function and hippocampal volumes in preterm born very-low-birth-weight (VLBW) young adults

Synne Aanes, Knut Jørgen Bjuland, Jon Skranes, Gro C.C. Løhaugen
NeuroImage 105 (2015) 76–83
http://dx.doi.org/10.1016/j.neuroimage.2014.10.023

The hippocampi are regarded as core structures for learning and memory functions, which is important for daily functioning and educational achievements. Previous studies have linked reduction in hippocampal volume to working memory problems in very low birth weight (VLBW; ≤1500 g) children and reduced general cognitive ability in VLBW adolescents. However, the relationship between memory function and hippocampal volume has not been described in VLBW subjects reaching adulthood. The aim of the study was to investigate memory function and hippocampal volume in VLBW young adults, both in relation to perinatal risk factors and compared to term born controls, and to look for structure–function relationships. Using Wechsler Memory Scale-III and MRI, we included 42 non-disabled VLBW and 61 control individuals at age 19–20 years, and related our findings to perinatal risk factors in the VLBW-group. The VLBW young adults achieved lower scores on several subtests of the Wechsler Memory Scale-III, resulting in lower results in the immediate memory indices (visual and auditory), the working memory index, and in the visual delayed and general memory delayed indices, but not in the auditory delayed and auditory recognition delayed indices. The VLBW group had smaller absolute and relative hippocampal volumes than the controls. In the VLBW group inferior memory function, especially for the working memory index, was related to smaller hippocampal volume, and both correlated with lower birth weight and more days in the neonatal intensive care unit (NICU). Our results may indicate a structural–functional relationship in the VLBW group due to aberrant hippocampal development and functioning after preterm birth.

The relation of infant attachment to attachment and cognitive and behavioural outcomes in early childhood

Yan-hua Ding, Xiu Xua, Zheng-yan Wang, Hui-rong Li, Wei-ping Wang
Early Human Development 90 (2014) 459–464
http://dx.doi.org/10.1016/j.earlhumdev.2014.06.004

Background: In China, research on the relation of mother–infant attachment to children’s development is scarce.
Aims: This study sought to investigate the relation of mother–infant attachment to attachment, cognitive and behavioral development in young children.                                                                                                                            Study design: This study used a longitudinal study design.
Subjects: The subjects included healthy infants (n=160) aged 12 to 18 months.
Outcome measures: Ainsworth’s “Strange Situation Procedure” was used to evaluate mother–infant attachment types. The attachment Q-set (AQS) was used to evaluate the attachment between young children and their mothers. The Bayley scale of infant development-second edition (BSID-II) was used to evaluate cognitive developmental level in early childhood. Achenbach’s child behavior checklist (CBCL) for 2- to 3-year-oldswas used to investigate behavioral problems.
Results: In total, 118 young children (73.8%) completed the follow-up; 89.7% of infants with secure attachment and 85.0% of infants with insecure attachment still demonstrated this type of attachment in early childhood (κ = 0.738, p b 0.05). Infants with insecure attachment collectively exhibited a significantly lower mental development index (MDI) in early childhood than did infants with secure attachment, especially the resistant type. In addition, resistant infants were reported to have greater social withdrawal, sleep problems and aggressive behavior in early childhood.
Conclusion: There is a high consistency in attachment development from infancy to early childhood. Secure mother–infant attachment predicts a better cognitive and behavioral outcome; whereas insecure attachment, especially the resistant attachment, may lead to a lower cognitive level and greater behavioral problems in early childhood.

representations of the HPA axis

representations of the HPA axis

representations of limbic stress-integrative pathways from the prefrontal cortex, amygdala and hippocampus

representations of limbic stress-integrative pathways from the prefrontal cortex, amygdala and hippocampus

Fetal programming of schizophrenia: Select mechanisms

Monojit Debnatha, Ganesan Venkatasubramanian, Michael Berk
Neuroscience and Biobehavioral Reviews 49 (2015) 90–104
http://dx.doi.org/10.1016/j.neubiorev.2014.12.003

Mounting evidence indicates that schizophrenia is associated with adverse intrauterine experiences. An adverse or suboptimal fetal environment can cause irreversible changes in brain that can subsequently exert long-lasting effects through resetting a diverse array of biological systems including endocrine, immune and nervous. It is evident from animal and imaging studies that subtle variations in the intrauterine environment can cause recognizable differences in brain structure and cognitive functions in the offspring. A wide variety of environmental factors may play a role in precipitating the emergent developmental dysregulation and the consequent evolution of psychiatric traits in early adulthood by inducing inflammatory, oxidative and nitrosative stress (IO&NS) pathways, mitochondrial dysfunction, apoptosis, and epigenetic dysregulation. However, the precise mechanisms behind such relationships and the specificity of the risk factors for schizophrenia remain exploratory. Considering the paucity of knowledge on fetal programming of schizophrenia, it is timely to consolidate the recent advances in the field and put forward an integrated overview of the mechanisms associated with fetal origin of schizophrenia.

NMDA receptor dysfunction in autism spectrum disorders

Eun-Jae Lee, Su Yeon Choi and Eunjoon Kim
Current Opinion in Pharmacology 2015, 20:8–13
http://dx.doi.org/10.1016/j.coph.2014.10.007

Autism spectrum disorders (ASDs) represent neurodevelopmental disorders characterized by two core symptoms;

(1)  impaired social interaction and communication, and
(2)  restricted and repetitive behaviors, interests, and activities.

ASDs affect ~ 1% of the population, and are considered to be highly genetic in nature. A large number (~600) of ASD-related genetic variations have been identified (sfari.org), and target gene functions are apparently quite diverse. However, some fall onto common pathways, including synaptic function and chromosome remodeling, suggesting that core mechanisms may exist.

Abnormalities and imbalances in neuronal excitatory and inhibitory synapses have been implicated in diverse neuropsychiatric disorders including autism spectrum disorders (ASDs). Increasing evidence indicates that dysfunction of NMDA receptors (NMDARs) at excitatory synapses is associated with ASDs. In support of this, human ASD-associated genetic variations are found in genes encoding NMDAR subunits. Pharmacological enhancement or suppression of NMDAR function ameliorates ASD symptoms in humans. Animal models of ASD display bidirectional NMDAR dysfunction, and correcting this deficit rescues ASD-like behaviors. These findings suggest that deviation of NMDAR function in either direction contributes to the development of ASDs, and that correcting NMDAR dysfunction has therapeutic potential for ASDs.

Among known synaptic proteins implicated in ASD are metabotropic glutamate receptors (mGluRs). Functional enhancement and suppression of mGluR5 are associated with fragile X syndrome and tuberous sclerosis, respectively, which share autism as a common phenotype. More recently, ionotropic glutamate receptors, namely NMDA receptors (NMDARs) and AMPA receptors (AMPARs), have also been implicated in ASDs. In this review, we will focus on NMDA receptors and summarize evidence supporting the hypothesis that NMDAR dysfunction contributes to ASDs, and, by extension, that correcting NMDAR dysfunction has therapeutic potential for ASDs. ASD-related human NMDAR genetic variants.

Chemokines roles within the hippocampus

Chemokines roles within the hippocampus

IL-1 mediates stress-induced activation of the HPA axis

IL-1 mediates stress-induced activation of the HPA axis

A systemic model of the beneficial role of immune processes in behavioral and neural plasticity

A systemic model of the beneficial role of immune processes in behavioral and neural plasticity

Three Classes of Glutamate Receptors

Three Classes of Glutamate Receptors

Clinical studies on ASDs have identified genetic variants of NMDAR subunit genes. Specifically, de novo mutations have been identified in the GRIN2B gene, encoding the GluN2B subunit. In addition, SNP analyses have linked both GRIN2A (GluN2A subunit) and GRIN2B with ASDs. Because assembled NMDARs contain four subunits, each with distinct properties, ASD-related GRIN2A/ GRIN2B variants likely alter the functional properties of NMDARs and/or NMDAR-dependent plasticity.

Pharmacological modulation of NMDAR function can improve ASD symptoms. D-cycloserine (DCS), an NMDAR agonist, significantly ameliorates social withdrawal and repetitive behavior in individuals with ASD. These results suggest that reduced NMDAR function may contribute to the development of ASDs in humans.

We can divide animal studies into two groups. The first group consists of animals in which NMDAR modulators were shown to normalize both NMDAR dysfunction and ASD-like behaviors, establishing strong association between NMDARs and ASD phenotypes (Fig.). In the second group, NMDAR modulators were shown to rescue ASD-like behaviors, but NMDAR dysfunction and its correction have not been demonstrated.

ASD models with data showing rescue of both NMDAR dysfunction and ASD like behaviors Mice lacking neuroligin-1, an excitatory postsynaptic adhesion molecule, show reduced NMDAR function in the hippocampus and striatum, as evidenced by a decrease in NMDA/AMPA ratio and long-term potentiation (LTP). Neuroligin-1 is thought to enhance synaptic NMDAR function, by directly interacting with and promoting synaptic localization of NMDARs.

Fig not shown.

Bidirectional NMDAR dysfunction in animal models of ASD. Animal models of ASD with bidirectional NMDAR dysfunction can be positioned on either side of an NMDAR function curve. Model animals were divided into two groups.

Group 1: NMDAR modulators normalize both NMDAR dysfunction and ASD-like behaviors (green).

Group 2: NMDAR modulators rescue ASD-like behaviors, but NMDAR dysfunction and its rescue have not been demonstrated (orange). Note that Group 2 animals are tentatively placed on the left-hand side of the slope based on the observed DCS rescue of their ASD-like phenotypes, but the directions of their NMDAR dysfunctions remain to be experimentally determined.

ASD models with data showing rescue of ASD-like behaviors but no demonstrated NMDAR dysfunction

Tbr1 is a transcriptional regulator, one of whose targets is the gene encoding the GluN2B subunit of NMDARs. Mice haploinsufficient for Tbr1 (Tbr1+/-) show structural abnormalities in the amygdala and limited GluN2B induction upon behavioral stimulation. Both systemic injection and local amygdalar infusion of DCS rescue social deficits and impaired associative memory in Tbr1+/- mice. However, reduced NMDAR function and its DCS-dependent correction have not been demonstrated.

Spatial working memory and attention skills are predicted by maternal stress during pregnancy

André Plamondon, Emis Akbari, Leslie Atkinson, Meir Steiner
Early Human Development 91 (2015) 23–29
http://dx.doi.org/10.1016/j.earlhumdev.2014.11.004

Introduction: Experimental evidence in rodents shows that maternal stress during pregnancy (MSDP) negatively impacts spatial learning and memory in the offspring. We aim to investigate the association between MSDP (i.e., life events) and spatial working memory, as well as attention skills (attention shifting and attention focusing), in humans. The moderating roles of child sex, maternal anxiety during pregnancy and postnatal care are also investigated.  Methods: Participants were 236mother–child dyads that were followed from the second trimester of pregnancy until 4 years postpartum. Measurements included questionnaires and independent observations.
Results: MSDP was negatively associated with attention shifting at 18monthswhen concurrent maternal anxiety was low. MSDP was associated with poorer spatial working memory at 4 years of age, but only for boys who experienced poorer postnatal care.
Conclusion: Consistent with results observed in rodents, MSDP was found to be associated with spatial working memory and attention skills. These results point to postnatal care and maternal anxiety during pregnancy as potential targets for interventions that aim to buffer children from the detrimental effects of MSDP.

Acute and massive bleeding from placenta previa and infants’ brain damage

Ken Furuta, Shuichi Tokunaga, Seishi Furukawa, Hiroshi Sameshima
Early Human Development 90 (2014) 455–458
http://dx.doi.org/10.1016/j.earlhumdev.2014.06.002

Background: Among the causes of third trimester bleeding, the impact of placenta previa on cerebral palsy is not well known.
Aims: To clarify the effect ofmaternal bleeding fromplacenta previa on cerebral palsy, and in particular when and how it occurs.
Study design: A descriptive study.
Subjects: Sixty infants born to mothers with placenta previa in our regional population-based study of 160,000 deliveries from 1998 to 2012. Premature deliveries occurring atb26 weeks of gestation and placenta accrete were excluded.
Outcome measures: Prevalence of cystic periventricular leukomalacia (PVL) and cerebral palsy (CP).
Results: Five infants had PVL and 4 of these infants developed CP (1/40,000 deliveries). Acute and massive bleeding (>500 g) within 8 h) occurred at around 30–31 weeks of gestation, and was severe enough to deliver the fetus. None of the 5 infants with PVL underwent antenatal corticosteroid treatment, and 1 infant had mild neonatal hypocapnia with a PaCO2 < 25 mm Hg. However, none of the 5 PVL infants showed umbilical arterial academia with pH < 7.2, an abnormal fetal heart rate monitoring pattern, or neonatal hypotension.
Conclusions: Our descriptive study showed that acute and massive bleeding from placenta previa at around 30 weeks of gestation may be a risk factor for CP, and requires careful neonatal follow-up. The underlying process connecting massive placental bleeding and PVL requires further investigation.

Impact of bilirubin-induced neurologic dysfunction on neurodevelopmental outcomes

Courtney J. Wusthoff, Irene M. Loe
Seminars in Fetal & Neonatal Medicine 20 (2015) 52e57
http://dx.doi.org/10.1016/j.siny.2014.12.003

Extreme neonatal hyperbilirubinemia has long been known to cause the clinical syndrome of kernicterus, or chronic bilirubin encephalopathy (CBE). Kernicterus most usually is characterized by choreoathetoid cerebral palsy (CP), impaired upward gaze, and sensorineural hearing loss, whereas cognition is relatively spared. The chronic condition of kernicterus may be, but is not always, preceded in the acute stage by acute bilirubin encephalopathy (ABE). This acute neonatal condition is also due to hyperbilirubinemia, and is characterized by lethargy and abnormal behavior, evolving to frank neonatal encephalopathy, opisthotonus, and seizures. Less completely defined is the syndrome of bilirubin-induced neurologic dysfunction (BIND).

Bilirubin-induced neurologic dysfunction (BIND) is the constellation of neurologic sequelae following milder degrees of neonatal hyperbilirubinemia than are associated with kernicterus. Clinically, BIND may manifest after the neonatal period as developmental delay, cognitive impairment, disordered executive function, and behavioral and psychiatric disorders. However, there is controversy regarding the relative contribution of neonatal hyperbilirubinemia versus other risk factors to the development of later neurodevelopmental disorders in children with BIND. In this review, we focus on the empiric data from the past 25 years regarding neurodevelopmental outcomes and BIND, including specific effects on developmental delay, cognition, speech and language development, executive function, and the neurobehavioral disorders, such as attention deficit/hyperactivity disorder and autism.

As noted in a technical report by the American Academy of Pediatrics Subcommittee on Hyperbilirubinemia, “it is apparent that the use of a single total serum bilirubin level to predict long-term outcomes is inadequate and will lead to conflicting results”. As described above, this has certainly been the case in research to date. To clarify how hyperbilirubinemia influences neurodevelopmental outcome, more sophisticated consideration is needed both of how to assess bilirubin exposure leading to neurotoxicity, and of those comorbid conditions which may lower the threshold for brain injury.

For example, premature infants are known to be especially susceptible to bilirubin neurotoxicity, with kernicterus reported following TB levels far lower than the threshold expected in term neonates. Similarly, among extremely preterm neonates, BBC is proportional to gestational age, meaning that the most premature infants have the highest UB, even for similar TB levels. Thus, future studies must be adequately powered to examine preterm infants separately from term infants, and should consider not just peak TB, but also BBC, as independent variables in neonates with hyperbilirubinemia. Similarly, an analysis by the NICHD NRN found that, among ELBW infants, higher UB levels were associated with a higher risk of death or NDI. However, increased TB levels were only associated with death or NDI in unstable infants. Again, UB or BBC appeared to be more useful than TB.

Are the neuromotor disabilities of bilirubin-induced neurologic dysfunction disorders related to the cerebellum and its connections?

Jon F. Watchko, Michael J. Painter, Ashok Panigrahy
Seminars in Fetal & Neonatal Medicine 20 (2015) 47e51
http://dx.doi.org/10.1016/j.siny.2014.12.004

Investigators have hypothesized a range of subcortical neuropathology in the genesis of bilirubin induced neurologic dysfunction (BIND). The current review builds on this speculation with a specific focus on the cerebellum and its connections in the development of the subtle neuromotor disabilities of BIND. The focus on the cerebellum derives from the following observations:
(i) the cerebellum is vulnerable to bilirubin-induced injury; perhaps the most vulnerable region within the central nervous system;
(ii) infants with cerebellar injury exhibit a neuromotor phenotype similar to BIND; and                                                       (iii) the cerebellum has extensive bidirectional circuitry projections to motor and non-motor regions of the brain-stem and cerebral cortex that impact a variety of neurobehaviors.
Future study using advanced magnetic resonance neuroimaging techniques have the potential to shed new insights into bilirubin’s effect on neural network topology via both structural and functional brain connectivity measurements.

Bilirubin-induced neurologic damage is most often thought of in terms of severe adverse neuromotor (dystonia with or without athetosis) and auditory (hearing impairment or deafness) sequelae. Observed together, they comprise the classic neurodevelopmental phenotype of chronic bilirubin encephalopathy or kernicterus, and may also be seen individually as motor or auditory predominant subtypes. These injuries reflect both a predilection of bilirubin toxicity for neurons (relative to glial cells) and the regional topography of bilirubin-induced neuronal damage characterized by prominent involvement of the globus pallidus, subthalamic nucleus, VIII cranial nerve, and cochlear nucleus.

It is also asserted that bilirubin neurotoxicity may be associated with other less severe neurodevelopmental disabilities, a condition termed “subtle kernicterus” or “bilirubin-induced neurologic dysfunction” (BIND). BIND is defined by a constellation of “subtle neurodevelopmental disabilities without the classical findings of kernicterus that, after careful evaluation and exclusion of other possible etiologies, appear to be due to bilirubin neurotoxicity”. These purportedly include:

(i) mild-to-moderate disorders of movement (e.g., incoordination, clumsiness, gait abnormalities, disturbances in static and dynamic balance, impaired fine motor skills, and ataxia);                                                                                             (ii) disturbances in muscle tone; and
(iii) altered sensorimotor integration. Isolated disturbances of central auditory processing are also included in the spectrum of BIND.

  • Cerebellar vulnerability to bilirubin-induced injury
  • Cerebellar injury phenotypes and BIND
  • Cerebellar projections
Transverse section of cerebellum and brainstem

Transverse section of cerebellum and brainstem

Transverse section of cerebellum and brain-stem from a 34 gestational-week premature kernicteric infant formalin-fixed for two weeks. Yellow staining is evident in the cerebellar dentate nuclei (upper arrow) and vestibular nuclei at the pontomedullary junction (lower arrowhead). Photo is courtesy of Mahmdouha Ahdab-Barmada and reprinted with permission from Taylor-Francis Group (Ahdab Barmada M. The neuropathology of kernicterus: definitions and debate. In: Maisel MJ, Watchko JF editors. Neonatal jaundice. Amsterdam: Harwood Academic Publishers; 2000. p. 75e88

Whether cerebellar injury is primal or an integral part of disturbed neural circuitry in bilirubin-induced CNS damage is unclear. Movement disorders, however, are increasingly recognized to arise from abnormalities of neuronal circuitry rather than localized, circumscribed lesions. The cerebellum has extensive bidirectional circuitry projections to an array of brainstem nuclei and the cerebral cortex that modulate and refine motor activities. In this regard, the cerebellum is characteristically subdivided into three lobes based on neuroanatomic and phylogenetic criteria as well as by their primary afferent and efferent connections. They include:
(i) flocculonodular lobe (archicerebellum);
(ii) anterior lobe (paleocerebellum); and
(iii) posterior lobe (neocerebellum).

The archicerebellum, the oldest division phylogenically, receives extensive input from the vestibular system and is therefore also known as the vestibulocerebellum and is important for equilibrium control. The paleocerebellum, also a primitive region, receives extensive somatosensory input from the spinal cord, including the anterior and posterior spinocerebellar pathways that convey unconscious proprioception, and is therefore also known as the spinocerebellum. The neocerebellum is the most recently evolved region, receives most of the input from the cerebral cortex, and is thus termed the cerebrocerebellum. This area has greatly expanded in association with the extensive development of the cerebral cortex in mammals and especially primates. To cause serious longstanding dysfunction, cerebellar injury must typically involve the deep cerebellar nuclei and their projections.

Schematic of the bidirectional connectivity between the cerebellum and other

Schematic of the bidirectional connectivity between the cerebellum and other

Schematic of the bidirectional connectivity between the cerebellum and other brain regions including the cerebral cortex. Most cerebro-cerebellar afferent projections pass through the basal (anterior or ventral) pontine nuclei and intermediate cerebellar peduncle, whereas most cerebello-cerebral efferent projections pass through the dentate and ventrolateral thalamic nuclei. DCN, deep cerebellar nuclei; RN, red nucleus; ATN, anterior thalamic nucleus; PFC, prefrontal cortex; MC, motor cortex; PC, parietal cortex; TC, temporal cortex; STN, subthalamic nucleus; APN, anterior pontine nuclei. Reprinted under the terms of the Creative Commons Attribution License from D’Angelo E, Casali S. Seeking a unified framework for cerebellar function and dysfunction: from circuit to cognition. Front Neural Circuits 2013; 6:116.

Given the vulnerability of the cerebellum to bilirubin-induced injury, cerebellar involvement should also be evident in classic kernicterus, contributing to neuromotor deficits observed therein. It is of interest, therefore, that cerebellar damage may play a role in the genesis of bilirubin-induced dystonia, a prominent neuromotor feature of chronic bilirubin encephalopathy in preterm and term neonates alike. This complex movement disorder is characterized by involuntary sustained muscle contractions that result in abnormal position and posture. Moreover, dystonia that is brief in duration results in chorea, and, if brief and repetitive, leads to athetosis ‒ conditions also classically observed in kernicterus. Recent evidence suggests that dystonic movements may depend on disruption of both basal ganglia and cerebellar neuronal networks, rather than isolated dysfunction of only one motor system.

Dystonia is also a prominent feature in Gunn rat pups and neonatal Ugt1‒/‒-deficient mice both robust models of kernicterus. The former is used as an experimental model of dystonia. Although these models show basal ganglia injury, the sine qua non of bilirubin-induced murine neuropathology is cerebellar damage and resultant cerebellar hypoplasia.

Studies are needed to define more precisely the motor network abnormalities in kernicterus and BIND. Magnetic resonance imaging (MRI) has been widely used in evaluating infants at risk for bilirubin-induced brain injury using conventional structural T1-and T2-weighted imaging. Infants with chronic bilirubin encephalopathy often demonstrate abnormal bilateral, symmetric, high-signal intensity on T2-weighted MRI of the globus pallidus and subthalamic nucleus, consistent with the neuropathology of kernicterus. Early postnatal MRI of at-risk infants, although frequently showing increased T1-signal in these regions, may give false-positive findings due to the presence of myelin in these structures.

Diffusion tensor imaging and tractography could be used to delineate long-term changes involving specific white matter pathways, further elucidating the neural basis of long-term disability in infants and children with chronic bilirubin encephalopathy and BIND. It will be equally valuable to use blood oxygen level-dependent (BOLD) “resting state” functional MRI to study intrinsic connectivity in order to identify vulnerable brain networks in neonates with kernicterus and BIND. Structural networks of the CNS (connectome) and functional network topology can be characterized in infants with kernicterus and BIND to determine disease-related pattern(s) with respect to both long- and short-range connectivity. These findings have the potential to shed novel insights into the pathogenesis of these disorders and their impact on complex anatomical connections and resultant functional deficits.

Audiologic impairment associated with bilirubin-induced neurologic damage

Cristen Olds, John S. Oghalai
Seminars in Fetal & Neonatal Medicine 20 (2015) 42e46
http://dx.doi.org/10.1016/j.siny.2014.12.006

Hyperbilirubinemia affects up to 84% of term and late preterm infants in the first week of life. The elevation of total serum/plasma bilirubin (TB) levels is generally mild, transitory, and, for most children, inconsequential. However, a subset of infants experiences lifelong neurological sequelae. Although the prevalence of classic kernicterus has fallen steadily in the USA in recent years, the incidence of jaundice in term and premature infants has increased, and kernicterus remains a significant problem in the global arena. Bilirubin-induced neurologic dysfunction (BIND) is a spectrum of neurological injury due to acute or sustained exposure of the central nervous system(CNS) to bilirubin. The BIND spectrum includes kernicterus, acute bilirubin encephalopathy, and isolated neural pathway dysfunction.

Animal studies have shown that unconjugated bilirubin passively diffuses across cell membranes and the blood‒brain barrier (BBB), and bilirubin not removed by organic anion efflux pumps accumulates within the cytoplasm and becomes toxic. Exposure of neurons to bilirubin results in increased oxidative stress and decreased neuronal proliferation and presynaptic neuro-degeneration at central glutaminergic synapses. Furthermore, bilirubin administration results in smaller spiral ganglion cell bodies, with decreased cellular density and selective loss of large cranial nerve VIII myelinated fibers. When exposed to bilirubin, neuronal supporting cells have been found to secrete inflammatory markers, which contribute to increased BBB permeability and bilirubin loading.

The jaundiced Gunn rat is the classic animal model of bilirubin toxicity. It is homozygous for a premature stop codon within the gene for UDP-glucuronosyltransferase family 1 (UGT1). The resultant gene product has reduced bilirubin-conjugating activity, leading to a state of hyperbilirubinemia. Studies with this rat model have led to the concept that impaired calcium homeostasis is an important mechanism of neuronal toxicity, with reduced expression of calcium-binding proteins in affected cells being a sensitive index of bilirubin-induced neurotoxicity. Similarly, application of bilirubin to cultured auditory neurons from brainstem cochlear nuclei results in hyperexcitability and excitotoxicity.

The auditory pathway and normal auditory brainstem response (ABR).

The auditory pathway and normal auditory brainstem response (ABR).

The auditory pathway and normal auditory brain-stem response (ABR). The ipsilateral (green) and contralateral (blue) auditory pathways are shown, with structures that are known to be affected by hyperbilirubinemia highlighted in red. Roman numerals in parentheses indicate corresponding waves in the normal human ABR (inset). Illustration adapted from the “Ear Anatomy” series by Robert Jackler and Christine Gralapp, with permission.

Bilirubin-induced neurologic dysfunction (BIND)

Vinod K. Bhutani, Ronald Wong
Seminars in Fetal & Neonatal Medicine 20 (2015) 1
http://dx.doi.org/10.1016/j.siny.2014.12.010

Beyond the traditional recognized areas of fulminant injury to the globus pallidus as seen in infants with kernicterus, other vulnerable areas include the cerebellum, hippocampus, and subthalamic nuclear bodies as well as certain cranial nerves. The hippocampus is a brain region that is particularly affected by age related morphological changes. It is generally assumed that a loss in hippocampal volume results in functional deficits that contribute to age-related cognitive deficits. Lower grey matter volumes within the limbic-striato-thalamic circuitry are common to other etiological mechanisms of subtle neurologic injury. Lower grey matter volumes in the amygdala, caudate, frontal and medial gyrus are found in schizophrenia and in the putamen in autism. Thus, in terms of brain volumetrics, schizophrenia and autism spectrum disorders have a clear degree of overlap that may reflect shared etiological mechanisms. Overlap with injuries observed in infants with BIND raises the question about how these lesions are arrived at in the context of the impact of common etiologies.

Stress-induced perinatal and transgenerational epigenetic programming of brain development and mental health

Olena Babenko, Igor Kovalchuk, Gerlinde A.S. Metz
Neuroscience and Biobehavioral Reviews 48 (2015) 70–91
http://dx.doi.org/10.1016/j.neubiorev.2014.11.013

Research efforts during the past decades have provided intriguing evidence suggesting that stressful experiences during pregnancy exert long-term consequences on the future mental wellbeing of both the mother and her baby. Recent human epidemiological and animal studies indicate that stressful experiences in utero or during early life may increase the risk of neurological and psychiatric disorders, arguably via altered epigenetic regulation. Epigenetic mechanisms, such as miRNA expression, DNA methylation, and histone modifications are prone to changes in response to stressful experiences and hostile environmental factors. Altered epigenetic regulation may potentially influence fetal endocrine programming and brain development across several generations. Only recently, however, more attention has been paid to possible transgenerational effects of stress. In this review we discuss the evidence of transgenerational epigenetic inheritance of stress exposure in human studies and animal models. We highlight the complex interplay between prenatal stress exposure, associated changes in miRNA expression and DNA methylation in placenta and brain and possible links to greater risks of schizophrenia, attention deficit hyperactivity disorder, autism, anxiety- or depression-related disorders later in life. Based on existing evidence, we propose that prenatal stress, through the generation of epigenetic alterations, becomes one of the most powerful influences on mental health in later life. The consideration of ancestral and prenatal stress effects on lifetime health trajectories is critical for improving strategies that support healthy development and successful aging.

Sensitive time-windows for susceptibility in neurodevelopmental disorders

Rhiannon M. Meredith, Julia Dawitz and Ioannis Kramvis
Trends in Neurosciences, June 2012; 35(6): 335-344
http://dx.doi.org:/10.1016/j.tins.2012.03.005

Many neurodevelopmental disorders (NDDs) are characterized by age-dependent symptom onset and regression, particularly during early postnatal periods of life. The neurobiological mechanisms preceding and underlying these developmental cognitive and behavioral impairments are, however, not clearly understood. Recent evidence using animal models for monogenic NDDs demonstrates the existence of time-regulated windows of neuronal and synaptic impairments. We propose that these developmentally-dependent impairments can be unified into a key concept: namely, time-restricted windows for impaired synaptic phenotypes exist in NDDs, akin to critical periods during normal sensory development in the brain. Existence of sensitive time-windows has significant implications for our understanding of early brain development underlying NDDs and may indicate vulnerable periods when the brain is more susceptible to current therapeutic treatments.

Fig (not shown)

Misregulated mechanisms underlying spine morphology in NDDs. Several proteins implicated in monogenic NDDs (highlighted in red) are linked to the regulation of the synaptic cytoskeleton via F-actin through different Rho-mediated signaling pathways (highlighted in green). Mutations in OPHN1, TSC1/2, FMRP, p21-activated kinase (PAK) are directly linked to human NDDs of intellectual disability. For instance, point mutations in OPHN1 and a PAK isoform are linked to non-syndromic mental retardation, whereas mutations or altered expression of TSC1/2 and FMRP are linked to TSC and FXS, respectively. Cytoplasmic interacting protein (CYFIP) and LIM-domain kinase 1 (LIMK1) are known to interact with FMRP and PAK, respectively [105]. LIMK1 is one of many dysregulated proteins contributing to the NDD Williams syndrome. Mouse models are available for all highlighted (red) proteins and reveal specific synaptic and behavioral deficits. Local protein synthesis in synapses, dendrites and glia is also regulated by proteins such as TSC1/2 and the FMRP/CYFIP complex. Abbreviations: 4EBP, 4E binding protein; eIF4E, eukaryotic translation initiation factor 4E.

Fig (not shown)

Sensitive time-windows, synaptic phenotypes and NDD gene targets. Sensitive time-windows exist in neural circuits, during which gene targets implicated in NDDs are normally expressed. Misregulation of these genes can affect multiple synaptic phenotypes during a restricted developmental period. The effect upon synaptic phenotypes is dependent upon the temporal expression of these NDD genes and their targets. (a) Expression outside a critical period of development will have no effect upon synaptic phenotypes. (b,c) A temporal expression pattern that overlaps with the onset (b) or closure (c) of a known critical period can alter the synaptic phenotype during that developmental time-window.

Outstanding questions

(1) Can treatment at early presymptomatic stages in animal models for NDDs prevent or ease the later synaptic, neuronal, and behavioral impairments?

(2) Are all sensory critical periods equally misregulated in mouse models for a specific NDD? Are there different susceptibilities for auditory, visual and somatosensory neurocircuits that reflect the degree of impairments observed in patients?

(3) If one critical period is missed or delayed during formation of a layer-specific connection in a network, does the network overcome this misregulated connectivity or plasticity window?

(4) In monogenic NDDs, does the severity of misregulating one particular time-window for synaptic establishment during development correlate with the importance of that gene for that synaptic circuit?

(5) Why do critical periods close in brain development?

(6) What underlies the regression of some altered synaptic phenotypes in Fmr1-KO mice?

(7) Can the concept of susceptible time-windows be applied to other NDDs, including schizophrenia and Tourette’s syndrome?

Cardiovascular

Cardiac output monitoring in newborns

Willem-Pieter de Boode
Early Human Development 86 (2010) 143–148
http://dx.doi.org:/10.1016/j.earlhumdev.2010.01.032

There is an increased interest in methods of objective cardiac output measurement in critically ill patients. Several techniques are available for measurement of cardiac output in children, although this remains very complex in newborns. Cardiac output monitoring could provide essential information to guide hemodynamic management. An overview is given of various methods of cardiac output monitoring with advantages and major limitations of each technology together with a short explanation of the basic principles.

Fick principle

According to the Fick principle the volume of blood flow in a given period equals the amount of substance entering the blood stream in the same period divided by the difference in concentrations of the substrate upstream respectively downstream to the point of entry in the circulation. This substance can be oxygen (O2-Fick) or carbon dioxide (CO2-FICK), so cardiac output can be calculated by dividing measured pulmonary oxygen uptake by the arteriovenous oxygen concentration difference. The direct O2-Fick method is regarded as gold standard in cardiac output monitoring in a research setting, despite its limitations. When the Fick principle is applied for carbon dioxide (CO2 Fick), the pulmonary carbon dioxide exchange is divided by the venoarterial CO2 concentration difference to calculate cardiac output.

In the modified CO2 Fick method pulmonary CO2 exchange is measured at the endotracheal tube. Measurement of total CO2 concentration in blood is more complex and simultaneous sampling of arterial and central venous blood is required. However, frequent blood sampling will result in an unacceptable blood loss in the neonatal population.

Blood flow can be calculated if the change in concentration of a known quantity of injected indicator is measured in time distal to the point of injection, so an indicator dilution curve can be obtained. Cardiac output can then be calculated with the use of the Stewart–Hamilton equation. Several indicators are used, such as indocyanine green, Evans blue and brilliant red in dye dilution, cold solutions in thermodilution, lithium in lithium dilution, and isotonic saline in ultrasound dilution.

Cardiovascular adaptation to extra uterine life

Alice Lawford, Robert MR Tulloh
Paediatrics And Child Health 2014; 25(1): 1-6.

The adaptation to extra uterine life is of interest because of its complexity and the ability to cause significant health concerns. In this article we describe the normal changes that occur and the commoner abnormalities that are due to failure of normal development and the effect of congenital cardiac disease. Abnormal development may occur as a result of problems with the mother, or with the fetus before birth. After birth it is essential to determine whether there is an underlying abnormality of the fetal pulmonary or cardiac development and to determine the best course of management of pulmonary hypertension or congenital cardiac disease. Causes of underdevelopment, maldevelopment and maladaptation are described as are the causes of critical congenital heart disease. The methods of diagnosis and management are described to allow the neonatologist to successfully manage such newborns.

Fetal vascular structures that exist to direct blood flow

Fetal structure Function
Arterial duct Connects pulmonary artery to the aorta and shunts blood right to left; diverting flow away from fetal lungs
Foramen ovale Opening between the two atria thatdirects blood flow returning to right

atrium through the septal wall into the left atrium bypassing lungs

Ductus venosus Receives oxygenated blood fromumbilical vein and directs it to the

inferior vena cava and right atrium

Umbilical arteries Carrying deoxygenated blood fromthe fetus to the placenta
Umbilical vein Carrying oxygenated blood from theplacenta to the fetus

Maternal causes of congenital heart disease

Maternal disorders rubella, SLE, diabetes mellitus
Maternal drug use Warfarin, alcohol
Chromosomal abnormality Down, Edward, Patau, Turner, William, Noonan

 

Fetal and Neonatal Circulation  The fetal circulation is specifically adapted to efficiently exchange gases, nutrients, and wastes through placental circulation. Upon birth, the shunts (foramen ovale, ductus arteriosus, and ductus venosus) close and the placental circulation is disrupted, producing the series circulation of blood through the lungs, left atrium, left ventricle, systemic circulation, right heart, and back to the lungs.

Clinical monitoring of systemic hemodynamics in critically ill newborns

Willem-Pieter de Boode
Early Human Development 86 (2010) 137–141
http://dx.doi.org:/10.1016/j.earlhumdev.2010.01.031

Circulatory failure is a major cause of mortality and morbidity in critically ill newborn infants. Since objective measurement of systemic blood flow remains very challenging, neonatal hemodynamics is usually assessed by the interpretation of various clinical and biochemical parameters. An overview is given about the predictive value of the most used indicators of circulatory failure, which are blood pressure, heart rate, urine output, capillary refill time, serum lactate concentration, central–peripheral temperature difference, pH, standard base excess, central venous oxygen saturation and color.

Key guidelines

➢ The clinical assessment of cardiac output by the interpretation of indirect parameters of systemic blood flow is inaccurate, irrespective of the level of experience of the clinician

➢ Using blood pressure to diagnose low systemic blood flow will consequently mean that too many patients will potentially be undertreated or overtreated, both with substantial risk of adverse effects and iatrogenic damage.

➢ Combining different clinical hemodynamic parameters enhances the predictive value in the detection of circulatory failure, although accuracy is still limited.

➢ Variation in time (trend monitoring) might possibly be more informative than individual, static values of clinical and biochemical parameters to evaluate the adequacy of neonatal circulation.

Monitoring oxygen saturation and heart rate in the early neonatal period

J.A. Dawson, C.J. Morley
Seminars in Fetal & Neonatal Medicine 15 (2010) 203e207
http://dx.doi.org:/10.1016/j.siny.2010.03.004

Pulse oximetry is commonly used to assist clinicians in assessment and management of newly born infants in the delivery room (DR). In many DRs, pulse oximetry is now the standard of care for managing high risk infants, enabling immediate and dynamic assessment of oxygenation and heart rate. However, there is little evidence that using pulse oximetry in the DR improves short and long term outcomes. We review the current literature on using pulse oximetry to measure oxygen saturation and heart rate and how to apply current evidence to management in the DR.

Practice points

  • Understand how SpO2 changes in the first minutes after birth.
  • Apply a sensor to an infant’s right wrist as soon as possible after birth.
  • Attach sensor to infant then to oximeter cable.
  • Use two second averaging and maximum sensitivity.

Using pulse oximetry assists clinicians:

  1. Assess changes in HR in real time during transition.
  2. Assess oxygenation and titrate the administration of oxygen to maintain oxygenation within the appropriate range for SpO2 during the first minutes after birth.

Research directions

  • What are the appropriate centiles to target during the minutes after birth to prevent hypoxia and hyperoxia: 25th to 75th, or 10th to 90th, or just the 50th (median)?
  • Can the inspired oxygen be titrated against the SpO2 to keep the SpO2 in the ‘normal range’?
  • Does the use of centile charts in the DR for HR and oxygen saturation reduce the rate of hyperoxia when infants are treated with oxygen.
  • Does the use of pulse oximetry immediately after birth improve short term outcomes, e.g. efficacy of immediate respiratory support, intubation rates in the DR, percentage of inspired oxygen, rate of use of adrenalin or chest compressions, duration of hypoxia/hyperoxia and bradycardia.
  • Does the use of pulse oximetry in the DR improve short term respiratory and long term neurodevelopmental outcomes for preterm infants, e.g. rate of intubation, use of surfactant, and duration of ventilation, continuous positive airway pressure, or supplemental oxygen?
  • Can all modern pulse oximeters be used effectively in the DR or do some have a longer delay before giving an accurate signal and more movement artefact?
  • Would a longer averaging time result in more stable data?

Peripheral haemodynamics in newborns: Best practice guidelines

Michael Weindling, Fauzia Paize
Early Human Development 86 (2010) 159–165
http://dx.doi.org:/10.1016/j.earlhumdev.2010.01.033

Peripheral hemodynamics refers to blood flow, which determines oxygen and nutrient delivery to the tissues. Peripheral blood flow is affected by vascular resistance and blood pressure, which in turn varies with cardiac function. Arterial oxygen content depends on the blood hemoglobin concentration (Hb) and arterial pO2; tissue oxygen delivery depends on the position of the oxygen-dissociation curve, which is determined by temperature and the amount of adult or fetal hemoglobin. Methods available to study tissue perfusion include near-infrared spectroscopy, Doppler flowmetry, orthogonal polarization spectral imaging and the peripheral perfusion index. Cardiac function, blood gases, Hb, and peripheral temperature all affect blood flow and oxygen extraction. Blood pressure appears to be less important. Other factors likely to play a role are the administration of vasoactive medications and ventilation strategies, which affect blood gases and cardiac output by changing the intrathoracic pressure.

graphic

NIRS with partial venous occlusion to measure venous oxygen saturation

NIRS with partial venous occlusion to measure venous oxygen saturation

NIRS with partial venous occlusion to measure venous oxygen saturation. Taken from Yoxall and Weindling

Schematic representation of the biphasic relationship between oxygen delivery and oxygen consumption in tissue

Schematic representation of the biphasic relationship between oxygen delivery and oxygen consumption in tissue

graphic

Schematic representation of the biphasic relationship between oxygen delivery and oxygen consumption in tissue.  (a) oxygen delivery (DO2). (b) As DO2 decreases, VO2 is dependent on DO2. The slope of the line indicates the FOE, which in this case is about 0.50. (c) The slope of the line indicates the FOE in the normal situation where oxygenation is DO2 independent, usually < 0.35

The oxygen-dissociation curve

The oxygen-dissociation curve

graphic

The oxygen-dissociation curve

Considerable information about the response of the peripheral circulation has been obtained using NIRS with venous occlusion. Although these measurements were validated against blood co-oximetry in human adults and infants, they can only be made intermittently by a trained operator and are thus not appropriate for general clinical use. Further research is needed to find other better measures of peripheral perfusion and oxygenation which may be easily and continuously monitored, and which could be useful in a clinical setting.

Peripheral oxygenation and management in the perinatal period

Michael Weindling
Seminars in Fetal & Neonatal Medicine 15 (2010) 208e215
http://dx.doi.org:/10.1016/j.siny.2010.03.005

The mechanisms for the adequate provision of oxygen to the peripheral tissues are complex. They involve control of the microcirculation and peripheral blood flow, the position of the oxygen dissociation curve including the proportion of fetal and adult hemoglobin, blood gases and viscosity. Systemic blood pressure appears to have little effect, at least in the non-shocked state. The adequate delivery of oxygen (DO2) depends on consumption (VO2), which is variable. The balance between VO2 and DO2 is given by fractional oxygen extraction (FOE ¼ VO2/DO2). FOE varies from organ to organ and with levels of activity. Measurements of FOE for the whole body produce a range of about 0.15-0.33, i.e. the body consumes 15-33% of oxygen transported.

Fig (not shown)

Biphasic relationship between oxygen delivery (DO2) and oxygen consumption (VO2) in tissue. Dotted lines show fractional oxygen extraction (FOE). ‘A’ indicates the normal situation when VO2 is independent ofDO2 and FOE is about 0.30. AsDO2 decreases in the direction of the arrow, VO2 remains independent of DO2 until the critical point is reached at ‘B’; in this illustration, FOE is about 0.50. The slope of the dotted line indicates the FOE (¼ VO2/DO2), which increases progressively as DO2 decreases.

Relationship between haemoglobin F fraction (HbF) and peripheral fractional oxygen extraction

Relationship between haemoglobin F fraction (HbF) and peripheral fractional oxygen extraction

Graphic
(A)Relationship between haemoglobin F fraction (HbF) and peripheral fractional oxygen extraction in anaemic and control infants. (From Wardle et al.)  (B) HbF synthesis and concentration. (From Bard and Widness.) (C) Oxygen dissociation curve.

Peripheral fractional oxygen extraction in babies

Peripheral fractional oxygen extraction in babies

graphic

Peripheral fractional oxygen extraction in babies with asymptomatic or symptomatic anemia compared to controls. Bars represent the median for each group. (From Wardle et al.)

Practice points

  • Peripheral tissue DO2 is complex: cardiac function, blood gases, Hb concentration and the proportion of HbF, and peripheral temperature all play a part in determining blood flow and oxygen extraction in the sick, preterm infant. Blood pressure appears to be less important.
  • Other factors likely to play a role are the administration of vasoactive medications and ventilation strategies, which affect blood gases and cardiac output by changing intrathoracic pressure.
  • Central blood pressure is a poor surrogate measurement for the adequacy of DO2 to the periphery. Direct measurement, using NIRS, laser Doppler flowmetry or other means, may give more useful information.
  • Reasons for total hemoglobin concentration (Hb) being a relatively poor indicator of the adequacy of the provision of oxygen to the tissues:
  1. Hb is only indirectly related to red blood cell volume, which may be a better indicator of the body’s oxygen delivering capacity.
  2. Hb-dependent oxygen availability depends on the position of the oxygen-hemoglobin dissociation curve.
  3. An individual’s oxygen requirements vary with time and from organ to organ. This means that DO2 also needs to vary.
  4. It is possible to compensate for a low Hb by increasing cardiac output and ventilation, and so the ability to compensate for anemia depends on an individual’s cardio-respiratory reserve as well as Hb.
  5. The normal decrease of Hb during the first few weeks of life in both full-term and preterm babies usually occurs without symptoms or signs of anemia or clinical consequences.

The relationship between VO2 and DO2 is complex and various factors need to be taken into account, including the position of the oxygen dissociation curve, determined by the proportion of HbA and HbF, temperature and pH. Furthermore, diffusion of oxygen from capillaries to the cell depends on the oxygen tension gradient between erythrocytes and the mitochondria, which depends on microcirculatory conditions, e.g. capillary PO2, distance of the cell from the capillary (characterized by intercapillary distances) and the surface area of open capillaries. The latter can change rapidly, for example, in septic shock where arteriovenous shunting occurs associated with tissue hypoxia in spite of high DO2 and a low FOE.

Changes in local temperature deserve particular consideration. When the blood pressure is low, there may be peripheral vasoconstriction with decreased local perfusion and DO2. However, the fall in local tissue temperature would also be expected to be associated with a decreased metabolic rate and a consequent decrease in VO2. Thus a decreased DO2 may still be appropriate for tissue needs.

Pulmonary

Accurate Measurements of Oxygen Saturation in Neonates: Paired Arterial and Venous Blood Analyses

Shyang-Yun Pamela K. Shiao
Newborn and Infant Nurs Rev,  2005; 5(4): 170–178
http://dx.doi.org:/10.1053/j.nainr.2005.09.001

Oxygen saturation (So2) measurements (functional measurement, So2; and fractional measurement, oxyhemoglobin [Hbo2]) and monitoring are commonly investigated as a method of assessing oxygenation in neonates. Differences exist between the So2 and Hbo2 when blood tests are performed, and clinical monitors indicate So2 values. Oxyhemoglobin will decrease with the increased levels of carbon monoxide hemoglobin (Hbco) and methemo-globin (MetHb), and it is the most accurate measurements of oxygen (O2) association of hemoglobin (Hb). Pulse oximeter (for pulse oximetry saturation [Spo2] measurement) is commonly used in neonates. However, it will not detect the changes of Hb variations in the blood for accurate So2 measurements. Thus, the measurements from clinical oximeters should be used with caution. In neonates, fetal hemoglobin (HbF) accounts for most of the circulating Hb in their blood. Fetal hemoglobin has a high O2 affinity, thus releases less O2 to the body tissues, presenting a left-shifted Hbo2 dissociation curve.5,6 To date, however, limited data are available with HbF correction, for accurate arterial and venous (AV) So2 measurements (arterial oxygen saturation [Sao2] and venous oxygen saturation [Svo2]) in neonates, using paired AV blood samples.

In a study of critically ill adult patients, increased pulmonary CO production and elevation in arterial Hbco but not venous Hbco were documented by inflammatory stimuli inducing pulmonary heme oxygenase–1. In normal adults, venous Hbco level might be slightly higher than or equal to arterial Hbco because of production of CO by enzyme heme oxygenase–2, which is predominantly produced in the liver and spleen. However, hypoxia or pulmonary inflammation could induce heme oxygenase–1 to increase endogenous CO, thus elevating pulmonary arterial and systemic arterial Hbco levels in adults. Both endogenous and exogenous CO can suppress proliferation of pulmonary smooth muscles, a significant consideration for the prevention of chronic lung diseases in newborns. Despite these considerations, a later study in healthy adults indicated that the AV differences in Hbco were from technical artifacts and perhaps from inadequate control of different instruments. Thus, further studies are needed to provide more definitive answers for the AV differences of Hbco for adults and neonates with acute and chronic lung diseases.

Methemoglobin is an indicator of Hb oxidation and is essential for accurate measurement of Hbo2, So2, and oxygenation status. No evidence exists to show the AV MetHb difference, although this difference was elucidated with the potential changes of MetHb with different O2 levels.  Methemoglobin can be increased with nitric oxide (NO) therapy, used in respiratory distress syndrome (RDS) to reduce pulmonary hypertension and during heart surgery. Nitric oxide, in vitro, is an oxidant of Hb, with increased O2 during ischemia reperfusion. In hypoxemic conditions in vivo, nitrohemoglobin is a product generated by vessel responsiveness to nitrovasodilators. Nitro-hemoglobin can be spontaneously reversible in vivo, requiring no chemical agents or reductase. However, when O2 levels were increased experimentally in vitro following acidic conditions (pH 6.5) to simulate reperfusion conditions, MetHb levels were increased for the hemolysates (broken red cells). Nitrite-induced oxidation of Hb was associated with an increase in red blood cell membrane rigidity, thus contributing to Hb breakdown. A newer in vitro study of whole blood cells, however, concluded that MetHb formation is not dependent on increased O2 levels. Additional studies are needed to examine in vivo reperfusion of O2 and MetHb effects.

Purpose: The aim of this study was to examine the accuracy of arterial oxygen saturation (Sao2) and venous oxygen saturation (Svo2) with paired arterial and venous (AV) blood in relation to pulse oximetry saturation (Spo2) and oxyhemoglobin (Hbo2) with fetal hemoglobin determination, and their Hbo2 dissociation curves. Method: Twelve preterm neonates with gestational ages ranging from 27 to 34 weeks at birth, who had umbilical AV lines inserted, were investigated. Analyses were performed with 37 pairs of AV blood samples by using a blood volume safety protocol. Results: The mean differences between Sao2 and Svo2, and AV Hbo2 were both 6 percent (F6.9 and F6.7 percent, respectively), with higher Svo2 than those reported for adults. Biases were 2.1 – 0.49 for Sao2, 2.0 – 0.44 for Svo2, and 3.1 – 0.45 for Spo2, compared against Hbo2. With left-shifted Hbo2 dissociation curves in neonates, for the critical values of oxygen tension values between 50 and 75 millimeters of mercury, Hbo2 ranged from 92 to 93.4 percent; Sao2 ranged from 94.5 to 95.7 percent; and Spo2 ranged from 93.7 to 96.3 percent (compared to 85–94 percent in healthy adults). Conclusions: In neonates, both left-shifted Hbo2 dissociation curve and lower AV differences of oxygen saturation measurements indicated low flow of oxygen to the body tissues. These findings demonstrate the importance of accurate assessment of oxygenation statues in neonates.

In these neonates, the mean AV blood differences for both So2 and Hbo2 were about 6 percent, which was much lower than those reported for healthy adults (23 percent) for O2 supply and demand. In addition, with very high levels of HbF releasing less O2 to the body tissue, the results of blood analyses are worrisome for these critically ill neonates for low systemic oxygen states.  O’Connor and Hall determined AV So2 in neonates without HbF determination. Much of the AV So2 difference is dependent on Svo2 measurement. The ranges of Svo2 spanned for 35 percent, and the ranges of Sao2 spanned 6 percent in these neonates. The greater intervals for Svo2 measurements contribute to greater sensitivity for the measurements (than Sao2 measurements) in responding to nursing care and changes of O2 demand. Thus, Svo2 measurement is essential for better assessment of oxygenation status in neonates.

The findings of this study on AV differences of So2 were limited with very small number of paired AV blood samples. However, critically ill neonates need accurate assessment of oxygenation status because of HbF, which releases less O2 to the tissues. Decreased differences of AV So2 measurements added further possibilities of lower flow of O2 to the body tissues and demonstrated the greater need to accurately assess the proper oxygenation in the neonates. The findings of this study continued to clarify the accuracy of So2 measurements for neonates. Additional studies are needed to examine So2 levels in neonates to further validate these findings by using larger sample sizes.

Neonatal ventilation strategies and long-term respiratory outcomes

Sandeep Shetty, Anne Greenough
Early Human Development 90 (2014) 735–739
http://dx.doi.org/10.1016/j.earlhumdev.2014.08.020

Long-term respiratory morbidity is common, particularly in those born very prematurely and who have developed bronchopulmonary dysplasia (BPD), but it does occur in those without BPD and in infants born at term. A variety of neonatal strategies have been developed, all with short-term advantages, but meta-analyses of randomized controlled trials (RCTs) have demonstrated that only volume-targeted ventilation and prophylactic high-frequency oscillatory ventilation (HFOV) may reduce BPD. Few RCTs have incorporated long-term follow-up, but one has demonstrated that prophylactic HFOV improves respiratory and functional outcomes at school age, despite not reducing BPD. Results from other neonatal interventions have demonstrated that any impact on BPD may not translate into changes in long-term outcomes. All future neonatal  ventilation RCTs should have long-term outcomes rather than BPD as their primary outcome if they are to impact on clinical practice.

A Model Analysis of Arterial Oxygen Desaturation during Apnea in Preterm Infants

Scott A. Sands, BA Edwards, VJ Kelly, MR Davidson, MH Wilkinson, PJ Berger
PLoS Comput Biol 5(12): e1000588
http://dx.doi.org:/10.1371/journal.pcbi.1000588

Rapid arterial O2 desaturation during apnea in the preterm infant has obvious clinical implications but to date no adequate explanation for why it exists. Understanding the factors influencing the rate of arterial O2 desaturation during apnea (_SSaO2 ) is complicated by the non-linear O2 dissociation curve, falling pulmonary O2 uptake, and by the fact that O2 desaturation is biphasic, exhibiting a rapid phase (stage 1) followed by a slower phase when severe desaturation develops (stage 2). Using a mathematical model incorporating pulmonary uptake dynamics, we found that elevated metabolic O2 consumption accelerates _SSaO2 throughout the entire desaturation process. By contrast, the remaining factors have a restricted temporal influence: low pre-apneic alveolar PO2 causes an early onset of desaturation, but thereafter has little impact; reduced lung volume, hemoglobin content or cardiac output, accelerates _SSaO2 during stage 1, and finally, total blood O2 capacity (blood volume and hemoglobin content) alone determines _SSaO2 during stage 2. Preterm infants with elevated metabolic rate, respiratory depression, low lung volume, impaired cardiac reserve, anemia, or hypovolemia, are at risk for rapid and profound apneic hypoxemia. Our insights provide a basic physiological framework that may guide clinical interpretation and design of interventions for preventing sudden apneic hypoxemia.

A novel approach to study oxidative stress in neonatal respiratory distress syndrome

Reena Negi, D Pande, K Karki, A Kumar, RS Khanna, HD Khanna
BBA Clinical 3 (2015) 65–69
http://dx.doi.org/10.1016/j.bbacli.2014.12.001

Oxidative stress is an imbalance between the systemic manifestation of reactive oxygen species and a biological system’s ability to readily detoxify the reactive intermediates or to repair the resulting damage. It is a physiological event in the fetal-to-neonatal transition, which is actually a great stress to the fetus. These physiological changes and processes greatly increase the production of free radicals, which must be controlled by the antioxidant defense system, the maturation of which follows the course of the gestation. This could lead to several functional alterations with important repercussions for the infants. Adequately mature and healthy infants are able to tolerate this drastic change in the oxygen concentration. A problem occurs when the intrauterine development is incomplete or abnormal. Preterm or intrauterine growth retarded (IUGR) and low birth weight neonates are typically of this kind. An oxidant/antioxidant imbalance in infants is implicated in the pathogenesis of the major complications of prematurity including respiratory distress syndrome (RDS), necrotizing enterocolitis (NEC), chronic lung disease, retinopathy of prematurity and intraventricular hemorrhage (IVH).

Background: Respiratory distress syndrome of the neonate (neonatal RDS) is still an important problem in treatment of preterm infants. It is accompanied by inflammatory processes with free radical generation and oxidative stress. The aim of study was to determine the role of oxidative stress in the development of neonatal RDS. Methods: Markers of oxidative stress and antioxidant activity in umbilical cord blood were studied in infants with neonatal respiratory distress syndrome with reference to healthy newborns. Results: Status of markers of oxidative stress (malondialdehyde, protein carbonyl and 8-hydroxy-2-deoxy guanosine) showed a significant increase with depleted levels of total antioxidant capacity in neonatal RDS when compared to healthy newborns. Conclusion: The study provides convincing evidence of oxidative damage and diminished antioxidant defenses in newborns with RDS. Neonatal RDS is characterized by damage of lipid, protein and DNA, which indicates the augmentation of oxidative stress. General significance: The identification of the potential biomarker of oxidative stress consists of a promising strategy to study the pathophysiology of neonatal RDS.

Neonatal respiratory distress syndrome represents the major lung complications of newborn babies. Preterm neonates suffer from respiratory distress syndrome (RDS) due to immature lungs and require assisted ventilation with high concentrations of oxygen. The pathogenesis of this disorder is based on the rapid formation of the oxygen reactive species, which surpasses the detoxification capacity of antioxidative defense system. The high chemical reactivity of free radical leads to damage to a variety of cellular macro molecules including proteins, lipids and nucleic acid. This results in cell injury and may induce respiratory cell death.

Malondialdehyde (MDA) is one of the final products of polyunsaturated fatty acids peroxidation. The present study showed increased concentration of MDA in neonates with respiratory disorders than that of control in consonance with the reported study.

Anemia, Apnea of Prematurity, and Blood Transfusions

Kelley Zagol, Douglas E. Lake, Brooke Vergales, Marion E. Moorman, et al
J Pediatr 2012;161:417-21
http://dx.doi.org:/10.1016/j.jpeds.2012.02.044

The etiology of apnea of prematurity is multifactorial; however, decreased oxygen carrying capacity may play a role. The respiratory neuronal network in neonates is immature, particularly in those born preterm, as demonstrated by their paradoxical response to hypoxemia. Although adults increase the minute ventilation in response to hypoxemia, newborns have a brief increase in ventilation followed by periodic breathing, respiratory depression, and occasionally cessation of respiratory effort. This phenomenon may be exacerbated by anemia in preterm newborns, where a decreased oxygen carrying capacity may result in decreased oxygen delivery to the central nervous system, a decreased efferent output of the respiratory neuronal network, and an increase in apnea.

Objective Compare the frequency and severity of apneic events in very low birth weight (VLBW) infants before and after blood transfusions using continuous electronic waveform analysis. Study design We continuously collected waveform, heart rate, and oxygen saturation data from patients in all 45 neonatal intensive care unit beds at the University of Virginia for 120 weeks. Central apneas were detected using continuous computer processing of chest impedance, electrocardiographic, and oximetry signals. Apnea was defined as respiratory pauses of >10, >20, and >30 seconds when accompanied by bradycardia (<100 beats per minute) and hypoxemia (<80% oxyhemoglobin saturation as detected by pulse oximetry). Times of packed red blood cell transfusions were determined from bedside charts. Two cohorts were analyzed. In the transfusion cohort, waveforms were analyzed for 3 days before and after the transfusion for all VLBW infants who received a blood transfusion while also breathing spontaneously. Mean apnea rates for the previous 12 hours were quantified and differences for 12 hours before and after transfusion were compared. In the hematocrit cohort, 1453 hematocrit values from all VLBW infants admitted and breathing spontaneously during the time period were retrieved, and the association of hematocrit and apnea in the next 12 hours was tested using logistic regression. Results Sixty-seven infants had 110 blood transfusions during times when complete monitoring data were available. Transfusion was associated with fewer computer-detected apneic events (P < .01). Probability of future apnea occurring within 12 hours increased with decreasing hematocrit values (P < .001). Conclusions Blood transfusions are associated with decreased apnea in VLBW infants, and apneas are less frequent at higher hematocrits.

Bronchopulmonary dysplasia: The earliest and perhaps the longest lasting obstructive lung disease in humans

Silvia Carraro, M Filippone, L Da Dalt, V Ferraro, M Maretti, S Bressan, et al.
Early Human Development 89 (2013) S3–S5
http://dx.doi.org/10.1016/j.earlhumdev.2013.07.015

Bronchopulmonary dysplasia (BPD) is one of the most important sequelae of premature birth and the most common form of chronic lung disease of infancy, an umbrella term for a number of different diseases that evolve as a consequence of a neonatal respiratory disorder. BPD is defined as the need for supplemental oxygen for at least 28 days after birth, and its severity is graded according to the respiratory support required at 36 post-menstrual weeks.

BPD was initially described as a chronic respiratory disease occurring in premature infants exposed to mechanical ventilation and oxygen supplementation. This respiratory disease (later named “old BPD”) occurred in relatively large premature newborn and, from a pathological standpoint, it was characterized by intense airway inflammation, disruption of normal pulmonary structures and lung fibrosis.

Bronchopulmonary dysplasia (BPD) is one of the most important sequelae of premature birth and the most common form of chronic lung disease of infancy. From a clinical standpoint BPD subjects are characterized by recurrent respiratory symptoms, which are very frequent during the first years of life and, although becoming less severe as children grow up, they remain more common than in term-born controls throughout childhood, adolescence and into adulthood. From a functional point of view BPD subjects show a significant airflow limitation that persists during adolescence and adulthood and they may experience an earlier and steeper decline in lung function during adulthood. Interestingly, patients born prematurely but not developing BPD usually fare better, but they too have airflow limitations during childhood and later on, suggesting that also prematurity per se has life-long detrimental effects on pulmonary function. For the time being, little is known about the presence and nature of pathological mechanisms underlying the clinical and functional picture presented by BPD survivors. Nonetheless, recent data suggest the presence of persistent neutrophilic airway inflammation and oxidative stress and it has been suggested that BPD may be sustained in the long term by inflammatory pathogenic mechanisms similar to those underlying COPD. This hypothesis is intriguing but more pathological data are needed.  A better understanding of these pathogenetic mechanisms, in fact, may be able to orient the development of novel targeted therapies or prevention strategies to improve the overall respiratory health of BPD patients.

We have a limited understanding of the presence and nature of pathological mechanisms in the lung of BPD survivors. The possible role of asthma-like inflammation has been investigated because BPD subjects often present with recurrent wheezing and other symptoms resembling asthma during their childhood and adolescence. But BPD subjects have normal or lower than normal exhaled nitric oxide levels and exhaled air temperatures, whereas they are higher than normal in asthmatic patients.

Of all obstructive lung diseases in humans, BPD has the earliest onset and is possibly the longest lasting. Given its frequent association with other conditions related to preterm birth (e.g. growth retardation, pulmonary hypertension, neurodevelopmental delay, hearing defects, and retinopathy of prematurity), it often warrants a multidisciplinary management.

Effects of Sustained Lung Inflation, a lung recruitment maneuver in primary acute respiratory distress syndrome, in respiratory and cerebral outcomes in preterm infants

Chiara Grasso, Pietro Sciacca, Valentina Giacchi, Caterina Carpinato, et al.
Early Human Development 91 (2015) 71–75
http://dx.doi.org/10.1016/j.earlhumdev.2014.12.002

Background: Sustained Lung Inflation (SLI) is a maneuver of lung recruitment in preterm newborns at birth that can facilitate the achieving of larger inflation volumes, leading to the clearance of lung fluid and formation of functional residual capacity (FRC). Aim: To investigate if Sustained Lung Inflation (SLI) reduces the need of invasive procedures and iatrogenic risks. Study design: 78 newborns (gestational age ≤ 34 weeks, weighing ≤ 2000 g) who didn’t breathe adequately at birth and needed to receive SLI in addition to other resuscitation maneuvers (2010 guidelines). Subjects: 78 preterm infants born one after the other in our department of Neonatology of Catania University from 2010 to 2012. Outcome measures: The need of intubation and surfactant, the ventilation required, radiological signs, the incidence of intraventricular hemorrhage (IVH), periventricular leukomalacia, retinopathy in prematurity from III to IV plus grades, bronchopulmonary dysplasia, patent ductus arteriosus, pneumothorax and necrotizing enterocolitis. Results: In the SLI group infants needed less intubation in the delivery room (6% vs 21%; p b 0.01), less invasive mechanical ventilation (14% vs 55%; p ≤ 0.001) and shorter duration of ventilation (9.1 days vs 13.8 days; p ≤ 0.001). There wasn’t any difference for nasal continuous positive airway pressure (82% vs 77%; p = 0.43); but there was less surfactant administration (54% vs 85%; p ≤ 0.001) and more infants received INSURE (40% vs 29%; p=0.17). We didn’t found any differences in the outcomes, except for more mild intraventricular hemorrhage in the SLI group (23% vs 14%; p = 0.15; OR= 1.83). Conclusion: SLI is easier to perform even with a single operator, it reduces the necessity of more complicated maneuvers and surfactant without statistically evident adverse effects.

Long-term respiratory consequences of premature birth at less than 32 weeks of gestation

Anne Greenough
Early Human Development 89 (2013) S25–S27
http://dx.doi.org/10.1016/j.earlhumdev.2013.07.004

Chronic respiratory morbidity is a common adverse outcome of very premature birth, particularly in infants who had developed bronchopulmonary dysplasia (BPD). Prematurely born infants who had BPD may require supplementary oxygen at home for many months and affected infants have increased healthcare utilization until school age. Chest radiograph abnormalities are common; computed tomography of the chest gives predictive information in children with ongoing respiratory problems. Readmission to hospital is common, particularly for those who have BPD and suffer respiratory syncytial virus lower respiratory infections (RSV LRTIs). Recurrent respiratory symptoms requiring treatment are common and are associated with evidence of airways obstruction and gas trapping. Pulmonary function improves with increasing age, but children with BPD may have ongoing airflow limitation. Lung function abnormalities may be more severe in those who had RSV LRTIs, although this may partly be explained by worse premorbid lung function. Worryingly, lung function may deteriorate during the first year. Longitudinal studies are required to determine if there is catch up growth.

Long-term pulmonary outcomes of patients with bronchopulmonary dysplasia

Anita Bhandari and Sharon McGrath-Morrow
Seminars in Perinatology 37 (2013)132–137
http://dx.doi.org/10.1053/j.semperi.2013.01.010

Bronchopulmonary dysplasia (BPD) is the commonest cause of chronic lung disease in infancy. The incidence of BPD has remained unchanged despite many advances in neonatal care. BPD starts in the neonatal period but its effects can persist long term. Premature infants with BPD have a greater incidence of hospitalization, and continue to have a greater respiratory morbidity and need for respiratory medications, compared to those without BPD. Lung function abnormalities, especially small airway abnormalities, often persist. Even in the absence of clinical symptoms, BPD survivors have persistent radiological abnormalities and presence of emphysema has been reported on chest computed tomography scans. Concern regarding their exercise tolerance remains. Long-term effects of BPD are still unknown, but given reports of a more rapid decline in lung function and their susceptibility to develop chronic obstructive pulmonary disease phenotype with aging, it is imperative that lung function of survivors of BPD be closely monitored.

Neonatal ventilation strategies and long-term respiratory outcomes

Sandeep Shetty, Anne Greenough
Early Human Development 90 (2014) 735–739
http://dx.doi.org/10.1016/j.earlhumdev.2014.08.020

Long-term respiratory morbidity is common, particularly in those born very prematurely and who have developed bronchopulmonary dysplasia (BPD), but it does occur in those without BPD and in infants born at term. A variety of neonatal strategies have been developed, all with short-term advantages, but meta-analyses of randomized controlled trials (RCTs) have demonstrated that only volume-targeted ventilation and prophylactic high-frequency oscillatory ventilation (HFOV) may reduce BPD. Few RCTs have incorporated long-term follow-up, but one has demonstrated that prophylactic HFOV improves respiratory and functional outcomes at school age, despite not reducing BPD. Results from other neonatal interventions have demonstrated that any impact on BPD may not translate into changes in long-term outcomes. All future neonatal ventilation RCTs should have long-term outcomes rather than BPD as their primary outcome if they are to impact on clinical practice.

Prediction of neonatal respiratory distress syndrome in term pregnancies by assessment of fetal lung volume and pulmonary artery resistance index

Mohamed Laban, GM Mansour, MSE Elsafty, AS Hassanin, SS EzzElarab
International Journal of Gynecology and Obstetrics 128 (2015) 246–250
http://dx.doi.org/10.1016/j.ijgo.2014.09.018

Objective: To develop reference cutoff values for mean fetal lung volume (FLV) and pulmonary artery resistance index (PA-RI) for prediction of neonatal respiratory distress syndrome (RDS) in low-risk term pregnancies. Methods: As part of a cross-sectional study, women aged 20–35 years were enrolled and admitted to a tertiary hospital in Cairo, Egypt, for elective repeat cesarean at 37–40 weeks of pregnancy between January 1, 2012, and July 31, 2013. FLV was calculated by virtual organ computer-aided analysis, and PA-RI was measured by Doppler ultrasonography before delivery. Results: A total of 80 women were enrolled. Neonatal RDS developed in 11 (13.8%) of the 80 newborns. Compared with neonates with RDS, healthy neonates had significantly higher FLVs (P b 0.001) and lower PA-RIs (P b 0.001). Neonatal RDS is less likely with FLV of at least 32 cm3 or PA-RI less than or equal to 0.74. Combining these two measures improved the accuracy of prediction. Conclusion: The use of either FLV or PA-RI predicted neonatal RDS. The predictive value increased when these two measures were combined

Pulmonary surfactant - a front line of lung host defense, 2003 JCI0318650.f2

Pulmonary surfactant – a front line of lung host defense, 2003 JCI0318650.f2

Pulmonary hypertension in bronchopulmonary dysplasia

Sara K.Berkelhamer, Karen K.Mestan, and Robin H. Steinhorn
Seminars In  Perinatology 37 (2013)124–131
http://dx.doi.org/10.1053/j.semperi.2013.01.009

Pulmonary hypertension (PH) is a common complication of neonatal respiratory diseases, including bronchopulmonary dysplasia (BPD), and recent studies have increased aware- ness that PH worsens the clinical course, morbidity and mortality of BPD. Recent evidence indicates that up to 18% of all extremely low-birth-weight infants will develop some degree of PH during their hospitalization, and the incidence rises to 25–40% of the infants with established BPD. Risk factors are not yet well understood, but new evidence shows that fetal growth restriction is a significant predictor of PH. Echocardiography remains the primary method for evaluation of BPD-associated PH, and the development of standardized screening timelines and techniques for identification of infants with BPD-associated PH remains an important ongoing topic of investigation. The use of pulmonary vasodilator medications, such as nitric oxide, sildenafil, and others, in the BPD population is steadily growing, but additional studies are needed regarding their long-term safety and efficacy.
An update on pharmacologic approaches to bronchopulmonary dysplasia

Sailaja Ghanta, Kristen Tropea Leeman, and Helen Christou
Seminars In Perinatology 37 (2013)115–123
http://dx.doi.org/10.1053/j.semperi.2013.01.008

Bronchopulmonary dysplasia (BPD) is the most prevalent long-term morbidity in surviving extremely preterm infants and is linked to increased risk of reactive airways disease, pulmonary hypertension, post-neonatal mortality, and adverse neurodevelopmental outcomes. BPD affects approximately 20% of premature newborns, and up to 60% of premature infants born before completing 26 weeks of gestation. It is characterized by the need for assisted ventilation and/or supplemental oxygen at 36 weeks postmenstrual age. Approaches to prevention and treatment of BPD have evolved with improved understanding of its pathogenesis. This review will focus on recent advancements and detail current research in pharmacotherapy for BPD. The evidence for both current and potential future experimental therapies will be reviewed in detail. As our understanding of the complex and multifactorial pathophysiology of BPD changes, research into these current and future approaches must continue to evolve.

Methylxanthines
Diuretics and bronchodilators
Corticosteroids
Macrolide antibiotics
Recombinant human Clara cell 10-kilodalton protein(rhCC10)
Vitamin A
Surfactant
Leukotriene receptor antagonist
Pulmonary vasodilators

Skeletal and Muscle

Skeletal Stem Cells in Space and Time

Moustapha Kassem and Paolo Bianco
Cell  Jan 15, 2015; 160: 17-19
http://dx.doi.org/10.1016/j.cell.2014.12.034

The nature, biological characteristics, and contribution to organ physiology of skeletal stem cells are not completely determined. Chan et al. and Worthley et al. demonstrate that a stem cell for skeletal tissues, and a system of more restricted, downstream progenitors, can be identified in mice and demonstrate its role in skeletal tissue maintenance and regeneration.

The groundbreaking concept that bone, cartilage, marrow adipocytes, and hematopoiesis-supporting stroma could originate from a common progenitor and putative stem cell was surprising at the time when it was formulated (Owen and Friedenstein, 1988). The putative stem cell, nonhematopoietic in nature, would be found in the postnatal bone marrow stroma, generate tissues previously thought of as foreign to each other, and support the turnover of tissues and organs that self-renew at a much slower rate compared to other tissues associated with stem cells (blood, epithelia). This concept also connected bone and bone marrow as parts of a single-organ system, implying their functional interplay. For many years, the evidence underpinning the concept has been incomplete.

While multipotency of stromal progenitors has been demonstrated by in vivo transplantation experiments, self-renewal, the defining property of a stem cell, has not been easily demonstrated until recently in humans (Sacchetti et al., 2007) and mice (Mendez-Ferrer et al., 2010). Meanwhile, a confusing and plethoric terminology has been introduced into the literature, which diverted and confounded the search for a skeletal stem cell and its physiological significance (Bianco et al., 2013).

Two studies in this issue of Cell (Chan et al., 2015; Worthley et al., 2015), using a combination of rigorous single-cell analyses and lineage tracing technologies, mark significant steps toward rectifying the course of skeletal stem cell discovery by making several important points, within and beyond skeletal physiology.

First, a stem cell for skeletal tissues, and a system of more restricted, downstream progenitors can in fact be identified and linked to defined phenotype(s) in the mouse. The system is framed conceptually, and approached experimentally, similar to the hematopoietic system.

Second, based on its assayable functions and potential, the stem cell at the top of the hierarchy is defined as a skeletal stem cell (SSC). As noted earlier (Sacchetti et al., 2007) (Bianco et al., 2013), this term clarifies, well beyond semantics, that the range of tissues that the self-renewing stromal progenitor (originally referred to as an ‘‘osteogenic’’ or ‘‘stromal’’ stem cell) (Owen and Friedenstein, 1988) can actually generate in vivo, overlaps with the range of tissues that make up the skeleton.

Third, these cells are spatially restricted, local residents of the bone/bone marrow organ. The systemic circulation is not a sizable contributor to their recruitment to locally deployed functions.

Fourth, a native skeletogenic potential is inherent to the system of progenitor/ stem cells found in the skeleton, and internally regulated by bone morphogenetic protein (BMP) signaling. This is reflected in the expression of regulators and antagonists of BMP signaling within the system, highlighting potential feedback mechanisms modulating expansion or quiescence of specific cell compartments.

Fifth, in cells isolated from other tissues, an assayable skeletogenic potential is not inherent: it can only be induced de novo by BMP reprogramming. These two studies (Chan et al., 2015, Worthley et al., 2015) corroborate the classical concept of ‘‘determined’’ and ‘‘inducible’’ skeletal progenitors (Owen and Friedenstein, 1988): the former residing in the skeleton, the latter found in nonskeletal tissues; the former capable of generating skeletal tissues, in vivo and spontaneously, the latter requiring reprogramming signals in order to acquire a skeletogenic capacity; the former operating in physiological bone formation, the latter in unwanted, ectopic bone formation in diseases such as fibrodysplasia ossificans progressiva.

To optimize our ability to obtain specific skeletal tissues for medical application, the study by Chan et al. offers a glimpse of another facet of the biology of SSC lineages and progenitors. Chan et al. show that a homogeneous cell population inherently committed to chondrogenesis can alter its output to generate bone if cotransplanted with multipotent progenitors. Conversely, osteogenic cells can be shifted to a chondrogenic fate by blockade of vascular endothelial growth factor receptor, consistent with the avascular and hypoxic milieu of cartilage. This has two important implications:

  • commitment is flexible in the system;
  • the choir is as important as the soloist and can modulate the solo tune.

Reversibility and population behavior thus emerge as two features that may be characteristic, albeit not unique, of the stromal system, resonating with conceptually comparable evidence in the human system.

The two studies by Chan et al. and Worthely et al. emphasize the relevance not only of their new data, but also of a proper concept of a skeletal stem cell per se, for proper clinical use. Confusion arising from improper conceptualization of skeletal stem cells has markedly limited clinical development of skeletal stem cell biology.

Gremlin 1 Identifies a Skeletal Stem Cell with Bone, Cartilage, and Reticular Stromal Potential

Daniel L. Worthley, Michael Churchill, Jocelyn T. Compton, Yagnesh Tailor, et al.
Cell, Jan 15, 2015; 160: 269–284
http://dx.doi.org/10.1016/j.cell.2014.11.042

The stem cells that maintain and repair the postnatal skeleton remain undefined. One model suggests that perisinusoidal mesenchymal stem cells (MSCs) give rise to osteoblasts, chondrocytes, marrow stromal cells, and adipocytes, although the existence of these cells has not been proven through fate-mapping experiments. We demonstrate here that expression of the bone morphogenetic protein (BMP) antagonist gremlin 1 defines a population of osteochondroreticular (OCR) stem cells in the bone marrow. OCR stem cells self-renew and generate osteoblasts, chondrocytes, and reticular marrow stromal cells, but not adipocytes. OCR stem cells are concentrated within the metaphysis of long bones not in the perisinusoidal space and are needed for bone development, bone remodeling, and fracture repair. Grem1 expression also identifies intestinal reticular stem cells (iRSCs) that are cells of origin for the periepithelial intestinal mesenchymal sheath. Grem1 expression identifies distinct connective tissue stem cells in both the bone (OCR stem cells) and the intestine (iRSCs).

Identification and Specification of the Mouse Skeletal Stem Cell

Charles K.F. Chan, Eun Young Seo, James Y. Chen, David Lo, A McArdle, et al.
Cell, Jan 15, 2015; 160: 285–298
http://dx.doi.org/10.1016/j.cell.2014.12.002

How are skeletal tissues derived from skeletal stem cells? Here, we map bone, cartilage, and stromal development from a population of highly pure, postnatal skeletal stem cells (mouse skeletal stem cells, mSSCs) to their downstream progenitors of bone, cartilage, and stromal tissue. We then investigated the transcriptome of the stem/progenitor cells for unique gene-expression patterns that would indicate potential regulators of mSSC lineage commitment. We demonstrate that mSSC niche factors can be potent inducers of osteogenesis, and several specific combinations of recombinant mSSC niche factors can activate mSSC genetic programs in situ, even in nonskeletal tissues, resulting in de novo formation of cartilage or bone and bone marrow stroma. Inducing mSSC formation with soluble factors and subsequently regulating the mSSC niche to specify its differentiation toward bone, cartilage, or stromal cells could represent a paradigm shift in the therapeutic regeneration of skeletal tissues.

Bone mesenchymal development

Bone mesenchymal development

Bone mesenchymal development

The bone-remodeling cycle

The bone-remodeling cycle

Nuclear receptor modulation – Role of coregulators in selective estrogen receptor modulator (SERM) actions

Qin Feng, Bert W. O’Malley
Steroids 90 (2014) 39–43
http://dx.doi.org/10.1016/j.steroids.2014.06.008

Selective estrogen receptor modulators (SERMs) are a class of small-molecule chemical compounds that bind to estrogen receptor (ER) ligand binding domain (LBD) with high affinity and selectively modulate ER transcriptional activity in a cell- and tissue-dependent manner. The prototype of SERMs is tamoxifen, which has agonist activity in bone, but has antagonist activity in breast. Tamoxifen can reduce the risk of breast cancer and, at same time, prevent osteoporosis in postmenopausal women. Tamoxifen is widely prescribed for treatment and prevention of breast cancer. Mechanistically the activity of SERMs is determined by the selective recruitment of coactivators and corepressors in different cell types and tissues. Therefore, understanding the coregulator function is the key to understanding the tissue selective activity of SERMs.

Hematopoietic

Hematopoietic Stem Cell Arrival Triggers Dynamic Remodeling of the Perivascular Niche

Owen J. Tamplin, Ellen M. Durand, Logan A. Carr, Sarah J. Childs, et al.
Cell, Jan 15, 2015; 160: 241–252
http://dx.doi.org/10.1016/j.cell.2014.12.032

Hematopoietic stem and progenitor cells (HSPCs) can reconstitute and sustain the entire blood system. We generated a highly specific transgenic reporter of HSPCs in zebrafish. This allowed us to perform high resolution live imaging on endogenous HSPCs not currently possible in mammalian bone marrow. Using this system, we have uncovered distinct interactions between single HSPCs and their niche. When an HSPC arrives in the perivascular niche, a group of endothelial cells remodel to form a surrounding pocket. This structure appears conserved in mouse fetal liver. Correlative light and electron microscopy revealed that endothelial cells surround a single HSPC attached to a single mesenchymal stromal cell. Live imaging showed that mesenchymal stromal cells anchor HSPCs and orient their divisions. A chemical genetic screen found that the compound lycorine promotes HSPC-niche interactions during development and ultimately expands the stem cell pool into adulthood. Our studies provide evidence for dynamic niche interactions upon stem cell colonization.

Neonatal anemia

Sanjay Aher, Kedar Malwatkar, Sandeep Kadam
Seminars in Fetal & Neonatal Medicine (2008) 13, 239e247
http://dx.doi.org:/10.1016/j.siny.2008.02.009

Neonatal anemia and the need for red blood cell (RBC) transfusions are very common in neonatal intensive care units. Neonatal anemia can be due to blood loss, decreased RBC production, or increased destruction of erythrocytes. Physiologic anemia of the newborn and anemia of prematurity are the two most common causes of anemia in neonates. Phlebotomy losses result in much of the anemia seen in extremely low birthweight infants (ELBW). Accepting a lower threshold level for transfusion in ELBW infants can prevent these infants being exposed to multiple donors.

Management of anemia in the newborn

Naomi L.C. Luban
Early Human Development (2008) 84, 493–498
http://dx.doi.org:/10.1016/j.earlhumdev.2008.06.007

Red blood cell (RBC) transfusions are administered to neonates and premature infants using poorly defined indications that may result in unintentional adverse consequences. Blood products are often manipulated to limit potential adverse events, and meet the unique needs of neonates with specific diagnoses. Selection of RBCs for small volume (5–20 mL/kg) transfusions and for massive transfusion, defined as extracorporeal bypass and exchange transfusions, are of particular concern to neonatologists. Mechanisms and therapeutic treatments to avoid transfusion are another area of significant investigation. RBCs collected in anticoagulant additive solutions and administered in small aliquots to neonates over the shelf life of the product can decrease donor exposure and has supplanted the use of fresh RBCs where each transfusion resulted in a donor exposure. The safety of this practice has been documented and procedures established to aid transfusion services in ensuring that these products are available. Less well established are the indications for transfusion in this population; hemoglobin or hematocrit alone are insufficient indications unless clinical criteria (e.g. oxygen desaturation, apnea and bradycardia, poor weight gain) also augment the justification to transfuse. Comorbidities increase oxygen consumption demands in these infants and include bronchopulmonary dysplasia, rapid growth and cardiac dysfunction. Noninvasive methods or assays have been developed to measure tissue oxygenation; however, a true measure of peripheral oxygen offloading is needed to improve transfusion practice and determine the value of recombinant products that stimulate erythropoiesis. The development of such noninvasive methods is especially important since randomized, controlled clinical trials to support specific practices are often lacking, due at least in part, to the difficulty of performing such studies in tiny infants.
The Effect of Blood Transfusion on the Hemoglobin Oxygen Dissociation Curve of Very Early Preterm Infants During the First Week of Life

Virginie De HaUeux, Anita Truttmann, Carmen Gagnon, and Harry Bard
Seminars in Perinatology, 2002; 26(6): 411-415
http://dx.doi.org:/10.1053/sper.2002.37313

This study was conducted during the first week of life to determine the changes in Ps0 (PO2 required to achieve a saturation of 50% at pH 7.4 and 37~ and the proportions of fetal hemoglobin (I-IbF) and adult hemoglobin (HbA) prior to and after transfusion in very early preterm infants. Eleven infants with a gestational age <–27 weeks have been included in study. The hemoglobin dissociation curve and the Ps0 was determined by Hemox-analyser. Liquid chromatography was also performed to determine the proportions of HbF and HbA. The mean gestational age of the 11 infants was 25.1 weeks (-+1 weeks) and their mean birth weight was 736 g (-+125 g). They received 26.9 mL/kg of packed red cells. The mean Ps0 prior and after transfusion was 18.5 +- 0.8 and 21.0 + 1 mm Hg (P = .0003) while the mean percentage of HbF was 92.9 -+ 1.1 and 42.6 -+ 5.7%, respectively. The data of this study show a decrease of hemoglobin oxygen affinity as a result of blood transfusion in very early preterm infants prone to O 2 toxicity. The shift in HbO 2 curve after transfusion should be taken into consideration when oxygen therapy is being regulated for these infants.

Effect of neonatal hemoglobin concentration on long-term outcome of infants affected by fetomaternal hemorrhage

Mizuho Kadooka, H Katob, A Kato, S Ibara, H Minakami, Yuko Maruyama
Early Human Development 90 (2014) 431–434
http://dx.doi.org/10.1016/j.earlhumdev.2014.05.010

Background: Fetomaternal hemorrhage (FMH) can cause severe morbidity. However, perinatal risk factors for long-term poor outcome due to FMH have not been extensively studied.                                                                                 Aims: To determine which FMH infants are likely to have neurological sequelae.
Study design: A single-center retrospective observational study. Perinatal factors, including demographic characteristics, Kleihauer–Betke test, blood gas analysis, and neonatal blood hemoglobin concentration ([Hb]), were analyzed in association with long-term outcomes.
Subjects: All 18 neonates referred to a Neonatal Intensive Care Unit of Kagoshima City Hospital and diagnosed with FMH during a 15-year study period. All had a neonatal [Hb] b7.5 g/dL and 15 of 17 neonates tested had Kleihauer–Betke test result N4.0%.
Outcome measures: Poor long-term outcome was defined as any of the following determined at 12 month old or more: cerebral palsy, mental retardation, attention deficit/hyperactivity disorder, and epilepsy.
Results: Nine of the 18 neonates exhibited poor outcomes. Among demographic characteristics and blood variables compared between two groups with poor and favorable outcomes, significant differences were observed in [Hb] (3.6 ± 1.4 vs. 5.4 ± 1.1 g/dL, P = 0.01), pH (7.09 ± 0.11 vs. 7.25 ± 0.13, P = 0.02) and base deficits (17.5 ± 5.4 vs. 10.4 ± 6.0 mmol/L, P = 0.02) in neonatal blood, and a number of infants with [Hb] ≤ 4.5 g/dL (78%[7/9] vs. 22%[2/9], P= 0.03), respectively. The base deficit in neonatal arterial blood increased significantly with decreasing neonatal [Hb].
Conclusions: Severe anemia causing severe base deficit is associated with neurological sequelae in FMH infants

Clinical and hematological presentation among Indian patients with common hemoglobin variants

Khushnooma Italia, Dipti Upadhye, Pooja Dabke, Harshada Kangane, et al.
Clinica Chimica Acta 431 (2014) 46–51
http://dx.doi.org/10.1016/j.cca.2014.01.028

Background: Co-inheritance of structural hemoglobin variants like HbS, HbD Punjab and HbE can lead to a variable clinical presentation and only few cases have been described so far in the Indian population.
Methods: We present the varied clinical and hematological presentation of 22 cases (HbSD Punjab disease-15, HbSE disease-4, HbD Punjab E disease-3) referred to us for diagnosis.
Results: Two of the 15 HbSDPunjab disease patients had moderate crisis, one presented with mild hemolytic anemia; however, the other 12 patients had a severe clinical presentation with frequent blood transfusion requirements, vaso occlusive crisis, avascular necrosis of the femur and febrile illness. The 4 HbSE disease patients had a mild to moderate presentation. Two of the 3 HbD Punjab E patients were asymptomatic with one patient’s sibling having a mild presentation. The hemoglobin levels of the HbSD Punjab disease patients ranged from 2.3 to 8.5 g/dl and MCV from 76.3 to 111.6 fl. The hemoglobin levels of the HbD Punjab E and HbSE patients ranged from 10.8 to 11.9 and 9.8 to 10.0 g/dl whereas MCV ranged from 67.1 to 78.2 and 74.5 to 76.0 fl respectively.
Conclusions: HbSD Punjab disease patients should be identified during newborn screening programs and managed in a way similar to sickle cell disease. Couple at risk of having HbSD Punjab disease children may be given the option of prenatal diagnosis in subsequent pregnancies.

Sickle cell anemia is the most common hemoglobinopathy seen across the world. It is caused by a point mutation in the 6th codon of the beta (β) globin gene leading to the substitution of the amino acid glutamic acid to valine. The sickle gene is frequently seen in Africa, some Mediterranean countries, India, Middle East—Saudi Arabia and North America. In India the prevalence of hemoglobin S (HbS) carriers varies from 2 to 40% among different population groups and HbS is mainly seen among the scheduled tribe, scheduled caste and other backward class populations in the western, central and parts of eastern and southern India. Sickle cell anemia has a variable clinical presentation in India with the most severe clinical presentation seen in central India whereas patients in the western region show a mild to moderate clinical presentation.

Hemoglobin D Punjab (HbD Punjab) (also known as HbD Los-Angeles, HbD Portugal, HbD North Carolina, D Oak Ridge and D Chicago) is another hemoglobin variant due to a point mutation in codon 121 of the β globin gene resulting in the substitution of the amino acid glutamic acid to glycine. It is a widely distributed hemoglobin with a relatively low prevalence of 0.86% in the Indo-Pak subcontinent, 1–3% in north-western India, 1–3% in the Black population in the Caribbean and North America and has also been reported among the English. It accounts for 55.6% of all the Hb variants seen in the Xenjiang province of China.

Hemoglobin E (HbE) is the most common abnormal hemoglobin in Southeast Asia. In India, the frequency ranges from 4% to 51% in the north eastern region and 3% to 4% in West Bengal in the east. The HbE mutation (β26 GAG→AAG) creates an alternative splice site and the βE chain is insufficiently synthesized, hence the phenotype of this disorder is that of a mild form of β thalassemia.

Though these 3 structural variants are prevalent in different regions of India, their interaction is increasingly seen in all states of the country due to migration of people to different regions for a better livelihood. There are very few reports on interaction of these commonly seen Hb variants and the phenotypic–genotypic presentation of these cases is important for genetic counseling and management.

HbF of patients with HbSD Punjab disease with variable clinical severity. The HbF values of 4 patients are not included as they were post blood transfusion

The genotypes of the patients were confirmed by restriction enzyme digestion and ARMS (Fig). Patients 1 to 15 were characterized as compound heterozygous for HbS and HbD Punjab whereas patients 16 to 19 were characterized as compound heterozygous for HbS and HbE. Patient nos. 20 to 22 were characterized as compound heterozygous for HbE and HbD Punjab.

Molecular characterization of HbS and HbDPunjab by restriction enzyme digestion and of HbE by ARMS.

Molecular characterization of HbS and HbDPunjab by restriction enzyme digestion and of HbE by ARMS.

Molecular characterization of HbS and HbDPunjab by restriction enzyme digestion and of HbE by ARMS.

The 3 common β globin gene variants of hemoglobin, HbS, HbE and HbD Punjab are commonly seen in India, with HbS having a high prevalence in the central belt and some parts of western, eastern and southern India, HbE in the eastern and north eastern region whereas HbD is mostly seen in the north western part of India. These hemoglobin variants have been reported in different population groups. However, with migration and intermixing of the different populations from different geographic regions, occasional cases of HbSD Punjab and HbSE are being reported. There are several HbD variants like HbD Punjab, HbD Iran, HbD Ibadan. However, of these only HbD Punjab interacts with HbS to form a clinically significant condition as the glutamine residue facilitates polymerization of HbS. HbD Iran and HbD Ibadan are non-interacting and produce benign conditions like the sickle cell trait. The first case of HbSD Punjab disease was a brother and sister considered to have atypical sickle cell disease in 1934. This family was further reinvestigated and reported as the first case of HbD Los Angeles which has the same mutation as the HbD Punjab. Serjeant et al. reported HbD Punjab in an English parent in 6 out of 11 HbSD-Punjab disease cases. This has been suggested to be due to the stationing of nearly 50,000 British troops on the Indian continent for a period of 200 y and the introduction into Britain of their Anglo-Indian children.

HbSD Punjab disease shows a similar pattern to HbS homozygous on alkaline hemoglobin electrophoresis but can be differentiated on acid agar gel electrophoresis and on HPLC. In HbSD Punjab disease cases, the peripheral blood films show anisocytosis, poikilocytosis, target cells and irreversibly sickled cells. Values of HbF and HbA2 are similar to those in sickle homozygous cases. HbSD Punjab disease is characterized by a moderately severe hemolytic anemia.

Twenty-one cases of HbSDPunjab were reported by Serjeant of which 16 were reported by different workers among patients originating from Caucasian, Spanish, Australian, Irish, English, Portuguese, Black, American, Venezuelan, Caribbean, Mexican, Turkish and Jamaican backgrounds. Yavarian et al. 2009 reported a multi centric origin of HbD Punjab which in combination with HbS results in sickle cell disease. Patel et al. 2010 have also reported 12 cases of HbSD Punjab from the Orissa state of eastern India. Majority of these cases were symptomatic, presenting with chronic hemolytic anemia and frequent painful crises.

HbF levels >20% were seen in 4 out of our 11 clinically severe patients of HbSD-Punjab disease with the mean HbF levels of 16.8% in 8 clinically severe patients, while 3 clinically severe patients were post transfused. However, the 3 patients with a mild to moderate clinical presentation showed a mean HbF level of 8.6%. This is in contrast to the relatively milder clinical presentation associated with high HbF seen in patients with sickle cell anemia. This was also reported by Adekile et al. 2010 in 5 cases of HbS-DLos Angeles where high HbF did not ameliorate the severe clinical presentation seen in these patients.

These 15 cases of HbSDPunjab disease give us an overall idea of the severe clinical presentation of the disease in different regions of India. However the HbDPunjabE cases were milder or asymptomatic and the HbSE cases were moderately symptomatic. Since most of the cases of HbSDPunjab disease were clinically severe, it is important to pick up these cases during newborn screening and enroll them into a comprehensive care program with the other sickle cell disease patients with introduction of therapeutic interventions such as penicillin prophylaxis if required and pneumococcal immunization. In fact, 2 of our cases (No. 6 and 7) were identified during newborn screening for sickle cell disorders. The parents can be given information on home care and educated to detect symptoms that may lead to serious medical emergencies. The parents of these patients as well as the couples who are at risk of having a child with HbSDPunjab disease could also be counseled about the option of prenatal diagnosis in subsequent pregnancies. It is thus important to document the clinical and hematological presentation of compound heterozygotes with these common β globin chain variants.

Common Hematologic Problems in the Newborn Nursery

Jon F. Watchko
Pediatr Clin N Am – (2015) xxx-xxx
http://dx.doi.org/10.1016/j.pcl.2014.11.011

Common RBC disorders include hemolytic disease of the newborn, anemia, and polycythemia. Another clinically relevant hematologic issue in neonates to be covered herein is thrombocytopenia. Disorders of white blood cells will not be reviewed.

KEY POINTS

(1)               Early clinical jaundice or rapidly developing hyperbilirubinemia are often signs of hemolysis, the differential diagnosis of which commonly includes immune-mediated disorders, red-cell enzyme deficiencies, and red-cell membrane defects.

(2)             Knowledge of the maternal blood type and antibody screen is critical in identifying non-ABO alloantibodies in the maternal serum that may pose a risk for severe hemolytic disease in the newborn.

(3)             Moderate to severe thrombocytopenia in an otherwise well-appearing newborn strongly suggests immune-mediated (alloimmune or autoimmune) thrombocytopenia.

Hemolytic conditions in the neonate

1. Immune-mediated (positive direct Coombs test)  a. Rhesus blood group: Anti-D, -c, -C, -e, -E, CW, and several others

  b. Non-Rhesus blood groups: Kell, Duffy, Kidd, Xg, Lewis, MNS, and others

  c. ABO blood group: Anti-A, -B

2. Red blood cell (RBC) enzyme defects

  a. Glucose-6-phosphate dehydrogenase (G6PD) deficiency

  b. Pyruvate kinase deficiency

  c. Others

3. RBC membrane defects

  a. Hereditary spherocytosis

  b. Elliptocytosis

  c. Stomatocytosis

  d. Pyknocytosis

  e. Others

4. Hemoglobinopathies

  a. alpha-thalassemia

  b. gamma-thalassemia

Standard maternal antibody screeningAlloantibody                                 Blood Group

D, C, c, E, e, f, CW, V                     Rhesus

K, k, Kpa, Jsa                                  Kell

Fya, Fyb                                          Duffy

Jka, Jkb                                           Kidd

Xga                                                  Xg

Lea, Leb                                          Lewis

S, s, M, N                                        MNS

P1                                                    P

Lub                                                  Lutheran

Non-ABO alloantibodies reported to cause moderate to severe hemolytic disease of the newbornWithin Rh system: Anti-D, -c, -C, -Cw, -Cx, -e, -E, -Ew, -ce, -Ces, -Rh29, -Rh32, -Rh42, -f, -G, -Goa, -Bea, -Evans, -Rh17, -Hro, -Hr, -Tar, -Sec, -JAL, -STEM

Outside Rh system:  Anti-LW, -K, -k, -Kpa, -Kpb, -Jka, -Jsa, -Jsb, -Ku, -K11, -K22, -Fya, -M, -N, -S, -s, -U, -PP1 pk, -Dib, -Far, -MUT, -En3, -Hut, -Hil, -Vel, -MAM, -JONES, -HJK, -REIT

 

Red Blood Cell Enzymopathies

G6PD9 and pyruvate kinase (PK) deficiency are the 2 most common red-cell enzyme disorders associated with marked neonatal hyperbilirubinemia. Of these, G6PD deficiency is the more frequently encountered and it remains an important cause of kernicterus worldwide, including the United States, Canada, and the United Kingdom, the prevalence in Western countries a reflection in part of immigration patterns and intermarriage. The risk of kernicterus in G6PD deficiency also relates to the potential for unexpected rapidly developing extreme hyperbilirubinemia in this disorder associated with acute severe hemolysis.

Red Blood Cell Membrane Defects

Establishing a diagnosis of RBC membrane defects is classically based on the development of Coombs-negative hyperbilirubinemia, a positive family history, and abnormal RBC smear, albeit it is often difficult because newborns normally exhibit a marked variation in red-cell membrane size and shape. Spherocytes, however, are not often seen on RBC smears of hematologically normal newborns and this morphologic abnormality, when prominent, may yield a diagnosis of hereditary spherocytosis (HS) in the immediate neonatal period. Given that approximately 75% of families affected with hereditary spherocytosis manifest an autosomal dominant phenotype, a positive family history can often be elicited and provide further support for this diagnosis. More recently, Christensen and Henry highlighted the use of an elevated mean corpuscular hemoglobin concentration (MCHC) (>36.0 g/dL) and/or elevated ratio of MCHC to mean corpuscular volume, the latter they term the “neonatal HS index” (>0.36, likely >0.40) as screening tools for HS. An index of greater than 0.36 had 97% sensitivity, greater than 99% specificity, and greater than 99% negative predictive value for identifying HS in neonates. Christensen and colleagues also provided a concise update of morphologic RBC features that may be helpful in diagnosing this and other underlying hemolytic conditions in newborns.

The diagnosis of HS can be confirmed using the incubated osmotic fragility test when coupled with fetal red-cell controls or eosin-5-maleimide flow cytometry. One must rule out symptomatic ABO hemolytic disease by performing a direct Coombs test, as infants so affected also may manifest prominent micro-spherocytosis. Moreover, HS and symptomatic ABO hemolytic disease can occur in the same infant and result in severe hyperbilirubinemia and anemia.  Of other red-cell membrane defects, only hereditary elliptocytosis,  stomato-cytosis, and infantile pyknocytosis have been reported to exhibit significant hemolysis in the newborn period. Hereditary elliptocytosis and stomatocytosis are both rare. Infantile pyknocytosis, a transient red-cell membrane abnormality manifesting itself during the first few months of life, is more common.

Risk factors for bilirubin neurotoxicityIsoimmune hemolytic disease

G6PD deficiency

Asphyxia

Sepsis

Acidosis

Albumin less than 3.0 g/dL
Data from Maisels MJ, Bhutani VK, Bogen D, et al. Hyperbilirubinemia in the newborn infant > or 535 weeks’ gestation: an update with clarifications. Pediatrics 2009; 124:1193–8.

Polycythemia

Polycythemia (venous hematocrit 65%) in seen in infants across a range of conditions associated with active erythropoiesis or passive transfusion.76,77 They include, among others, placental insufficiency, the infant of a diabetic mother, recipient in twin-twin transfusion syndrome, and several aneuploidies, including trisomy. The clinical concern related to polycythemia is the risk for microcirculatory complications of hyperviscosity. However, determining which polycythemic infants are hyperviscous and when to intervene is a challenge.

 

 

Liver

Metabolic disorders presenting as liver disease

Germaine Pierre, Efstathia Chronopoulou
Paediatrics and Child Health 2013; 23(12): 509-514
The liver is a highly metabolically active organ and many inherited metabolic disorders have hepatic manifestations. The clinical presentation in these patients cannot usually be distinguished from liver disease due to acquired causes like infection, drugs or hematological disorders. Manifestations include acute and chronic liver failure, cholestasis and hepatomegaly. Metabolic causes of acute liver failure in childhood can be as high as 35%. Certain disorders like citrin deficiency and Niemann-Pick C disease may present in infancy with self-limiting cholestasis before presenting in later childhood or adulthood with irreversible disease. This article reviews important details from the history and clinical examination when evaluating the pediatric patient with suspected metabolic disease, the specialist and genetic tests when investigating, and also discusses specific disorders, their clinical course and treatment. The role of liver transplantation is also briefly discussed. Increased awareness of this group of disorders is important as in many cases, early diagnosis leads to early intervention with improved outcome. Diagnosis also allows genetic counselling and future family planning.

Adult liver disorders caused by inborn errors of metabolism: Review and update

Sirisak Chanprasert, Fernando Scaglia
Molecular Genetics and Metabolism 114 (2015) 1–10
http://dx.doi.org/10.1016/j.ymgme.2014.10.011

Inborn errors of metabolism (IEMs) are a group of genetic diseases that have protean clinical manifestations and can involve several organ systems. The age of onset is highly variable but IEMs afflict mostly the pediatric population. However, in the past decades, the advancement in management and new therapeutic approaches have led to the improvement in IEM patient care. As a result, many patients with IEMs are surviving into adulthood and developing their own set of complications. In addition, some IEMs will present in adulthood. It is important for internists to have the knowledge and be familiar with these conditions because it is predicted that more and more adult patients with IEMs will need continuity of care in the near future. The review will focus on Wilson disease, alpha-1 antitrypsin deficiency, citrin deficiency, and HFE-associated hemochromatosis which are typically found in the adult population. Clinical manifestations and pathophysiology, particularly those that relate to hepatic disease as well as diagnosis and management will be discussed in detail.

Inborn errors of metabolism (IEMs) are a group of genetic diseases characterized by abnormal processing of biochemical reactions, resulting in accumulation of toxic substances that could interfere with normal organ functions, and failure to synthesize essential compounds. IEMs are individually rare, but collectively numerous. The clinical presentations cover a broad spectrum and can involve almost any organ system. The age of onset is highly variable but IEMs afflict mostly the pediatric population.

Wilson disease is an autosomal recessive genetic disorder of copper metabolism. It is characterized by an abnormal accumulation of inorganic copper in various tissues, most notably in the liver and the brain, especially in the basal ganglia. The disease was first described in 1912 by Kinnier Wilson, and affects between 1 in 30,000 and 1 in 100,000 individuals. Clinical features are variable and depend on the extent  and the severity of copper deposition. Typically, patients tend to develop hepatic disease at a younger age than the neuropsychiatric manifestations. Individuals withWilson disease eventually succumb to complications of end stage liver disease or become debilitated from neurological problems, if they are left untreated.

The clinical presentations of Wilson disease are varied affecting many organ systems. However, the overwhelming majority of cases display hepatic and neurologic symptoms. In general, patients with hepatic disease present between the first and second decades of life although patients as young as 3 years old or over 50 years old have also been reported. The most common modes of presentations are acute self-limited hepatitis and chronic active hepatitis that are indistinguishable from other hepatic disorders although liver aminotransferases are generally much lower than in autoimmune or viral hepatitis. Acute fulminant hepatic failure is less common but is observed in approximately 3% of all cases of acute liver failure. Symptoms of acute liver failure include jaundice, coagulopathy, and hepatic encephalopathy. Cirrhosis can develop over time and may be clinically silent. Hepatocellular carcinoma (HCC) is rarely associated with Wilson disease, but may occur in the setting of cirrhosis and chronic inflammation.

Copper is an essential element, and is required for the proper functioning of various proteins and enzymes. The total body content of copper in a healthy adult individual is approximately 70–100 mg, while the daily requirements are estimated to be between 1 and 5 mg. Absorption occurs in the small intestine. Copper is taken up to the hepatocytes via the copper transporter hTR1. Once inside the cell, copper is bound to various proteins including metallothionein and glutathione, however, it is the metal chaperone, ATOX1 that helps direct copper to the ATP7B protein for intracellular transport and excretion. At the steady state, copper will be bound to ATP7B and is then incorporated to ceruloplasmin and secreted into the systemic circulation. When the cellular copper concentration arises, ATP7B protein will be redistributed from the trans-Golgi network to the prelysosomal vesicles facilitating copper excretion into the bile. The molecular defects in ATP7B lead to a reduction of copper excretion. Excess copper is accumulated in the liver causing tissue injury. The rate of accumulation of copper varies among individuals, and it may depend on other factors such as alcohol consumption, or viral hepatitis infections. If the liver damage is not severe, patients will accumulate copper in various tissues including the brain, the kidney, the eyes, and the musculoskeletal system leading to clinical disease. A failure of copper to incorporate into ceruloplasmin leads to secretion of the unsteady protein that has a shorter half-life, resulting in the reduced concentrations of ceruloplasmin seen in most patients with Wilson disease.

Wilson disease used to be a progressive fatal condition during the first half of the 20th century because there was no effective treatment available at that time. Penicillamine was the first pharmacologic agent introduced in 1956 for treating this condition. Penicillamine is a sulfhydryl-bearing amino acid cysteine doubly substituted with methyl groups. This drug acts as a chelating agent that promotes the urinary excretion of copper. It is rapidly absorbed in the gastrointestinal track, and over 80% of circulating penicillamine is excreted via the kidneys. Although it is very effective, approximately 10%–50% of Wilson disease patients with neuropsychiatric presentations may experience worsening of their symptoms, and often times the worsening symptoms may not be reversible.

Alpha1-antitrypsin deficiency

Alpha1-antitrypsin deficiency (AATD) is one of the most common genetic liver diseases in children and adults, affecting 1 in 2000 to 1 in 3000 live births worldwide. It is transmitted in an autosomal co-dominant fashion with variable expressivity. Alpha1 antitrypsin (A1AT) is a member of the serine protease inhibitor (SERPIN) family. Its function is to counteract the proteolytic effect of neutrophil elastase and other neutrophil proteases. Mutations in the SERPINA1, the gene encoding A1AT, result in changes in the protein structure with the PiZZ phenotype being the most common cause of liver and lung disease-associated AATDs. Although, it classically causes early onset chronic obstructive pulmonary disease (COPD) in adults, liver disease characterized by chronic inflammation, hepatic fibrosis, and cirrhosis is not uncommon in the adult population. Decreased plasma concentration of A1AT predisposes lung tissue to be more susceptible to injury from protease enzymes. However, the underlying mechanism of liver injury is different, and is believed to be caused by accumulation of polymerized mutant A1AT in the hepatocyte endoplasmic reticulum (ER). Currently, there is no specific treatment for liver disease-associated AATD, but A1AT augmentation therapy is available for patients affected with pulmonary involvement.

A1AT is a single-chain, 52-kDa polypeptide of approximately 394 amino acids [56]. It is synthesized in the liver, circulates in the plasma, and functions as an inhibitor of neutrophil elastase and other proteases such as cathepsin G, and proteinase 3. A1AT has a globular shape composed of two central β sheets surrounded by a small β sheet and nine α helices. The pathophysiology underlying liver disease is thought to be a toxic gain-of-function mutation associated with the PiZZ phenotypes. This hypothesis has been supported by the fact that null alleles which produce no detectable plasma A1AT, are not associated with liver disease. In addition, the transgenic mouse model of AATD PiZZ developed periodic acid-Schiff-positive diastase-resistant intrahepatic globule early in life similar to AATD patients. The PiZZ phenotype results in the blockade of the final processing of A1AT in the liver, as only 15% of the A1AT reaches the circulation whereas 85% of non-secreted protein is accumulated in the hepatocytes.

Citrin deficiency

Citrin deficiency is a relatively newly-defined autosomal recessive disease. It encompasses two different sub-groups of patients, neonatal intrahepatic cholestasis caused by citrin deficiency (NICCD), and adult onset citrullinemia type 2 (CTLN 2).

AGC2 exports aspartate out of the mitochondrial matrix in exchange for glutamate and a proton. Thus, this protein has an important role in ureagenesis and gluconeogenesis. In CTLN2, a defect in this protein is believed to limit the supply of aspartate for the formation of argininosuccinate in the cytosol resulting in impairment of ureagenesis. Interestingly, the mouse model of citrin deficiency (Ctrn−/−) fails to develop symptoms of CTLN2 suggesting that the mitochondrial aspartate is not the only source of ureagenesis. However, it should be noted that the rodent liver expresses higher glycerol-phosphate shuttle activity than the human counterpart. With the intact glycerol-phosphate dehydrogenase, it can compensate for the deficiency of AGC2, as demonstrated by the AGC2 and glycerol-phosphate dehydrogenase double knock-out mice that exhibit similar features to those observed in human CTLN2.

HFE-associated hemochromatosis

HFE-associated hemochromatosis is an inborn error of iron metabolism characterized by excessive iron storage resulting in tissue and organ damage. It is the most common autosomal recessive disorder in the Caucasian population, affecting 0.3%–0.5% of individuals of Northern European descent. The term “hemochromatosis” was coined in 1889 by the German pathologist Friedrich Daniel Von Recklinghausen, who described it as bronze stain of organs caused by a blood borne pigment.

The classic clinical triad of cirrhosis, diabetes, and bronze skin pigmentation is rarely observed nowadays given the early recognition, diagnosis, and treatment of this condition. The most common presenting symptoms are nonspecific including weakness, lethargy, and arthralgia.

The liver is a major site of iron storage in healthy individuals and as such it is the organ that is universally affected in HFE-associated hemochromatosis. Elevation of liver aminotransferases indicative of hepatocyte injury is the most common mode of presentation and it can be indistinguishable from other causes of hepatitis. Approximately 15%–40% of patients with HFE-associated hemochromatosis have other liver conditions, including chronic viral hepatitis B or C infection, nonalcoholic fatty liver disease, and alcoholic liver disease.

 

The liver in haemochromatosis

Rune J. Ulvik
Journal of Trace Elements in Medicine and Biology xxx (2014) xxx–xxx
http://dx.doi.org/10.1016/j.jtemb.2014.08.005

The review deals with genetic, regulatory and clinical aspects of iron homeostasis and hereditary hemochromatosis. Hemochromatosis was first described in the second half of the 19th century as a clinical entity characterized by excessive iron overload in the liver. Later, increased absorption of iron from the diet was identified as the pathophysiological hallmark. In the 1970s genetic evidence emerged supporting the apparent inheritable feature of the disease. And finally in 1996 a new “hemochromato-sis gene” called HFE was described which was mutated in about 85% of the patients. From the year2000 onward remarkable progress was made in revealing the complex molecular regulation of iron trafficking in the human body and its disturbance in hemochromatosis. The discovery of hepcidin and ferroportin and their interaction in regulating the release of iron from enterocytes and macrophages to plasma were important milestones. The discovery of new, rare variants of non-HFE-hemochromatosis was explained by mutations in the multicomponent signal transduction pathway controlling hepcidin transcription. Inhibited transcription induced by the altered function of mutated gene products, results in low plasma levels of hepcidin which facilitate entry of iron from enterocytes into plasma. In time this leads to progressive accumulation of iron and subsequently development of disease in the liver and other parenchymatous organs. Being the major site of excess iron storage and hepcidin synthesis the liver is a cornerstone in maintaining normal systemic iron homeostasis. Its central pathophysiological role in HFE-hemochromatosis with downgraded hepcidin synthesis, was recently shown by the finding that liver transplantation normalized the hepcidin levels in plasma and there was no sign of iron accumulation in the new liver.

Gastrointestinal

Decoding the enigma of necrotizing enterocolitis in premature infants

Roberto Murgas TorrazzaNan Li, Josef Neu
Pathophysiology 21 (2014) 21–27
http://dx.doi.org/10.1016/j.pathophys.2013.11.011

Necrotizing enterocolitis (NEC) is an enigmatic disease that affects primarily premature infants. It often occurs suddenly and when it occurs, treatment attempts at treatment often fail and results in death. If the infant survives, there is a significant risk of long term sequelae including neurodevelopmental delays. The pathophysiology of NEC is poorly understood and thus prevention has been difficult. In this review, we will provide an overview of why progress may be slow in our understanding of this disease, provide a brief review diagnosis, treatment and some of the current concepts about the pathophysiology of this disease.

Necrotizing enterocolitis (NEC) has been reported since special care units began to house preterm infants .With the advent of modern neonatal intensive care approximately 40 years ago, the occurrence and recognition of the disease markedly increased. It is currently the most common and deadly gastro-intestinal illness seen in preterm infants. Despite major efforts to better understand, treat and prevent this devastating disease, little if any progress has been made during these 4 decades. Underlying this lack of progress is the fact that what is termed “NEC” is likely more than one disease, or mimicked by other diseases, each with a different etiopathogenesis.

Human gut microbiome

Human gut microbiome

Term or near term infants with “NEC” when compared to matched controls usually have occurrence of their disease in the first week after birth, have a significantly higher frequency of prolonged rupture of membranes, chorio-amnionitis, Apgar score <7 at 1 and 5 min, respiratory problems, congenital heart disease, hypoglycemia, and exchange transfusions. When a “NEC” like illness presents in term or near term infants, it should be noted that these are likely to be distinct in pathogenesis than the most common form of NEC and should be differentiated as such.

The infants who suffer primary ischemic necrosis are term or near term infants (although this can occur in preterms) who have concomitant congenital heart disease, often related to poor left ventricular output or obstruction. Other factors that have been associated with primary ischemia are maternal cocaine use, hyperviscosity caused by polycythemia or a severe antecedent hypoxic–ischemic event. Whether the dis-ease entity that results from this should be termed NEC can be debated on historical grounds, but the etiology is clearly different from the NEC seen in most preterm infants.

The pathogenesis of NEC is uncertain, and the etiology seems to be multifactorial. The “classic” form of NEC is highly associated with prematurity; intestinal barrier immaturity, immature immune response, and an immature regulation of intestinal blood flow (Fig.). Although genetics appears to play a role, the environment, especially a dysbiotic intestinal microbiota acting in concert with host immaturities predisposes the preterm infant to disruption of the intestinal epithelia, increased permeability of tight junctions, and release of inflammatory mediators that leads to intestinal mucosa injury and therefore development of necrotizing enterocolitis.

NEC is a multifactorial disease

NEC is a multifactorial disease

What causes NEC? NEC is a multifactorial disease with an interaction of several etiophathologies

It is clear from this review that there are several entities that have been described as NEC. What is also clear is that despite having some overlap in the final parts of the pathophysiologic cascade that lead to necrosis, the disease that is most commonly seen in the preterm infant is likely to have an origin that differs markedly from that seen in term infants with congenital heart disease or severe hypoxic–ischemic injury. Thus, epidemiologic studies will need to differentiate these entities, if the aim is to dissect common features that are most highly associated with development of the disease. At this juncture, we areleft with more of a population based preventative approach, where the use of human milk, evidence based feeding guide-lines, considerations for microbial therapy once these are proved safe and effective and approved as such by regulatory authorities, and perhaps even measures that prevent prematurity will have a major impact on this devastating disease.

Influenced by the microbiota, intestinal epithelial cells (IECs) elaborate cytokines

Influenced by the microbiota, intestinal epithelial cells (IECs) elaborate cytokines

Influenced by the microbiota, intestinal epithelial cells (IECs) elaborate cytokines, including thymic stromal lymphoprotein (TSLP), transforming growthfactor (TGF), and interleukin-10 (IL-10), that can influence pro-inflammatory cytokine production by dendritic cells (DC) and macrophages present in the laminapropria (GALT) and Peyer’s patches. Signals from commensal organisms may influence tissue-specific functions, resulting in T-cell expansion and regulation of the numbers of Th-1,
Th-2, and Th-3 cells. Also modulated by the microbiota, other IEC derived factors, including APRIL (a proliferation-inducing ligand),B-cell activating factor (BAFF), secretory leukocyte peptidase inhibitor (SLPI), prostaglandin E2(PGE2), and other metabolites, directly regulate functions ofboth antigen presenting cells and lymphocytes in the intestinal ecosystem. NK: natural killer cell; LN: lymph node; DC: dendritic cells.Modified from R. Sharma, C. Young, M. Mshvildadze, J. Neu, Intestinal microbiota does it play a role in diseases of the neonate? NeoReviews 10 (4) (2009)e166, with permission

Cross-talk between monocyte.macrophage cells and T.NK lymphocytes

Cross-talk between monocyte.macrophage cells and T.NK lymphocytes

Current Issues in the Management of Necrotizing Enterocolitis

Marion C. W. Henry and R. Lawrence Moss
Seminars in Perinatology, 2004; 28(3): 221-233
http://dx.doi.org:/10.1053/j.semperi.2004.03.010

Necrotizing enterocolitis is almost exclusively a disease of prematurity, with 90% of all cases occurring in premature infants and 90% of those infants weighing less than 2000 g. Prematurity is the only risk factor for necrotizing enterocolitis consistently identified in case control studies and the disease is rare in countries where prematurity is uncommon such as Japan and Sweden. When necrotizing enterocolitis does occur in full-term infants, it appears to by a somewhat different disease, typically associated with some predisposing condition.

NEC occurs in one to three in 1,000 live births and most commonly affects babies born between 30-32 weeks. It is most often diagnosed during the second week of life and occurs more often in previously fed infants. The mortality from NEC has been cited as 10% to 50% of all NEC cases. Surgical mortality has decreased over the last several decades from 70% to between 20 and 50%. The incremental cost per case of acute hospital care is estimated at $74 to 186 thousand compared to age matched controls, not including additional costs of long term care for the infants’ with lifelong morbidity. Survivors may develop short bowel syndrome, recurrent bouts of catheter-related sepsis, malabsorption, malnutrition, and TPN induced liver failure.

Although extensive research concerning the pathophysiology of necrotizing enterocolitis has occurred, a complete understanding has not been fully elucidated. The classic histologic finding is coagulation necrosis; present in over 90% of specimens. This finding suggests the importance of ischemia in the pathogenesis of NEC. Inflammation and bacterial overgrowth also are present. These findings support the assumptions by Kosloske that NEC occurs by the interaction of 3 events:

  • intestinal ischemia,
  • colonization by pathogenic bacteria and
  • excess protein substrate in the intestinal lumen.

Additionally, the immunologic immaturity of the neonatal gut has been implicated in the development of NEC. Reparative tissue changes including epithelial regeneration, formation of granulation tissue and fibrosis, and mixed areas of acute and chronic inflammatory changes suggest that the pathogenesis of NEC may involve a chronic process of injury and repair.

Premature newborns born prior to the 32nd week of gestational age may have compromised intestinal peristalsis and decreased motility. These motility problems may lead to poor clearance of bacteria, and subsequent bacterial overgrowth. Premature infants also have an immature intestinal tract in terms of immunologic immunity.

There are fewer functional B lymphocytes present and the ability to produce sufficient secretory IgA is reduced. Pepsin, gastric acid and mucus are also not produced as well in prematurity. All of these factors may contribute to the limited proliferation of intestinal flora and the decreased binding of these flora to mucosal cells (Fig).

Role of nitric oxide in the pathogenesis of NEC

Role of nitric oxide in the pathogenesis of NEC

Role of nitric oxide in the pathogenesis of NEC.

Characteristics of the immature gut leading to increased risk of necrotizing enterocolitis

Characteristics of the immature gut leading to increased risk of necrotizing enterocolitis

Characteristics of the immature gut leading to increased risk of necrotizing enterocolitis.

As understanding of the pathophysiology of necrotizing enterocolitis continues to evolve, a unifying concept is emerging. Initially, there is likely a subclinical insult leading to NEC. This may arise from a brief episode of hypoxia or infection. With colonization of the intestines, bacteria bind to the injured mucosa eliciting an inflammatory response which leads to further inflammation.

Intestinal Microbiota Development in Preterm Neonates and Effect of Perinatal Antibiotics

Silvia Arboleya, Borja Sanchez,, Christian Milani, Sabrina Duranti, et al.
Pediatr 2014;-:—).  http://dx.doi.org/10.1016/j.jpeds.2014.09.041

Objectives Assess the establishment of the intestinal microbiota in very low birth-weight preterm infants and to evaluate the impact of perinatal factors, such as delivery mode and perinatal antibiotics.
Study design We used 16S ribosomal RNA gene sequence-based microbiota analysis and quantitative polymerase chain reaction to evaluate the establishment of the intestinal microbiota. We also evaluated factors affecting the microbiota, during the first 3 months of life in preterm infants (n = 27) compared with full-term babies (n = 13).
Results Immaturity affects the microbiota as indicated by a reduced percentage of the family Bacteroidaceae during the first months of life and by a higher initial percentage of Lactobacillaceae in preterm infants compared with full term infants. Perinatal antibiotics, including intrapartum antimicrobial prophylaxis, affects the gut microbiota, as indicated by increased Enterobacteriaceae family organisms in the infants.

Human gut microbiome

Human gut microbiome

Conclusions Prematurity and perinatal antibiotic administration strongly affect the initial establishment of microbiota with potential consequences for later health.

Ischemia and necrotizing enterocolitis: where, when, and how

Philip T. Nowicki
Seminars in Pediatric Surgery (2005) 14, 152-158
http://dx.doi.org:/10.1053/j.sempedsurg.2005.05.003

While it is accepted that ischemia contributes to the pathogenesis of necrotizing enterocolitis (NEC), three important questions regarding this role subsist. First, where within the intestinal circulation does the vascular pathophysiology occur? It is most likely that this event begins within the intramural microcirculation, particularly the small arteries that pierce the gut wall and the submucosal arteriolar plexus insofar as these represent the principal sites of resistance regulation in the gut. Mucosal damage might also disrupt the integrity or function of downstream villous arterioles leading to damage thereto; thereafter, noxious stimuli might ascend into the submucosal vessels via downstream venules and lymphatics. Second, when during the course of pathogenesis does ischemia occur? Ischemia is unlikely to the sole initiating factor of NEC; instead, it is more likely that ischemia is triggered by other events, such as inflammation at the mucosal surface. In this context, it is likely that ischemia plays a secondary, albeit critical role in disease extension. Third, how does the ischemia occur? Regulation of vascular resistance within newborn intestine is principally determined by a balance between the endothelial production of the vasoconstrictor peptide endothelin-1 (ET-1) and endothelial production of the vasodilator free radical nitric oxide (NO). Under normal conditions, the balance heavily favors NO-induced vasodilation, leading to a low resting resistance and high rate of flow. However, factors that disrupt endothelial cell function, eg, ischemia-reperfusion, sustained low-flow perfusion, or proinflammatory mediators, alter the ET-1:NO balance in favor of constriction. The unique ET-1–NO interaction thereafter might facilitate rapid extension of this constriction, generating a viscous cascade wherein ischemia rapidly extends into larger portions of the intestine.

Schematic representation of the intestinal microcirculation

Schematic representation of the intestinal microcirculation

Schematic representation of the intestinal microcirculation. Small mesenteric arteries pierce the muscularis layers and terminate in the submucosa where they give rise to 1A (1st order) arterioles. 2A (2nd order) arterioles arise from the 1A. Although not shown here, these 2A arterioles connect merge with several 1A arterioles, thus generating an arteriolar plexus, or manifold that serves to pressurize the terminal downstream microvasculature. 3A (3rd order) arterioles arise from the 2A and proceed to the mucosa, giving off a 4A branch just before descent into the mucosa. This 4A vessel travels to the muscularis layers. Each 3A vessel becomes the single arteriole perfusing each villus.

Collectively, these studies indicate that disruption of endothelial cell function has the potential to disrupt the normal balance between NO and ET-1 within the newborn intestinal circulation, and that such an event can generate significant ischemia. In this context, it is important to note that NO and ET-1 each regulate the expression and activity of the other. An increased [NO] within the microvascular environment reduces ET-1 expression and compromises ligand binding to the ETA receptor (thus decreasing its contractile efficacy), while ET-1 compromises eNOS expression. Thus, factors that upset the balance between NO and ET-1 will have an immediate and direct effect on vascular tone, but also exert an additional indirect effect by extenuating the disruption of balance between these two factors.

It is not difficult to construct a hypothesis that links the perturbations of I/R and sustained low-flow perfusion with an initial inflammatory insult. Initiation of an inflammatory process at the mucosal–luminal interface could have a direct impact on villus and mucosal 3A arterioles, damaging arteriolar integrity and disrupting villus hemodynamics. Ascent of proinflammatory mediators to the submucosal 1A–2A arteriolar plexus could occur via draining venules and lymphatics, generating damage to vascular effector systems therein; these mediators might include cytokines and platelet activating factor, as these elements have been recovered from human infants with NEC. This event, coupled with a generalized loss of 3A flow throughout a large portion of the mucosal surface, could compromise flow rate within the submucosal arteriolar plexus.

Necrotizing enterocolitis: An update

Loren Berman, R. Lawrence Moss
Seminars in Fetal & Neonatal Medicine 16 (2011) 145e150
http://dx.doi.org:/10.1016/j.siny.2011.02.002

Necrotizing enterocolitis (NEC) is a leading cause of death among patients in the neonatal intensive care unit, carrying a mortality rate of 15e30%. Its pathogenesis is multifactorial and involves an over reactive response of the immune system to an insult. This leads to increased intestinal permeability, bacterial translocation, and sepsis. There are many inflammatory mediators involved in this process, but thus far none has been shown to be a suitable target for preventive or therapeutic measures. NEC usually occurs in the second week of life after the initiation of enteral feeds, and the diagnosis is made based on physical examination findings, laboratory studies, and abdominal radiographs. Neonates with NEC are followed with serial abdominal examinations and radiographs, and may require surgery or primary peritoneal drainage for perforation or necrosis. Many survivors are plagued with long term complications including short bowel syndrome, abnormal growth, and neurodevelopmental delay. Several evidence-based strategies exist that may decrease the incidence of NEC including promotion of human breast milk feeding, careful feeding advancement, and prophylactic probiotic administration in at-risk patients. Prevention is likely to have the greatest impact on decreasing mortality and morbidity related to NEC, as little progress has been made with regard to improving outcomes for neonates once the disease process is underway.

Immune Deficiencies

Primary immunodeficiencies: A rapidly evolving story

Nima Parvaneh, Jean-Laurent Casanova,  LD Notarangelo, ME Conley
J Allergy Clin Immunol 2013;131:314-23.
http://dx.doi.org/10.1016/j.jaci.2012.11.051

The characterization of primary immunodeficiencies (PIDs) in human subjects is crucial for a better understanding of the biology of the immune response. New achievements in this field have been possible in light of collaborative studies; attention paid to new phenotypes, infectious and otherwise; improved immunologic techniques; and use of exome sequencing technology. The International Union of Immunological Societies Expert Committee on PIDs recently reported on the updated classification of PIDs. However, new PIDs are being discovered at an ever-increasing rate. A series of 19 novel primary defects of immunity that have been discovered after release of the International Union of Immunological Societies report are discussed here. These new findings highlight the molecular pathways that are associated with clinical phenotypes and suggest potential therapies for affected patients.

Combined Immunodeficiencies

  • T-cell receptor a gene mutation: T-cell receptor ab1 T-cell depletion

T cells comprise 2 distinct lineages that express either ab or gd T-cell receptor (TCR) complexes that perform different tasks in immune responses. During T-cell maturation, the precise order and efficacy of TCR gene rearrangements determine the fate of the cells. Productive β-chain gene rearrangement produces a pre-TCR on the cell surface in association with pre-Tα invariant peptide (β-selection). Pre-TCR signals promote α-chain recombination and transition to a double-positive stage (CD41CD81). This is the prerequisite for central tolerance achieved through positive and negative selection of thymocytes.

  • Ras homolog gene family member H deficiency: Loss of naive T cells and persistent human papilloma virus infections
  • MST1 deficiency: Loss of naive T cells

New insight into the role of MST1 as a critical regulator of T-cell homing and function was provided by the characterization of 8 patients from 4 unrelated families who had homozygous nonsense mutations in STK4, the gene encoding MST1. MST1 was originally identified as an ubiquitously expressed kinase with structural homology to yeast Ste. MST1 is the mammalian homolog of the Drosophila Hippo protein, controlling cell growth, apoptosis, and tumorigenesis. It has both proapoptotic and antiapoptotic functions.

  • Lymphocyte-specific protein tyrosine kinase deficiency: T-cell deficiency with CD41 lymphopenia

Defects in pre-TCR– and TCR-mediated signaling lead to aberrant T-cell development and function (Fig). One of the earliest biochemical events occurring after engagement of the (pre)-TCR is the activation of lymphocyte-specific protein tyrosine kinase (LCK), a member of the SRC family of protein tyrosine kinases. This kinase then phosphorylates immunoreceptor tyrosine-based activation motifs of intracellular domains of CD3 subunits. Phosphorylated immunoreceptor tyrosine-based activation motifs recruit z-chain associated protein kinase of 70 kDa, which, after being phosphorylated by LCK, is responsible for activation of critical downstream events. Major consequences include activation of the membrane-associated enzyme phospholipase Cg1, activation of the mitogen-activated protein kinase, nuclear translocation of nuclear factor kB (NFkB), and Ca21/Mg21 mobilization. Through these pathways, LCK controls T-cell development and activation. In mice lacking LCK, T-cell development in the thymus is profoundly blocked at an early double-negative stage.

TCR signaling

TCR signaling

TCR signaling. Multiple signal transduction pathways are stimulated through the TCR. These pathways collectively activate transcription factors that organize T-cell survival, proliferation, differentiation, homeostasis, and migration. Mutant molecules in patients with TCR-related defects are indicated in red.

  • Uncoordinated 119 deficiency: Idiopathic CD41 lymphopenia

Idiopathic CD41 lymphopenia (ICL) is a very heterogeneous clinical entity that is defined, by default, by persistent CD41 T-cell lymphopenia (<300 cells/mL or <20% of total T cells) in the absence of HIV infection or any other known cause of immunodeficiency.

Well-Defined Syndromes with Immunodeficiency

  • Wiskott-Aldrich syndrome protein–interacting protein deficiency: Wiskott-Aldrich syndrome-like phenotype

In hematopoietic cells Wiskott-Aldrich syndrome protein (WASP) is stabilized through forming a complex with WASP interacting protein (WIP).

  • Phospholipase Cg2 gain-of-function mutations: Cold urticaria, immunodeficiency, and autoimmunity/autoinflammatory

This is a unique phenotype, sharing features of antibody deficiency, autoinflammatory diseases, and immune dysregulatory disorders, making its classification difficult. Two recent studies validated the pleiotropy of genetic alterations in the same gene.

Predominantly Antibody Defects

  • Defect in the p85a subunit of phosphoinositide 3-kinase: Agammaglobulinemia and absent B cells
  • CD21 deficiency: Hypogammaglobulinemia
  • LPS-responsive beige-like anchor deficiency:
  • Hypogammaglobulinemia with autoimmunity and

early colitis

Defects Of Immune Dysregulation

  • Pallidin deficiency: Hermansky-Pudlak syndrome type 9
  • CD27 deficiency: Immune dysregulation and
  • persistent EBV infection

Congenital Defects Of Phagocyte Number, Function, Or Both

  • Interferon-stimulated gene 15 deficiency: Mendelian susceptibility to mycobacterial diseases

Defects In Innate Immunity

  • NKX2-5 deficiency: Isolated congenital asplenia
  • Toll/IL-1 receptor domain–containing adaptor inducing IFN-b and TANK-binding kinase 1 deficiencies: Herpes simplex encephalitis
  • Minichromosome maintenance complex component 4 deficiency: NK cell deficiency associated with growth retardation and adrenal insufficiency

Autoinflammatory Disorders

  • A disintegrin and metalloproteinase 17 deficiency: Inflammatory skin and bowel disease

 

Cross-talk between monocyte.macrophage cells and T.NK lymphocytes

Cross-talk between monocyte.macrophage cells and T.NK lymphocytes

Cross-talk between monocyte/macrophage cells and T/NK lymphocytes. Genes in the IL-12/IFN-g pathway are particularly important for protection against mycobacterial disease. IRF8 is an IFN-g–inducible transcription factor required for the induction of various target genes, including IL-12. The NF-kB essential modulator (NEMO) mutations in the LZ domain impair CD40-NEMO–dependent pathways. Some gp91phox mutations specifically abolish the respiratory burst in monocyte-derived macrophages. ISG15 is secreted by neutrophils and potentiates IFN-g production by NK/T cells. Genetic defects that preclude monocyte development (eg, GATA2) can also predispose to mycobacterial infections (not shown). Mutant molecules in patients with unusual susceptibility to infection are indicated in red.

The field of PIDs is advancing at full speed in 2 directions. New genetic causes of known PIDs are being discovered (eg, CD21 and TRIF). Moreover, new phenotypes qualify as PIDs with the identification of a first genetic cause (eg, generalized pustular psoriasis). Recent findings contribute fundamental knowledge about immune system biology and its perturbation in disease. They are also of considerable clinical benefit for the patients and their families. A priority is to further translate these new discoveries into improved diagnostic methods and more effective therapeutic strategies, promoting the well-being of patients with PIDs.

Primary immunodeficiencies

Luigi D. Notarangelo
J Allergy Clin Immunol 2010; 125(2): S182-194
http://dx.doi.org:/10.1016/j.jaci.2009.07.053

In the last years, advances in molecular genetics and immunology have resulted in the identification of a growing number of genes causing primary immunodeficiencies (PIDs) in human subjects and a better understanding of the pathophysiology of these disorders. Characterization of the molecular mechanisms of PIDs has also facilitated the development of novel diagnostic assays based on analysis of the expression of the protein encoded by the PID-specific gene. Pilot newborn screening programs for the identification of infants with severe combined immunodeficiency have been initiated. Finally, significant advances have been made in the treatment of PIDs based on the use of subcutaneous immunoglobulins, hematopoietic cell transplantation from unrelated donors and cord blood, and gene therapy. In this review we will discuss the pathogenesis, diagnosis, and treatment of PIDs, with special attention to recent advances in the field.

 

 

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Classification of Microbiota –

An Overview of Clinical Microbiology, Classification, and Antimicrobial Resistance

Author and Curator: Larry H. Bernstein, MD, FCAP

Classification of Microbiota

Introduction to Overview of Microbiology

This is a contribution to a series of pieces on the history of biochemistry, molecular biology, physiology and medicine in the 20th century.  Here I describe the common microbial organisms encountered in the clinical laboratory, the method of their collection, plating, culture and identification, and antibiotic sensitivity testing and resistant strains.

I may begin with the recognition that there are common strains in the environment that are not pathogenic, and there are pathogenic bacteria.
In addition, there are bacteria that coexist in the body habitat under specific conditions so that we are able to map the types expected to location, such as, skin, mouth and nasal cavities, the colon, the vagina and urinary system.  Meningitides occur as a result of extension from the nasal cavity to the brain.  When bacteria invade the circulation, it is referred to as septicemia, and the bacteria can cause valvular heart damage.

Bacteriology can be traced to origins in the 19th century.  The clinical features of localized infection are classically referred to as redness, heat, a raised lesion (pustule), and exudate (serous or purulent – watery or cellular).  This not only holds for a focal lesion (as skin), but also for pneumonia, urinary infection, and genital. It may be accompanied by cough, or bloody cough and wheezing, or by an unclear urine. In the case of septicemia, there is fever, and there may be seizures or delirium.

Collection and handling of specimens

Specimens are collected by sterile technique by a nurse or physician and sent to a lab as a swab, or as a blood specimen.  In the case of a febrile illness, blood cultures may be obtained from opposite arms, and another an hour later.  This is related to the possible cyclical seeding of bacteria into the circulation.  If the specimen is collected from a site of infection, a swab may be put onto a glass slide for gram staining.  The specimen collected is sent to the laboratory.

We may consider syphilis and tuberculosis special cases that I’ll set aside.  I shall not go into virology either, although I may referred to smallpox, influenza, polio, HIV under epidemic.  The first step in identification is the Gram stain, developed in the 19th century.  Organisms of the skin are Gram positive and appear blue on staining.  They are cocci, or circular, organized in characteristic clusters (staphylococcus, streptococcus) or in pairs (diplococci, eg. Pneumococcus), and if from the intestine (enterococcus).  If they are elongated rods, they might be coliform.  If they stain red, they are Gram negative.  Gram negative rods are coliform, and are enterobacteriaceae. Meningococci are Gram negative cocci.  So we have certain information about these organisms before we plate them for growth.

Laboratory growth characteristics

The specimen is applied to an agar plate with a metal rod applicator, or perhaps onto more than one agar plate.  The agar plate contains a growth media or a growth inhibitor that is more favorable to certain species than to others.  The bacteria are grown at 37o C in an incubator and colonies develop that are white or nonwhite, and they are smooth or wrinkled.  The appearance of the colonies is characteristic for certain strains.  If there is no contamination, all of the colonies look the same.  The next step is to:

  • Gram stain from a colony
  • Transfer samples from the colony to a series of growth media that identify presence or absence of specific nutrient requirements for growth (which is presumed from the prior findings).

In addition, the colony samples are grown on an agar to which is applied antibiotic tabs.  The tabs either allow or repress growth.  It wa some 50 years ago that the infectious disease physician and microbiologist Abraham Braude would culture the bacteria on agar plates that had a gradient of antibiotic to check for concentration that would inhibit growth.

Principles of Diagnosis (Extracts)

By John A. Washington

The clinical presentation of an infectious disease reflects the interaction between the host and the microorganism. This interaction is affected by the host immune status and microbial virulence factors. Signs and symptoms vary according to the site and severity of infection. Diagnosis requires a composite of information, including history, physical examination, radiographic findings, and laboratory data.

Microbiologic Examination

Direct Examination and Techniques: Direct examination of specimens reveals gross pathology. Microscopy may identify microorganisms. Immunofluorescence, immuno-peroxidase staining, and other immunoassays may detect specific microbial antigens. Genetic probes identify genus- or species-specific DNA or RNA sequences.

Culture: Isolation of infectious agents frequently requires specialized media. Nonselective (noninhibitory) media permit the growth of many microorganisms. Selective media contain inhibitory substances that permit the isolation of specific types of microorganisms.

Microbial Identification: Colony and cellular morphology may permit preliminary identification. Growth characteristics under various conditions, utilization of carbohydrates and other substrates, enzymatic activity, immunoassays, and genetic probes are also used.

Serodiagnosis: A high or rising titer of specific IgG antibodies or the presence of specific IgM antibodies may suggest or confirm a diagnosis.

Antimicrobial Susceptibility: Microorganisms, particularly bacteria, are tested in vitro to determine whether they are susceptible to antimicrobial agents.

Diagnostic medical microbiology is the discipline that identifies etiologic agents of disease. The job of the clinical microbiology laboratory is to test specimens from patients for microorganisms that are, or may be, a cause of the illness and to provide information (when appropriate) about the in vitro activity of antimicrobial drugs against the microorganisms identified (Fig. 1).

Laboratory procedures used in confirming a clinical diagnosis of infectious disease with a bacterial etiology

http://www.ncbi.nlm.nih.gov/books/NBK8014/bin/ch10f1.jpg

A variety of microscopic, immunologic, and hybridization techniques have been developed for rapid diagnosis

techniques have been developed for rapid diagnosis

techniques have been developed for rapid diagnosis

From: Chapter 10, Principles of Diagnosis
Medical Microbiology. 4th edition.
Baron S, editor.
Galveston (TX): University of Texas Medical Branch at Galveston; 1996.

For immunologic detection of microbial antigens, latex particle agglutination, coagglutination, and enzyme-linked immunosorbent assay (ELISA) are the most frequently used techniques in the clinical laboratory. Antibody to a specific antigen is bound to latex particles or to a heat-killed and treated protein A-rich strain of Staphylococcus aureus to produce agglutination (Fig. 10-2). There are several approaches to ELISA; the one most frequently used for the detection of microbial antigens uses an antigen-specific antibody that is fixed to a solid phase, which may be a latex or metal bead or the inside surface of a well in a plastic tray. Antigen present in the specimen binds to the antibody as inFig. 10-2. The test is then completed by adding a second antigen-specific antibody bound to an enzyme that can react with a substrate to produce a colored product. The initial antigen antibody complex forms in a manner similar to that shown inFigure 10-2. When the enzyme-conjugated antibody is added, it binds to previously unbound antigenic sites, and the antigen is, in effect, sandwiched between the solid phase and the enzyme-conjugated antibody. The reaction is completed by adding the enzyme substrate.

agglutination test ch10f2

agglutination test ch10f2

Figure 2 Agglutination test in which inert particles (latex beads or heat-killed S aureus Cowan 1 strain with protein A) are coated with antibody to any of a variety of antigens and then used to detect the antigen in specimens or in isolated bacteria

http://www.ncbi.nlm.nih.gov/books/NBK8014/bin/ch10f2.jpg

Genetic probes are based on the detection of unique nucleotide sequences with the DNA or RNA of a microorganism. Once such a unique nucleotide sequence, which may represent a portion of a virulence gene or of chromosomal DNA, is found, it is isolated and inserted into a cloning vector (plasmid), which is then transformed into Escherichia coli to produce multiple copies of the probe. The sequence is then reisolated from plasmids and labeled with an isotope or substrate for diagnostic use. Hybridization of the sequence with a complementary sequence of DNA or RNA follows cleavage of the double-stranded DNA of the microorganism in the specimen.

The use of molecular technology in the diagnoses of infectious diseases has been further enhanced by the introduction of gene amplication techniques, such as the polymerase chain reaction (PCR) in which DNA polymerase is able to copy a strand of DNA by elongating complementary strands of DNA that have been initiated from a pair of closely spaced oligonucleotide primers. This approach has had major applications in the detection of infections due to microorganisms that are difficult to culture (e.g. the human immunodeficiency virus) or that have not as yet been successfully cultured (e.g. the Whipple’s disease bacillus).

Solid media, although somewhat less sensitive than liquid media, provide isolated colonies that can be quantified if necessary and identified. Some genera and species can be recognized on the basis of their colony morphologies.

In some instances one can take advantage of differential carbohydrate fermentation capabilities of microorganisms by incorporating one or more carbohydrates in the medium along with a suitable pH indicator. Such media are called differential media (e.g., eosin methylene blue or MacConkey agar) and are commonly used to isolate enteric bacilli. Different genera of the Enterobacteriaceae can then be presumptively identified by the color as well as the morphology of colonies.

Culture media can also be made selective by incorporating compounds such as antimicrobial agents that inhibit the indigenous flora while permitting growth of specific microorganisms resistant to these inhibitors. One such example is Thayer-Martin medium, which is used to isolate Neisseria gonorrhoeae. This medium contains vancomycin to inhibit Gram-positive bacteria, colistin to inhibit most Gram-negative bacilli, trimethoprim-sulfamethoxazole to inhibit Proteus species and other species that are not inhibited by colistin and anisomycin to inhibit fungi. The pathogenic Neisseria species, N gonorrhoeae and N meningitidis, are ordinarily resistant to the concentrations of these antimicrobial agents in the medium.

Infection of the bladder (cystitis) or kidney (pyelone-phritis) is usually accompanied by bacteriuria of about ≥ 104 CFU/ml. For this reason, quantitative cultures (Fig. 10-3) of urine must always be performed. For most other specimens a semiquantitative streak method (Fig. 10-3) over the agar surface is sufficient. For quantitative cultures, a specific volume of specimen is spread over the agar surface and the number of colonies per milliliter is estimated.

Identification of bacteria (including mycobacteria) is based on growth characteristics (such as the time required for growth to appear or the atmosphere in which growth occurs), colony and microscopic morphology, and biochemical, physiologic, and, in some instances, antigenic or nucleotide sequence characteristics. The selection and number of tests for bacterial identification depend upon the category of bacteria present (aerobic versus anaerobic, Gram-positive versus Gram-negative, cocci versus bacilli) and the expertise of the microbiologist examining the culture. Gram-positive cocci that grow in air with or without added CO2 may be identified by a relatively small number of tests. The identification of most Gram-negative bacilli is far more complex and often requires panels of 20 tests for determining biochemical and physiologic characteristics.

Antimicrobial susceptibility tests are performed by either disk diffusion or a dilution method. In the former, a standardized suspension of a particular microorganism is inoculated onto an agar surface to which paper disks containing various antimicrobial agents are applied. Following overnight incubation, any zone diameters of inhibition about the disks are measured. An alternative method is to dilute on a log2 scale each antimicrobial agent in broth to provide a range of concentrations and to inoculate each tube or, if a microplate is used, each well containing the antimicrobial agent in broth with a standardized suspension of the microorganism to be tested. The lowest concentration of antimicrobial agent that inhibits the growth of the microorganism is the minimal inhibitory concentration.

Classification Principles

This Week’s Citation Classic®_______ Sneath P H A & Sokal R R.
Numerical taxonomy: the principles and practice of
numerical classification. San Francisco: Freeman, 1973. 573 p.
[Medical Research Council Microbial Systematics Unit, Univ. Leicester, England
and Dept. Ecology and Evolution, State Univ. New York, Stony Brook, NY]
Numerical taxonomy establishes classification
of organisms based on their similarities. It utilizes
many equally weighted characters and employs
clustering and similar algorithms to yield
objective groupings. It can beextended to give
phylogenetic or diagnostic systems and can be
applied to many other fields of endeavour.

Mathematical Foundations of Computer Science 1998
Lecture Notes in Computer Science Volume 1450, 1998, pp 474-482
Date: 28 May 2006
Positive Turing and truth-table completeness for NEXP are incomparable 1998
Levke Bentzien

The truth-table method [matrix method] is one of the decision procedures for sentence logic (q.v., §3.2). The method is based on the fact that the truth value of a compound formula of sentence logic, construed as a truth-function, is determined by the truth values of its arguments (cf. “Sentence logic” §2.2). To decide whether a formula A is a tautology or not, we list all possible combinations of truth values to the variables in A: A is a tautology if it takes the value truth under each assignment.

Using ideas introduced by Buhrman et al. ([2], [3]) to separate various completeness notions for NEXP = NTIME (2poly), positive Turing complete sets for NEXP are studied. In contrast to many-one completeness and bounded truth-table completeness with norm 1 which are known to coincide on NEXP ([3]), whence any such set for NEXP is positive Turing complete, we give sets A and B such that

A is ≤ bT(2) P -complete but not ≤ posT P -complete for NEXP

B is ≤ posT P -complete but not ≤ tt P -complete for NEXP. These results come close to optimality since a further strengthening of (1), as was done by Buhrman in [1] for EXP = DTIME(2poly), seems to require the assumption NEXP = co-NEXP.

Computability and Models
The University Series in Mathematics 2003, pp 1-10
Truth-Table Complete Computably Enumerable Sets
Marat M. Arslanov

We prove a truth-table completeness criterion for computably enumerable sets.
The authors research was partially supported by Russian Foundation of Basic Research, Project 99-01-00830, and RFBR-INTAS, Project 97-91-71991.

TRUTH TABLE CLASSIFICATION AND IDENTIFICATION*
EUGENE W. RYPKA
Department of Microbiology, Lovelace Foundation for Medical Education and Research,
Albuquerque, N.M. 87108, U.S.A.
Space life sciences 1971-12-1; 3(2): pp 135-156
http://dx.doi.org:/10.1007/BF00927988
(Received 15 July, 1971)
Abstract. A logical basis for classification is that elements grouped together and higher categories of elements should have a high degree of similarity with the provision that all groups and categories be disjoint to some degree. A methodology has been developed for constructing classifications automatically that gives
nearly instantaneous correlations of character patterns of organisms with time and clusters with apparent similarity. This means that automatic numerical identification will always construct schemes from which disjoint answers can be obtained if test sensitivities for characters are correct. Unidentified organisms are recycled through continuous classification with reconstruction of identification schemes. This process is
cyclic and self-correcting. The method also accumulates and analyzes data which updates and presents a more accurate biological picture.

Syndromic classification: A process for amplifying information using S-clustering

Eugene W. Rypka, PHD

http://dx.doi.org:/10.1016/S0899-9007(96)00315-2

Optimal classification/Rypka < Optimal classification>

Contents

1 Rypka’s Method

1.1 Equations

1.2 Examples

2 Notes and References

Rypka’s Method

Rypka’s[1] method[2] utilizes the theoretical and empirical separatory equations shown below to perform the task of optimal classification. The method finds the optimal order of the fewest attributes, which in combination define a bounded class of elements.

Application of the method begins with construction of an attribute-valued system in truth table[3] or spreadsheet form with elements listed in the left most column beginning in the second row. Characteristics[4] are listed in the first row beginning in the second column with the code name of the data in the upper left most cell. The values which connect each characteristic with each element are placed in the intersecting cells. Selecting appropriate characteristics to universally define the class of elements may be the most difficult part for the classifier of utilizing this method.

The elements are first sorted in descending order according to their truth table value, which is calculated from the existing sequence and value of characteristics for each element. Duplicate truth table values or multisets for the entire bounded class reveal either the need to eliminate duplicate elements or the need to include additional characteristics.

An empirical separatory value is calculated for each characteristic in the set and the characteristic with the greatest empirical separatory value is exchanged with the characteristic which occupies the most significant attribute position.

Next the second most significant characteristic is found by calculating an empirical separatory value for each remaining characteristic in combination with the first characteristic. The characteristic which produces the greatest separatory value is then exchanged with the characteristic which occupies the second most significant attribute position.

Next the third most significant characteristic is found by calculating an empirical separatory value for each remaining characteristic in combination with the first and second characteristics. The characteristic which produces the greatest empirical separatory value is then exchanged with the characteristic which occupies the third most significant attribute position. This procedure may continue until all characteristics have been processed or until one hundred percent separation of the elements has been achieved.

A larger radix will allow faster identification by excluding a greater percentage of elements per characteristic. A binary radix for instance excludes only fifty percent of the elements per characteristic whereas a five-valued radix excludes eighty percent of the elements per characteristic.[5] What follows is an elucidation of the matrix and separatory equations.[6]

Computational Example
Bounded Class Data

bounded class data

Bounded Class Dimensions

G = 28 – 28 elements – i = 0…G-1[1]

C = 10 – 10 characteristics or attributes – j = 0…C-1

V = 5 – 5 valued logic – l = 0…V-1

Order of Elements

order of elements

Count multisets

count multisets

Squared multiset Counts

squared multiset counts

Separatory Values

separatory values

T=

max(T) = 309 = S8 = highest initial separatory value

Notes

Mathcad’s ORIGIN function applies to all arrays such that if more than one array is being used and one array requires a zero origin then the other arrays must use a zero origin with all variables being adapted as well.

Rypka’s Method Edit

Rypka’s[1] method[2] utilizes the theoretical and empirical separatory equations shown below to perform the task of optimal classification. The method finds the optimal order of the fewest attributes, which in combination define a bounded class of elements.

Application of the method begins with construction of an attribute-valued system in truth table[3] or spreadsheet form with elements listed in the left most column beginning in the second row. Characteristics[4] are listed in the first row beginning in the second column with the title of the attributes in the upper left most cell. Normally the file name of the data is given the title of the element class. The values which connect each characteristic with each element are placed in the intersecting cells. Selecting characteristics which all elements share may be the most difficult part of creating a database which can utilizing this method.

The elements are first sorted in descending order according to their truth table value, which is calculated from the existing sequence and value of characteristics for each element. Duplicate truth table values or multisets for the entire bounded class reveal either the need to eliminate duplicate elements or the need to include additional characteristics.

An empirical separatory value is calculated for each characteristic in the set and the characteristic with the greatest empirical separatory value is exchanged with the characteristic which occupies the most significant attribute position.

Next the second most significant characteristic is found by calculating an empirical separatory value for each remaining characteristic in combination with the first characteristic. The characteristic which produces the greatest separatory value is then exchanged with the characteristic which occupies the second most significant attribute position.

Next the third most significant characteristic is found by calculating an empirical separatory value for each remaining characteristic in combination with the first and second characteristics. The characteristic which produces the greatest empirical separatory value is then exchanged with the characteristic which occupies the third most significant attribute position. This procedure may continue until all characteristics have been processed or until one hundred percent separation of the elements has been achieved.

A larger radix will allow faster identification by excluding a greater percentage of elements per characteristic. A binary radix for instance excludes only fifty percent of the elements per characteristic whereas a five-valued radix excludes eighty percent of the elements per characteristic.[5] What follows is an elucidation of the matrix and separatory equations.[6]

Syndromic Classification: A Process for Amplifying Information Using S-Clustering

Eugene W. Rypka, PhD
University of New Mexico, Albuquerque, New Mexico, USA
Statistics Editor: Marcello Pagano, PhD
Harvard School of Public Health, Boston, Massachusetts, USA
Nutrition 1996; 12(11/12): 827-829

In a previous issue of Nutrition, Drs. Bernstein and Pleban’ use the method of S-clustering to aid in nutritional classification of patients directly on-line. Classification of this type is called primary or syndromic classification.* It is created by a process called separatory (S-) clustering (E. Rypka, unpublished observations). The authors use S-clustering in Table I.  S-clustering extracts features (analytes, variables) from endogenous data that amplify or maximize structural information to create classes of patients (pathophysiologic events) which are the most disjointed or separable. S-clustering differs from other classificatory methods because it finds in a database a theoretic- or more- number of variables with the required variety that map closest to an ideal, theoretic, or structural information standard. In Table I of their article, Bernstein and Pleban’ indicate there would have to be 3 ’ = 243 rows to show all possible patterns. In Table II of this article, I have used a 33 = 27 row truth table to convey the notion of mapping amplified information to an ideal, theoretic standard using just the first three columns. Variables are scaled for use in S-clustering.

A Survey of Binary Similarity and Distance Measures
Seung-Seok Choi, Sung-Hyuk Cha, Charles C. Tappert
SYSTEMICS, CYBERNETICS AND INFORMATICS 2010; 8(1): 43-48
The binary feature vector is one of the most common
representations of patterns and measuring similarity and
distance measures play a critical role in many problems
such as clustering, classification, etc. Ever since Jaccard
proposed a similarity measure to classify ecological
species in 1901, numerous binary similarity and distance
measures have been proposed in various fields. Applying
appropriate measures results in more accurate data
analysis. Notwithstanding, few comprehensive surveys
on binary measures have been conducted. Hence we
collected 76 binary similarity and distance measures used
over the last century and reveal their correlations through
the hierarchical clustering technique.

This paper is organized as follows. Section 2 describes
the definitions of 76 binary similarity and dissimilarity
measures. Section 3 discusses the grouping of those
measures using hierarchical clustering. Section 4
concludes this work.

Historically, all the binary measures observed above have
had a meaningful performance in their respective fields.
The binary similarity coefficients proposed by Peirce,
Yule, and Pearson in 1900s contributes to the evolution
of the various correlation based binary similarity
measures. The Jaccard coefficient proposed at 1901 is
still widely used in the various fields such as ecology and
biology. The discussion of inclusion or exclusion of
negative matches was actively arisen by Sokal & Sneath
in during 1960s and by Goodman & Kruskal in 1970s.

Polyphasic Taxonomy of the Genus Vibrio: Numerical Taxonomy of Vibrio cholerae, Vibrio
parahaemolyticus, and Related Vibrio Species
R. R. COLWELL
JOURNAL OF BACTERIOLOGY, Oct. 1970;  104(1): 410-433
A set of 86 bacterial cultures, including 30 strains of Vibrio cholerae, 35 strains of
V. parahaemolyticus, and 21 representative strains of Pseudomonas, Spirillum,
Achromobacter, Arthrobacter, and marine Vibrio species were tested for a total of 200
characteristics. Morphological, physiological, and biochemical characteristics were
included in the analysis. Overall deoxyribonucleic acid (DNA) base compositions
and ultrastructure, under the electron microscope, were also examined. The taxonomic
data were analyzed by computer by using numerical taxonomy programs
designed to sort and cluster strains related phenetically. The V. cholerae strains
formed an homogeneous cluster, sharing overall S values of >75%. Two strains,
V. cholerae NCTC 30 and NCTC 8042, did not fall into the V. cholerae species
group when tested by the hypothetical median organism calculation. No separation
of “classic” V. cholerae, El Tor vibrios, and nonagglutinable vibrios was observed.
These all fell into a single, relatively homogeneous, V. cholerae species cluster.
PJ. parahaemolyticus strains, excepting 5144, 5146, and 5162, designated members
of the species V. alginolyticus, clustered at S >80%. Characteristics uniformly
present in all the Vibrio species examined are given, as are also characteristics and
frequency of occurrence for V. cholerae and V. parahaemolyticus. The clusters formed
in the numerical taxonomy analyses revealed similar overall DNA base compositions,
with the range for the Vibrio species of 40 to 48% guanine plus cytosine. Generic
level of relationship of V. cholerae and V. parahaemolyticus is considered
dubious. Intra- and intergroup relationships obtained from the numerical taxonomy
studies showed highly significant correlation with DNA/DNA reassociation data.

A Numerical Classification of the Genus Bacillus
By FERGUS G . PRIEST, MICHAEL GOODFELLOW AND CAROLE TODD
Journal of General Microbiology (1988), 134, 1847-1882.

Three hundred and sixty-eight strains of aerobic, endospore-forming bacteria which included type and reference cultures of Bacillus and environmental isolates were studied. Overall similarities of these strains for 118 unit characters were determined by the SSMS,, and Dp coefficients and clustering achieved using the UPGMA algorithm. Test error was within acceptable limits. Six cluster-groups were defined at 70% SSM which corresponded to 69% Sp and 48-57% SJ.G roupings obtained with the three coefficients were generally similar but there were some changes in the definition and membership of cluster-groups and clusters, particularly with the SJ coefficient. The Bacillus strains were distributed among 31 major (4 or more strains), 18 minor (2 or 3 strains) and 30 single-member clusters at the 83% SsMle vel. Most of these clusters can be regarded as taxospecies. The heterogeneity of several species, including Bacillus breuis, B. circulans, B. coagulans, B. megateriun, B . sphaericus and B . stearothermophilus, has been indicated  and the species status of several taxa of hitherto uncertain validity confirmed. Thus on the basis of the numerical phenetic and appropriate (published) molecular genetic data, it is proposed
that the following names be recognized; BacillusJlexus (Batchelor) nom. rev., Bacillus fusiformis (Smith et al.) comb. nov., Bacillus kaustophilus (Prickett) nom. rev., Bacilluspsychrosaccharolyticus (Larkin & Stokes) nom. rev. and Bacillus simplex (Gottheil) nom. rev. Other phenetically well-defined taxospecies included ‘ B. aneurinolyticus’, ‘B. apiarius’, ‘B. cascainensis’, ‘B. thiaminolyticus’ and three clusters of environmental isolates related to B . firmus and previously described as ‘B. firmus-B. lentus intermediates’. Future developments in the light of the numerical phenetic data are discussed.

Numerical Classification of Bacteria
Part II. * Computer Analysis of Coryneform Bacteria (2)
Comparison of Group-Formations Obtained on Two
Different Methods of Scoring Data
By Eitaro MASUOan d Toshio NAKAGAWA
[Agr. Biol. Chem., 1969; 33(8): 1124-1133.
Sixty three organisms selected from 12 genera of bacteria were subjected to numerical analysis. The purpose of this work is to examine the relationships among 38 coryneform bacteria included in the test organisms by two coding methods-Sneath’s and Lockhart’s systems-, and to compare the results with conventional classification. In both cases of codification, five groups and one or two single item(s) were found in the resultant classifications. Different codings brought, however, a few distinct differences in some groups , especially in a group of sporogenic bacilli or lactic-acid bacteria. So far as the present work concerns, the result obtained on Lockhart’s coding rather than that obtained on Sneath’s coding resembled the conventional classification. The taxonomic positions of corynebacteria were quite different from those of the conventional classification, regardless
of which coding method was applied.
Though animal corynebacteria have conventionally been considered to occupy the
taxonomic position neighboring to genera Arthrobacter and Cellulornonas and regarded to be the nucleus of so-called “coryneform bacteria,’ the present work showed that many of the corynebacteria are akin to certain mycobacteria rather than to the organisms belonging to the above two genera.

Numerical Classification of Bacteria
Part III. Computer Analysis of “Coryneform Bacteria” (3)
Classification Based on DNA Base Compositions
By EitaroM ASUaOnd ToshioN AKAGAWA
Agr. Biol. Chem., 1969; 33(11): 1570-1576
It has been known that the base compositions of deoxyribonucleic acids (DNA) are
quite different from organism to organism. A pertinent example of this diversity is
found in bacterial species. The base compositions of DNA isolated from a wide variety
of bacteria are distributed in a range from 25 to 75 GC mole-percent (100x(G+C)/
(A+T+G+C)).1) The usefulness of the information of DNA base composition for
the taxonomy of bacteria has been emphasized by several authors. Lee et al.,” Sueoka,” and Freese) have speculated on the evolutionary significance of microbial DNA base composition. They pointed out that closely related microorganisms generally showed similar base compositions of DNA, and suggested that phylogenetic relationship should be reflected in the GC content.
In the present paper are compared the results of numerical classifications of 45
bacteria based on the two different similarity matrices: One representing the overall
similarities of phenotypic properties, the other representing the similarities of GC contents.

Advanced computational algorithms for microbial community analysis using massive 16S rRNA
sequence data
Y Sun, Y Cai, V Mai, W Farmerie, F Yu, J Li and S Goodison
Nucleic Acids Research, 2010; 38(22): e205
http://dx.doi.org:/10.1093/nar/gkq872

With the aid of next-generation sequencing technology, researchers can now obtain millions of microbial signature sequences for diverse applications ranging from human epidemiological studies to global ocean surveys. The development of advanced computational strategies to maximally extract pertinent information from massive nucleotide data has become a major focus of the bioinformatics community. Here, we describe a novel analytical strategy including discriminant and topology analyses that enables researchers to deeply investigate the hidden world of microbial communities, far beyond basic microbial diversity estimation. We demonstrate the utility of our
approach through a computational study performed on a previously published massive human gut 16S rRNA data set. The application of discriminant and
topology analyses enabled us to derive quantitative disease-associated microbial signatures and describe microbial community structure in far more detail than previously achievable. Our approach provides rigorous statistical tools for sequence based studies aimed at elucidating associations between known or unknown organisms and a variety of physiological or environmental conditions.

What is Drug Resistance?

Antimicrobial resistance is the ability of microbes, such as bacteria, viruses, parasites, or fungi, to grow in the presence of a chemical (drug) that would normally kill it or limit its growth.

Diagram showing the difference between non-resistant bacteria and drug resistant bacteria.

Credit: NIAID

DrugResistance difference between non-resistant bacteria and drug resistant bacteria

DrugResistance difference between non-resistant bacteria and drug resistant bacteria

http://www.niaid.nih.gov/SiteCollectionImages/topics/antimicrobialresistance/1whatIsDrugResistance.gif

Diagram showing the difference between non-resistant bacteria and drug resistant bacteria. Non-resistant bacteria multiply, and upon drug treatment, the bacteria die. Drug resistant bacteria multiply as well, but upon drug treatment, the bacteria continue to spread.

Between 5 and 10 percent of all hospital patients develop an infection. About 90,000 of these patients die each year as a result of their infection, up from 13,300 patient deaths in 1992.

According to the Centers for Disease Control and Prevention (April 2011), antibiotic resistance in the United States costs an estimated $20 billion a year in excess health care costs, $35 million in other societal costs and more than 8 million additional days that people spend in the hospital.

Resistance to Antibiotics: Are We in the Post-Antibiotic Era?

Alfonso J. Alanis
Archives of Medical Research 36 (2005) 697–705
http://dx.doi.org:/10.1016/j.arcmed.2005.06.009

Serious infections caused by bacteria that have become resistant to commonly used antibiotics have become a major global healthcare problem in the 21st century. They not only are more severe and require longer and more complex treatments, but they are also significantly more expensive to diagnose and to treat. Antibiotic resistance, initially a problem of the hospital setting associated with an increased number of hospital acquired infections usually in critically ill and immunosuppressed patients, has now extended into the community causing severe infections difficult to diagnose and treat. The molecular mechanisms by which bacteria have become resistant to antibiotics are diverse and complex. Bacteria have developed resistance to all different classes of antibiotics discovered to date. The most frequent type of resistance is acquired and transmitted horizontally via the conjugation of a plasmid. In recent times new mechanisms of resistance have resulted in the simultaneous development of resistance to several antibiotic classes creating very dangerous multidrug-resistant (MDR) bacterial strains, some also known as ‘‘superbugs’’. The indiscriminate and inappropriate use of antibiotics in outpatient clinics, hospitalized patients and in the food industry is the single largest factor leading to antibiotic resistance. The pharmaceutical industry, large academic institutions or the government are not investing the necessary resources to produce the next generation of newer safe and effective antimicrobial drugs. In many cases, large pharmaceutical companies have terminated their anti-infective research programs altogether due to economic reasons. The potential negative consequences of all these events are relevant because they put society at risk for the spread of potentially serious MDR bacterial infections.

Targeting the Human Macrophage with Combinations of Drugs and Inhibitors of Ca2+ and K+ Transport to Enhance the Killing of Intracellular Multi-Drug Resistant M. tuberculosis (MDR-TB) – a Novel, Patentable Approach to Limit the Emergence of XDR-TB

Marta Martins
Recent Patents on Anti-Infective Drug Discovery, 2011, 6, 000-000

The emergence of resistance in Tuberculosis has become a serious problem for the control of this disease. For that reason, new therapeutic strategies that can be implemented in the clinical setting are urgently needed. The design of new compounds active against mycobacteria must take into account that Tuberculosis is mainly an intracellular infection of the alveolar macrophage and therefore must maintain activity within the host cells. An alternative therapeutic approach will be described in this review, focusing on the activation of the phagocytic cell and the subsequent killing of the internalized bacteria. This approach explores the combined use of antibiotics and phenothiazines, or Ca2+ and K+ flux inhibitors, in the infected macrophage. Targeting the infected macrophage and not the internalized bacteria could overcome the problem of bacterial multi-drug resistance. This will potentially eliminate the appearance of new multi-drug resistant tuberculosis (MDR-TB) cases and subsequently prevent the emergence of extensively-drug resistant tuberculosis (XDR-TB). Patents resulting from this novel and innovative approach could be extremely valuable if they can be implemented in the clinical setting. Other patents will also be discussed such as the treatment of TB using immunomodulator compounds (for example: betaglycans).

Six Epigenetic Faces of Streptococcus

Kevin Mayer
http://www.genengnews.com/gen-news-highlights/six-epigenetic-faces-of-streptococcus/81250430/

Medical illustration of Streptococcus pneumonia. [CDC]

Streptococcus pneumonia

Streptococcus pneumonia

It appears that S. pneumoniae has even more personalities, each associated with a different proclivity toward invasive, life-threatening disease. In fact, any of six personalities may emerge depending on the action of a single genetic switch.

To uncover the switch, an international team of scientists conducted a study in genomics, but they looked beyond nucleotide polymorphisms or accessory regions as possible phenotype-shifting mechanisms. Instead, they focused on the potential of restriction-modification (RM) systems to mediate gene regulation via epigenetic changes.

Scientists representing the University of Leicester, Griffith University’s Institute for Glycomics, theUniversity of Adelaide, and Pacific Biosciences realized that the S. pneumoniae genome contains two Type I, three Type II, and one Type IV RM systems. Of these, only the DpnI Type II RM system had been described in detail. Switchable Type I systems had been described previously, but these reports did not provide evidence for differential methylation or for phenotypic impact.

As it turned out, the Type I system embodied a mechanism capable of randomly changing the bacterium’s characteristics into six alternative states. The mechanism’s details were presented September 30 in Nature Communications, in an article entitled, “A random six-phase switch regulates pneumococcal virulence via global epigenetic changes.”

“The underlying mechanism for such phase variation consists of genetic rearrangements in a Type I restriction-modification system (SpnD39III),” wrote the authors. “The rearrangements generate six alternative specificities with distinct methylation patterns, as defined by single-molecule, real-time (SMRT) methylomics.”

Eradication of multidrug-resistant A. baumanniii in burn wounds by antiseptic pulsed electric field.

A Golberg, GF Broelsch, D Vecchio,S Khan, MR Hamblin, WG Austen, Jr, RL Sheridan,  ML Yarmush.

Emerging bacterial resistance to multiple drugs is an increasing problem in burn wound management. New non-pharmacologic interventions are needed for wound disinfection. Here we report on a novel physical method for disinfection: antiseptic pulsed electric field (PEF) applied externally to the infected wounds.  In an animal model, we show that PEF can reduce the load of multidrug resistant Acinetobacter baumannii present in a full thickness burn wound by more than four orders of magnitude, as detected by bioluminescence imaging. Furthermore, using a finite element numerical model, we demonstrate that PEF provides non-thermal, homogeneous, full thickness treatment for the burn wound, thus, overcoming the limitation of treatment depth for many topical antimicrobials. These modeling tools and our in vivo results will be extremely useful for further translation of the PEF technology to the clinical setting. We believe that PEF, in combination with systemic antibiotics, will synergistically eradicate multidrug-resistant burn wound infections, prevent biofilm formation and restore natural skin microbiome. PEF provides a new platform for infection combat in patients, therefore it has a potential to significantly decreasing morbidity and mortality.

Golberg, A. & Yarmush, M. L. Nonthermal irreversible electroporation: fundamentals, applications, and challenges. IEEE Trans Biomed Eng 60, 707-14 (2013).

Mechanisms Of Antibiotic Resistance In Salmonella: Efflux Pumps, Genetics, Quorum Sensing And Biofilm Formation.

Martins M, McCusker M, Amaral L, Fanning S
Perspectives in Drug Discovery and Design 02/2011; 8:114-123.

In Salmonella the main mechanisms of antibiotic resistance are mutations in target genes (such as DNA gyrase and topoisomerase IV) and the over-expression of efflux pumps. However, other mechanisms such as changes in the cell envelope; down regulation of membrane porins; increased lipopolysaccharide (LPS) component of the outer cell membrane; quorum sensing and biofilm formation can also contribute to the resistance seen in this microorganism. To overcome this problem new therapeutic approaches are urgently needed. In the case of efflux-mediated multidrug resistant isolates, one of the treatment options could be the use of efflux pump inhibitors (EPIs) in combination with the antibiotics to which the bacteria is resistant. By blocking the efflux pumps resistance is partly or wholly reversed, allowing antibiotics showing no activity against the MDR strains to be used to treat these infections. Compounds that show potential as an EPI are therefore of interest, as well as new strategies to target the efflux systems. Quorum sensing (QS) and biofilm formation are systems also known to be involved in antibiotic resistance. Consequently, compounds that can disrupt or inhibit these bacterial “communication systems” will be of use in the treatment of these infections.

Role of Phenothiazines and Structurally Similar Compounds of Plant Origin in the Fight against Infections by Drug Resistant Bacteria

SG Dastidar, JE Kristiansen, J Molnar and L Amaral
Antibiotics 2013, 2, 58-71;
http://dx.doi.org:/10.3390/antibiotics2010058

Phenothiazines have their primary effects on the plasma membranes of prokaryotes and eukaryotes. Among the components of the prokaryotic plasma membrane affected are efflux pumps, their energy sources and energy providing enzymes, such as ATPase, and genes that regulate and code for the permeability aspect of a bacterium. The response of multidrug and extensively drug resistant tuberculosis to phenothiazines shows an alternative therapy for its treatment. Many phenothiazines have shown synergistic activity with several antibiotics thereby lowering the doses of antibiotics administered for specific bacterial infections. Trimeprazine is synergistic with trimethoprim. Flupenthixol (Fp) has been found to be synergistic with penicillin and chlorpromazine (CPZ); in addition, some antibiotics are also synergistic. Along with the antibacterial action described in this review, many phenothiazines possess plasmid curing activities, which render the bacterial carrier of the plasmid sensitive to antibiotics. Thus, simultaneous applications of a phenothiazine like TZ would not only act as an additional antibacterial agent but also would help to eliminate drug resistant plasmid from the infectious bacterial cells.

Multidrug Efflux Pumps Described for Staphylococcus aureus

Efflux Pump  Family Regulator(s) Substrate Specificity  References 
Chromosomally-encoded Efflux Systems 
NorA MFS MgrA, NorG(?) Hydrophilic fluoroquinolones (ciprofloxacin, norfloxacin)QACs (tetraphenylphosphonium, benzalkonium chloride)

Dyes (e.g. ethidium bromide, rhodamine)

[16,18,19]
NorB MFS MgrA, NorG Fluoroquinolones (e.g. hydrophilic: ciprofloxacin, norfloxacin and hydrophobic: moxifloxacin,
sparfloxacin)TetracyclineQACs (e.g. tetraphenylphosphonium, cetrimide)Dyes (e.g. ethidium bromide)
[31]
NorC MFS MgrA(?), NorG Fluoroquinolones (e.g. hydrophilic: ciprofloxacin and hydrophobic: moxifloxacin)Dyes (e.g. rhodamine) [35,36]
MepA MATE MepR Fluoroquinolones (e.g. hydrophilic: ciprofloxacin, norfloxacin and hydrophobic: moxifloxacin,
sparfloxacin)Glycylcyclines (e.g. tigecycline)QACs (e.g. tetraphenylphosphonium, cetrimide, benzalkonium chloride)Dyes (e.g. ethidium bromide)
[37,38]
MdeA MFS n.i. Hydrophilic fluoroquinolones (e.g. ciprofloxacin, norfloxacin)Virginiamycin, novobiocin, mupirocin, fusidic acid

QACs (e.g. tetraphenylphosphonium, benzalkonium chloride, dequalinium)

Dyes (e.g. ethidium bromide)

[39,40]
SepA n.d. n.i. QACs (e.g. benzalkonium chloride)Biguanidines (e.g. chlorhexidine)

Dyes (e.g. acriflavine)

[41]
SdrM MFS n.i. Hydrophilic fluoroquinolones (e.g. norfloxacin)Dyes (e.g. ethidium bromide, acriflavine) [42]
LmrS MFS n.i. Oxazolidinone (linezolid)Phenicols (e.g. choramphenicol, florfenicol)

Trimethoprim, erythromycin, kanamycin, fusidic acid

QACs (e.g. tetraphenylphosphonium)

Detergents (e.g. sodium docecyl sulphate)

Dyes (e.g. ethidium bromide)

[43]

Plasmid-encoded Efflux Systems

QacA MFS QacR QACs (e.g. tetraphenylphosphonium, benzalkonium chloride, dequalinium)Biguanidines (e.g. chlorhexidine)

Diamidines (e.g. pentamidine)

Dyes (e.g. ethidium bromide, rhodamine, acriflavine)

[45,49]
QacB MFS QacR QACs (e.g. tetraphenylphosphonium, benzalkonium chloride)Dyes (e.g. ethidium bromide, rhodamine, acriflavine) [53]
Smr SMR n.i. QACs (e.g. benzalkonium chloride, cetrimide)Dyes (e.g. ethidium bromide) [58,61]
QacG SMR n.i. QACs (e.g. benzalkonium chloride, cetyltrymethylammonium)Dyes (e.g. ethidium bromide) [67]
QacH SMR n.i. QACs (e.g. benzalkonium chloride, cetyltrymethylammonium)Dyes (e.g. ethidium bromide) [68]
QacJ SMR n.i. QACs (e.g. benzalkonium chloride, cetyltrymethylammonium)Dyes (e.g. ethidium bromide) [69]

a n.d.: The family of transporters to which SepA belongs is not elucidated to date.
b n.i.: The transporter has no regulator identified to date.
QACs: quaternary ammonium compounds
The importance of efflux pumps in bacterial antibiotic resistance

  1. A. Webber and L. J. V. Piddock
    Journal of Antimicrobial Chemotherapy (2003) 51, 9–11
    http://dx.doi.org:/10.1093/jac/dkg050Efflux pumps are transport proteins involved in the extrusion of toxic substrates (including virtually all classes of clinically relevant antibiotics) from within cells into the external environment. These proteins are found in both Gram-positive and -negative bacteria as well as in eukaryotic organisms. Pumps may be specific for one substrate or may transport a range of structurally dissimilar compounds (including antibiotics of multiple classes); such pumps can be associated with multiple drug resistance (MDR). In the prokaryotic kingdom there are five major families of efflux transporter: MF (major facilitator), MATE (multidrug and toxic efflux), RND (resistance-nodulation-division), SMR (small multidrug resistance) and ABC (ATP binding cassette). All these systems utilize the proton motive force as an energy source. Advances in DNA technology have led to the identification of members of the above families. Transporters that efflux multiple substrates, including antibiotics, have not evolved in response to the stresses of the antibiotic era. All bacterial genomes studied contain efflux pumps that indicate their ancestral origins. It has been estimated that ∼5–10% of all bacterial genes are involved in transport and a large proportion of these encode efflux pumps.
The efflux pump

The efflux pump

Multidrug-resistance efflux pumps — not just for resistance

Laura J. V. Piddock
Nature Reviews | Microbiology | Aug 2006; 4: 629

It is well established that multidrug-resistance efflux pumps encoded by bacteria can confer clinically relevant resistance to antibiotics. It is now understood that these efflux pumps also have a physiological role(s). They can confer resistance to natural substances produced by the host, including bile, hormones and host defense molecules. In addition, some efflux pumps of the resistance nodulation division (RND) family have been shown to have a role in the colonization and the persistence of bacteria in the host. Here, I present the accumulating evidence that multidrug-resistance efflux pumps have roles in bacterial pathogenicity and propose that these pumps therefore have greater clinical relevance than is usually attributed to them.

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Summary and Perspectives: Impairments in Pathological States: Endocrine Disorders, Stress Hypermetabolism and Cancer


Summary and Perspectives: Impairments in Pathological States: Endocrine Disorders, Stress Hypermetabolism and Cancer

Author and Curator: Larry H. Bernstein, MD, FCAP

This summary is the last of a series on the impact of transcriptomics, proteomics, and metabolomics on disease investigation, and the sorting and integration of genomic signatures and metabolic signatures to explain phenotypic relationships in variability and individuality of response to disease expression and how this leads to  pharmaceutical discovery and personalized medicine.  We have unquestionably better tools at our disposal than has ever existed in the history of mankind, and an enormous knowledge-base that has to be accessed.  I shall conclude here these discussions with the powerful contribution to and current knowledge pertaining to biochemistry, metabolism, protein-interactions, signaling, and the application of the -OMICS to diseases and drug discovery at this time.

The Ever-Transcendent Cell

Deriving physiologic first principles By John S. Torday | The Scientist Nov 1, 2014
http://www.the-scientist.com/?articles.view/articleNo/41282/title/The-Ever-Transcendent-Cell/

Both the developmental and phylogenetic histories of an organism describe the evolution of physiology—the complex of metabolic pathways that govern the function of an organism as a whole. The necessity of establishing and maintaining homeostatic mechanisms began at the cellular level, with the very first cells, and homeostasis provides the underlying selection pressure fueling evolution.

While the events leading to the formation of the first functioning cell are debatable, a critical one was certainly the formation of simple lipid-enclosed vesicles, which provided a protected space for the evolution of metabolic pathways. Protocells evolved from a common ancestor that experienced environmental stresses early in the history of cellular development, such as acidic ocean conditions and low atmospheric oxygen levels, which shaped the evolution of metabolism.

The reduction of evolution to cell biology may answer the perennially unresolved question of why organisms return to their unicellular origins during the life cycle.

As primitive protocells evolved to form prokaryotes and, much later, eukaryotes, changes to the cell membrane occurred that were critical to the maintenance of chemiosmosis, the generation of bioenergy through the partitioning of ions. The incorporation of cholesterol into the plasma membrane surrounding primitive eukaryotic cells marked the beginning of their differentiation from prokaryotes. Cholesterol imparted more fluidity to eukaryotic cell membranes, enhancing functionality by increasing motility and endocytosis. Membrane deformability also allowed for increased gas exchange.

Acidification of the oceans by atmospheric carbon dioxide generated high intracellular calcium ion concentrations in primitive aquatic eukaryotes, which had to be lowered to prevent toxic effects, namely the aggregation of nucleotides, proteins, and lipids. The early cells achieved this by the evolution of calcium channels composed of cholesterol embedded within the cell’s plasma membrane, and of internal membranes, such as that of the endoplasmic reticulum, peroxisomes, and other cytoplasmic organelles, which hosted intracellular chemiosmosis and helped regulate calcium.

As eukaryotes thrived, they experienced increasingly competitive pressure for metabolic efficiency. Engulfed bacteria, assimilated as mitochondria, provided more bioenergy. As the evolution of eukaryotic organisms progressed, metabolic cooperation evolved, perhaps to enable competition with biofilm-forming, quorum-sensing prokaryotes. The subsequent appearance of multicellular eukaryotes expressing cellular growth factors and their respective receptors facilitated cell-cell signaling, forming the basis for an explosion of multicellular eukaryote evolution, culminating in the metazoans.

Casting a cellular perspective on evolution highlights the integration of genotype and phenotype. Starting from the protocell membrane, the functional homolog for all complex metazoan organs, it offers a way of experimentally determining the role of genes that fostered evolution based on the ontogeny and phylogeny of cellular processes that can be traced back, in some cases, to our last universal common ancestor.  ….

As eukaryotes thrived, they experienced increasingly competitive pressure for metabolic efficiency. Engulfed bacteria, assimilated as mitochondria, provided more bioenergy. As the evolution of eukaryotic organisms progressed, metabolic cooperation evolved, perhaps to enable competition with biofilm-forming, quorum-sensing prokaryotes. The subsequent appearance of multicellular eukaryotes expressing cellular growth factors and their respective receptors facilitated cell-cell signaling, forming the basis for an explosion of multicellular eukaryote evolution, culminating in the metazoans.

Casting a cellular perspective on evolution highlights the integration of genotype and phenotype. Starting from the protocell membrane, the functional homolog for all complex metazoan organs, it offers a way of experimentally determining the role of genes that fostered evolution based on the ontogeny and phylogeny of cellular processes that can be traced back, in some cases, to our last universal common ancestor.

Given that the unicellular toolkit is complete with all the traits necessary for forming multicellular organisms (Science, 301:361-63, 2003), it is distinctly possible that metazoans are merely permutations of the unicellular body plan. That scenario would clarify a lot of puzzling biology: molecular commonalities between the skin, lung, gut, and brain that affect physiology and pathophysiology exist because the cell membranes of unicellular organisms perform the equivalents of these tissue functions, and the existence of pleiotropy—one gene affecting many phenotypes—may be a consequence of the common unicellular source for all complex biologic traits.  …

The cell-molecular homeostatic model for evolution and stability addresses how the external environment generates homeostasis developmentally at the cellular level. It also determines homeostatic set points in adaptation to the environment through specific effectors, such as growth factors and their receptors, second messengers, inflammatory mediators, crossover mutations, and gene duplications. This is a highly mechanistic, heritable, plastic process that lends itself to understanding evolution at the cellular, tissue, organ, system, and population levels, mediated by physiologically linked mechanisms throughout, without having to invoke random, chance mechanisms to bridge different scales of evolutionary change. In other words, it is an integrated mechanism that can often be traced all the way back to its unicellular origins.

The switch from swim bladder to lung as vertebrates moved from water to land is proof of principle that stress-induced evolution in metazoans can be understood from changes at the cellular level.

http://www.the-scientist.com/Nov2014/TE_21.jpg

A MECHANISTIC BASIS FOR LUNG DEVELOPMENT: Stress from periodic atmospheric hypoxia (1) during vertebrate adaptation to land enhances positive selection of the stretch-regulated parathyroid hormone-related protein (PTHrP) in the pituitary and adrenal glands. In the pituitary (2), PTHrP signaling upregulates the release of adrenocorticotropic hormone (ACTH) (3), which stimulates the release of glucocorticoids (GC) by the adrenal gland (4). In the adrenal gland, PTHrP signaling also stimulates glucocorticoid production of adrenaline (5), which in turn affects the secretion of lung surfactant, the distension of alveoli, and the perfusion of alveolar capillaries (6). PTHrP signaling integrates the inflation and deflation of the alveoli with surfactant production and capillary perfusion.  THE SCIENTIST STAFF

From a cell-cell signaling perspective, two critical duplications in genes coding for cell-surface receptors occurred during this period of water-to-land transition—in the stretch-regulated parathyroid hormone-related protein (PTHrP) receptor gene and the β adrenergic (βA) receptor gene. These gene duplications can be disassembled by following their effects on vertebrate physiology backwards over phylogeny. PTHrP signaling is necessary for traits specifically relevant to land adaptation: calcification of bone, skin barrier formation, and the inflation and distention of lung alveoli. Microvascular shear stress in PTHrP-expressing organs such as bone, skin, kidney, and lung would have favored duplication of the PTHrP receptor, since sheer stress generates radical oxygen species (ROS) known to have this effect and PTHrP is a potent vasodilator, acting as an epistatic balancing selection for this constraint.

Positive selection for PTHrP signaling also evolved in the pituitary and adrenal cortex (see figure on this page), stimulating the secretion of ACTH and corticoids, respectively, in response to the stress of land adaptation. This cascade amplified adrenaline production by the adrenal medulla, since corticoids passing through it enzymatically stimulate adrenaline synthesis. Positive selection for this functional trait may have resulted from hypoxic stress that arose during global episodes of atmospheric hypoxia over geologic time. Since hypoxia is the most potent physiologic stressor, such transient oxygen deficiencies would have been acutely alleviated by increasing adrenaline levels, which would have stimulated alveolar surfactant production, increasing gas exchange by facilitating the distension of the alveoli. Over time, increased alveolar distension would have generated more alveoli by stimulating PTHrP secretion, impelling evolution of the alveolar bed of the lung.

This scenario similarly explains βA receptor gene duplication, since increased density of the βA receptor within the alveolar walls was necessary for relieving another constraint during the evolution of the lung in adaptation to land: the bottleneck created by the existence of a common mechanism for blood pressure control in both the lung alveoli and the systemic blood pressure. The pulmonary vasculature was constrained by its ability to withstand the swings in pressure caused by the systemic perfusion necessary to sustain all the other vital organs. PTHrP is a potent vasodilator, subserving the blood pressure constraint, but eventually the βA receptors evolved to coordinate blood pressure in both the lung and the periphery.

Gut Microbiome Heritability

Analyzing data from a large twin study, researchers have homed in on how host genetics can shape the gut microbiome.
By Tracy Vence | The Scientist Nov 6, 2014

Previous research suggested host genetic variation can influence microbial phenotype, but an analysis of data from a large twin study published in Cell today (November 6) solidifies the connection between human genotype and the composition of the gut microbiome. Studying more than 1,000 fecal samples from 416 monozygotic and dizygotic twin pairs, Cornell University’s Ruth Ley and her colleagues have homed in on one bacterial taxon, the family Christensenellaceae, as the most highly heritable group of microbes in the human gut. The researchers also found that Christensenellaceae—which was first described just two years ago—is central to a network of co-occurring heritable microbes that is associated with lean body mass index (BMI).  …

Of particular interest was the family Christensenellaceae, which was the most heritable taxon among those identified in the team’s analysis of fecal samples obtained from the TwinsUK study population.

While microbiologists had previously detected 16S rRNA sequences belonging to Christensenellaceae in the human microbiome, the family wasn’t named until 2012. “People hadn’t looked into it, partly because it didn’t have a name . . . it sort of flew under the radar,” said Ley.

Ley and her colleagues discovered that Christensenellaceae appears to be the hub in a network of co-occurring heritable taxa, which—among TwinsUK participants—was associated with low BMI. The researchers also found that Christensenellaceae had been found at greater abundance in low-BMI twins in older studies.

To interrogate the effects of Christensenellaceae on host metabolic phenotype, the Ley’s team introduced lean and obese human fecal samples into germ-free mice. They found animals that received lean fecal samples containing more Christensenellaceae showed reduced weight gain compared with their counterparts. And treatment of mice that had obesity-associated microbiomes with one member of the Christensenellaceae family, Christensenella minuta, led to reduced weight gain.   …

Ley and her colleagues are now focusing on the host alleles underlying the heritability of the gut microbiome. “We’re running a genome-wide association analysis to try to find genes—particular variants of genes—that might associate with higher levels of these highly heritable microbiota.  . . . Hopefully that will point us to possible reasons they’re heritable,” she said. “The genes will guide us toward understanding how these relationships are maintained between host genotype and microbiome composition.”

J.K. Goodrich et al., “Human genetics shape the gut microbiome,” Cell,  http://dx.doi.org:/10.1016/j.cell.2014.09.053, 2014.

Light-Operated Drugs

Scientists create a photosensitive pharmaceutical to target a glutamate receptor.
By Ruth Williams | The Scentist Nov 1, 2014
http://www.the-scientist.com/?articles.view/articleNo/41279/title/Light-Operated-Drugs/

light operated drugs MO1

light operated drugs MO1

http://www.the-scientist.com/Nov2014/MO1.jpg

The desire for temporal and spatial control of medications to minimize side effects and maximize benefits has inspired the development of light-controllable drugs, or optopharmacology. Early versions of such drugs have manipulated ion channels or protein-protein interactions, “but never, to my knowledge, G protein–coupled receptors [GPCRs], which are one of the most important pharmacological targets,” says Pau Gorostiza of the Institute for Bioengineering of Catalonia, in Barcelona.

Gorostiza has taken the first step toward filling that gap, creating a photosensitive inhibitor of the metabotropic glutamate 5 (mGlu5) receptor—a GPCR expressed in neurons and implicated in a number of neurological and psychiatric disorders. The new mGlu5 inhibitor—called alloswitch-1—is based on a known mGlu receptor inhibitor, but the simple addition of a light-responsive appendage, as had been done for other photosensitive drugs, wasn’t an option. The binding site on mGlu5 is “extremely tight,” explains Gorostiza, and would not accommodate a differently shaped molecule. Instead, alloswitch-1 has an intrinsic light-responsive element.

In a human cell line, the drug was active under dim light conditions, switched off by exposure to violet light, and switched back on by green light. When Gorostiza’s team administered alloswitch-1 to tadpoles, switching between violet and green light made the animals stop and start swimming, respectively.

The fact that alloswitch-1 is constitutively active and switched off by light is not ideal, says Gorostiza. “If you are thinking of therapy, then in principle you would prefer the opposite,” an “on” switch. Indeed, tweaks are required before alloswitch-1 could be a useful drug or research tool, says Stefan Herlitze, who studies ion channels at Ruhr-Universität Bochum in Germany. But, he adds, “as a proof of principle it is great.” (Nat Chem Biol, http://dx.doi.org:/10.1038/nchembio.1612, 2014)

Enhanced Enhancers

The recent discovery of super-enhancers may offer new drug targets for a range of diseases.
By Eric Olson | The Scientist Nov 1, 2014
http://www.the-scientist.com/?articles.view/articleNo/41281/title/Enhanced-Enhancers/

To understand disease processes, scientists often focus on unraveling how gene expression in disease-associated cells is altered. Increases or decreases in transcription—as dictated by a regulatory stretch of DNA called an enhancer, which serves as a binding site for transcription factors and associated proteins—can produce an aberrant composition of proteins, metabolites, and signaling molecules that drives pathologic states. Identifying the root causes of these changes may lead to new therapeutic approaches for many different diseases.

Although few therapies for human diseases aim to alter gene expression, the outstanding examples—including antiestrogens for hormone-positive breast cancer, antiandrogens for prostate cancer, and PPAR-γ agonists for type 2 diabetes—demonstrate the benefits that can be achieved through targeting gene-control mechanisms.  Now, thanks to recent papers from laboratories at MIT, Harvard, and the National Institutes of Health, researchers have a new, much bigger transcriptional target: large DNA regions known as super-enhancers or stretch-enhancers. Already, work on super-enhancers is providing insights into how gene-expression programs are established and maintained, and how they may go awry in disease.  Such research promises to open new avenues for discovering medicines for diseases where novel approaches are sorely needed.

Super-enhancers cover stretches of DNA that are 10- to 100-fold longer and about 10-fold less abundant in the genome than typical enhancer regions (Cell, 153:307-19, 2013). They also appear to bind a large percentage of the transcriptional machinery compared to typical enhancers, allowing them to better establish and enforce cell-type specific transcriptional programs (Cell, 153:320-34, 2013).

Super-enhancers are closely associated with genes that dictate cell identity, including those for cell-type–specific master regulatory transcription factors. This observation led to the intriguing hypothesis that cells with a pathologic identity, such as cancer cells, have an altered gene expression program driven by the loss, gain, or altered function of super-enhancers.

Sure enough, by mapping the genome-wide location of super-enhancers in several cancer cell lines and from patients’ tumor cells, we and others have demonstrated that genes located near super-enhancers are involved in processes that underlie tumorigenesis, such as cell proliferation, signaling, and apoptosis.

Super-enhancers cover stretches of DNA that are 10- to 100-fold longer and about 10-fold less abundant in the genome than typical enhancer regions.

Genome-wide association studies (GWAS) have found that disease- and trait-associated genetic variants often occur in greater numbers in super-enhancers (compared to typical enhancers) in cell types involved in the disease or trait of interest (Cell, 155:934-47, 2013). For example, an enrichment of fasting glucose–associated single nucleotide polymorphisms (SNPs) was found in the stretch-enhancers of pancreatic islet cells (PNAS, 110:17921-26, 2013). Given that some 90 percent of reported disease-associated SNPs are located in noncoding regions, super-enhancer maps may be extremely valuable in assigning functional significance to GWAS variants and identifying target pathways.

Because only 1 to 2 percent of active genes are physically linked to a super-enhancer, mapping the locations of super-enhancers can be used to pinpoint the small number of genes that may drive the biology of that cell. Differential super-enhancer maps that compare normal cells to diseased cells can be used to unravel the gene-control circuitry and identify new molecular targets, in much the same way that somatic mutations in tumor cells can point to oncogenic drivers in cancer. This approach is especially attractive in diseases for which an incomplete understanding of the pathogenic mechanisms has been a barrier to discovering effective new therapies.

Another therapeutic approach could be to disrupt the formation or function of super-enhancers by interfering with their associated protein components. This strategy could make it possible to downregulate multiple disease-associated genes through a single molecular intervention. A group of Boston-area researchers recently published support for this concept when they described inhibited expression of cancer-specific genes, leading to a decrease in cancer cell growth, by using a small molecule inhibitor to knock down a super-enhancer component called BRD4 (Cancer Cell, 24:777-90, 2013).  More recently, another group showed that expression of the RUNX1 transcription factor, involved in a form of T-cell leukemia, can be diminished by treating cells with an inhibitor of a transcriptional kinase that is present at the RUNX1 super-enhancer (Nature, 511:616-20, 2014).

Fungal effector Ecp6 outcompetes host immune receptor for chitin binding through intrachain LysM dimerization 
Andrea Sánchez-Vallet, et al.   eLife 2013;2:e00790 http://elifesciences.org/content/2/e00790#sthash.LnqVMJ9p.dpuf

LysM effector

LysM effector

http://img.scoop.it/ZniCRKQSvJOG18fHbb4p0Tl72eJkfbmt4t8yenImKBVvK0kTmF0xjctABnaLJIm9

While host immune receptors

  • detect pathogen-associated molecular patterns to activate immunity,
  • pathogens attempt to deregulate host immunity through secreted effectors.

Fungi employ LysM effectors to prevent

  • recognition of cell wall-derived chitin by host immune receptors

Structural analysis of the LysM effector Ecp6 of

  • the fungal tomato pathogen Cladosporium fulvum reveals
  • a novel mechanism for chitin binding,
  • mediated by intrachain LysM dimerization,

leading to a chitin-binding groove that is deeply buried in the effector protein.

This composite binding site involves

  • two of the three LysMs of Ecp6 and
  • mediates chitin binding with ultra-high (pM) affinity.

The remaining singular LysM domain of Ecp6 binds chitin with

  • low micromolar affinity but can nevertheless still perturb chitin-triggered immunity.

Conceivably, the perturbation by this LysM domain is not established through chitin sequestration but possibly through interference with the host immune receptor complex.

Mutated Genes in Schizophrenia Map to Brain Networks
From www.nih.gov –  Sep 3, 2013

Previous studies have shown that many people with schizophrenia have de novo, or new, genetic mutations. These misspellings in a gene’s DNA sequence

  • occur spontaneously and so aren’t shared by their close relatives.

Dr. Mary-Claire King of the University of Washington in Seattle and colleagues set out to

  • identify spontaneous genetic mutations in people with schizophrenia and
  • to assess where and when in the brain these misspelled genes are turned on, or expressed.

The study was funded in part by NIH’s National Institute of Mental Health (NIMH). The results were published in the August 1, 2013, issue of Cell.

The researchers sequenced the exomes (protein-coding DNA regions) of 399 people—105 with schizophrenia plus their unaffected parents and siblings. Gene variations
that were found in a person with schizophrenia but not in either parent were considered spontaneous.

The likelihood of having a spontaneous mutation was associated with

  • the age of the father in both affected and unaffected siblings.

Significantly more mutations were found in people

  • whose fathers were 33-45 years at the time of conception compared to 19-28 years.

Among people with schizophrenia, the scientists identified

  • 54 genes with spontaneous mutations
  • predicted to cause damage to the function of the protein they encode.

The researchers used newly available database resources that show

  • where in the brain and when during development genes are expressed.

The genes form an interconnected expression network with many more connections than

  • that of the genes with spontaneous damaging mutations in unaffected siblings.

The spontaneously mutated genes in people with schizophrenia

  • were expressed in the prefrontal cortex, a region in the front of the brain.

The genes are known to be involved in important pathways in brain development. Fifty of these genes were active

  • mainly during the period of fetal development.

“Processes critical for the brain’s development can be revealed by the mutations that disrupt them,” King says. “Mutations can lead to loss of integrity of a whole pathway,
not just of a single gene.”

These findings support the concept that schizophrenia may result, in part, from

  • disruptions in development in the prefrontal cortex during fetal development.

James E. Darnell’s “Reflections”

A brief history of the discovery of RNA and its role in transcription — peppered with career advice
By Joseph P. Tiano

James Darnell begins his Journal of Biological Chemistry “Reflections” article by saying, “graduate students these days

  • have to swim in a sea virtually turgid with the daily avalanche of new information and
  • may be momentarily too overwhelmed to listen to the aging.

I firmly believe how we learned what we know can provide useful guidance for how and what a newcomer will learn.” Considering his remarkable discoveries in

  • RNA processing and eukaryotic transcriptional regulation

spanning 60 years of research, Darnell’s advice should be cherished. In his second year at medical school at Washington University School of Medicine in St. Louis, while
studying streptococcal disease in Robert J. Glaser’s laboratory, Darnell realized he “loved doing the experiments” and had his first “career advancement event.”
He and technician Barbara Pesch discovered that in vivo penicillin treatment killed streptococci only in the exponential growth phase and not in the stationary phase. These
results were published in the Journal of Clinical Investigation and earned Darnell an interview with Harry Eagle at the National Institutes of Health.

Darnell arrived at the NIH in 1956, shortly after Eagle  shifted his research interest to developing his minimal essential cell culture medium, still used. Eagle, then studying cell metabolism, suggested that Darnell take up a side project on poliovirus replication in mammalian cells in collaboration with Robert I. DeMars. DeMars’ Ph.D.
adviser was also James  Watson’s mentor, so Darnell met Watson, who invited him to give a talk at Harvard University, which led to an assistant professor position
at the MIT under Salvador Luria. A take-home message is to embrace side projects, because you never know where they may lead: this project helped to shape
his career.

Darnell arrived in Boston in 1961. Following the discovery of DNA’s structure in 1953, the world of molecular biology was turning to RNA in an effort to understand how
proteins are made. Darnell’s background in virology (it was discovered in 1960 that viruses used RNA to replicate) was ideal for the aim of his first independent lab:
exploring mRNA in animal cells grown in culture. While at MIT, he developed a new technique for purifying RNA along with making other observations

  • suggesting that nonribosomal cytoplasmic RNA may be involved in protein synthesis.

When Darnell moved to Albert Einstein College of Medicine for full professorship in 1964,  it was hypothesized that heterogenous nuclear RNA was a precursor to mRNA.
At Einstein, Darnell discovered RNA processing of pre-tRNAs and demonstrated for the first time

  • that a specific nuclear RNA could represent a possible specific mRNA precursor.

In 1967 Darnell took a position at Columbia University, and it was there that he discovered (simultaneously with two other labs) that

  • mRNA contained a polyadenosine tail.

The three groups all published their results together in the Proceedings of the National Academy of Sciences in 1971. Shortly afterward, Darnell made his final career move
four short miles down the street to Rockefeller University in 1974.

Over the next 35-plus years at Rockefeller, Darnell never strayed from his original research question: How do mammalian cells make and control the making of different
mRNAs? His work was instrumental in the collaborative discovery of

  • splicing in the late 1970s and
  • in identifying and cloning many transcriptional activators.

Perhaps his greatest contribution during this time, with the help of Ernest Knight, was

  • the discovery and cloning of the signal transducers and activators of transcription (STAT) proteins.

And with George Stark, Andy Wilks and John Krowlewski, he described

  • cytokine signaling via the JAK-STAT pathway.

Darnell closes his “Reflections” with perhaps his best advice: Do not get too wrapped up in your own work, because “we are all needed and we are all in this together.”

Darnell Reflections - James_Darnell

Darnell Reflections – James_Darnell

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Recent findings on presenilins and signal peptide peptidase

By Dinu-Valantin Bălănescu

γ-secretase and SPP

γ-secretase and SPP

Fig. 1 from the minireview shows a schematic depiction of γ-secretase and SPP

http://www.asbmb.org/assets/0/366/418/428/85528/85529/85530/c2de032a-daad-41e5-ba19-87a17bd26362.png

GxGD proteases are a family of intramembranous enzymes capable of hydrolyzing

  • the transmembrane domain of some integral membrane proteins.

The GxGD family is one of the three families of

  • intramembrane-cleaving proteases discovered so far (along with the rhomboid and site-2 protease) and
  • includes the γ-secretase and the signal peptide peptidase.

Although only recently discovered, a number of functions in human pathology and in numerous other biological processes

  • have been attributed to γ-secretase and SPP.

Taisuke Tomita and Takeshi Iwatsubo of the University of Tokyo highlighted the latest findings on the structure and function of γ-secretase and SPP
in a recent minireview in The Journal of Biological Chemistry.

  • γ-secretase is involved in cleaving the amyloid-β precursor protein, thus producing amyloid-β peptide,

the main component of senile plaques in Alzheimer’s disease patients’ brains. The complete structure of mammalian γ-secretase is not yet known; however,
Tomita and Iwatsubo note that biochemical analyses have revealed it to be a multisubunit protein complex.

  • Its catalytic subunit is presenilin, an aspartyl protease.

In vitro and in vivo functional and chemical biology analyses have revealed that

  • presenilin is a modulator and mandatory component of the γ-secretase–mediated cleavage of APP.

Genetic studies have identified three other components required for γ-secretase activity:

  1. nicastrin,
  2. anterior pharynx defective 1 and
  3. presenilin enhancer 2.

By coexpression of presenilin with the other three components, the authors managed to

  • reconstitute γ-secretase activity.

Tomita and Iwatsubo determined using the substituted cysteine accessibility method and by topological analyses, that

  • the catalytic aspartates are located at the center of the nine transmembrane domains of presenilin,
  • by revealing the exact location of the enzyme’s catalytic site.

The minireview also describes in detail the formerly enigmatic mechanism of γ-secretase mediated cleavage.

SPP, an enzyme that cleaves remnant signal peptides in the membrane

  • during the biogenesis of membrane proteins and
  • signal peptides from major histocompatibility complex type I,
  • also is involved in the maturation of proteins of the hepatitis C virus and GB virus B.

Bioinformatics methods have revealed in fruit flies and mammals four SPP-like proteins,

  • two of which are involved in immunological processes.

By using γ-secretase inhibitors and modulators, it has been confirmed

  • that SPP shares a similar GxGD active site and proteolytic activity with γ-secretase.

Upon purification of the human SPP protein with the baculovirus/Sf9 cell system,

  • single-particle analysis revealed further structural and functional details.

HLA targeting efficiency correlates with human T-cell response magnitude and with mortality from influenza A infection

From www.pnas.org –  Sep 3, 2013 4:24 PM

Experimental and computational evidence suggests that

  • HLAs preferentially bind conserved regions of viral proteins, a concept we term “targeting efficiency,” and that
  • this preference may provide improved clearance of infection in several viral systems.

To test this hypothesis, T-cell responses to A/H1N1 (2009) were measured from peripheral blood mononuclear cells obtained from a household cohort study
performed during the 2009–2010 influenza season. We found that HLA targeting efficiency scores significantly correlated with

  • IFN-γ enzyme-linked immunosorbent spot responses (P = 0.042, multiple regression).

A further population-based analysis found that the carriage frequencies of the alleles with the lowest targeting efficiencies, A*24,

  • were associated with pH1N1 mortality (r = 0.37, P = 0.031) and
  • are common in certain indigenous populations in which increased pH1N1 morbidity has been reported.

HLA efficiency scores and HLA use are associated with CD8 T-cell magnitude in humans after influenza infection.
The computational tools used in this study may be useful predictors of potential morbidity and

  • identify immunologic differences of new variant influenza strains
  • more accurately than evolutionary sequence comparisons.

Population-based studies of the relative frequency of these alleles in severe vs. mild influenza cases

  • might advance clinical practices for severe H1N1 infections among genetically susceptible populations.

Metabolomics in drug target discovery

J D Rabinowitz et al.

Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ.
Cold Spring Harbor Symposia on Quantitative Biology 11/2011; 76:235-46.
http://dx.doi.org:/10.1101/sqb.2011.76.010694 

Most diseases result in metabolic changes. In many cases, these changes play a causative role in disease progression. By identifying pathological metabolic changes,

  • metabolomics can point to potential new sites for therapeutic intervention.

Particularly promising enzymatic targets are those that

  • carry increased flux in the disease state.

Definitive assessment of flux requires the use of isotope tracers. Here we present techniques for

  • finding new drug targets using metabolomics and isotope tracers.

The utility of these methods is exemplified in the study of three different viral pathogens. For influenza A and herpes simplex virus,

  • metabolomic analysis of infected versus mock-infected cells revealed
  • dramatic concentration changes around the current antiviral target enzymes.

Similar analysis of human-cytomegalovirus-infected cells, however, found the greatest changes

  • in a region of metabolism unrelated to the current antiviral target.

Instead, it pointed to the tricarboxylic acid (TCA) cycle and

  • its efflux to feed fatty acid biosynthesis as a potential preferred target.

Isotope tracer studies revealed that cytomegalovirus greatly increases flux through

  • the key fatty acid metabolic enzyme acetyl-coenzyme A carboxylase.
  • Inhibition of this enzyme blocks human cytomegalovirus replication.

Examples where metabolomics has contributed to identification of anticancer drug targets are also discussed. Eventual proof of the value of

  • metabolomics as a drug target discovery strategy will be
  • successful clinical development of therapeutics hitting these new targets.

 Related References

Use of metabolic pathway flux information in targeted cancer drug design. Drug Discovery Today: Therapeutic Strategies 1:435-443, 2004.

Detection of resistance to imatinib by metabolic profiling: clinical and drug development implications. Am J Pharmacogenomics. 2005;5(5):293-302. Review. PMID: 16196499

Medicinal chemistry, metabolic profiling and drug target discovery: a role for metabolic profiling in reverse pharmacology and chemical genetics.
Mini Rev Med Chem.  2005 Jan;5(1):13-20. Review. PMID: 15638788 [PubMed – indexed for MEDLINE] Related citations

Development of Tracer-Based Metabolomics and its Implications for the Pharmaceutical Industry. Int J Pharm Med 2007; 21 (3): 217-224.

Use of metabolic pathway flux information in anticancer drug design. Ernst Schering Found Symp Proc. 2007;(4):189-203. Review. PMID: 18811058

Pharmacological targeting of glucagon and glucagon-like peptide 1 receptors has different effects on energy state and glucose homeostasis in diet-induced obese mice. J Pharmacol Exp Ther. 2011 Jul;338(1):70-81. http://dx.doi.org:/10.1124/jpet.111.179986. PMID: 21471191

Single valproic acid treatment inhibits glycogen and RNA ribose turnover while disrupting glucose-derived cholesterol synthesis in liver as revealed by the
[U-C(6)]-d-glucose tracer in mice. Metabolomics. 2009 Sep;5(3):336-345. PMID: 19718458

Metabolic Pathways as Targets for Drug Screening, Metabolomics, Dr Ute Roessner (Ed.), ISBN: 978-953-51-0046-1, InTech, Available from: http://www.intechopen.com/books/metabolomics/metabolic-pathways-as-targets-for-drug-screening

Iron regulates glucose homeostasis in liver and muscle via AMP-activated protein kinase in mice. FASEB J. 2013 Jul;27(7):2845-54.
http://dx.doi.org:/10.1096/fj.12-216929. PMID: 23515442

Metabolomics and systems pharmacology: why and how to model the human metabolic network for drug discovery

Drug Discov. Today 19 (2014), 171–182     http://dx.doi.org:/10.1016/j.drudis.2013.07.014

Highlights

  • We now have metabolic network models; the metabolome is represented by their nodes.
  • Metabolite levels are sensitive to changes in enzyme activities.
  • Drugs hitchhike on metabolite transporters to get into and out of cells.
  • The consensus network Recon2 represents the present state of the art, and has predictive power.
  • Constraint-based modelling relates network structure to metabolic fluxes.

Metabolism represents the ‘sharp end’ of systems biology, because changes in metabolite concentrations are

  • necessarily amplified relative to changes in the transcriptome, proteome and enzyme activities, which can be modulated by drugs.

To understand such behaviour, we therefore need (and increasingly have) reliable consensus (community) models of

  • the human metabolic network that include the important transporters.

Small molecule ‘drug’ transporters are in fact metabolite transporters, because

  • drugs bear structural similarities to metabolites known from the network reconstructions and
  • from measurements of the metabolome.

Recon2 represents the present state-of-the-art human metabolic network reconstruction; it can predict inter alia:

(i) the effects of inborn errors of metabolism;

(ii) which metabolites are exometabolites, and

(iii) how metabolism varies between tissues and cellular compartments.

However, even these qualitative network models are not yet complete. As our understanding improves

  • so do we recognise more clearly the need for a systems (poly)pharmacology.

Introduction – a systems biology approach to drug discovery

It is clearly not news that the productivity of the pharmaceutical industry has declined significantly during recent years

  • following an ‘inverse Moore’s Law’, Eroom’s Law, or
  • that many commentators, consider that the main cause of this is
  • because of an excessive focus on individual molecular target discovery rather than a more sensible strategy
  • based on a systems-level approach (Fig. 1).
drug discovery science

drug discovery science

Figure 1.

The change in drug discovery strategy from ‘classical’ function-first approaches (in which the assay of drug function was at the tissue or organism level),
with mechanistic studies potentially coming later, to more-recent target-based approaches where initial assays usually involve assessing the interactions
of drugs with specified (and often cloned, recombinant) proteins in vitro. In the latter cases, effects in vivo are assessed later, with concomitantly high levels of attrition.

Arguably the two chief hallmarks of the systems biology approach are:

(i) that we seek to make mathematical models of our systems iteratively or in parallel with well-designed ‘wet’ experiments, and
(ii) that we do not necessarily start with a hypothesis but measure as many things as possible (the ’omes) and

  • let the data tell us the hypothesis that best fits and describes them.

Although metabolism was once seen as something of a Cinderella subject,

  • there are fundamental reasons to do with the organisation of biochemical networks as
  • to why the metabol(om)ic level – now in fact seen as the ‘apogee’ of the ’omics trilogy –
  •  is indeed likely to be far more discriminating than are
  • changes in the transcriptome or proteome.

The next two subsections deal with these points and Fig. 2 summarises the paper in the form of a Mind Map.

metabolomics and systems pharmacology

metabolomics and systems pharmacology

http://ars.els-cdn.com/content/image/1-s2.0-S1359644613002481-gr2.jpg

Metabolic Disease Drug Discovery— “Hitting the Target” Is Easier Said Than Done

David E. Moller, et al.   http://dx.doi.org:/10.1016/j.cmet.2011.10.012

Despite the advent of new drug classes, the global epidemic of cardiometabolic disease has not abated. Continuing

  • unmet medical needs remain a major driver for new research.

Drug discovery approaches in this field have mirrored industry trends, leading to a recent

  • increase in the number of molecules entering development.

However, worrisome trends and newer hurdles are also apparent. The history of two newer drug classes—

  1. glucagon-like peptide-1 receptor agonists and
  2. dipeptidyl peptidase-4 inhibitors—

illustrates both progress and challenges. Future success requires that researchers learn from these experiences and

  • continue to explore and apply new technology platforms and research paradigms.

The global epidemic of obesity and diabetes continues to progress relentlessly. The International Diabetes Federation predicts an even greater diabetes burden (>430 million people afflicted) by 2030, which will disproportionately affect developing nations (International Diabetes Federation, 2011). Yet

  • existing drug classes for diabetes, obesity, and comorbid cardiovascular (CV) conditions have substantial limitations.

Currently available prescription drugs for treatment of hyperglycemia in patients with type 2 diabetes (Table 1) have notable shortcomings. In general,

Therefore, clinicians must often use combination therapy, adding additional agents over time. Ultimately many patients will need to use insulin—a therapeutic class first introduced in 1922. Most existing agents also have

  • issues around safety and tolerability as well as dosing convenience (which can impact patient compliance).

Pharmacometabolomics, also known as pharmacometabonomics, is a field which stems from metabolomics,

  • the quantification and analysis of metabolites produced by the body.

It refers to the direct measurement of metabolites in an individual’s bodily fluids, in order to

  • predict or evaluate the metabolism of pharmaceutical compounds, and
  • to better understand the pharmacokinetic profile of a drug.

Alternatively, pharmacometabolomics can be applied to measure metabolite levels

  • following the administration of a pharmaceutical compound, in order to
  • monitor the effects of the compound on certain metabolic pathways(pharmacodynamics).

This provides detailed mapping of drug effects on metabolism and

  • the pathways that are implicated in mechanism of variation of response to treatment.

In addition, the metabolic profile of an individual at baseline (metabotype) provides information about

  • how individuals respond to treatment and highlights heterogeneity within a disease state.

All three approaches require the quantification of metabolites found

relationship between -OMICS

relationship between -OMICS

http://upload.wikimedia.org/wikipedia/commons/thumb/e/eb/OMICS.png/350px-OMICS.png

Pharmacometabolomics is thought to provide information that

Looking at the characteristics of an individual down through these different levels of detail, there is an

  • increasingly more accurate prediction of a person’s ability to respond to a pharmaceutical compound.
  1. the genome, made up of 25 000 genes, can indicate possible errors in drug metabolism;
  2. the transcriptome, made up of 85,000 transcripts, can provide information about which genes important in metabolism are being actively transcribed;
  3. and the proteome, >10,000,000 members, depicts which proteins are active in the body to carry out these functions.

Pharmacometabolomics complements the omics with

  • direct measurement of the products of all of these reactions, but with perhaps a relatively
  • smaller number of members: that was initially projected to be approximately 2200 metabolites,

but could be a larger number when gut derived metabolites and xenobiotics are added to the list. Overall, the goal of pharmacometabolomics is

  • to more closely predict or assess the response of an individual to a pharmaceutical compound,
  • permitting continued treatment with the right drug or dosage
  • depending on the variations in their metabolism and ability to respond to treatment.

Pharmacometabolomic analyses, through the use of a metabolomics approach,

  • can provide a comprehensive and detailed metabolic profile or “metabolic fingerprint” for an individual patient.

Such metabolic profiles can provide a complete overview of individual metabolite or pathway alterations,

This approach can then be applied to the prediction of response to a pharmaceutical compound

  • by patients with a particular metabolic profile.

Pharmacometabolomic analyses of drug response are

Pharmacogenetics focuses on the identification of genetic variations (e.g. single-nucleotide polymorphisms)

  • within patients that may contribute to altered drug responses and overall outcome of a certain treatment.

The results of pharmacometabolomics analyses can act to “inform” or “direct”

  • pharmacogenetic analyses by correlating aberrant metabolite concentrations or metabolic pathways to potential alterations at the genetic level.

This concept has been established with two seminal publications from studies of antidepressants serotonin reuptake inhibitors

  • where metabolic signatures were able to define a pathway implicated in response to the antidepressant and
  • that lead to identification of genetic variants within a key gene
  • within the highlighted pathway as being implicated in variation in response.

These genetic variants were not identified through genetic analysis alone and hence

  • illustrated how metabolomics can guide and inform genetic data.

en.wikipedia.org/wiki/Pharmacometabolomics

Benznidazole Biotransformation and Multiple Targets in Trypanosoma cruzi Revealed by Metabolomics

Andrea Trochine, Darren J. Creek, Paula Faral-Tello, Michael P. Barrett, Carlos Robello
Published: May 22, 2014   http://dx.doi.org:/10.1371/journal.pntd.0002844

The first line treatment for Chagas disease, a neglected tropical disease caused by the protozoan parasite Trypanosoma cruzi,

  • involves administration of benznidazole (Bzn).

Bzn is a 2-nitroimidazole pro-drug which requires nitroreduction to become active. We used a

  • non-targeted MS-based metabolomics approach to study the metabolic response of T. cruzi to Bzn.

Parasites treated with Bzn were minimally altered compared to untreated trypanosomes, although the redox active thiols

  1. trypanothione,
  2. homotrypanothione and
  3. cysteine

were significantly diminished in abundance post-treatment. In addition, multiple Bzn-derived metabolites were detected after treatment.

These metabolites included reduction products, fragments and covalent adducts of reduced Bzn

  • linked to each of the major low molecular weight thiols:
  1. trypanothione,
  2. glutathione,
  3. g-glutamylcysteine,
  4. glutathionylspermidine,
  5. cysteine and
  6. ovothiol A.

Bzn products known to be generated in vitro by the unusual trypanosomal nitroreductase, TcNTRI,

  • were found within the parasites,
  • but low molecular weight adducts of glyoxal, a proposed toxic end-product of NTRI Bzn metabolism, were not detected.

Our data is indicative of a major role of the

  • thiol binding capacity of Bzn reduction products
  • in the mechanism of Bzn toxicity against T. cruzi.

 

 

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Introduction to Proteomics

Author and Curator: Larry H. Bernstein, MD, FCAP  

 

We have had a considerable extended discussion of preoteins and peptides, protein sinthesis, amino acid incorporation into protein, and metabolism of carbohydrates and lipids.  It is also clear that the historic practice of medicine, and the classification of biological systems has been highly dependent on the observations related to the observed phenotypical traits and disturbances of normal function that could be measured by traditional metabolic pathways for over a century.

What did we gain from the genomic revolution?

  1. Traceability of protein expression to a basic coded message
  2. The possibility of tracing disturbed cellular function to mutation related loss-of-function
  3. The ability to trace generational traits over long periods of time
  4. The promise of regenerating the enterprise of pharmacology and pharmaceutical intervention based on the silencing of or readjustment of regulated metabolic pathways to bring an adaptive rebalancing favoring extended life

What can we expect as we progress further as a result of the last two decades?

  1. There is a huge amount of information, as well as missing information that is necessary for adequately tackling the mastery of the life processes.
  2. There is a complex web of knowledge that goes beyond the genome and the one-gene one-enzyme, and the DNA-RNA-protein hypotheses that can only be realized by more full disclosure of the many metabolic control circuits involved in cellular homeostasis and adaptive control.
  3. The ability to come to disclosure and understanding of this cellular balancing will require the comprehensive exploration of the proteome and the active role of proteins and peptides in the functioning of all cells, and the organism.
  4. Proteomics will open up the discovery of new approaches to diagnostics and pharmaceutical discovery.

What about proteins?  What can proteins do? What can’t they do!

  • Enzymes are proteins that make sure that chemical reactions in your body take place up to a million times faster than they would without enzymes.
  • Antibodies are proteins that help your immune system to fight disease.
  • When you get an injury, the bleeding stops because of blood clots, thanks to the proteins fibrinogen and thrombin.
  • Transport! Some proteins carry vitamins ot hormones from one place to another, or form tunnels (pores) in cell membranes that will let only specific molecules (or ions) through. Hemoglobin, a protein in your blood, carries oxygen from your lungs to your cells.
  • Strength and support! Other proteins like collagen and keratin are strong and tough and make up your skin, hair, and fingernails. Collagen also supports your cells and organs so they don’t slosh around.
  • Motion! The proteins myosin and actin make up much of your muscle tissue. They work together so your muscles can move you around. Some bacteria have cilia and flagella made out of proteins. The bacteria can whip these around to move from place to place.

http://www.pslc.ws/macrog/kidsmac/protein.htm

Proteins (/ˈprˌtnz/ or /ˈprti.ɨnz/) are large biological molecules, or macromolecules,

Proteins perform a vast array of functions within living organisms, including

  1. catalyzing metabolic reactions,
  2. replicating DNA,
  3. responding to stimuli, and
  4. transporting molecules from one location to another.

Proteins differ from one another primarily in

  1. their sequence of amino acids,
  2. which is dictated by the nucleotide sequence of their genes, and
  3. which usually results in folding of the protein into

A linear chain of amino acid residues is called a polypeptide. A protein contains at least one long polypeptide. Short polypeptides, containing less than about 20-30 residues, are rarely considered to be proteins and are commonly called peptides, or sometimes oligopeptides. The individual amino acid residues are bonded together by peptide bonds and adjacent amino acid residues. The sequence of amino acid residues in a protein is defined by

In general, the genetic code specifies 20 standard amino acids; however, in certain organisms the genetic code can include selenocysteine and—in certain archaeapyrrolysine. Shortly after or even during synthesis,

  • the residues in a protein are often chemically modified by posttranslational modification,
  • which alters the physical and chemical properties, folding, stability, activity, and ultimately, the function of the proteins.

http://en.wikipedia.org/wiki/Protein

Posttranslational modification (PTM) is a step in protein biosynthesis. Proteins created by ribosomes translating mRNA into polypeptide chains may undergo PTM (such as folding, cutting and other processes) before becoming the mature protein product.  After translation, the posttranslational modification of amino acids extends the range of functions of the protein by attaching it to other biochemical functional groups (such as acetate, phosphate, various lipids and carbohydrates), changing the chemical nature of an amino acid (e.g. citrullination), or making structural changes (e.g. formation of disulfide bridges).

Also, enzymes may remove amino acids from the amino end of the protein, or cut the peptide chain in the middle. For instance, the peptide hormone insulin is cut twice after disulfide bonds are formed, and a propeptide is removed from the middle of the chain; the resulting protein consists of two polypeptide chains connected by disulfide bonds. Also, most nascent polypeptides start with the amino acid methionine because the “start” n mRNA also codes for this amino acid. This amino acid is usually taken off during post-translational modification. Other modifications, like phosphorylation, are part of common mechanisms for controlling the behavior of a protein, for instance activating or inactivating an enzyme.

posttranslational modification of insulin

posttranslational modification of insulin

Posttranslational modification of insulin. At the top, the ribosome translates a mRNA sequence into a protein, insulin, and passes the protein through the endoplasmic reticulum, where it is cut, folded and held in shape by disulfide (-S-S-) bonds. Then the protein passes through the golgi apparatus, where it is packaged into a vesicle. In the vesicle, more parts are cut off, and it turns into mature insulin.

Genetic Code mapped

Genetic Code mapped

The genetic code diagram showing the amino acid residues as target of modification.

PTMs involving addition of cofactors for enhanced enzymatic activity

http://en.wikipedia.org/wiki/Posttranslational_modification

Sometimes proteins have non-peptide groups attached, which can be called prosthetic groups or cofactors.  Examples of cofactors include metal ions like iron and zinc. Proteins can also work together to achieve a particular function, and they often associate to form stable protein complexes.

cofactor-examples

cofactor-examples

Coenzymes are molecules that work at the active site of an enzyme and aid in recognizing, attracting, or repulsing a substrate or product. Many are derived from vitamins. The substrate is the molecule upon which an enzyme catalyzes a reaction transforming A to B by removal or addition of a hydrogen, or a hydroxyl group, or a methyl group, and so forth. This is  how an alcohol or an aldehyde is produced. Such a reaction is critical is carbohydrate metabolism for producing two 3-carbon sugars from a 6-carbon sugar. Coenzymes shuttle chemical groups from one enzyme to another enzyme. They may bind loosely to enzymes, while another group of cofactors do not.

Prosthetic groups are cofactors that bind tightly to proteins or enzymes. As if holding on for dear life, they are not easily removed. They can be organic or metal ions and are often attached to proteins by a covalent bond. The same cofactors can bind multiple different types of enzymes and may bind some enzymes loosely, as a coenzyme, and others tightly, as a prosthetic group. Some cofactors may always tightly bind their enzymes. It’s important to note, though, that these prosthetic groups can also bind to proteins other than enzymes.  A holoenzyme is an enzyme with any metal ions or coenzymes attached to it that is now ready to catalyze a reaction.

prosthetic-groups

prosthetic-groups

http://education-portal.com/academy/lesson/coenzymes-cofactors-prosthetic-groups-function-and-interactions.html#lesson

Around the world, millions of people don’t get enough protein. Protein malnutrition leads to the condition known as kwashiorkor. Lack of protein can cause growth failure, loss of muscle mass, decreased immunity, weakening of the heart and respiratory system, and death.

All Protein Isn’t Alike

Protein is built from building blocks called amino acids. Our bodies make amino acids in two different ways: Either from scratch, or by modifying others. A few amino acids (known as the essential amino acids) must come from food.

  • Animal sources of protein tend to deliver all the amino acids we need.
  • Other protein sources, such as fruits, vegetables, grains, nuts and seeds, lack one or more essential amino acids.

Vegetarians need to be aware of this. People who don’t eat meat, fish, poultry, eggs, or dairy products need to eat a variety of protein-containing foods each day in order to get all the amino acids needed to make new protein.

http://www.hsph.harvard.edu/nutritionsource/what-should-you-eat/protein/
Molecular Biologists Guide to Proteomics

PR. Graves and TA.J. Haystead*
Microbiol Mol Biol Rev. Mar 2002; 66(1): 39–63  PMC120780
http://dx.doi.org:/10.1128/MMBR.66.1.39-63.2002

The emergence of proteomics, the large-scale analysis of proteins, has been inspired by the realization that

  • the final product of a gene is inherently more complex and
  • closer to function than the gene itself.

Shortfalls in the ability of bioinformatics to predict

  • both the existence and function of genes have also illustrated
  • the need for protein analysis.

Moreover, only through the study of proteins can posttranslational modifications be determined,

  • which can profoundly affect protein function.

Proteomics has been enabled by

  • the accumulation of both DNA and protein sequence databases,
  • improvements in mass spectrometry, and
  • the development of computer algorithms for database searching.

In this review, we describe why proteomics is important,

  • how it is conducted, and
  • how it can be applied to complement other existing technologies.

We conclude that currently, the most practical application of proteomics is

  • the analysis of target proteins as opposed to entire proteomes.

This type of proteomics, referred to as functional proteomics, is always

  • driven by a specific biological question.

In this way, protein identification and characterization has a meaningful outcome. We discuss some of the advantages

  • of a functional proteomics approach and

provide examples of how different methodologies can be utilized to address a wide variety of biological problems.

Entry of our laboratory into proteomics 5 years ago was driven by a need to define a complex mixture of proteins (∼36 proteins) we had affinity isolated that bound specifically to the catalytic subunit of protein phosphatase 1 (PP-1, a serine/threonine protein phosphatase that regulates multiple dephosphorylation events in cells). We were faced with the task of trying to understand the significance of these proteins, and the only obvious way to begin to do this was to identify them by sequencing. Since the majority of intact eukaryotic proteins are not immediately accessible to Edman sequencing

  • due to posttranslational N-terminal modifications,
  • we invented mixed-peptide sequencing.

This method enables internal peptide sequence information to be derived from proteins

  • electroblotted onto hydrophobic membranes.

Using the mixed-peptide sequencing strategy, we identified all 36 proteins in about a week. The mixture contained at least two known PP-1 regulatory subunits, but most were novel proteins of unknown function. Herein lies the lesson of proteomics. Identifying long lists of potentially interesting proteins often generates more questions than it seeks to answer.

Despite learning this obvious lesson, our early sequencing experiences were an epiphany that has subsequently altered our whole scientific strategy for probing protein function in cells. The sequencing of the 36 proteins has opened new avenues to further explore the functions of PP-1 in intact cells. Because of increased sensitivity, our approaches now routinely use state-of-the-art mass spectrometry (MS) techniques. However, rather than using proteomics to simply characterize large numbers of proteins in complex mixtures, we see the real application of this technology as a tool to enhance the power of existing approaches currently used by the modern molecular biologist such as classical yeast and mouse genetics, tissue culture, protein expression systems, and site-directed mutagenesis.

Importantly, the one message we would want the reader to take away from reading this review is that one should always let the biological question in mind drive the application of proteomics rather than simply engaging in an orgy of protein sequencing. From our experiences, we believe that if the appropriate controls are performed, proteomics is an extremely powerful approach for addressing important physiological questions. One should always design experiments to define a selected number of relevant proteins in the mixture of interest. Examples of such experiments that we routinely perform include defining early phosphorylation events in complex protein mixtures after hormone treatment of intact cells or comparing patterns of protein derived from a stimulated versus nonstimulated cell in an affinity pull-down experiment. Only the proteins that were specifically phosphorylated or bound in response to the stimulus are sequenced in the complex mixtures. Sequencing proteins that are regulated then has a meaningful outcome and directs all subsequent biological investigation.

The term “proteomics” was first coined in 1995 and was defined as the large-scale characterization of the entire protein complement of a cell line, tissue, or organism. Today, two definitions of proteomics are encountered. The first is the more classical definition, restricting the large-scale analysis of gene products to studies involving only proteins. The second and more inclusive definition combines protein studies with analyses that have a genetic readout such as mRNA analysis, genomics, and the yeast two-hybrid analysis. However, the goal of proteomics remains the same, i.e., to obtain a more global and integrated view of biology by studying all the proteins of a cell rather than each one individually.

Using the more inclusive definition of proteomics, many different areas of study are now grouped under the rubric of proteomics (Fig. (Fig.1).1). These include protein-protein interaction studies, protein modifications, protein function, and protein localization studies to name a few. The aim of proteomics is not only to identify all the proteins in a cell but also to create a complete three-dimensional (3-D) map of the cell indicating where proteins are located. These ambitious goals will certainly require the involvement of a large number of different disciplines such as molecular biology, biochemistry, and bioinformatics. It is likely that in bioinformatics alone, more powerful computers will have to be devised to organize the immense amount of information generated from these endeavors.

Types of proteomics and their applications to biology

Types of proteomics and their applications to biology

In the quest to characterize the proteome of a given cell or organism, it should be remembered that the proteome is dynamic. The proteome of a cell will reflect the immediate environment in which it is studied. In response to internal or external cues, proteins can be modified by posttranslational modifications, undergo translocations within the cell, or be synthesized or degraded. Thus, examination of the proteome of a cell is like taking a “snapshot” of the protein environment at any given time. Considering all the possibilities, it is likely that any given genome can potentially give rise to an infinite number of proteomes.

The first major technology to emerge for the identification of proteins was the sequencing of proteins by Edman degradation. A major breakthrough was the development of microsequencing techniques for electroblotted proteins. This technique was used for the identification of proteins from 2-D gels to create the first 2-D databases.  One of the most important developments in protein identification has been the development of MS technology. In the last decade, the sensitivity of analysis and accuracy of results for protein identification by MS have increased by several orders of magnitude. It is now estimated that proteins in the femtomolar range can be identified in gels. Because MS is more sensitive, can tolerate protein mixtures, and is amenable to high-throughput operations, it has essentially replaced Edman sequencing as the protein identification tool of choice.

The growth of proteomics is a direct result of advances made in large-scale nucleotide sequencing of expressed sequence tags and genomic DNA. Without this information, proteins could not be identified even with the improvements made in MS. Protein identification (by MS or Edman sequencing) relies on the presence of some form of database for the given organism. The majority of DNA and protein sequence information has accumulated within the last 5 to 10 years. In 1995, the first complete genome of an organism was sequenced, that of Haemophilus influenzae. At the time of this writing, the sequencing of the genomes of 45 microorganisms has been completed and that of 170 more is under way (http://www.tiger.org/tdb/mdb/mdbcomplete.html). To date, five eukaryotic genomes have been completed: Arabidopsis thaliana, Saccharomyces cerevisiae, Schizosaccharomyces pombe, Caenorhabditis elegans, and Drosophila melanogaster. In addition, the rice, mouse, and human genomes are near completion.

One of the first applications of proteomics will be to identify the total number of genes in a given genome. This “functional annotation” of a genome is necessary because

  • it is still difficult to predict genes accurately from genomic data. One problem is that
  • the exon-intron structure of most genes cannot be accurately predicted by bioinformatics.

To achieve this goal, genomic information will have to be integrated with

  • data obtained from protein studies to confirm the existence of a particular gene.

The analysis of mRNA is

  • not a direct reflection of the protein content in the cell.

Many studies have shown a poor correlation

  • between mRNA and protein expression levels.

The formation of mRNA is only the first step in a long sequence of events resulting in the synthesis of a protein (Fig. (Fig.2).2).

  1. mRNA is subject to posttranscriptional control in the form of alternative splicing, polyadenylation, and mRNA editing. Many different protein isoforms can be generated from a single gene at this step.
  2. mRNA then can be subject to regulation at the level of protein translation. Proteins, having been formed, are subject to posttranslational modification. It is estimated that up to 200 different types of posttranslational protein modification exist. Proteins can also be regulated by proteolysis and compartmentalization. It is clear that the tenet of “one gene, one protein” is an oversimplification.
Mechanisms by which a single gene can give rise to multiple gene products

Mechanisms by which a single gene can give rise to multiple gene products

Mechanisms by which a single gene can give rise to multiple gene products. Multiple protein isoforms can be generated by RNA processing when RNA is alternatively spliced or edited to form mature mRNA. mRNA, in turn, can be regulated by stability and efficiency
One of the most important applications of proteomics will be the characterization of posttranslational protein modifications. Proteins are known to be modified posttranslationally in response to a variety of intracellular and extracellular signals. For example, protein phosphorylation is an important signaling mechanism and disregulation of protein kinases or phosphatases can result in oncogenesis. By using a proteomics approach, changes in the modifications of many proteins expressed by a cell can be analyzed simultaneously.
Of fundamental importance in biology is the understanding of protein-protein interactions. The process of cell growth, programmed cell death, and the decision to proceed through the cell cycle are all regulated by signal transduction through protein complexes. Proteomics aims to develop a complete 3-D map of all protein interactions in the cell. One step toward this goal was recently completed for the microorganism Helicobacter pylori. Using the yeast two-hybrid method to detect protein interactions, 1,200 connections were identified between H. pylori proteins covering 46.6% of the genome. A comprehensive two-hybrid analysis has also been performed on all the proteins from the yeast S. cerevisiae.
mixed peptide sequencing with MS

mixed peptide sequencing with MS

The process of mixed-peptide sequencing involves separation of a complex protein mixture by polyacrylamide gel electrophoresis (1-D or 2-D) and then transfer of the proteins to an inert membrane by electroblotting (Fig. (Fig.4).4). The proteins of interest are visualized on the membrane surface, excised, and fragmented chemically at methionine (by CNBr) or tryptophan (by skatole) into several large peptide fragments.
FASTF and FASTS search programs

FASTF and FASTS search programs

The mixed-sequence data are fed into the FASTF or TFASTF algorithms, which sort and match the data against protein (FASTF) and DNA (TFASTF) databases to unambiguously identify the protein. The FASTF and TFASTF programs were written in collaboration with William Pearson (Department of Biochemistry, University of Virginia). Because minimal sample handling is involved, mixed-peptide sequencing can be a sensitive approach for identifying proteins in polyacrylamide gels at the 0.1- to 1-pmol level.  A recent variation of T/FASTF has been devised for MS (101) (Fig. (Fig.5B).5B). The T/FASTF/S programs are available at http://fasta.bioch.virginia.edu/ (Table (Table11).

triple quadrupole MS

triple quadrupole MS

Triple-quadrupole mass spectrometers are most commonly used to obtain amino acid sequences. In the first stage of analysis, the machine is operated in MS scan mode and all ions above a certain m/z ratio are transmitted to the third quadrupole for mass analysis (Fig. (Fig.6)6) (82, 173). In the second stage, the mass spectrometer is operated in MS/MS mode and a particular peptide ion is selectively passed into the collision chamber. Inside the collision chamber, peptide ions are fragmented by interactions with an inert gas by a process known as collision-induced dissociation or collisionally activated dissociation. The peptide ion fragments are then resolved on the basis of their m/z ratio by the third quadrupole (Fig. (Fig.6).6). Since two different mass spectra are obtained in this analysis, it is referred to as tandem mass spectrometry (MS/MS). MS/MS is used to obtain the amino acid sequence of peptides by generating a series of peptides that differ in mass by a single amino acid.

The largest application of proteomics continues to be protein expression profiling. Through the use of two-dimensional gels or novel techniques such as ICAT, the expression levels of proteins or changes in their level of modification between two different samples can be compared and the proteins can be identified. This approach can facilitate the dissection of signaling mechanisms or identify disease-specific proteins.

Cancer cells are good candidates for proteomics studies because they can be compared to their non-transformed counterparts. Analysis of differentially expressed proteins in normal versus cancer cells can

(i) identify novel tumor cell biomarkers that can be used for diagnosis,

(ii) provide clues to mechanisms of cancer development, and

(iii) identify novel targets for therapeutic intervention. Protein expression profiling has been used in the study of breast, esophageal, bladder and prostate cancer. From these studies, tumor-specific proteins were identified and 2-D protein expression databases were generated. Many of these 2-D protein databases are now available on the World Wide Web.

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Summary of Transcription, Translation ond Transcription Factors

Author and Curator:  Larry H. Bernstein, MD, FCAP  

 

Proteins are integral to the composition of the cytoskeleton, and also to the extracellular matrix.  Many proteins are actually enzymes, carrying out the transformation of some substrate, a derivative of the food we ingest.  They have a catalytic site, and they function with a cofactor – either a multivalent metal or a nucleotide. Proteins also are critically involved in the regulation of cell metabolism, and they are involved in translation of the DNA code, as they make up transcription factors (TFs). There are 20 essential amino acids that go into protein synthesis that are derived from animal or plant protein.   Protein synthesis is carried out by the transport of mRNA out of the nucleus to the ribosome, where tRNA is paired with a matching amino acid, and the primary sequence of a protein is constructed as a linear string of amino acids.

This is illustrated in the following three pictures:

protein synthesis

protein synthesis

mcell-transcription-translation

mcell-transcription-translation

transcription_translation

transcription_translation

Proteins synthesized at distal locations frequently contain intrinsically disordered segments. These regions are generally rich in assembly-promoting modules and are often regulated by post-translational modifications. Such proteins are tightly regulated but display distinct temporal dynamics upon stimulation with growth factors. Thus, proteins synthesized on-site may rapidly alter proteome composition and act as dynamically regulated scaffolds to promote the formation of reversible cellular assemblies.
RJ Weatheritt, et al. Nature Structural & Molecular Biology 24 Aug, 2014; 21: 833–839 http://dx.do.orgi:/10.1038/nsmb.2876

An overview of the potential advantages conferred by distal-site protein synthesis

An overview of the potential advantages conferred by distal-site protein synthesis

Turquoise and red filled circle represents off-target and correct interaction partners, respectively. Wavy lines represent a disordered region within a distal site synthesis protein. Grey and red line in graphs represents profiles of t…  http://www.nature.com/nsmb/journal/v21/n9/carousel/nsmb.2876-F5.jpg

In the the transcription process an RNA sequence is read.  This is essential for protein synthesis through the ordering of the amino acids in the primary structure. However, there are microRNAs and noncoding RNAs, and there are transcription factors.  The transcription factors bind to chromatin, and the RNAs also have some role in regulating the transcription process. (see picture above)

Transcription factors (TFs) interact dynamically in vivo with chromatin binding sites. Four different techniques are currently used to measure their kinetics in live cells,

  1. fluorescence recovery after photobleaching (FRAP),
  2. fluorescence correlation spectroscopy (FCS),
  3. single molecule tracking (SMT) and
  4. competition ChIP (CC).

A comparison of data from each of these techniques raises an important question:

  • do measured transcription kinetics reflect biologically functional interactions at specific sites (i.e. working TFs) or
  • do they reflect non-specific interactions (i.e. playing TFs)?

There are five key unresolved biological questions related to

  • the functionality of transient and prolonged binding events at both
  • specific promoter response elements as well as non-specific sites.

In support of functionality,

  • there are data suggesting that TF residence times are tightly regulated, and
  • that this regulation modulates transcriptional output at single genes.

In addition to this site-specific regulatory role, TF residence times

  • also determine the fraction of promoter targets occupied within a cell
  • thereby impacting the functional status of cellular gene networks.
  • TF residence times, then, are key parameters that could influence transcription in multiple ways.

Quantifying transcription factor kinetics: At work or at play? Mueller F., et al.  http://dx.doi.org:/10.3109/10409238.2013.833891

Dr. Virginie Mattot works in the team “Angiogenesis, endothelium activation and Cancer” directed by Dr. Fabrice Soncin at the Institut de Biologie de Lille in France where she studies the roles played by microRNAs in endothelial cells during physiological and pathological processes such as angiogenesis or endothelium activation. She has been using Target Site Blockers to investigate the role of microRNAs on putative targets.

A few years ago, the team identified

  • an endothelial cell-specific gene which
  • harbors a microRNA in its intronic sequence.

They have since been working on understanding the functions of

  • both this new gene and its intronic microRNA in endothelial cells.

While they were searching for the functions of the intronic microRNA,

  • theye identified an unknown gene as a putative target.

The aim of my project was to investigate if this unknown gene was actually a genuine target and

  • if regulation of this gene by the microRNA was involved in endothelial cell function.

They had already shown the endothelial cell phenotype is associated with the inhibition of the intronic microRNA.
They then used miRCURY LNA™ Target Site Blockers to demonstrate

  • the expression of this unknown gene is actually controlled by this microRNA.
  • the microRNA regulates specific endothelial cell properties through regulation of this unknown gene.

MicroRNA function in endothelial cells – Solving the mystery of an unknown target gene using Target Site Blockers to investigate the role of microRNAs on putative targets

We first verified that this TSB was functional by analyzing

  • the expression of the miRNA target against which the TSB was directed
  • we then showed the TSB induced similar phenotypes as those when we inhibited the microRNA in the same cells.

Target Site Blockers were shown to be efficient tools to demonstrate the specific involvement of

  • putative microRNA targets
  • in the function played by this microRNA.

Some genes are known to have several different alternatively spliced protein variants, but the Scripps Research Institute’s Paul Schimmel and his colleagues have uncovered almost 250 protein splice variants of an essential, evolutionarily conserved family of human genes. The results were published July 17 in Science.

Focusing on the 20-gene family of aminoacyl tRNA synthetases (AARSs),

  • the team captured AARS transcripts from human tissues—some fetal, some adult—and showed that
  • many of these messenger RNAs (mRNAs) were translated into proteins.

Previous studies have identified several splice variants of these enzymes that have novel functions, but uncovering so many more variants was unexpected, Schimmel said. Most of these new protein products

  • lack the catalytic domain but retain other AARS non-catalytic functional domains.

This study fundamentally effects how we view protein-synthesis, according to  Michael Ibba (who was not involved in the work), The Scientist reported. “The unexpected and potentially vast expanded functional networks that emerge from this study have the potential to influence virtually any aspect of cell growth.”

The team—comprehensively captured and sequenced the AARS mRNAs from six human tissue types using high-throughput deep sequencing. They next showed that a proportion of these transcripts, including those missing the catalytic domain, indeed resulted in stable protein products:

  • 48 of these splice variants associated with polysomes.

In vitro translation assays and the expression of more than 100 of these variants in cells confirmed that

  • many of these variants could be made into stable protein products.

The AARS enzymes—of which there’s one for each of the 20 amino acids—bring together an amino acid with its appropriate transfer RNA (tRNA) molecule. This reaction allows a ribosome to add the amino acid to a growing peptide chain during protein translation. AARS enzymes can be found in all living organisms and are thought to be among the first proteins to have originated on Earth.

One goal of human genetics is to understand how the information for precise and dynamic gene expression programs is encoded in the genome. The interactions of transcription factors (TFs) with DNA regulatory elements clearly

  • play an important role in determining gene expression outputs, yet
  • the regulatory logic underlying functional transcription factor binding is poorly understood.

An important question in genomics is to understand how a class of proteins called ‘‘transcription factors’’ controls the expression level of other genes in the genome in a cell type-specific manner – a process that is essential to human development. One major approach to this problem is to study where these transcription factors bind in the genome, but this does not tell us about the effect of that binding on gene expression levels and

  • it is generally accepted that much of the binding does not strongly influence gene expression.

DA Cusanovich et al. PLoS Genet 2014;10(3):e1004226.  http://dx.doi.org:/10.1371/journal.pgen.1004226

We knocked down 59 TFs and chromatin modifiers in one HapMap lymphoblastoid cell line

  • to evaluate the context of functional TF binding.

We then identified genes whose expression was affected by the knockdowns

  • by intersecting the gene expression data with transcription factor binding data
    (based on ChIP-seq and DNase-seq)
  • within 10 kb of the transcription start sites of expressed genes.

This combination of data allowed us to infer functional TF binding.
Only a small subset of genes bound by a factor were

  • differentially expressed following the knockdown of that factor,
  • suggesting that most interactions between TF and chromatin
  • do not result in measurable changes in gene expression levels
  • of putative target genes.

We found that functional TF binding is enriched

  • in regulatory elements that harbor a large number of TF binding sites,
  • at sites with predicted higher binding affinity, and
  • at sites that are enriched in genomic regions annotated as ‘‘active enhancers.’’

We aim to be able to predict the expression pattern of a gene based on its regulatory
sequence alone.

Combining a TF knockdown approach with TF binding data can help us to

  • distinguish functional binding from non-functional binding

This approach has previously been applied to the study of human TFs, although for the most part studies have only focused on

  • the regulatory relationship of a single factor with its downstream targets.

The FANTOM consortium knocked down 52 different transcription factors in

  • the THP-1 cell line, an acute monocytic leukemia-derived cell line, and
  • used a subset of these to validate certain regulatory predictions based on binding motif enrichments.

We and others previously studied the regulatory architecture of gene expression in

  • the model system of HapMap lymphoblastoid cell lines (LCLs) using both
  • binding map strategies and QTL mapping strategies.

We now sought to use knockdown experiments targeting transcription factors in a HapMap LCL

  • to refine our understanding of the gene regulatory circuitry of the human genome.

Therefore, We integrated the results of the knockdown experiments with previous data on TF binding to

  • better characterize the regulatory targets of 59 different factors and
  • to learn when a disruption in transcription factor binding
  • is most likely to be associated with variation in the expression level of a nearby gene.

Gene expression levels following the knockdown were compared to

  • expression data collected from six samples that were transfected with negative control siRNA.

Depending on the factor targeted, the knockdowns resulted in

  • between 39 and 3,892 differentially expressed genes at an FDR of 5%
    (Figure 1B; see Table S3 for a summary of the results).

The knockdown efficiency for the 59 factors ranged

  • from 50% to 90% (based on qPCR; Table S1).

The qPCR measurements of the knockdown level were significantly

  • correlated with estimates of the TF expression levels
  • based on the microarray data (P =0.001; Figure 1C).

 

Did the factors tended to have a consistent effect (either up- or down-regulation)

  • on the expression levels of genes they purportedly regulated?

All factors we tested are associated with both up- and down-regulation of downstream targets (Figure 6).

While there is compelling evidence for our inferences, the current chromatin functional annotations

  • do not fully explain the regulatory effects of the knockdown experiments.

For example, the enrichments for binding in ‘‘strong enhancer’’ regions of the genome range from 7.2% to 50.1% (median = 19.2%),

  • much beyond what is expected by chance alone, but far from accounting for all functional binding.

A slight majority of downstream target genes were expressed at higher levels

  • following the knockdown for 15 of the 29 factors for which we had binding information (Figure 6B).

The factor that is associated with the largest fraction (68.8%) of up-regulated target genes following the knockdown is EZH2,

  • the enzymatic component of the Polycomb group complex.

On the other end of the spectrum was JUND, a member of the AP-1 complex, for which

  • 66.7% of differentially expressed targets were down-regulated following the knockdown.

Our results, combined with the previous work from our group and others make for a complicated view

  • of the role of transcription factors in gene regulation as
  • it seems difficult to reconcile the inference from previous work that
  • many transcription factors should primarily act as activators with the results presented here.

One somewhat complicated hypothesis, which nevertheless can resolve the apparent discrepancy, is that

  • the ‘‘repressive’’ effects we observe for known activators may be
  • at sites in which the activator is acting as a weak enhancer of transcription and
  • that reducing the cellular concentration of the factor
  • releases the regulatory region to binding by an alternative, stronger activator.

Integrative study of Arabidopsis thaliana metabolomic and transcriptomic data
with the interactiveMarVis-Graph software

M Landesfeind, A Kaever, K Feussner, C Thurow, C Gatz, I Feussner and P Meinicke
PeerJ 2:e239;   http://dx.doi.org /10.7717/peerj.239

High-throughput technologies notoriously generate large datasets often including data from different omics platforms. Each dataset contains data for several thousand experimental markers, e.g., mass-to-charge ratios in mass spectrometry or spots in DNA microarray analysis. An experimental marker is associated with an intensity profile which may include several measurements according to different experimental conditions (Dettmer, Aronov & Hammock, 2007).

The combined analysis and visualization of data from different high-throughput technologies remains a key challenge in bioinformatics.We present here theMarVis-Graph software for integrative analysis of metabolic and transcriptomic data. All experimental data is investigated in terms of the full metabolic network obtained from a reference database. The reactions of the network are scored based on the associated data, and

  • sub-networks, according to connected high-scoring reactions, are identified.

Finally, MarVis-Graph scores the detected sub-networks,

  • evaluates them by means of a random permutation test and
  • presents them as a ranked list.

Furthermore, MarVis-Graph features an interactive network visualization that provides researchers with a convenient view on the results.

The key advantage ofMarVis-Graph is the analysis of reactions detached from their pathways so that

  • it is possible to identify new pathways or
  • to connect known pathways by previously unrelated reactions.

TheMarVis-Graph software is freely available for academic use and can be downloaded at: http://marvis.gobics.de/marvis-graph.

Significant differences or clusters may be explained by associated annotations, e.g., in terms of metabolic pathways or biological functions. During recent years, numerous specialized tools have been developed to aid biological researchers in automating all these steps (e.g., Medina et al., 2010; Kaever et al., 2009; Waegele et al., 2012). Comprehensive studies can be performed by combining technologies from different omics fields. The combination of transcriptomic and proteomic data sets revealed a strong
correlation between both kinds of data (Nie et al., 2007) and supported the detection of complex interactions, e.g., in RNA silencing (Haq et al., 2010). Moreover, correlations
were detected between RNA expression levels and metabolite abundances (Gibon et al., 2006). Therefore, tools that integrate, analyze and visualize experimental markers from different platforms are needed. To cope with the complexity of genome-wide studies, pathway models are utilized extensively as a simple abstraction of the underlying complex mechanisms. Set Enrichment Analysis (Subramanian et al., 2005) and Over-Representation Analysis (Huang, Sherman & Lempicki, 2009) have become state-of-the-art tools for analyzing large-scale datasets: both methods evaluate predefined sets of entities, e.g., the accumulation of differentially expressed genes in a pathway.

While manually curated pathways are convenient and easy to interpret, experimental studies have shown that all metabolic and signaling pathways are heavily interconnected (Kunkel & Brooks, 2002; Laule et al., 2003). Data from biomolecular databases support these studies: the metabolic network of Arabidopsis thaliana in the KEGG database (Kanehisa et al., 2012; Kanehisa & Goto, 2000) contains 1606 reactions from which 1464 are connected in a single sub-network (>91%), i.e., they
share a metabolite as product or substrate. In the AraCyc 10.0 database (Mueller, Zhang & Rhee, 2003; Rhee et al., 2006), more than 89% of the reactions are counted in a single sub-network. In both databases, most other reactions are completely disconnected. Additionally, Set Enrichment Analyses can not identify links between the predefined sets easily. This becomes even more important when analyzing smaller pathways as provided by the MetaCyc (Caspi et al., 2008; Caspi et al., 2012) database. Moreover, methods that utilize pathways as predefined sets ignore reactions and related biomolecular entities (e.g., metabolites, genes) which are not associated with a single pathway. For example, this affects 4000 reactions in MetaCyc and 2500 in KEGG, respectively (Altman et al., 2013). Therefore, it is desirable to develop additional methods

  • that do not require predefined sets but may detect enriched sub-networks in the full metabolic network.

While several tools support the statistical analysis of experimental markers from one or more omics technologies and then utilize variants of Set Enrichment Analysis (Xia et al., 2012; Chen et al., 2013; Howe et al., 2011),

  • no tool is able to explicitly search for connected reactions that include
  • most of the metabolites, genes, and enyzmes with experimental evidence.

However, the automatic identification of sub-networks has been proven useful in other contexts, e.g., in the analysis of protein–protein-interaction networks (Alcaraz et al., 2012; Baumbach et al., 2012; Maeyer et al., 2013).

MarVis-Graph imports experimental markers from different high-throughput experiments and

  • analyses them in the context of reaction-chains in full metabolic networks.

Then, MarVis-Graph scores the reactions in the metabolic network

  • according to the number of associated experimental markers and
  • identifies sub-networks consisting of subsequent, high-scoring reactions.

The resulting sub-networks are

  • ranked according to a scoring method and visualized interactively.

Hereby, sub-networks consisting of reactions from different pathways may be identified to be important

  • whereas the single pathways may not be found to be significantly enriched.

MarVis-Graph may also connect reactions without an assigned pathway

  • to reactions within a particular pathway.

TheMarVis-Graph tool was applied in a case-study investigating the wound response in Arabidopsis thaliana to analyze combined metabolomic and transcriptomic high-throughput data.

Figure 1 Schema of the metabolic network representation in MarVis-Graph. Metabolite markers are shown in gray, metabolites in red, reactions in blue, enzymes in green, genes in yellow, transcript markers in pink, and pathways in turquoise color. The edges are shown in black with labels that comply with the biological meaning. The orange arrows depict the flow of score for the initial scoring (described in section “Initial Scoring”). (not shown)

In MarVis-Graph, metabolite markers obtained from mass-spectrometry experiments additionally contain the experimental mass. The experimental mass has to be
calculated based on the mass-to-charge ratio (m/z-value) and specific isotope- or adduct-corrections (Draper et al., 2009) by means of specialized tools, e.g.,MarVis-Filter
(Kaever et al., 2012).

For each transcript marker the corresponding annotation has to be given. In DNA microarray experiments, each spot (transcript marker) is specific for a gene and can
therefore be used for annotation. For other technologies an annotation has to be provided by external tools.

In MarVis-Graph, each reaction is scored initially based on the associated experimental data (see “Initial scoring”). This initial scoring is refined (see “Refining the scoring”) and afterwards reactions with a score below a user-defined threshold are removed. The network is

  • decomposed into subsequent high-scoring reactions that constitute the sub-networks.

The weight of each experimental marker (see “Experimental markers”) is equally distributed over all metabolites and genes associated with the metabolite marker or
transcript marker, respectively. For all vertices, this is repeated as illustrated in Fig. 1 until the weights are accumulated by the reactions.

The initial reaction scores are used as input scoring for the random walk algorithm. The algorithm is performed as described by Glaab et al. (2012) with a user-defined
restart-probability r (default value 0.8). After convergence of the algorithm, reactions with a score lower than the user-defined threshold t (default value t = 1−r) are removed from the reaction network. During the removal process,

  • the network is decomposed into pairwise disconnected sub-networks containing only high-scoring reactions.

In the following, a resulting sub-network is denoted by a prime: G′ = (V′,L′) with V′ = M′ ∪C′ ∪R′ ∪E′ ∪G′ ∪T′ ∪P′.

The scores of the identified sub-networks can be assessed using a random permutation test, evaluating the marker annotations under the null hypothesis of being connected
randomly. Here, the assignments

  • from metabolite markers to metabolites and from transcript markers to genes are randomized.

For each association between a metabolite marker and a metabolite,

  • this connection is replaced by a connection between a randomly chosen metabolite marker and a randomly chosen metabolite.

The random metabolite marker is chosen from the pool of formerly connected metabolite markers. Each connected transcript marker

  • is associated with a randomly chosen gene.

Choosing from the list of already connected experimental markers ensures that

  • the sum of weights from the original and the permuted network are equal.

This method differs from the commonly utilized XSwap permutation (Hanhij¨arvi, Garriga & Puolam¨aki, 2009) that is based on swapping endpoints of two random edges. The main difference of our permutation method is that it results in a network with different topological structure, i.e., different degree of the metabolite and gene nodes.

Finally, the sub-networks are detected and scored with the same parameters applied for the original network. Based on the scores of the networks identified in the random
permutations, the family-wise-error-rate (FWER) and false-discovery-rate (FDR) are calculated for each originally identified sub-network.

MarVis-Graph was applied in a case study investigating the A. thaliana wound response. Data from a metabolite fingerprinting (Meinicke et al., 2008) and a DNA microarray
experiment (Yan et al., 2007) were imported into a metabolic network specific for A. thaliana created from the AraCyc 10.0 database (Lamesch et al., 2011). The metabolome
and transcriptome have been measured before wounding as control and at specific time points after wounding in wild-type and in the allene oxide synthase (AOS) knock-out
mutant dde-2-2 (Park et al., 2002) of A. thaliana Columbia (see Table 1). The AOS mutant was chosen, because AOS catalyzes the first specific step in the biosynthesis of the hormone jasmonic acid, which is the key regulator in wound response of plants (Wasternack & Hause, 2013).

Both datasets have been preprocessed with theMarVis-Filter tool (Kaever et al., 2012) utilizing the Kruskal–Wallis p-value calculation on the intensity profiles. Based on the ranking of ascending p-values,

  • the first 25% of the metabolite markers and 10% of the transcript markers have been selected for further investigation (Data S2).

The filtered metabolite and transcript markers were imported into the metabolic network. For metabolite markers, metabolites were associated

  • if the metabolite marker’s detected mass differs from the metabolites monoisotopic mass by a maximum of 0.005u.

Transcript markers were linked to the genes whose ID equaled the ID given in the CATMA database (Sclep et al., 2007) for that transcript marker.

Table 2 Vertices in the A. thaliana specific metabolic network after import of experimental markers. Number of objects in the metabolic network
in absolute counts and relative abundances. For experimental markers, the with annotation column gives the number of metabolite markers and
transcript markers that were annotated with a metabolite or gene, respectively. The direct evidence column contains the number of metabolites
and genes, that are associated with a metabolite marker or transcript marker. For enzymes, this is the number of enzymes encoded by a gene with
direct evidence. The number of vertices with an association to a reaction is given in the with reaction column. In the last column, this is given for
associations to metabolic pathways. (not shown)

MarVis-Graph detected a total of 133 sub-networks. The sub-networks were ranked according to size Ss, diameter Sd, and sum-of-weights Ssow
scores (Table S4). Interestingly, the different rankings show a high correlation with all pairwise correlations higher than 0.75 (Pearson correlation
coefficient) and 0.6 (Spearman rank correlation).

Allene-oxide cyclase sub-network
In all rankings, the sub-network allene-oxide cyclase (named after the reaction with the highest score in this sub-network) appeared as top candidate.

This sub-network is constituted of reactions from different pathways related to fatty acids. Figure 2 shows a visualization of the sub-network.
Jasmonic acid biosynthesis. The main part of the sub-network is formed by reactions from the “jasmonic acid biosynthesis” (PlantMetabolic Network, 2013)
resulting in jasmonic acid (jasmonate). The presence of this pathway is very well established because of its central role in mediating the plants wound response
(Reymond & Farmer, 1998; Creelman, Tierney & Mullet, 1992). Additionally, metabolites and transcripts from this pathway were expected to show prominent
expression profiles because AOS, a key enzyme in this pathway, is knocked-out in themutant plant. Jasmonic acid derivatives and hormones.

Jasmonic acid derivatives and hormones. Jasmonate is a precursor for a broad variety of plant hormones (Wasternack & Hause, 2013), e.g., the derivative (-)-
jasmonic acid methyl ester (also Methyl Jasmonic Acid; MeJA) is a volatile, airborne signal mediating wound response between plants (Farmer&Ryan, 1990).
Reactions from the jasmonoyl-amino acid conjugates biosynthesis I (PMN, 2013a) pathway connect jasmonate to different amino acids, including L-valine,
L-leucine, and L-isoleucine. Via these amino acids, this sub-network is connected to the indole-3-acetylamino acid biosynthesis (PMN, 2013b) (IAA biosynthesis).
Again, this pathway produces a well known plant hormone: Auxine (Woodward & Bartel, 2005). Even though, jasmonate and auxin are both plant hormones, their
connection in this subnetwork is of minor relevance because amino acid conjugates are often utilized as active or storage forms of signaling molecules.While
jasmonoyl-amino acid conjugates represent the active signaling form of jasmonates, IAA amino acid conjugates are the storage form of this hormone (Staswick et al.,
2005).

polyhydroxy fatty acids synthesis

polyhydroxy fatty acids synthesis

 

Figure 2 Schema of the allene-oxide cyclase sub-network. Metabolites are shown in red, reactions in blue, and enzymes in green color. Metabolites and reactions without direct experimental evidence are marked by a dashed outline and a brighter color while enzymes without experimental evidence are hidden. The metabolic pathways described in section “Resulting sub-networks” are highlighted with different colors. The orange and green parts indicate the reaction chains required to build jasmonate and its amino acid conjugates. The coloring of pathways was done manually after export from MarVis-Graph.

The ω-3-fatty acid desaturase should catalyze a reaction from linoleate to α-linolenate. Metabolite markers that match the mass of crepenynic acid do also match α-linolenate
because both molecules have the same sum-formula and monoisotopic mass. As mentioned above, MarVis-Graph compiled the metabolic network for this study
from the AraCyc database version 10.0. On June 4th, a curator changed the database to remove theΔ12-fatty acid dehydrogenase prior to the release of AraCyc version 11.0.

The presented new software tool MarVis-Graph supports the investigation and visualization of omics data from different fields of study. The introduced algorithm for
identification of sub-networks is able to identify reaction-chains across different pathways and includes reactions that are not associated with a single pathway. The application of MarVis-Graph in the case study on A. thaliana wound response resulted in a convenient graphical representation of high-throughput data which allows the analysis of the complex dynamics in a metabolic network.

 

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Transcription Modulation

Author and Curator: Larry H. Bernstein, MD, FCAP 

 

This portion of the transcription series deals with transcription factors and the effects of their binding on metabolism. This also has implications for pharmaceutical target identification.

The Functional Consequences of Variation in Transcription Factor Binding
DA. Cusanovich, B Pavlovic, JK. Pritchard*, Y Gilad*
1 Department of Human Genetics, 2 Howard Hughes Medical Institute, University of Chicago, Chicago, IL 3 Departments of Genetics and Biology and Howard Hughes Medical Institute, Stanford University, Stanford, CA.
PLoS Genet 2014;10(3):e1004226.  http://dx.doi.org:/10.1371/journal.pgen.1004226

One goal of human genetics is to understand how the information for precise and dynamic gene expression programs is encoded in the genome. The interactions of transcription factors (TFs) with DNA regulatory elements clearly

  • play an important role in determining gene expression outputs, yet
  • the regulatory logic underlying functional transcription factor binding is poorly understood.

An important question in genomics is to understand how a class of proteins called ‘‘transcription factors’’ controls the expression level of other genes in the genome in a cell type-specific manner – a process that is essential to human development. One major approach to this problem is to study where these transcription factors bind in the genome, but this does not tell us about the effect of that binding on gene expression levels and

  • it is generally accepted that much of the binding does not strongly influence gene expression.

To address this issue, we artificially reduced the concentration of 59 different transcription factors in the cell and then

  • examined which genes were impacted by the reduced transcription factor level.

Our results implicate some attributes

  • that might influence what binding is functional, but they also suggest that
  • a simple model of functional vs. non-functional binding may not suffice.

Many studies have focused on characterizing the genomic locations of TF binding, but

  • it is unclear whether TF binding at any specific locus has
  • functional consequences with respect to gene expression output.

We knocked down 59 TFs and chromatin modifiers in one HapMap lymphoblastoid cell line

  • to evaluate the context of functional TF binding.

We then identified genes whose expression was affected by the knockdowns

  • by intersecting the gene expression data with transcription factor binding data
    (based on ChIP-seq and DNase-seq)
  • within 10 kb of the transcription start sites of expressed genes.

This combination of data allowed us to infer functional TF binding.
Only a small subset of genes bound by a factor were

  • differentially expressed following the knockdown of that factor,
  • suggesting that most interactions between TF and chromatin
  • do not result in measurable changes in gene expression levels
  • of putative target genes.

We found that functional TF binding is enriched

  • in regulatory elements that harbor a large number of TF binding sites,
  • at sites with predicted higher binding affinity, and
  • at sites that are enriched in genomic regions annotated as ‘‘active enhancers.’’

We aim to be able to predict the expression pattern of a gene based on its regulatory
sequence alone. However, the regulatory code of the human genome is much more complicated than

  • the triplet code of protein coding sequences, and is highly context-specific,
  • depending on cell-type and other factors.

Moreover, regulatory regions are not necessarily organized into

  • discrete, easily identifiable regions of the genome and
  • may exert their influence on genes over large genomic distances

Genomic studies addressing questions of the regulatory logic of the human genome have largely taken one of two approaches.

  1. collecting transcription factor binding maps using techniques such as ChIPseq
    and DNase-seq
  2. mapping various quantitative trait loci (QTL), such as gene expression levels
    (eQTLs) [7], DNA methylation (meQTLs) [8] and chromatin accessibility (dsQTLs)

Cumulatively, binding map studies and QTL map studies have

  • led to many insights into the principles and mechanisms of gene regulation.

However, there are questions that neither mapping approach on its own is well equipped to address. One outstanding issue is

  • the fraction of factor binding in the genome that is ‘‘functional’’,
    which we define here to mean that
  • disturbing the protein-DNA interaction leads to a measurable
  • downstream effect on gene regulation.

Transcription factor knockdown could be used to address this problem, whereby

  • the RNA interference pathway is employed to greatly reduce
  • the expression level of a specific target gene by using small interfering RNAs (siRNAs).

The response to the knockdown can then be measured by collecting RNA after the knockdown and

  • measuring global changes in gene expression patterns
  • after specifically attenuating the expression level of a given factor.

Combining a TF knockdown approach with TF binding data can help us to

  • distinguish functional binding from non-functional binding

This approach has previously been applied to the study of human TFs, although for the most part studies have only focused on

  • the regulatory relationship of a single factor with its downstream targets.

The FANTOM consortium knocked down 52 different transcription factors in

  • the THP-1 cell line, an acute monocytic leukemia-derived cell line, and
  • used a subset of these to validate certain regulatory predictions based on binding motif enrichments.

We and others previously studied the regulatory architecture of gene expression in

  • the model system of HapMap lymphoblastoid cell lines (LCLs) using both
  • binding map strategies and QTL mapping strategies.

We now sought to use knockdown experiments targeting transcription factors in a HapMap LCL

  • to refine our understanding of the gene regulatory circuitry of the human genome.

Therefore, We integrated the results of the knockdown experiments with previous data on TF binding to

  • better characterize the regulatory targets of 59 different factors and
  • to learn when a disruption in transcription factor binding
  • is most likely to be associated with variation in the expression level of a nearby gene.

Gene expression levels following the knockdown were compared to

  • expression data collected from six samples that were transfected with negative control siRNA.

The expression data from all samples were normalized together using

  • quantile  normalization followed by batch correction using the RUV-2 method.

We then performed several quality control analyses to confirm

  1. that the quality of the data was high,
  2. that there were no outlier samples, and
  3. that the normalization methods reduced the influence of confounders

In order to identify genes that were expressed at a significantly different level

  • in the knockdown samples compared to the negative controls,
  • we used likelihood-ratio tests within the framework of a fixed effect linear model.

Following normalization and quality control of the arrays,

  • we identified genes that were differentially expressed between
  • the three knockdown replicates of each factor and the six controls.

Depending on the factor targeted, the knockdowns resulted in

  • between 39 and 3,892 differentially expressed genes at an FDR of 5%
    (Figure 1B; see Table S3 for a summary of the results).

The knockdown efficiency for the 59 factors ranged

  • from 50% to 90% (based on qPCR; Table S1).

The qPCR measurements of the knockdown level were significantly

  • correlated with estimates of the TF expression levels
  • based on the microarray data (P =0.001; Figure 1C).

Reassuringly, we did not observe a significant correlation between

  • the knockdown efficiency of a given factor and
  • the number of genes classified as differentially expressed foci.

Because we knocked down 59 different factors in this experiment

  • we were able to assess general patterns associated with the perturbation of transcription factors
  • beyond merely the number of affected target genes.

Globally, despite the range in the number of genes we identified as

  • differentially expressed in each knockdown,
  • the effect sizes of the differences in expression were relatively modest and
  • consistent in magnitude across all knockdowns.

The median effect size following the knockdown experiment for genes classified as

  • differentially expressed at an FDR of 5% in any knockdown was
  • a 9.2% difference in expression level between the controls and the knockdown (Figure 2),
  • while the median effect size for any individual knockdown experiment ranged between 8.1% and 11.0%.
    (this was true whether we estimated the knockdown effect based on qPCR (P = 0.10; Figure 1D) or microarray (P = 0.99; not shown) data.

Nor did we observe a correlation between

  • variance in qPCR-estimated knockdown efficiency (between replicates) and
  • the number of genes differentially expressed (P = 0.94; Figure 1E).

We noticed that the large variation in the number of differentially expressed genes

  • extended even to knockdowns of factors from the same gene family.

Figure 1. Differential expression analysis.
(a) Examples of differential expression analysis results for the genes HCST and IRF4. The top two panels are ‘MA plots’ of the mean Log2(expression level) between the knockdown arrays and the controls for each gene (x-axis) to the Log2(Fold-Change) between the knockdowns and controls (y-axis). Differentially expressed genes at an FDR of 5% are plotted in yellow (points 50% larger). The gene targeted by the siRNA is highlighted in red. The bottom two panels are ‘volcano plots’ of the Log2(Fold-Change) between the knockdowns and controls (x-axis) to the P-value for differential expression (y-axis). The dashed line marks the 5% FDR threshold. Differentially expressed genes at an FDR of 5% are plotted in yellow (points 50% larger). The red dot marks the gene targeted by the siRNA.
(b) Barplot of number of differentially expressed genes in each knockdown experiment.
(c) Comparison of the knockdown level measured by qPCR (RNA sample collected 48 hours posttransfection) and the knockdown level measured by microarray.
(d) Comparison of the level of knockdown of the transcription factor at 48 hrs (evaluated by qPCR; x-axis) and the number of genes differentially expressed in the knockdown experiment (y-axis).
(e) Comparison of the variance in knockdown efficiency between replicates for each transcription factor (evaluated by qPCR; x-axis) and the number of differentially expressed genes in the knockdown experiment (y-axis).

Differential expression analysis

Differential expression analysis

http://dx.doi.org:/10.1371/journal.pgen.1004226.g001

Figure 2. Effect sizes for differentially expressed genes.
Boxplots of absolute Log2(fold-change) between knockdown arrays and control arrays for all genes identified as differentially expressed in each experiment. Outliers are not plotted. The gray bar indicates the interquartile range across all genes differentially expressed in all knockdowns. Boxplots are ordered by the number of genes differentially expressed in each experiment. Outliers were not plotted.

Effect sizes for differentially expressed genes

Effect sizes for differentially expressed genes

http://dx.doi.org:/10.1371/journal.pgen.1004226.g002

Knocking down SREBF2 (1,286 genes differentially expressed), a key regulator of cholesterol homeostasis,

  • results in changes in the expression of genes that are
  • significantly enriched for cholesterol and sterol biosynthesis annotations.

While not all factors exhibited striking enrichments for relevant functional categories and pathways,

  • the overall picture is that perturbations of many of the factors
  • primarily affected pathways consistent with their known biology.

In order to assess functional TF binding, we next incorporated

  • binding maps together with the knockdown expression data.

We combined binding data based on DNase-seq footprints in 70 HapMap LCLs, reported by Degner et al. (Table S5)

  • and from ChIP-seq experiments in LCL GM12878, published by ENCODE.

We were thus able to obtain genome wide binding maps for a total of 131 factors that were either

  • directly targeted by an siRNA in our experiment (29 factors) or were
  • differentially expressed in one of the knockdown experiments.

We classified a gene as a bound target of a particular factor when

  • binding of that factor was inferred within 10kb of the transcription start site (TSS) of the target gene.

Using this approach, we found that the 131 TFs were bound

  • in proximity to a median of 1,922 genes per factor (range 11 to 7,053 target genes).

We considered binding of a factor to be functional if the target gene

  • was differentially expressed after perturbing the expression level the bound transcription factor.

We then asked about the concordance between

  • the transcription factor binding data and the knockdown expression data.
  •  the extent to which differences in gene expression levels following the knockdowns
  • might be predicted by binding of the transcription factors
  • within the putative regulatory regions of the responsive genes. and also
  • what proportion of putative target (bound) genes of a given TF were
  • differentially expressed following the knockdown of the factor.

Focusing only on the binding sites classified using the DNase-seq data
(which were assigned to a specific instance of the binding motif, unlike the ChIP data),

  • we examined sequence features that might distinguish functional binding.

In particular, whether binding at conserved sites was more likely to be functional  and

  • whether binding sites that better matched the known PWM for the factor were more likely to be functional.

We did not observe a significant shift in the conservation of functional binding sites (Wilcoxon rank sum P = 0.34),

  • but we did observe that binding around differentially expressed genes occurred at sites
  • that were significantly better matches to the canonical binding motif.

Figure 3. Intersecting binding data and expression data for each knockdown.
(a) Example Venn diagrams showing the overlap of binding and differential expression for the knockdowns of HCST and IRF4 (the same genes as in Figure 1).
(b) Boxplot summarizing the distribution of the fraction of all expressed genes that are bound by the targeted gene or downstream factors.
(c) Boxplot summarizing the distribution of the fraction of bound genes that are classified as differentially expressed, using an FDR of either 5% or 20%.

Intersecting binding data and expression data for each knockdown

Intersecting binding data and expression data for each knockdown

http://dx.doi.org:/10.1371/journal.pgen.1004226.g003

Considering bound targets determined from either the ChIP-seq or DNase-seq data, we observed that

  • differentially expressed genes were associated with both
  • a higher number of binding events for the relevant factors within 10 kb of the TSS (P,10216; Figure 4A)
  • as well as with a larger number of different binding factors
    (considering the siRNA-targeted factor and any TFs that were DE in the knockdown; P,10216; Figure 4B).

Figure 4. Degree of binding correlated with function. Boxplots comparing
(a) the number of sites bound, and
(b) the number of differentially expressed transcription factors binding events near functionally or non-functionally bound genes. We considered binding for siRNA-targeted factor and any factor differentially expressed in the knockdown.
(c) Focusing only on genes differentially expressed in common between each pairwise set of knockdowns we tested for enrichments of functional binding (y-axis). Pairwise comparisons between knockdown experiments were binned by the fraction of differentially expressed transcription factors in common between the two experiments. For these boxplots, outliers were not plotted.

Degree of binding correlated with function

Degree of binding correlated with function

http://dx.doi.org:/10.1371/journal.pgen.1004226.g004

We examined the distribution of binding about the TSS. Most factor binding was concentrated

  • near the TSS whether or not the genes were classified as differentially expressed (Figure 5A).
  • the distance from the TSS to the binding sites was significantly longer for differentially expressed genes (P,10216; Fig. 5B).

Figure 5. Distribution of functional binding about the TSS.
(a) A density plot of the distribution of bound sites within 10 kb of the TSS for both functional and non-functional genes. Inset is a zoom-in of the region +/21 kb from the TSS (b) Boxplots comparing the distances from the TSS to the binding sites for functionally bound genes and non-functionally bound genes. For the boxplots, 0.001 was added before log10 transforming the distances and outliers were not plotted.

Distribution of functional binding about the TSS

Distribution of functional binding about the TSS

http://dx.doi.doi:/10.1371/journal.pgen.1004226.g005

We investigated the distribution of factor binding across various chromatin states, as defined by Ernst et al. This dataset lists

  • regions of the genome that have been assigned to different activity states
  • based on ChIP-seq data for various histone modifications and CTCF binding.

For each knockdown, we separated binding events

  • by the genomic state in which they occurred and then
  • tested whether binding in that state was enriched around differentially expressed genes.

After correcting for multiple testing of genes that were differentially expressed.

  • 19 knockdowns showed significant enrichment for binding in ‘‘strong enhancers’’
  • four knockdowns had significant enrichments for ‘‘weak enhancers’’,
  • eight knockdowns showed significant depletion of binding in ‘‘active promoters’’ ,
  • six knockdowns had significant depletions for ‘‘transcription elongation’’,

Did the factors tended to have a consistent effect (either up- or down-regulation)

  • on the expression levels of genes they purportedly regulated?

All factors we tested are associated with both up- and down-regulation of downstream targets (Figure 6).

A slight majority of downstream target genes were expressed at higher levels

  • following the knockdown for 15 of the 29 factors for which we had binding information (Figure 6B).

The factor that is associated with the largest fraction (68.8%) of up-regulated target genes following the knockdown is EZH2,

  • the enzymatic component of the Polycomb group complex.

On the other end of the spectrum was JUND, a member of the AP-1 complex, for which

  • 66.7% of differentially expressed targets were down-regulated following the knockdown.

Figure 6. Magnitude and direction of differential expression after knockdown.
(a) Density plot of all Log2(fold-changes) between the knockdown arrays and controls for genes that are differentially expressed at 5% FDR in one of the knockdown experiments as well as bound by the targeted transcription factor.
(b) Plot of the fraction of differentially expressed putative direct targets that were up-regulated in each of the knockdown experiments.

Magnitude and direction of differential expression after knockdown

Magnitude and direction of differential expression after knockdown

http://dx.doi.org:/10.1371/journal.pgen.1004226.g006

We found no correlation between the number of paralogs and the fraction of bound targets that were differentially expressed. We also did not observe a significant correlation when we considered whether

  • the percent identity of the closest paralog might be predicative of
  • the fraction of bound genes that were differentially expressed following the knockdown (Figure S8).

While there is compelling evidence for our inferences, the current chromatin functional annotations

  • do not fully explain the regulatory effects of the knockdown experiments.

For example, the enrichments for binding in ‘‘strong enhancer’’ regions of the genome range from 7.2% to 50.1% (median = 19.2%),

  • much beyond what is expected by chance alone, but far from accounting for all functional binding.

In addition to considering

  • the distinguishing characteristics of functional binding, we also examined
  • the direction of effect that perturbing a transcription factor had on the expression level of its direct targets.

We specifically addressed whether

  • knocking down a particular factor tended to drive expression of its putatively direct (namely, bound) targets up or down,
  • which can be used to infer that the factor represses or activates the target, respectively.

Transcription factors have traditionally been thought of primarily as activators, and previous work from our group is consistent with that notion. Surprisingly, the most straightforward inference from the present study is that

  • many of the factors function as repressors at least as often as they function as activators.
  1. EZH2 had a negative regulatory relationship with the largest fraction of direct targets (68.8%),
    consistent with – the known role of EZH2 as the active member of the Polycomb group complex PC2
  2. while JUND seemed to have a positive regulatory relationship with the largest fraction of direct targets (66.7%),
    and with – the biochemical characterization of the AP-1 complex (of which JUND is a component) as a transactivator.

More generally, however, our results, combined with the previous work from our group and others make for a complicated view

  • of the role of transcription factors in gene regulation as
  • it seems difficult to reconcile the inference from previous work that
  • many transcription factors should primarily act as activators with the results presented here.

One somewhat complicated hypothesis, which nevertheless can resolve the apparent discrepancy, is that

  • the ‘‘repressive’’ effects we observe for known activators may be
  • at sites in which the activator is acting as a weak enhancer of transcription and
  • that reducing the cellular concentration of the factor
  • releases the regulatory region to binding by an alternative, stronger activator.

To more explicitly address the effect that our proximity-based definition of target genes might have on our analyses, we reanalyzed

  • the overlap between factor binding and differential expression following the knockdowns
  • using an independent, empirically determined set of target genes.

Thurman et al. used correlations in DNase hypersensitivity between

  • intergenic hypersensitive sites and promoter hypersensitive sites across diverse tissues
  • to assign intergenic regulatory regions to specific genes,
  • independently of proximity to a particular promoter.

We performed this alternative analysis in which we

  • assigned binding events to genes based on the classification of Thurman et al.

We then considered the overlap between binding and differential expression in this new data set. The results were largely

  • consistent with our proximity-based observations.

A median of 9.5% of genes that were bound by a factor were

  • also differentially expressed following the knockdown of that factor
    (compared to 11.1% when the assignment of binding sites to genes is based on proximity).

From the opposite perspective, a median of 28.0% of differentially expressed genes were bound by that factor
(compared to 32.3% for the proximity based definition). The results of this analysis are summarized in Table S7.

Our results should not be considered a comprehensive census of regulatory events in the human genome. Instead, we adopted a gene-centric approach,

  • focusing only on binding events near the genes for which we could measure expression
  • to learn some of the principles of functional transcription factor binding.

In light of our observations a reassessment of our estimates of binding may be warranted. In particular, because functional binding is skewed away from promoters (our system is apparently not well-suited to observe functional promoter binding, perhaps because of protection by large protein complexes),

  • a more conservative estimate of the fraction of binding that is indeed functional would not consider data within the promoter.

Importantly, excluding the putative promoter region from our analysis (i.e. only considering a window .1 kb from the TSS and ,10 kb from the TSS)

  • does not change our conclusions.

Considering this smaller window,

  • a median of 67.0% of expressed genes are still classified as bound by
  1. either the knocked down transcription factor or
  2. a downstream factors that is differentially expressed in each experiment,

yet a median of only 8.1% of the bound genes are

  • also differentially expressed after the knockdowns.

Much of what distinguishes functional binding (as we define it) has yet to be explained. We are unable to explain much of the differential expression observed in our experiments by the presence of least one relevant binding event. This may not be altogether surprising, as

  • we are only considering binding in a limited window around the transcription start site.

To address these issues, more factors should be perturbed to further evaluate the robustness of our results and to add insight. Together, such studies will help us develop a more sophisticated understanding of functional transcription factor binding in particular, the gene regulatory logic more generally.

Assessing quality and completeness of human transcriptional regulatory pathways on a genome-wide scale

E Shmelkov, Z Tang, I Aifantis, A Statnikov*
Biology Direct 2011; 6(15).  http://www.biology-direct.com/content/6/1/15

Recently the biological pathways have become a common and probably the most popular form of representing biochemical information for hypothesis generation and validation. These maps store wide knowledge of complex molecular interactions and regulations occurring in the living organism in a simple and obvious way, often using intuitive graphical notation. Two major types of biological pathways could be distinguished.

  1. Metabolic pathways incorporate complex networks of protein-based interactions and modifications, while
  2. signal transduction and transcriptional regulatory pathways are usually considered to provide information on mechanisms of transcription

While there are a lot of data collected on human metabolic processes,

  • the content of signal transduction and transcriptional regulatory pathways varies greatly in quality and completeness.

An indicative comparison of MYC transcriptional targets reported in ten different pathway databases reveals that these databases differ greatly from each other (Figure 1). Given that MYC is involved

  • in the transcriptional regulation of approximately 15% of all genes,

one cannot argue that the majority of pathway databases that contain

  • less than thirty putative transcriptional targets of MYC are even close to complete.

More importantly, to date there have been no prior genome-wide evaluation studies (that are based on genome-wide binding and gene expression assays) assessing pathway databases

Background: While pathway databases are becoming increasingly important in most types of biological and translational research, little is known about the quality and completeness of pathways stored in these databases. The present study conducts a comprehensive assessment of transcriptional regulatory pathways in humans for seven well-studied transcription factors:

  1. MYC,
  2. NOTCH1,
  3. BCL6,
  4. TP53,
  5. AR,
  6. STAT1,
  7. RELA.

The employed benchmarking methodology first involves integrating

  • genome-wide binding with functional gene expression data
  • to derive direct targets of transcription factors.

Then the lists of experimentally obtained direct targets

  • are compared with relevant lists of transcriptional targets from 10 commonly used pathway databases.

Results: The results of this study show that for the majority of pathway databases,

  • the overlap between experimentally obtained target genes and
  • targets reported in transcriptional regulatory pathway databases is
  • surprisingly small and often is not statistically significant.

The only exception is MetaCore pathway database which

  • yields statistically significant intersection with experimental results in 84% cases.

The lists of experimentally derived direct targets obtained in this study can be used

  • to reveal new biological insight in transcriptional regulation,  and we
  • suggest novel putative therapeutic targets in cancer.

Conclusions: Our study opens a debate on validity of using many popular pathway databases to obtain transcriptional regulatory targets. We conclude that the choice of pathway databases should be informed by

  • solid scientific evidence and rigorous empirical evaluation.

In the current study we perform

(1) an evaluation of ten commonly used pathway databases,

  • assessing the transcriptional regulatory pathways, considered in the current study as
  • the interactions of the type ‘transcription factor-transcriptional targets’.

This involves integration of human genome wide functional microarray or RNA-seq gene expression data with

  • protein-DNA binding data from ChIP-chip, ChIP-seq, or ChIP-PET platforms
  • to find direct transcriptional targets of the seven well known transcription factors:
  • MYC, NOTCH1, BCL6, TP53, AR, STAT1, and RELA.

The choice of transcription factors is based on their important role in oncogenesis and availability of binding and expression data in the public domain.

(2) the lists of experimentally derived direct targets are used to assess the quality and completeness of 84 transcriptional regulatory pathways from four publicly available (BioCarta, KEGG, WikiPathways and Cell Signaling Technology) and six commercial (MetaCore, Ingenuity Pathway Analysis, BKL TRANSPATH, BKL TRANSFAC, Pathway Studio and GeneSpring Pathways) pathway databases.

(3) We measure the overlap between pathways and experimentally obtained target genes and assess statistical significance of this overlap, and we demonstrate that experimentally derived lists of direct transcriptional targets

  • can be used to reveal new biological insight on transcriptional regulation.

We show this by analyzing common direct transcriptional targets of

  • MYC, NOTCH1 and RELA
  • that act in interconnected molecular pathways.

Detection of such genes is important as it could reveal novel targets of cancer therapy.

Figure 1 Number of genes in common between MYC transcriptional targets derived from ten different pathway databases. Cells are colored according to their values from white (low values) to red (high values). (not shown)

statistical methodology for comparison

statistical methodology for comparison

Figure 2 Illustration of statistical methodology for comparison between a gold-standard and a pathway database

Since we are seeking to compare gene sets from different studies/databases, it is essential to transform genes to standard identifiers. That is why we transformed all
gene sets to the HUGO Gene Nomenclature Committee approved gene symbols and names. In order to assess statistical significance of the overlap between the resulting gene sets, we used the hypergeometric test at 5% a-level with false discovery rate correction for multiple comparisons by the method of Benjamini and Yekutieli. The alternative hypothesis of this test is that two sets of genes (set A from pathway
database and set B from experiments) have greater number of genes in common than two randomly selected gene sets with the same number of genes as in sets A and B. For example, consider that for some transcription factor there are 300 direct targets in the pathway database #1 and 700 in the experimentally derived list (gold-standard), and their intersection is 16 genes (Figure 2a). If we select on random from a total of
20,000 genes two sets with 300 and 700 genes each, their overlap would be greater or equal to 16 genes in 6.34% times. Thus, this overlap will not be statistically significant at 5% a-level (p = 0.0634). On the other hand, consider that for the pathway database #2, there are 30 direct targets of that transcription factor, and their intersection with the 700-gene gold-standard is only 6 genes. Even though the size of this intersection is rather small, it is unlikely to randomly select 30 genes (out of 20,000) with an overlap greater or equal to 6 genes with a 700-gene gold-standard (p = 0.0005, see Figure 2a). This overlap is statistically significant at 5% a-level.

We also calculate an enrichment fold change ratio (EFC) for every intersection between a gold-standard and a pathway database. For a given pair of a gold-standard and a pathway database, EFC is equal to the observed number of genes in their intersection, divided by the expected size of intersection under the null hypothesis (plus machine epsilon, to avoid division by zero). Notice however that larger values of EFC may correspond to databases that are highly incomplete and contain only a few relations. For example, consider that for some transcription factor there are 300 direct targets in the pathway database #1 and 50 in the experimentally derived list (gold-standard), and their intersection is 30 genes (Figure 2b). If we select on random from a total of 20,000 genes two sets with 300 and 50 genes each, their expected overlap under the null hypothesis will be equal to 0.75. Thus, the EFC ratio will be equal to 40 (= 30/0.75). On the other hand, consider that for the pathway database #2, there are 2 direct
targets of that transcription factor, and their intersection with the 50-gene gold-standard is only 1 gene. Even though the expected overlap under the null hypothesis will be equal to 0.005 and EFC equal to 200 (5 times bigger than for the database #1), the size of this intersection with the gold-standard is 30 times less than for database #1 (Figure 2b).

Figure 3 Comparison between different pathway databases and experimentally derived gold-standards for all considered transcription factors. Value in a given cell is a number of overlapping genes between a gold-standard and a pathway-derived gene set. Cells
are colored according to their values from white (low values) to red (high values). Underlined values in red represent statistically significant intersections. (not shown)

Figure 4 Summary of the pathway databases assessment. Green cells represent statistically significant intersections between experimentally derived gold-standards and transcriptional regulatory pathways. White cells denote results that are not statistically significant. Numbers are the enrichment fold change ratios (EFC) calculated for each intersection. (not shown)

At the core of this study was creation of gold-standards of transcriptional regulation in humans that can be compared with target genes reported in transcriptional regulatory pathways. We focused on seven well known transcription factors and obtained gold-standards

  • by integrating genome-wide transcription factor-DNA binding data (from ChIP-chip, ChIP-seq, or ChIP-PET platforms)
  • with functional gene expression microarray and RNA-seq data.

The latter data allows to survey changes in the transcriptomes on a genome-wide scale

  • after the inhibition or over-expression of the transcription factor in question.

However, change in the expression of a particular gene could be caused either by the direct effect of the removal or introduction of a given transcription factor, as well as by an indirect effect, through the change in expression level of some other gene(s). It is essential

  • to integrate data from these two sources to
  • obtain an accurate list of gene targets that are directly regulated by a transcription factor.

It is worth noting that tested pathway databases typically do not give distinction between cell-lines, experimental conditions, and other details relevant to experimental systems in which data were obtained. These databases in a sense propose a ‘universal’ list of transcriptional targets. However, it is known that

  • transcriptional regulation in a cell is dynamic and works differently for different systems and stimuli.

This accentuates the major limitation of pathway databases and emphasizes

  • importance of deriving a specific list of transcriptional targets for the current experimental system.

In this study we followed the latter approach by developing gold-standards for specific cell characterized biological systems and experimental conditions.

The approach used here  for building gold-standards of direct mechanistic knowledge has several limitations. (see article).  Nevertheless, our results suggest that multiple transcription factors can co-operate and control both physiological differentiation and malignant transformation, as demonstrated utilizing combinatorial gene-profiling for

  • NOTCH1, MYC and RELA targets.

These studies might lead us to multi-pathway gene expression “signatures”

  • essential for the prediction of genes that could be targeted in cancer treatments.

In agreement with this hypothesis, several of the genes identified in our analysis have been suggested to be putative therapeutic targets in leukemia, with either preclinical or clinical trials underway (CDK4, CDK6, GSK3b, MYC, LCK, NFkB2, BCL2L1, NOTCH1).

Single-molecule tracking in live cells reveals distinct target-search strategies of transcription factors in the nucleus

I Izeddin†, V Récamier†‡, L Bosanac, II Cissé, L Boudarene, et al.
1Functional Imaging of Transcription, Institut de Biologie de l’Ecole Normale Supérieure (IBENS), Inserm, and CNRS UMR; 2Laboratoire Kastler Brossel, CNRS UMR, Departement de Physique et Institut de Biologie
de l’Ecole Normale Supérieure (IBENS), Paris, Fr; 3Transcription Imaging Consortium, Janelia Farm Research Campus, Howard Hughes Medical Institute, Ashburn, US; + more.
Biophysics and structural biology | Cell biology eLife 2014;3:e02230. http://dx.doi.org:/10.7554/eLife.02230

Transcription factors are

  • proteins that control the expression of genes in the nucleus, and
  • they do this by binding to other proteins or DNA.

First, however, these regulatory proteins need to overcome the challenge of

  • finding their targets in the nucleus, which is crowded with other proteins and DNA.

Much research to date has focused on measuring how fast proteins can diffuse and spread out throughout the nucleus. However these measurements only make sense if these proteins have access to the same space within the nucleus.

Now, Izeddin, Récamier et al. have developed a new technique to track

  • single protein molecules in the nucleus of mammalian cells.

A transcription factor called c-Myc and another protein called P-TEFb

  • were tracked and while they diffused at similar rates,
  • they ‘explored’ the space inside the nucleus in very different ways.

Izeddin, Récamier et al. found that c-Myc explores the nucleus in a so-called ‘non-compact’ manner: this means that it

  • can move almost everywhere inside the nucleus, and has an equal chance
  • of reaching any target regardless of its position in this space.

P-TEFb, on the other hand, searches

  • the nucleus in a ‘compact’ way.

This means that it is constrained to follow a specific path

  • through the nucleus and is therefore guided to its potential targets.

Izeddin, Récamier et al. explain that

  • the different ‘search strategies’ used by these two proteins
  • influence how long it takes them to find their targets and
  • how far they can travel in a given time.

These findings, together with information about

  • where and when different proteins interact in the nucleus,

will be essential to understand how the organization of the genome within the nucleus

  • can control the expression of genes.

The next challenge will now be to

  • uncover what determines a
  • protein’s search strategy in the nucleus, as well as
  • the potential ways that this strategy might be regulated.

Mueller et al., 2010; Normanno et al., 2012). These transient interactions are essential to ensure a fine regulation of binding site occupancy—by competition or by altering the TF concentration—but must also be persistent enough to enable the assembly of multicomponent complexes (Dundr, 2002; Darzacq and Singer, 2008; Gorski et al., 2008; Cisse et al., 2013).
In parallel to the experimental evidence of the fast diffusive motion of nuclear factors, our understanding of the intranuclear space has evolved from a homogeneous environment to an organelle where spatial arrangement among genes and regulatory sequences play an important role in transcriptional control (Heard and Bickmore, 2007). The nucleus of eukaryotes displays a hierarchy of organized structures (Gibcus and Dekker, 2013) and is often referred to as a
crowded environment.
How crowding influences transport properties of macromolecules and organelles in the cell is a fundamental question in quantitative molecular biology. While a restriction of the available space for diffusion can slow down transport processes, it can also channel molecules towards their targets increasing their chance to meet interacting partners. A widespread observation in quantitative cell biology is that the diffusion of molecules is anomalous, often attributed to crowding in the nucleoplasm, cytoplasm, or in the membranes of the cell (Höfling and Franosch, 2013). An open debate remains on how to determine whether diffusion is anomalous or normal (Malchus and Weiss, 2009; Saxton, 2012), and the mechanisms behind anomalous diffusion (Saxton, 2007). The answer to these questions bears important consequences for the understanding of the biochemical reactions of the cell.
The problem of diffusing molecules in non-homogenous media has been investigated in different fields. Following the seminal work of de Gennes (1982a), (1982b) in polymer physics, the study of diffusivity of particles and their reactivity has been generalized to random or disordered media (Kopelman, 1986; Lindenberg et al., 1991). These works have set a framework to interpret the mobility of macromolecular complexes in the cell, and recently in terms of kinetics of biochemical reactions (Condamin et al., 2007). Experimental evidence has also been found, showing the influence
of the glass-like properties of the bacterial cytoplasm in the molecular dynamics of intracellular processes (Parry et al., 2014). These studies demonstrate that the geometry of the medium in which diffusion takes place has important repercussions for the search kinetics of molecules. The notion of compact and non-compact exploration was introduced by de Gennes (1982a) in the context of dense polymers and describes two fundamental types of diffusive behavior. While a non-compact explorer leaves a significant number of available sites unvisited, a compact explorer performs a redundant
exploration of the space. In chemistry, the influence of compactness is well established to describe dimensional effects on reaction rates (Kopelman, 1986).
In this study, we aim to elucidate the existence of different types of mobility of TFs in the eukaryotic nucleus, as well as the principles governing nuclear exploration of factors relevant to transcriptional control. To this end, we used single-molecule (SM) imaging to address the relationship between the nuclear geometry and the search dynamics of two nuclear factors having distinct functional roles: the proto-oncogene c-Myc and the positive transcription elongation factor (P-TEFb). c-Myc is a basic helix-loop-helix DNA-binding transcription factor that binds to E-Boxes; 18,000 E-boxes are found in the genome, and c-Myc affects the transcription of numerous genes (Gallant and Steiger, 2009).
Recently, c-Myc has been demonstrated to be a general transcriptional activator upregulating transcription of nearly all genes (Lin et al., 2012; Nie et al., 2012). P-TEFb is an essential actor in the transcription regulation driven by RNA Polymerase II. P-TEFb is a cyclin-dependent kinase, comprising a CDK9 and a Cyclin T subunit. It phosphorylates the elongation control factors SPT5 and NELF to allow productive elongation of class II gene transcription (Wada et al., 1998). The carboxy-terminal domain (CTD) of the catalytic subunit RPB1 of polymerase II is also a major target of P-TEFb (Zhou et al., 2012). c-Myc and P-TEFb are therefore two good examples of transcriptional regulators binding to numerous sites in the nucleus; the latter binds to the transcription machinery itself and the former directly to DNA.

Single particle tracking (SPT) constitutes a powerful method to probe the mobility of molecules in living cells (Lord et al., 2010). In the nucleus, SPT has been first employed to investigate the dynamics of mRNAs (Fusco et al., 2003; Shav-Tal et al., 2004) or for rheological measurements of the nucleoplasm using inert probes (Bancaud et al., 2009). Recently, the tracking of single nuclear factors has been facilitated by the advent of efficient in situ tagging methods such as Halo
tags (Mazza et al., 2012). An alternative approach takes advantage of photoconvertible tags (Lippincott-Schwartz and Patterson, 2009) and photoactivated localization microscopy (PALM) (Betzig et al., 2006; Hess et al., 2006). Single particle tracking PALM (sptPALM) was first used to achieve high-density diffusion maps of membrane proteins (Manley et al., 2008). However, spt-PALM experiments have typically been limited to proteins with slow mobility (Manley et al., 2008) or those that undergo restricted motions (Frost et al., 2010; English et al., 2011).

Recently, by inclusion of light-sheet illumination, it has been used to determine the binding characteristics of TFs to DNA (Gebhardt et al., 2013). In this study, we developed a new sptPALM procedure adapted for the recording of individual proteins rapidly diffusing in the nucleus of mammalian cells. We used the photoconvertible fluorophore Dendra2 (Gurskaya et al., 2006) and took advantage of tilted illumination (Tokunaga et al., 2008). A careful control of the photoconversion rate minimized the background signal due to out-of-focus activated molecules, and we could thus follow the motion of individual proteins freely diffusing within the nuclear volume. With this sptPALM technique, we recorded large data sets (on the order of 104 single translocations in a single imaging session), which were essential for a proper statistical analysis of the search dynamics.
We applied our technique to several nuclear proteins and found that diffusing factors do not sense a unique nucleoplasmic architecture: c-Myc and P-TEFb adopt different nuclear space-exploration strategies, which drastically change the way they reach their specific targets. The differences observed between the two factors were not due to their diffusive kinetic parameters but to the geometry of their exploration path. c-Myc and our control protein, ‘free’ Dendra2, showed free diffusion in a three-dimensional nuclear space. In contrast, P-TEFb explored the nuclear volume by sampling a space of reduced dimensionality, displaying characteristics of exploration constrained in fractal structures.
The role of the space-sampling mode in the search strategy has long been discussed from a theoretical point of view (de Gennes, 1982a; Kopelman, 1986; Lindenberg et al., 1991). Our experimental results support the notion that it could indeed be a key parameter for diffusion-limited chemical reactions in the closed environment of the nucleus (Bénichou et al., 2010). We discuss the implications of our observations in terms of gene expression control, and its relation to the spatial organization of genes within the nucleus.

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Complex Models of Signaling: Therapeutic Implications


Complex Models of Signaling: Therapeutic Implications

Curator: Larry H. Bernstein, MD, FCAP

Updated 6/24/2019

Fishy Business: Effect of Omega-3 Fatty Acids on Zinc Transporters and Free Zinc Availability in Human Neuronal Cells

Damitha De Mel and Cenk Suphioglu *

NeuroAllergy Research Laboratory (NARL), School of Life and Environmental Sciences, Faculty of Science, Engineering and Built Environment, Waurn Ponds, Victoria, Australia.

Nutrients 2014, 6, 3245-3258; http://dx.doi.org:/10.3390/nu6083245

Omega-3 (ω-3) fatty acids are one of the two main families of long chain polyunsaturated fatty acids (PUFA). The main omega-3 fatty acids in the mammalian body are

  • α-linolenic acid (ALA), docosahexaenoic acid (DHA) and eicosapentaenoic acid (EPA).

Central nervous tissues of vertebrates are characterized by a high concentration of omega-3 fatty acids. Moreover, in the human brain,

  • DHA is considered as the main structural omega-3 fatty acid, which comprises about 40% of the PUFAs in total.

DHA deficiency may be the cause of many disorders such as depression, inability to concentrate, excessive mood swings, anxiety, cardiovascular disease, type 2 diabetes, dry skin and so on.

On the other hand,

  • zinc is the most abundant trace metal in the human brain.

There are many scientific studies linking zinc, especially

  • excess amounts of free zinc, to cellular death.

Neurodegenerative diseases, such as Alzheimer’s disease, are characterized by altered zinc metabolism. Both animal model studies and human cell culture studies have shown a possible link between

  • omega-3 fatty acids, zinc transporter levels and
  • free zinc availability at cellular levels.

Many other studies have also suggested a possible

  • omega-3 and zinc effect on neurodegeneration and cellular death.

Therefore, in this review, we will examine

  • the effect of omega-3 fatty acids on zinc transporters and
  • the importance of free zinc for human neuronal cells.

Moreover, we will evaluate the collective understanding of

  • mechanism(s) for the interaction of these elements in neuronal research and their
  • significance for the diagnosis and treatment of neurodegeneration.

Epidemiological studies have linked high intake of fish and shellfish as part of the daily diet to

  • reduction of the incidence and/or severity of Alzheimer’s disease (AD) and senile mental decline in

Omega-3 fatty acids are one of the two main families of a broader group of fatty acids referred to as polyunsaturated fatty acids (PUFAs). The other main family of PUFAs encompasses the omega-6 fatty acids. In general, PUFAs are essential in many biochemical events, especially in early post-natal development processes such as

  • cellular differentiation,
  • photoreceptor membrane biogenesis and
  • active synaptogenesis.

Despite the significance of these

two families, mammals cannot synthesize PUFA de novo, so they must be ingested from dietary sources. Though belonging to the same family, both

  • omega-3 and omega-6 fatty acids are metabolically and functionally distinct and have
  • opposing physiological effects. In the human body,
  • high concentrations of omega-6 fatty acids are known to increase the formation of prostaglandins and
  • thereby increase inflammatory processes [10].

the reverse process can be seen with increased omega-3 fatty acids in the body.

Many other factors, such as

  1. thromboxane A2 (TXA2),
  2. leukotriene
  3. B4 (LTB4),
  4. IL-1,
  5. IL-6,
  6. tumor necrosis factor (TNF) and
  7. C-reactive protein,

which are implicated in various health conditions, have been shown to be increased with high omega-6 fatty acids but decreased with omega-3 fatty acids in the human body.

Dietary fatty acids have been identified as protective factors in coronary heart disease, and PUFA levels are known to play a critical role in

  • immune responses,
  • gene expression and
  • intercellular communications.

omega-3 fatty acids are known to be vital in

  • the prevention of fatal ventricular arrhythmias, and
  • are also known to reduce thrombus formation propensity by decreasing platelet aggregation, blood viscosity and fibrinogen levels

.Since omega-3 fatty acids are prevalent in the nervous system, it seems logical that a deficiency may result in neuronal problems, and this is indeed what has been identified and reported.

The main omega-3 fatty acids in the mammalian body are

  1. α-linolenic acid (ALA),
  2. docosahexenoic acid (DHA) and
  3. eicosapentaenoic acid (EPA).

In general, seafood is rich in omega-3 fatty acids, more specifically DHA and EPA (Table 1). Thus far, there are nine separate epidemiological studies that suggest a possible link between

  • increased fish consumption and reduced risk of AD
  • and eight out of ten studies have reported a link between higher blood omega-3 levels

Table 1. Total percentage of omega-3 fatty acids in common foods and supplements.

Food/Supplement EPA DHA ALA Total %
Fish
SalmonSardine

Anchovy

Halibut

Herring

Mackerel

Tuna

Fresh Bluefin

XX

X

X

X

X

X

X

XX

X

X

X

X

X

X

>50%>50%

>50%

>50%

>50%

>50%

>50%

>50%

Oils/Supplements
Fish oil capsulesCod liver oils

Salmon oil

Sardine oil

XX

X

X

XX

X

X

>50%>50%

>50%

>50%

Black currant oilCanola oil Mustard seed oils

Soybean oil

Walnut oil

Wheat germ oil

XX

X

X

X

X

10%–50%10%–50%

10%–50%

10%–50%

10%–50%

10%–50%

Seeds and other foods
Flaxseeds/LinseedsSpinach

Wheat germ Human milk

Peanut butter

Soybeans

Olive oil

Walnuts

XX

X

X

X

X

X

X

>50%>50%

10%–50%

10%–50%

<10%

<10%

<10%

<10%

 

Table adopted from Maclean C.H. et al. [18].

In another study conducted with individuals of 65 years of age or older (n = 6158), it was found that

  • only high fish consumption, but
  • not dietary omega-3 acid intake,
  • had a protective effect on cognitive decline

In 2005, based on a meta-analysis of the available epidemiology and preclinical studies, clinical trials were conducted to assess the effects of omega-3 fatty acids on cognitive protection. Four of the trials completed have shown

a protective effect of omega-3 fatty acids only among those with mild cognitive impairment conditions.

A  trial of subjects with mild memory complaints demonstrated

  • an improvement with 900 mg of DHA.

We review key findings on

  • the effect of the omega-3 fatty acid DHA on zinc transporters and the
  • importance of free zinc to human neuronal cells.

DHA is the most abundant fatty acid in neural membranes, imparting appropriate

  • fluidity and other properties,

and is thus considered as the most important fatty acid in neuronal studies. DHA is well conserved throughout the mammalian species despite their dietary differences. It is mainly concentrated

  • in membrane phospholipids at synapses and
  • in retinal photoreceptors and
  • also in the testis and sperm.

In adult rats’ brain, DHA comprises approximately

  • 17% of the total fatty acid weight, and
  • in the retina it is as high as 33%.

DHA is believed to have played a major role in the evolution of the modern human –

  • in particular the well-developed brain.

Premature babies fed on DHA-rich formula show improvements in vocabulary and motor performance.

Analysis of human cadaver brains have shown that

  • people with AD have less DHA in their frontal lobe
  • and hippocampus compared with unaffected individuals

Furthermore, studies in mice have increased support for the

  • protective role of omega-3 fatty acids.

Mice administrated with a dietary intake of DHA showed

  • an increase in DHA levels in the hippocampus.

Errors in memory were decreased in these mice and they demonstrated

  • reduced peroxide and free radical levels,
  • suggesting a role in antioxidant defense.

Another study conducted with a Tg2576 mouse model of AD demonstrated that dietary

  • DHA supplementation had a protective effect against reduction in
  • drebrin (actin associated protein), elevated oxidation, and to some extent, apoptosis via
  • decreased caspase activity.

 

Zinc

Zinc is a trace element, which is indispensable for life, and it is the second most abundant trace element in the body. It is known to be related to

  • growth,
  • development,
  • differentiation,
  • immune response,
  • receptor activity,
  • DNA synthesis,
  • gene expression,
  • neuro-transmission,
  • enzymatic catalysis,
  • hormonal storage and release,
  • tissue repair,
  • memory,
  • the visual process

and many other cellular functions. Moreover, the indispensability of zinc to the body can be discussed in many other aspects,  as

  • a component of over 300 different enzymes
  • an integral component of a metallothioneins
  • a gene regulatory protein.

Approximately 3% of all proteins contain

  • zinc binding motifs .

The broad biological functionality of zinc is thought to be due to its stable chemical and physical properties. Zinc is considered to have three different functions in enzymes;

  1. catalytic,
  2. coactive and

Indeed, it is the only metal found in all six different subclasses

of enzymes. The essential nature of zinc to the human body can be clearly displayed by studying the wide range of pathological effects of zinc deficiency. Anorexia, embryonic and post-natal growth retardation, alopecia, skin lesions, difficulties in wound healing, increased hemorrhage tendency and severe reproductive abnormalities, emotional instability, irritability and depression are just some of the detrimental effects of zinc deficiency.

Proper development and function of the central nervous system (CNS) is highly dependent on zinc levels. In the mammalian organs, zinc is mainly concentrated in the brain at around 150 μm. However, free zinc in the mammalian brain is calculated to be around 10 to 20 nm and the rest exists in either protein-, enzyme- or nucleotide bound form. The brain and zinc relationship is thought to be mediated

  • through glutamate receptors, and
  • it inhibits excitatory and inhibitory receptors.

Vesicular localization of zinc in pre-synaptic terminals is a characteristic feature of brain-localized zinc, and

  • its release is dependent on neural activity.

Retardation of the growth and development of CNS tissues have been linked to low zinc levels. Peripheral neuropathy, spina bifida, hydrocephalus, anencephalus, epilepsy and Pick’s disease have been linked to zinc deficiency. However, the body cannot tolerate excessive amounts of zinc.

The relationship between zinc and neurodegeneration, specifically AD, has been interpreted in several ways. One study has proposed that β-amyloid has a greater propensity to

  • form insoluble amyloid in the presence of
  • high physiological levels of zinc.

Insoluble amyloid is thought to

  • aggregate to form plaques,

which is a main pathological feature of AD. Further studies have shown that

  • chelation of zinc ions can deform and disaggregate plaques.

In AD, the most prominent injuries are found in

  • hippocampal pyramidal neurons, acetylcholine-containing neurons in the basal forebrain, and in
  • somatostatin-containing neurons in the forebrain.

All of these neurons are known to favor

  • rapid and direct entry of zinc in high concentration
  • leaving neurons frequently exposed to high dosages of zinc.

This is thought to promote neuronal cell damage through oxidative stress and mitochondrial dysfunction. Excessive levels of zinc are also capable of

  • inhibiting Ca2+ and Na+ voltage gated channels
  • and up-regulating the cellular levels of reactive oxygen species (ROS).

High levels of zinc are found in Alzheimer’s brains indicating a possible zinc related neurodegeneration. A study conducted with mouse neuronal cells has shown that even a 24-h exposure to high levels of zinc (40 μm) is sufficient to degenerate cells.

If the human diet is deficient in zinc, the body

  • efficiently conserves zinc at the tissue level by compensating other cellular mechanisms

to delay the dietary deficiency effects of zinc. These include reduction of cellular growth rate and zinc excretion levels, and

  • redistribution of available zinc to more zinc dependent cells or organs.

A novel method of measuring metallothionein (MT) levels was introduced as a biomarker for the

  • assessment of the zinc status of individuals and populations.

In humans, erythrocyte metallothionein (E-MT) levels may be considered as an indicator of zinc depletion and repletion, as E-MT levels are sensitive to dietary zinc intake. It should be noted here that MT plays an important role in zinc homeostasis by acting

  • as a target for zinc ion binding and thus
  • assisting in the trafficking of zinc ions through the cell,
  • which may be similar to that of zinc transporters

Zinc Transporters

Deficient or excess amounts of zinc in the body can be catastrophic to the integrity of cellular biochemical and biological systems. The gastrointestinal system controls the absorption, excretion and the distribution of zinc, although the hydrophilic and high-charge molecular characteristics of zinc are not favorable for passive diffusion across the cell membranes. Zinc movement is known to occur

  • via intermembrane proteins and zinc transporter (ZnT) proteins

These transporters are mainly categorized under two metal transporter families; Zip (ZRT, IRT like proteins) and CDF/ZnT (Cation Diffusion Facilitator), also known as SLC (Solute Linked Carrier) gene families: Zip (SLC-39) and ZnT (SLC-30). More than 20 zinc transporters have been identified and characterized over the last two decades (14 Zips and 8 ZnTs).

Members of the SLC39 family have been identified as the putative facilitators of zinc influx into the cytosol, either from the extracellular environment or from intracellular compartments (Figure 1).

The identification of this transporter family was a result of gene sequencing of known Zip1 protein transporters in plants, yeast and human cells. In contrast to the SLC39 family, the SLC30 family facilitates the opposite process, namely zinc efflux from the cytosol to the extracellular environment or into luminal compartments such as secretory granules, endosomes and synaptic vesicles; thus decreasing intracellular zinc availability (Figure 1). ZnT3 is the most important in the brain where

  • it is responsible for the transport of zinc into the synaptic vesicles of
  • glutamatergic neurons in the hippocampus and neocortex,

 

Figure 1. Putative cellular localization of some of the different human zinc transporters (i.e., Zip1- Zip4 and ZnT1- ZnT7). Arrows indicate the direction of zinc passage by the appropriate putative zinc transporters in a generalized human cell. Although there are fourteen Zips and eight ZnTs known so far, only the main zinc transporters are illustrated in this figure for clarity and brevity.

Figure 1: Subcellular localization and direction of transport of the zinc transporter families, ZnT and ZIP. Arrows show the direction of zinc mobilization for the ZnT (green) and ZIP (red) proteins. A net gain in cytosolic zinc is achieved by the transportation of zinc from the extracellular region and organelles such as the endoplasmic reticulum (ER) and Golgi apparatus by the ZIP transporters. Cytosolic zinc is mobilized into early secretory compartments such as the ER and Golgi apparatus by the ZnT transporters. Figures were produced using Servier Medical Art, http://www.servier.com/.   http://www.hindawi.com/journals/jnme/2012/173712.fig.001.jpg

zinc transporters

zinc transporters

 

 

Early zinc signaling (EZS) and late zinc signaling (LZS)

Early zinc signaling (EZS) and late zinc signaling (LZS)

http://www.hindawi.com/journals/jnme/2012/floats/173712/thumbnails/173712.fig.002_th.jpg

 

Figure 2: Early zinc signaling (EZS) and late zinc signaling (LZS). EZS involves transcription-independent mechanisms where an extracellular stimulus directly induces an increase in zinc levels within several minutes by releasing zinc from intracellular stores (e.g., endoplasmic reticulum). LSZ is induced several hours after an external stimulus and is dependent on transcriptional changes in zinc transporter expression. Components of this figure were produced using Servier Medical Art, http://www.servier.com/ and adapted from Fukada et al. [30].

 

DHA and Zinc Homeostasis

Many studies have identified possible associations between DHA levels, zinc homeostasis, neuroprotection and neurodegeneration. Dietary DHA deficiency resulted in

  • increased zinc levels in the hippocampus and
  • elevated expression of the putative zinc transporter, ZnT3, in the rat brain.

Altered zinc metabolism in neuronal cells has been linked to neurodegenerative conditions such as AD. A study conducted with transgenic mice has shown a significant link between ZnT3 transporter levels and cerebral amyloid plaque pathology. When the ZnT3 transporter was silenced in transgenic mice expressing cerebral amyloid plaque pathology,

  • a significant reduction in plaque load
  • and the presence of insoluble amyloid were observed.

In addition to the decrease in plaque load, ZnT3 silenced mice also exhibited a significant

  • reduction in free zinc availability in the hippocampus
  • and cerebral cortex.

Collectively, the findings from this study are very interesting and indicate a clear connection between

  • zinc availability and amyloid plaque formation,

thus indicating a possible link to AD.

DHA supplementation has also been reported to limit the following:

  1. amyloid presence,
  2. synaptic marker loss,
  3. hyper-phosphorylation of Tau,
  4. oxidative damage and
  5. cognitive deficits in transgenic mouse model of AD.

In addition, studies by Stoltenberg, Flinn and colleagues report on the modulation of zinc and the effect in transgenic mouse models of AD. Given that all of these are classic pathological features of AD, and considering the limiting nature of DHA in these processes, it can be argued that DHA is a key candidate in preventing or even curing this debilitating disease.

In order to better understand the possible links and pathways of zinc and DHA with neurodegeneration, we designed a study that incorporates all three of these aspects, to study their effects at the cellular level. In this study, we were able to demonstrate a possible link between omega-3 fatty acid (DHA) concentration, zinc availability and zinc transporter expression levels in cultured human neuronal cells.

When treated with DHA over 48 h, ZnT3 levels were markedly reduced in the human neuroblastoma M17 cell line. Moreover, in the same study, we were able to propose a possible

  • neuroprotective mechanism of DHA,

which we believe is exerted through

  • a reduction in cellular zinc levels (through altering zinc transporter expression levels)
  • that in turn inhibits apoptosis.

DHA supplemented M17 cells also showed a marked depletion of zinc uptake (up to 30%), and

  • free zinc levels in the cytosol were significantly low compared to the control

This reduction in free zinc availability was specific to DHA; cells treated with EPA had no significant change in free zinc levels (unpublished data). Moreover, DHA-repleted cells had

  • low levels of active caspase-3 and
  • high Bcl-2 levels compared to the control treatment.

These findings are consistent with previous published data and further strengthen the possible

  • correlation between zinc, DHA and neurodegeneration.

On the other hand, recent studies using ZnT3 knockout (ZnT3KO) mice have shown the importance of

  • ZnT3 in memory and AD pathology.

For example, Sindreu and colleagues have used ZnT3KO mice to establish the important role of

  • ZnT3 in zinc homeostasis that modulates presynaptic MAPK signaling
  • required for hippocampus-dependent memory

Results from these studies indicate a possible zinc-transporter-expression-level-dependent mechanism for DHA neuroprotection.

Collectively from these studies, the following possible mechanism can be proposed (Figure 2).

possible benefits of DHA in neuroprotection through reduction of ZnT3 transporter

possible benefits of DHA in neuroprotection through reduction of ZnT3 transporter

 

Figure 2. Proposed neuroprotection mechanism of docosahexaenoic acid (DHA) in reference to synaptic zinc. Schematic diagram showing possible benefits of DHA in neuroprotection through reduction of ZnT3 transporter expression levels in human neuronal cells, which results in a reduction of zinc flux and thus lowering zinc concentrations in neuronal synaptic vesicles, and therefore contributing to a lower incidence of neurodegenerative diseases (ND), such as Alzheimer’s disease (AD).

More recent data from our research group have also shown a link between the expression levels of histone H3 and H4 proteins in human neuronal cells in relation to DHA and zinc. Following DHA treatment, both H3 and H4 levels were up-regulated. In contrast, zinc treatment resulted in a down-regulation of histone levels. Both zinc and DHA have shown opposing effects on histone post-translational modifications, indicating a possible distinctive epigenetic pattern. Upon treatment with zinc, M17 cells displayed an increase in histone deacetylase (HDACs) and a reduction in histone acetylation. Conversely, with DHA treatment, HDAC levels were significantly reduced and the acetylation of histones was up-regulated. These findings also support a possible interaction between DHA and zinc availability.

Conclusions

It is possible to safely claim that there is more than one potential pathway by which DHA and zinc interact at a cellular level, at least in cultured human neuronal cells. Significance and importance of both DHA and zinc in neuronal survival is attested by the presence of these multiple mechanisms.
Most of these reported studies were conducted using human neuroblastoma cells, or similar cell types, due to the lack of live mature human neuronal cells. Thus, the results may differ from results achieved under actual human physiological conditions due to the structural and functional differences between these cells and mature human neurons. Therefore, an alternative approach that can mimic the human neuronal cells more effectively would be advantageous.

Sphingosine-1-phosphate signaling as a therapeutic target          

E Giannoudaki, DJ Swan, JA Kirby, S Ali

Applied Immunobiology and Transplantation Research Group, Institute of Cellular Medicine, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, UK

Cell Health and Cytoskeleton 2012; 4: 63–72

S1P is a 379Da member of the lysophospholipid family. It is the direct metabolite of sphingosine through the action of two sphingosine kinases, SphK1 and SphK2. The main metabolic pathway starts with the hydrolysis of sphingomyelin, a membrane sphingolipid, into ceramide by the enzyme sphingomyelinase and the subsequent production of sphingosine by ceramidase (Figure 1). Ceramide can also be produced de novo in the endoplasmic reticulum (ER) from serine and palmitoyl coenzyme A through multiple intermediates. S1P production is regulated by various S1P-specific and general lipid phosphatases, as well as S1P lyase, which irreversibly degrades S1P into phosphoethanolamine and hexadecanal. The balance between intracellular S1P and its metabolite ceramide can determine cellular fate. Ceramide promotes apoptosis, while S1P suppresses cell death and promotes cell survival. This creates an S1P ceramide “rheostat” inside the cells. S1P lyase expression in tissue is higher than it is in erythrocytes and platelets, the main “suppliers” of S1P in blood. This causes a tissue–blood gradient of S1P, which is important in many S1P-mediated responses, like the lymphocyte egress from lymphoid organs.

S1P signaling overview

S1P is produced inside cells; however, it can also be found extracellularly, in a variety of different tissues. It is abundant in the blood, at concentrations of 0.4–1.5 μM, where it is mainly secreted by erythrocytes and platelets. Blood S1P can be found separately, but mainly it exists in complexes with high-density lipoprotein (HDL) (∼60%).  Many of the cardioprotective effects of HDL are hypothesized to involve S1P. Before 1996, S1P was thought to act mainly intracellularly as a second messenger. However, the identification of several GPCRs that bind S1P led to the initiation of many studies on

  • extracellular S1P signaling through those receptors.

There are five receptors that have been identified currently. These can be coupled with different G-proteins. Assuming that each receptor coupling with a G protein has a slightly different function, one can recognize the complexity of S1P receptor signaling.

S1P as a second messenger

S1P is involved in many cellular processes through its GPCR signaling; studies demonstrate that S1P also acts at an intracellular level. Intracellular S1P plays a role in maintaining the balance of cell survival signal toward apoptotic signals, creating a

  • cell “rheostat” between S1P and its precursor ceramide.

Important evidence that S1P can act intracellularly as a second messenger came from yeast (Saccharomyces cerevisiae) and plant (Arabidopsis thaliana) cells. Yeast cells do not express any S1P receptors, although they can be affected by S1P during heat-shock responses. Similarly, Arabidopsis has only one GPCR-like protein, termed “GCR1,” which does not bind S1P, although S1P regulates stomata closure during drought.

Sphingosine-1-phosphate

Sphingosine-1-phosphate

In mammals, the sphingosine kinases have been found to localize in different cell compartments, being responsible for the accumulation of S1P in those compartments to give intracellular signals. In mitochondria, for instance,

  • S1P was recently found to interact with prohibitin 2,

a conserved protein that maintains mitochondria assembly and function. According to the same study,

SphK2 is the major producer of S1P in mitochondria and the knockout of its gene can cause

  • disruption of mitochondrial respiration and cytochrome c oxidase function.

SphK2 is also present in the nucleus of many cells and has been implicated to cause cell cycle arrest, and it causes S1P accumulation in the nucleus. It seems that nuclear S1P is affiliated with the histone deacetylases HDAC1 and HDAC2,

  • inhibiting their activity, thus having an indirect effect in epigenetic regulation of gene expression.

In the ER, SphK2 has been identified to translocate during stress, and promote apoptosis. It seems that S1P has specific targets in the ER that cause apoptosis, probably through calcium mobilization signals.

Sphingosine 1-phosphate (S1P) is a small bioactive lipid molecule that is involved in several processes both intracellularly and extracellularly. It acts intracellularly

  • to promote the survival and growth of the cell,

through its interaction with molecules in different compartments of the cell.

It can also exist at high concentrations extracellularly, in the blood plasma and lymph. This causes an S1P gradient important for cell migration. S1P signals through five G protein-coupled receptors, S1PR1–S1PR5, whose expression varies in different types of cells and tissue. S1P signaling can be involved in physiological and pathophysiological conditions of the cardiovascular, nervous, and immune systems and diseases such as ischemia/reperfusion injury, autoimmunity, and cancer. In this review, we discuss how it can be used to discover novel therapeutic targets.

The involvement of S1P signaling in disease

In a mouse model of myocardial ischemia-reperfusion injury (IRI), S1P and its carrier, HDL, can help protect myocardial tissue and decrease the infarct size. It seems they reduce cardiomyocyte apoptosis and neutrophil recruitment to the ischemic tissue and may decrease leukocyte adhesion to the endothelium. This effect appears to be S1PR3 mediated, since in S1PR3 knockout mice it is alleviated.

Ischemia activates SphK1, which is then translocated to the plasma membrane. This leads to an increase of intracellular S1P, helping to promote cardiomyocyte survival against apoptosis, induced by ceramide. SphK1 knockout mice cannot be preconditioned against IRI, whereas SphK1 gene induction in the heart protects it from IRI. Interestingly, a recent study shows SphK2 may also play a role, since its knockout reduces the cardioprotective effects of preconditioning. Further, administration of S1P or sphingosine during reperfusion results in better recovery and attenuation of damage to cardiomyocytes. As with preconditioning, SphK1 deficiency also affects post-conditioning of mouse hearts after ischemia reperfusion (IR).

S1P does not only protect the heart from IRI. During intestinal IR, multiple organs can be damaged, including the lungs. S1P treatment of mice during intestinal IR seems to have a protective effect on lung injury, probably due to suppression of iNOS-induced nitric oxide generation. In renal IRI, SphK1 seems to be important, since its deficiency increased the damage in kidney tissue, whereas the lentiviral overexpression of the SphK1 gene protected from injury. Another study suggests that, after IRI, apoptotic renal cells release S1P, which recruits macrophages through S1PR3 activation and might contribute to kidney regeneration and restoration of renal epithelium. However, SphK2 is negatively implicated in hepatic IRI, its inhibition helping protect hepatocytes and restoring mitochondrial function.

Further studies are implicating S1P signaling or sphingosine kinases in several kinds of cancer as well as autoimmune diseases.

Figure 2 FTY720-P causes retention of T cells in the lymph nodes.

Notes: C57BL/6 mice were injected with BALB/c splenocytes in the footpad to create an allogenic response then treated with FTY720-P or vehicle every day on days 2 to 5. On day 6, the popliteal lymph nodes were removed. Popliteal node-derived cells were mixed with BALB/c splenocytes in interferon gamma (IFN-γ) cultured enzyme-linked immunosorbent spot reactions. Bars represent the mean number of IFN-γ spot-forming cells per 1000 popliteal node-derived cells, from six mice treated with vehicle and seven with FTY720-P. **P , 0.01.  (not shown)

Fingolimod (INN, trade name Gilenya, Novartis) is an immunomodulating drug, approved for treating multiple sclerosis. It has reduced the rate of relapses in relapsing-remitting multiple sclerosis by over half. Fingolimod is a sphingosine-1-phosphate receptor modulator, which sequesters lymphocytes in lymph nodes, preventing them from contributing to an autoimmune reaction.

Fingolimod3Dan

Fingolimod3Dan

 

http://upload.wikimedia.org/wikipedia/commons/thumb/4/48/Fingolimod3Dan.gif/200px-Fingolimod3Dan.gif

The S1P antagonist FTY720 has been approved by the US Food and Drug Administration to be used as a drug against multiple sclerosis (MS). FTY720 is in fact a prodrug, since it is phosphorylated in vivo by SphK2 into FTY720-P, an S1P structural analog, which can activate S1PR1, 3, 4, and 5. FTY720-P binding to S1PR1 causes internalization of the receptor, as does S1P – but instead of recycling it back to the cell surface, it promotes its ubiquitination and degradation at the proteasome. This has a direct effect on lymphocyte trafficking through the lymph nodes, since it relies on S1PR1 signaling and S1P gradient (Figure 2). In MS, it stops migrating lymphocytes into the brain, but it may also have direct effects on the CNS through neuroprotection. FTY720 can pass the blood–brain barrier and it could be phosphorylated by local sphingosine kinases to act through S1PR1 and S1PR3 receptors that are mainly expressed in the CNS. In MS lesions, astrocytes upregulate those two receptors and it has been shown that FTY720-P treatment in vitro inhibits astrocyte production of inflammatory cytokines. A recent study confirms the importance of S1PR3 signaling on activated astrocytes, as well as SphK1, that are upregulated and promote the secretion of the potentially neuroprotective cytokine CXCL-1.

There are several studies implicating the intracellular S1P ceramide rheostat to cancer cell survival or apoptosis and resistance to chemotherapy or irradiation in vitro. Studies with SphK1 inhibition in pancreatic, prostate cancers, and leukemia, show increased ceramide/S1P ratio and induction of apoptosis. However, S1P receptor signaling plays conflicting roles in cancer cell migration and metastasis.

Modulation of S1P signaling: therapeutic potential

S1P signaling can be involved in many pathophysiological conditions. This means that we could look for therapeutic targets in all the molecules taking part in S1P signaling and production, most importantly the S1P receptors and the sphingosine kinases. S1P agonists and antagonists could also be used to modulate S1P signaling during pathological conditions.

S1P can have direct effects on the cardiovascular system. During IRI, intracellular S1P can protect the cardiomyocytes and promote their survival. Pre- or post-conditioning of the heart with S1P could be used as a treatment, but upregulation of sphingosine kinases could also increase intracellular S1P bioavailability. S1P could also have effects on endothelial cells and neutrophil trafficking. Vascular endothelial cells mainly express S1PR1 and S1PR3; only a few types express S1PR2. S1PR1 and S1PR3 activation on these cells has been shown to enhance their chemotactic migration, probably through direct phosphorylation of S1PR1 by Akt, in a phosphatidylinositol 3-kinase and Rac1-dependent signaling pathway. Moreover, it stimulates endothelial cell proliferation through an ERK pathway. S1PR2 activation, however, inhibits endothelial cell migration, morphogenesis, and angiogenesis, most likely through Rho-dependent inhibition of Rac signaling pathway, as Inoki et al showed in mouse cells with the use of S1PR1 and S1PR3 specific antagonists.

Regarding permeability of the vascular endothelium and endothelial barrier integrity, S1P receptors can have different effects. S1PR1 activation enhances endothelial barrier integrity by stimulation of cellular adhesion and upregulation of adhesion molecules. However, S1PR2 and S1PR3 have been shown to have barrier-disrupting effects in vitro, and vascular permeability increasing effects in vivo. All the effects S1P can have on vascular endothelium and smooth muscle cells suggest that activation of S1PR2, not S1PR1 and S1PR3, signaling, perhaps with the use of S1PR2 specific agonists, could be used therapeutically to inhibit angiogenesis and disrupt vasculature, suppressing tumor growth and progression.

An important aspect of S1P signaling that is being already therapeutically targeted, but could be further investigated, is immune cell trafficking. Attempts have already been made to regulate lymphocyte cell migration with the use of the drug FTY720, whose phosphorylated form can inhibit the cells S1PR1-dependent egress from the lymph nodes, causing lymphopenia. FTY720 is used as an immunosuppressant for MS but is also being investigated for other autoimmune conditions and for transplantation. Unfortunately, Phase II and III clinical trials for the prevention of kidney graft rejection have not shown an advantage over standard therapies. Moreover, FTY720 can have some adverse cardiac effects, such as bradycardia. However, there are other S1PR1 antagonists that could be considered instead, including KRP-203, AUY954, and SEW2871. KRP-203 in particular has been shown to prolong rat skin and heart allograft survival and attenuate chronic rejection without causing bradycardia, especially when combined with other immunomodulators.

There are studies that argue S1P pretreatment has a negative effect on neutrophil chemotaxis toward the chemokine CXCL-8 (interleukin-8) or the potent chemoattractant formyl-methionyl-leucyl-phenylalanine. S1P pretreatment might also inhibit trans-endothelial migration of neutrophils, without affecting their adhesion to the endothelium. S1P effects on neutrophil migration toward CXCL-8 might be the result of S1PRs cross-linking with the CXCL-8 receptors in neutrophils, CXCR-1 and CXCR-2. Indeed, there is evidence suggesting S1PR4 and S1PR3 form heterodimers with CXCR-1 in neutrophils. Another indication that S1P plays a role in neutrophil trafficking is a recent paper on S1P lyase deficiency, a deficiency that impairs neutrophil migration from blood to tissue in knockout mice.

S1P lyase and S1PRs in neutrophils may be new therapeutic targets against IRI and inflammatory conditions in general. Consistent with these results, another study has shown that inhibition of S1P lyase can have a protective effect on the heart after IRI and this effect is alleviated when pretreated with an S1PR1 and S1PR3 antagonist. Inhibition was achieved with a US Food and Drug Administration-approved food additive, 2-acetyl-4-tetrahydroxybutylimidazole, providing a possible new drug perspective. Another S1P lyase inhibitor, LX2931, a synthetic analog of 2-acetyl-4-tetrahydroxybutylimidazole, has been shown to cause peripheral lymphopenia when administered in mice, providing a potential treatment for autoimmune diseases and prevention of graft rejection in transplantation. This molecule is currently under Phase II clinical trials in rheumatoid arthritis patients.

S1P signaling research has the potential to discover novel therapeutic targets. S1P signaling is involved in many physiological and pathological processes. However, the complexity of S1P signaling makes it necessary to consider every possible pathway, either through its GPCRs, or intracellularly, with S1P as a second messenger. Where the activation of one S1P receptor may lead to the desired outcome, the simultaneous activation of another S1P receptor may lead to the opposite outcome. Thus, if we are to target a specific signaling pathway, we might need specific agonists for S1P receptors to activate one S1P receptor pathway, while, at the same time, we might need to inhibit another through S1P receptor antagonists.

Evidence of sphingolipid signaling in cancer

Biologically active lipids are important cellular signaling molecules and play a role in cell communication and cancer cell proliferation, and cancer stem cell biology.  A recent study in ovarian cancer cell lines shows that exogenous sphingosine 1 phosphate (SIP1) or overexpression of the sphingosine kinase (SPHK1) increases ovarian cancer cell proliferation, invasion and contributes to cancer stem cell like phenotype.  The diabetes drug metformin was shown to be an inhibitor of SPHK1 and reduce ovarian cancer tumor growth.

 2019 Apr;17(4):870-881. doi: 10.1158/1541-7786.MCR-18-0409. Epub 2019 Jan 17.

SPHK1 Is a Novel Target of Metformin in Ovarian Cancer.

Abstract

The role of phospholipid signaling in ovarian cancer is poorly understood. Sphingosine-1-phosphate (S1P) is a bioactive metabolite of sphingosine that has been associated with tumor progression through enhanced cell proliferation and motility. Similarly, sphingosine kinases (SPHK), which catalyze the formation of S1P and thus regulate the sphingolipid rheostat, have been reported to promote tumor growth in a variety of cancers. The findings reported here show that exogenous S1P or overexpression of SPHK1 increased proliferation, migration, invasion, and stem-like phenotypes in ovarian cancer cell lines. Likewise, overexpression of SPHK1 markedly enhanced tumor growth in a xenograft model of ovarian cancer, which was associated with elevation of key markers of proliferation and stemness. The diabetes drug, metformin, has been shown to have anticancer effects. Here, we found that ovarian cancer patients taking metformin had significantly reduced serum S1P levels, a finding that was recapitulated when ovarian cancer cells were treated with metformin and analyzed by lipidomics. These findings suggested that in cancer the sphingolipid rheostat may be a novel metabolic target of metformin. In support of this, metformin blocked hypoxia-induced SPHK1, which was associated with inhibited nuclear translocation and transcriptional activity of hypoxia-inducible factors (HIF1α and HIF2α). Further, ovarian cancer cells with high SPHK1 were found to be highly sensitive to the cytotoxic effects of metformin, whereas ovarian cancer cells with low SPHK1 were resistant. Together, the findings reported here show that hypoxia-induced SPHK1 expression and downstream S1P signaling promote ovarian cancer progression and that tumors with high expression of SPHK1 or S1P levels might have increased sensitivity to the cytotoxic effects of metformin. IMPLICATIONS: Metformin targets sphingolipid metabolism through inhibiting SPHK1, thereby impeding ovarian cancer cell migration, proliferation, and self-renewal.

Nrf2:INrf2(Keap1) Signaling in Oxidative Stress

James W. Kaspar, Suresh K. Niture, and Anil K. Jaiswal*

Department of Pharmacology, University of Maryland School of Medicine, Baltimore, MD

Free Radic Biol Med. 2009 Nov 1; 47(9): 1304–1309. http://dx.doi.org:/10.1016/j.freeradbiomed.2009.07.035

Nrf2:INrf2(Keap1) are cellular sensors of chemical and radiation induced oxidative and electrophilic stress. Nrf2 is a nuclear transcription factor that

  • controls the expression and coordinated induction of a battery of defensive genes encoding detoxifying enzymes and antioxidant proteins.

This is a mechanism of critical importance for cellular protection and cell survival. Nrf2 is retained in the cytoplasm by an inhibitor INrf2. INrf2 functions as an adapter for

  • Cul3/Rbx1 mediated degradation of Nrf2.
  • In response to oxidative/electrophilic stress,
  • Nrf2 is switched on and then off by distinct

early and delayed mechanisms.

Oxidative/electrophilic modification of INrf2cysteine151 and/or PKC phosphorylation of Nrf2serine40 results in the escape or release of Nrf2 from INrf2. Nrf2 is stabilized and translocates to the nucleus, forms heterodimers with unknown proteins, and binds antioxidant response element (ARE) that leads to coordinated activation of gene expression. It takes less than fifteen minutes from the time of exposure

  • to switch on nuclear import of Nrf2.

This is followed by activation of a delayed mechanism that controls

  • switching off of Nrf2 activation of gene expression.

GSK3β phosphorylates Fyn at unknown threonine residue(s) leading to

  • nuclear localization of Fyn.

Fyn phosphorylates Nrf2tyrosine568 resulting in

  • nuclear export of Nrf2,
  • binding with INrf2 and
  • degradation of Nrf2.

The switching on and off of Nrf2 protects cells against free radical damage, prevents apoptosis and promotes cell survival.

NPRA-mediated suppression of AngII-induced ROS production contributes to the antiproliferative effects of B-type natriuretic peptide in VSMC

Pan Gao, De-Hui Qian, Wei Li,  Lan Huang
Mol Cell Biochem (2009) 324:165–172

http://dx.doi.org/10.1007/s11010-008-9995-y

Excessive proliferation of vascular smooth cells (VSMCs) plays a critical role in the pathogenesis of diverse vascular disorders, and inhibition of VSMCs proliferation has been proved to be beneficial to these diseases.

In this study, we investigated the antiproliferative effect of

  • B-type natriuretic peptide (BNP), a natriuretic peptide with potent antioxidant capacity,

on rat aortic VSMCs, and the possible mechanisms involved. The results indicate that

  • BNP potently inhibited Angiotensin II (AngII)-induced VSMCs proliferation,

as evaluated by [3H]-thymidine incorporation assay. Consistently, BNP significantly decreased

  • AngII-induced intracellular reactive oxygen species (ROS)
  • and NAD(P)H oxidase activity.

8-Br-cGMP, a cGMP analog,

  • mimicked these effects.

To confirm its mechanism, siRNA of natriuretic peptide receptor-A(NRPA) strategy technology was used

  • to block cGMP production in VSMCs, and
  • siNPRA attenuated the inhibitory effects of BNP in VSMCs.

Taken together, these results indicate that

  • BNP was capable of inhibiting VSMCs proliferation by
  • NPRA/cGMP pathway,

which might be associated with

  • the suppression of ROS production.

These results might be related, at least partly, to the anti-oxidant property of BNP.

Cellular prion protein is required for neuritogenesis: fine-tuning of multiple signaling pathways involved in focal adhesions and actin cytoskeleton dynamics

A Alleaume-Butaux, C Dakowski, M Pietri, S Mouillet-Richard, Jean-Marie Launay, O Kellermann, B Schneider

1INSERM, UMR-S 747, 2Paris Descartes University, Sorbonne Paris, 3Public Hospital of Paris, Department of Biochemistry, Paris, France; 4Pharma Research Department, Hoffmann La Roche Ltd, Basel, Switzerland

Cell Health and Cytoskeleton 2013; 5: 1–12

Neuritogenesis is a complex morphological phenomena accompanying neuronal differentiation. Neuritogenesis relies on the initial breakage of the rather spherical symmetry of neuroblasts and the formation of buds emerging from the postmitotic neuronal soma. Buds then evolve into neurites, which later convert into an axon or dendrites. At the distal tip of neurites, the growth cone integrates extracellular signals and guides the neurite to its target. The acquisition of neuronal polarity depends on deep modifications of the neuroblast cytoskeleton characterized by the remodeling and activation of focal adhesions (FAs) and localized destabilization of the actin network in the neuronal sphere.Actin instability in unpolarized neurons allows neurite sprouting, ie, the protrusion of microtubules, and subsequent neurite outgrowth. Once the neurite is formed, actin microfilaments recover their stability and exert a sheathed action on neurites, a dynamic process necessary for the maintenance and integrity of neurites.

A combination of extrinsic and intrinsic cues pilots the architectural and functional changes in FAs and the actin network along neuritogenesis. This process includes neurotrophic factors (nerve growth factor, brain derived neurotrophic factor, neurotrophin, ciliary neurotrophic factor, glial derived neurotrophic factor) and their receptors, protein components of the extracellular matrix (ECM) (laminin, vitronectin, fibronectin), plasma membrane integrins and neural cell adhesion molecules (NCAM), and intracellular molecular protagonists such as small G proteins (RhoA, Rac, Cdc42) and their downstream targets.

Neuritogenesis is a dynamic phenomenon associated with neuronal differentiation that allows a rather spherical neuronal stem cell to develop dendrites and axon, a prerequisite for the integration and transmission of signals. The acquisition of neuronal polarity occurs in three steps:

(1) neurite sprouting, which consists of the formation of buds emerging from the postmitotic neuronal soma;

(2) neurite outgrowth, which represents the conversion of buds into neurites, their elongation and evolution into axon or dendrites; and

(3) the stability and plasticity of neuronal polarity.

In neuronal stem cells, remodeling and activation of focal adhesions (FAs) associated with deep modifications of the actin cytoskeleton is a prerequisite for neurite sprouting and subsequent neurite outgrowth. A multiple set of growth factors and interactors located in the extracellular matrix and the plasma membrane orchestrate neuritogenesis

  • by acting on intracellular signaling effectors,
  • notably small G proteins such as RhoA, Rac, and Cdc42,
  • which are involved in actin turnover and the dynamics of FAs.

The cellular prion protein (PrPC), a glycosylphosphatidylinositol

  • (GPI)-anchored membrane protein

mainly known for its role in a group of fatal

  • neurodegenerative diseases,

has emerged as a central player in neuritogenesis.

Here, we review the contribution of PrPC to neuronal polarization and detail the current knowledge on the

  • signaling pathways fine-tuned by PrPC
  • to promote neurite sprouting, outgrowth, and maintenance.

We emphasize that PrPC-dependent neurite sprouting is a process in which PrPC

  • governs the dynamics of FAs and the actin cytoskeleton
  • via β1 integrin signaling.

The presence of PrPC is necessary to render neuronal stem cells

  • competent to respond to neuronal inducers and
  • to develop neurites.

In differentiating neurons, PrPC exerts

  • a facilitator role towards neurite elongation.

This function relies on the interaction of PrPC with a set of diverse partners such as

  1. elements of the extracellular matrix,
  2. plasma membrane receptors,
  3. adhesion molecules, and
  4. soluble factors that control actin cytoskeleton turnover through Rho-GTPase signaling.

Once neurons have reached their terminal stage of differentiation and acquired their polarized morphology, PrPC also

  • takes part in the maintenance of neurites.

By acting on tissue nonspecific alkaline phosphatase, or

  • matrix metalloproteinase type 9,

PrPC stabilizes interactions between

  • neurites and the extracellular matrix.

Keywords: prion, neuronal differentiation

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