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Posts Tagged ‘Messenger RNA’

Proteomics, Metabolomics, Signaling Pathways, and Cell Regulation: a Compilation of Articles in the Journal http://pharmaceuticalintelligence.com

Compilation of References by Leaders in Pharmaceutical Business Intelligence in the Journal http://pharmaceuticalintelligence.com about
Proteomics, Metabolomics, Signaling Pathways, and Cell Regulation

Curator: Larry H Bernstein, MD, FCAP

Proteomics

  1. The Human Proteome Map Completed

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

http://pharmaceuticalintelligence.com/2014/08/28/the-human-proteome-map-completed/

  1. Proteomics – The Pathway to Understanding and Decision-making in Medicine

Author and Curator, Larry H Bernstein, MD, FCAP

http://pharmaceuticalintelligence.com/2014/06/24/proteomics-the-pathway-to-
understanding-and-decision-making-in-medicine/

3. Advances in Separations Technology for the “OMICs” and Clarification of Therapeutic Targets

Author and Curator, Larry H Bernstein, MD, FCAP

http://pharmaceuticalintelligence.com/2012/10/22/advances-in-separations-technology-for-the-omics-and-clarification-         of-therapeutic-targets/

  1. Expanding the Genetic Alphabet and Linking the Genome to the Metabolome

Author and Curator, Larry H Bernstein, MD, FCAP

http://pharmaceuticalintelligence.com/2012/09/24/expanding-the-genetic-alphabet-and-linking-the-genome-to-the-                metabolome/

5. Genomics, Proteomics and standards

Larry H Bernstein, MD, FCAP, Author and Curator

http://pharmaceuticalintelligence.com/2014/07/06/genomics-proteomics-and-standards/

6. Proteins and cellular adaptation to stress

Larry H Bernstein, MD, FCAP, Author and Curator

http://pharmaceuticalintelligence.com/2014/07/08/proteins-and-cellular-adaptation-to-stress/

 

Metabolomics

  1. Extracellular evaluation of intracellular flux in yeast cells

Larry H. Bernstein, MD, FCAP, Reviewer and Curator

http://pharmaceuticalintelligence.com/2014/08/25/extracellular-evaluation-of-intracellular-flux-in-yeast-cells/

  1. Metabolomic analysis of two leukemia cell lines. I.

Larry H. Bernstein, MD, FCAP, Reviewer and Curator

http://pharmaceuticalintelligence.com/2014/08/23/metabolomic-analysis-of-two-leukemia-cell-lines-_i/

  1. Metabolomic analysis of two leukemia cell lines. II.

Larry H. Bernstein, MD, FCAP, Reviewer and Curator

http://pharmaceuticalintelligence.com/2014/08/24/metabolomic-analysis-of-two-leukemia-cell-lines-ii/

  1. Metabolomics, Metabonomics and Functional Nutrition: the next step in nutritional metabolism and biotherapeutics

Reviewer and Curator, Larry H. Bernstein, MD, FCAP

http://pharmaceuticalintelligence.com/2014/08/22/metabolomics-metabonomics-and-functional-nutrition-the-next-step-          in-nutritional-metabolism-and-biotherapeutics/

  1. Buffering of genetic modules involved in tricarboxylic acid cycle metabolism provides homeomeostatic regulation

Larry H. Bernstein, MD, FCAP, Reviewer and curator

http://pharmaceuticalintelligence.com/2014/08/27/buffering-of-genetic-modules-involved-in-tricarboxylic-acid-cycle-              metabolism-provides-homeomeostatic-regulation/

Metabolic Pathways

  1. Pentose Shunt, Electron Transfer, Galactose, more Lipids in brief

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

http://pharmaceuticalintelligence.com/2014/08/21/pentose-shunt-electron-transfer-galactose-more-lipids-in-brief/

  1. Mitochondria: More than just the “powerhouse of the cell”

Ritu Saxena, PhD

http://pharmaceuticalintelligence.com/2012/07/09/mitochondria-more-than-just-the-powerhouse-of-the-cell/

  1. Mitochondrial fission and fusion: potential therapeutic targets?

Ritu saxena

http://pharmaceuticalintelligence.com/2012/10/31/mitochondrial-fission-and-fusion-potential-therapeutic-target/

4.  Mitochondrial mutation analysis might be “1-step” away

Ritu Saxena

http://pharmaceuticalintelligence.com/2012/08/14/mitochondrial-mutation-analysis-might-be-1-step-away/

  1. Selected References to Signaling and Metabolic Pathways in PharmaceuticalIntelligence.com

Curator: Larry H. Bernstein, MD, FCAP

http://pharmaceuticalintelligence.com/2014/08/14/selected-references-to-signaling-and-metabolic-pathways-in-                     leaders-in-pharmaceutical-intelligence/

  1. Metabolic drivers in aggressive brain tumors

Prabodh Kandal, PhD

http://pharmaceuticalintelligence.com/2012/11/11/metabolic-drivers-in-aggressive-brain-tumors/

  1. Metabolite Identification Combining Genetic and Metabolic Information: Genetic association links unknown metabolites to functionally related genes

Writer and Curator, Aviva Lev-Ari, PhD, RD

http://pharmaceuticalintelligence.com/2012/10/22/metabolite-identification-combining-genetic-and-metabolic-                        information-genetic-association-links-unknown-metabolites-to-functionally-related-genes/

  1. Mitochondria: Origin from oxygen free environment, role in aerobic glycolysis, metabolic adaptation

Larry H Bernstein, MD, FCAP, author and curator

http://pharmaceuticalintelligence.com/2012/09/26/mitochondria-origin-from-oxygen-free-environment-role-in-aerobic-            glycolysis-metabolic-adaptation/

  1. Therapeutic Targets for Diabetes and Related Metabolic Disorders

Reporter, Aviva Lev-Ari, PhD, RD

http://pharmaceuticalintelligence.com/2012/08/20/therapeutic-targets-for-diabetes-and-related-metabolic-disorders/

10.  Buffering of genetic modules involved in tricarboxylic acid cycle metabolism provides homeomeostatic regulation

Larry H. Bernstein, MD, FCAP, Reviewer and curator

http://pharmaceuticalintelligence.com/2014/08/27/buffering-of-genetic-modules-involved-in-tricarboxylic-acid-cycle-              metabolism-provides-homeomeostatic-regulation/

11. The multi-step transfer of phosphate bond and hydrogen exchange energy

Larry H. Bernstein, MD, FCAP, Curator:

http://pharmaceuticalintelligence.com/2014/08/19/the-multi-step-transfer-of-phosphate-bond-and-hydrogen-                          exchange-energy/

12. Studies of Respiration Lead to Acetyl CoA

http://pharmaceuticalintelligence.com/2014/08/18/studies-of-respiration-lead-to-acetyl-coa/

13. Lipid Metabolism

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

http://pharmaceuticalintelligence.com/2014/08/15/lipid-metabolism/

14. Carbohydrate Metabolism

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

http://pharmaceuticalintelligence.com/2014/08/13/carbohydrate-metabolism/

15. Update on mitochondrial function, respiration, and associated disorders

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

http://pharmaceuticalintelligence.com/2014/07/08/update-on-mitochondrial-function-respiration-and-associated-                   disorders/

16. Prologue to Cancer – e-book Volume One – Where are we in this journey?

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

http://pharmaceuticalintelligence.com/2014/04/13/prologue-to-cancer-ebook-4-where-are-we-in-this-journey/

17. Introduction – The Evolution of Cancer Therapy and Cancer Research: How We Got Here?

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

http://pharmaceuticalintelligence.com/2014/04/04/introduction-the-evolution-of-cancer-therapy-and-cancer-research-          how-we-got-here/

18. Inhibition of the Cardiomyocyte-Specific Kinase TNNI3K

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

http://pharmaceuticalintelligence.com/2013/11/01/inhibition-of-the-cardiomyocyte-specific-kinase-tnni3k/

19. The Binding of Oligonucleotides in DNA and 3-D Lattice Structures

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

http://pharmaceuticalintelligence.com/2013/05/15/the-binding-of-oligonucleotides-in-dna-and-3-d-lattice-structures/

20. Mitochondrial Metabolism and Cardiac Function

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

http://pharmaceuticalintelligence.com/2013/04/14/mitochondrial-metabolism-and-cardiac-function/

21. How Methionine Imbalance with Sulfur-Insufficiency Leads to Hyperhomocysteinemia

Curator: Larry H. Bernstein, MD, FCAP

http://pharmaceuticalintelligence.com/2013/04/04/sulfur-deficiency-leads_to_hyperhomocysteinemia/

22. AMPK Is a Negative Regulator of the Warburg Effect and Suppresses Tumor Growth In Vivo

Author and Curator: Stephen J. Williams, PhD

http://pharmaceuticalintelligence.com/2013/03/12/ampk-is-a-negative-regulator-of-the-warburg-effect-and-suppresses-         tumor-growth-in-vivo/

23. A Second Look at the Transthyretin Nutrition Inflammatory Conundrum

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

http://pharmaceuticalintelligence.com/2012/12/03/a-second-look-at-the-transthyretin-nutrition-inflammatory-                         conundrum/

24. Mitochondrial Damage and Repair under Oxidative Stress

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

http://pharmaceuticalintelligence.com/2012/10/28/mitochondrial-damage-and-repair-under-oxidative-stress/

25. Nitric Oxide and Immune Responses: Part 2

Author and Curator: Aviral Vatsa, PhD, MBBS

http://pharmaceuticalintelligence.com/2012/10/28/nitric-oxide-and-immune-responses-part-2/

26. Overview of Posttranslational Modification (PTM)

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

http://pharmaceuticalintelligence.com/2014/07/29/overview-of-posttranslational-modification-ptm/

27. Malnutrition in India, high newborn death rate and stunting of children age under five years

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

http://pharmaceuticalintelligence.com/2014/07/15/malnutrition-in-india-high-newborn-death-rate-and-stunting-of-                   children-age-under-five-years/

28. Update on mitochondrial function, respiration, and associated disorders

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

http://pharmaceuticalintelligence.com/2014/07/08/update-on-mitochondrial-function-respiration-and-associated-                  disorders/

29. Omega-3 fatty acids, depleting the source, and protein insufficiency in renal disease

Larry H. Bernstein, MD, FCAP, Curator

http://pharmaceuticalintelligence.com/2014/07/06/omega-3-fatty-acids-depleting-the-source-and-protein-insufficiency-         in-renal-disease/

30. Introduction to e-Series A: Cardiovascular Diseases, Volume Four Part 2: Regenerative Medicine

Larry H. Bernstein, MD, FCAP, writer, and Aviva Lev- Ari, PhD, RN

http://pharmaceuticalintelligence.com/2014/04/27/larryhbernintroduction_to_cardiovascular_diseases-                                  translational_medicine-part_2/

31. Epilogue: Envisioning New Insights in Cancer Translational Biology
Series C: e-Books on Cancer & Oncology

Author & Curator: Larry H. Bernstein, MD, FCAP, Series C Content Consultant

http://pharmaceuticalintelligence.com/2014/03/29/epilogue-envisioning-new-insights/

32. Ca2+-Stimulated Exocytosis:  The Role of Calmodulin and Protein Kinase C in Ca2+ Regulation of Hormone                         and Neurotransmitter

Writer and Curator: Larry H Bernstein, MD, FCAP and
Curator and Content Editor: Aviva Lev-Ari, PhD, RN

http://pharmaceuticalintelligence.com/2013/12/23/calmodulin-and-protein-kinase-c-drive-the-ca2-regulation-of-                    hormone-and-neurotransmitter-release-that-triggers-ca2-stimulated-exocy

33. Cardiac Contractility & Myocardial Performance: Therapeutic Implications of Ryanopathy (Calcium Release-                           related Contractile Dysfunction) and Catecholamine Responses

Author, and Content Consultant to e-SERIES A: Cardiovascular Diseases: Justin Pearlman, MD, PhD, FACC
Author and Curator: Larry H Bernstein, MD, FCAP
and Article Curator: Aviva Lev-Ari, PhD, RN

http://pharmaceuticalintelligence.com/2013/08/28/cardiac-contractility-myocardium-performance-ventricular-arrhythmias-      and-non-ischemic-heart-failure-therapeutic-implications-for-cardiomyocyte-ryanopathy-calcium-release-related-                    contractile/

34. Role of Calcium, the Actin Skeleton, and Lipid Structures in Signaling and Cell Motility

Author and Curator: Larry H Bernstein, MD, FCAP Author: Stephen Williams, PhD, and Curator: Aviva Lev-Ari, PhD, RN

http://pharmaceuticalintelligence.com/2013/08/26/role-of-calcium-the-actin-skeleton-and-lipid-structures-in-signaling-and-cell-motility/

35. Identification of Biomarkers that are Related to the Actin Cytoskeleton

Larry H Bernstein, MD, FCAP, Author and Curator

http://pharmaceuticalintelligence.com/2012/12/10/identification-of-biomarkers-that-are-related-to-the-actin-                           cytoskeleton/

36. Advanced Topics in Sepsis and the Cardiovascular System at its End Stage

Author: Larry H Bernstein, MD, FCAP

http://pharmaceuticalintelligence.com/2013/08/18/advanced-topics-in-Sepsis-and-the-Cardiovascular-System-at-its-              End-Stage/

37. The Delicate Connection: IDO (Indolamine 2, 3 dehydrogenase) and Cancer Immunology

Demet Sag, PhD, Author and Curator

http://pharmaceuticalintelligence.com/2013/08/04/the-delicate-connection-ido-indolamine-2-3-dehydrogenase-and-               immunology/

38. IDO for Commitment of a Life Time: The Origins and Mechanisms of IDO, indolamine 2, 3-dioxygenase

Demet Sag, PhD, Author and Curator

http://pharmaceuticalintelligence.com/2013/08/04/ido-for-commitment-of-a-life-time-the-origins-and-mechanisms-of-             ido-indolamine-2-3-dioxygenase/

39. Confined Indolamine 2, 3 dioxygenase (IDO) Controls the Homeostasis of Immune Responses for Good and Bad

Curator: Demet Sag, PhD, CRA, GCP

http://pharmaceuticalintelligence.com/2013/07/31/confined-indolamine-2-3-dehydrogenase-controls-the-hemostasis-           of-immune-responses-for-good-and-bad/

40. Signaling Pathway that Makes Young Neurons Connect was discovered @ Scripps Research Institute

Reporter: Aviva Lev-Ari, PhD, RN

http://pharmaceuticalintelligence.com/2013/06/26/signaling-pathway-that-makes-young-neurons-connect-was-                     discovered-scripps-research-institute/

41. Naked Mole Rats Cancer-Free

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

http://pharmaceuticalintelligence.com/2013/06/20/naked-mole-rats-cancer-free/

42. Late Onset of Alzheimer’s Disease and One-carbon Metabolism

Reporter and Curator: Dr. Sudipta Saha, Ph.D.

http://pharmaceuticalintelligence.com/2013/05/06/alzheimers-disease-and-one-carbon-metabolism/

43. Problems of vegetarianism

Reporter and Curator: Dr. Sudipta Saha, Ph.D.

http://pharmaceuticalintelligence.com/2013/04/22/problems-of-vegetarianism/

44.  Amyloidosis with Cardiomyopathy

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

http://pharmaceuticalintelligence.com/2013/03/31/amyloidosis-with-cardiomyopathy/

45. Liver endoplasmic reticulum stress and hepatosteatosis

Larry H Bernstein, MD, FACP

http://pharmaceuticalintelligence.com/2013/03/10/liver-endoplasmic-reticulum-stress-and-hepatosteatosis/

46. The Molecular Biology of Renal Disorders: Nitric Oxide – Part III

Curator and Author: Larry H Bernstein, MD, FACP

http://pharmaceuticalintelligence.com/2012/11/26/the-molecular-biology-of-renal-disorders/

47. Nitric Oxide Function in Coagulation – Part II

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

http://pharmaceuticalintelligence.com/2012/11/26/nitric-oxide-function-in-coagulation/

48. Nitric Oxide, Platelets, Endothelium and Hemostasis

Curator and Author: Larry H Bernstein, MD, FACP

http://pharmaceuticalintelligence.com/2012/11/08/nitric-oxide-platelets-endothelium-and-hemostasis/

49. Interaction of Nitric Oxide and Prostacyclin in Vascular Endothelium

Curator and Author: Larry H Bernstein, MD, FACP

http://pharmaceuticalintelligence.com/2012/09/14/interaction-of-nitric-oxide-and-prostacyclin-in-vascular-endothelium/

50. Nitric Oxide and Immune Responses: Part 1

Curator and Author:  Aviral Vatsa PhD, MBBS

http://pharmaceuticalintelligence.com/2012/10/18/nitric-oxide-and-immune-responses-part-1/

51. Nitric Oxide and Immune Responses: Part 2

Curator and Author:  Aviral Vatsa PhD, MBBS

http://pharmaceuticalintelligence.com/2012/10/28/nitric-oxide-and-immune-responses-part-2/

52. Mitochondrial Damage and Repair under Oxidative Stress

Curator and Author: Larry H Bernstein, MD, FACP

http://pharmaceuticalintelligence.com/2012/10/28/mitochondrial-damage-and-repair-under-oxidative-stress/

53. Is the Warburg Effect the cause or the effect of cancer: A 21st Century View?

Curator and Author: Larry H Bernstein, MD, FACP

http://pharmaceuticalintelligence.com/2012/10/17/is-the-warburg-effect-the-cause-or-the-effect-of-cancer-a-21st-                 century-view/

54. Ubiquinin-Proteosome pathway, autophagy, the mitochondrion, proteolysis and cell apoptosis

Curator and Author: Larry H Bernstein, MD, FACP

http://pharmaceuticalintelligence.com/2012/10/30/ubiquinin-proteosome-pathway-autophagy-the-mitochondrion-                  proteolysis-and-cell-apoptosis/

55. Ubiquitin-Proteosome pathway, Autophagy, the Mitochondrion, Proteolysis and Cell Apoptosis: Part III

Curator and Author: Larry H Bernstein, MD, FACP

http://pharmaceuticalintelligence.com/2013/02/14/ubiquinin-proteosome-pathway-autophagy-the-mitochondrion-                   proteolysis-and-cell-apoptosis-reconsidered/

56. Nitric Oxide and iNOS have Key Roles in Kidney Diseases – Part II

Curator and Author: Larry H Bernstein, MD, FACP

http://pharmaceuticalintelligence.com/2012/11/26/nitric-oxide-and-inos-have-key-roles-in-kidney-diseases/

57. New Insights on Nitric Oxide donors – Part IV

Curator and Author: Larry H Bernstein, MD, FACP

http://pharmaceuticalintelligence.com/2012/11/26/new-insights-on-no-donors/

58. Crucial role of Nitric Oxide in Cancer

Curator and Author: Ritu Saxena, Ph.D.

http://pharmaceuticalintelligence.com/2012/10/16/crucial-role-of-nitric-oxide-in-cancer/

59. Nitric Oxide has a ubiquitous role in the regulation of glycolysis -with a concomitant influence on mitochondrial function

Curator and Author: Larry H Bernstein, MD, FACP

http://pharmaceuticalintelligence.com/2012/09/16/nitric-oxide-has-a-ubiquitous-role-in-the-regulation-of-glycolysis-with-         a-concomitant-influence-on-mitochondrial-function/

60. Targeting Mitochondrial-bound Hexokinase for Cancer Therapy

Curator and Author: Ziv Raviv, PhD, RN 04/06/2013

http://pharmaceuticalintelligence.com/2013/04/06/targeting-mitochondrial-bound-hexokinase-for-cancer-therapy/

61. Biochemistry of the Coagulation Cascade and Platelet Aggregation – Part I

Curator and Author: Larry H Bernstein, MD, FACP

http://pharmaceuticalintelligence.com/2012/11/26/biochemistry-of-the-coagulation-cascade-and-platelet-aggregation/

Genomics, Transcriptomics, and Epigenetics

  1. What is the meaning of so many RNAs?

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

http://pharmaceuticalintelligence.com/2014/08/06/what-is-the-meaning-of-so-many-rnas/

  1. RNA and the transcription the genetic code

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

http://pharmaceuticalintelligence.com/2014/08/02/rna-and-the-transcription-of-the-genetic-code/

  1. A Primer on DNA and DNA Replication

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

http://pharmaceuticalintelligence.com/2014/07/29/a_primer_on_dna_and_dna_replication/

4. Synthesizing Synthetic Biology: PLOS Collections

Reporter: Aviva Lev-Ari

http://pharmaceuticalintelligence.com/2012/08/17/synthesizing-synthetic-biology-plos-collections/

5. Pathology Emergence in the 21st Century

Author and Curator: Larry Bernstein, MD, FCAP

http://pharmaceuticalintelligence.com/2014/08/03/pathology-emergence-in-the-21st-century/

6. RNA and the transcription the genetic code

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

http://pharmaceuticalintelligence.com/2014/08/02/rna-and-the-transcription-of-the-genetic-code/

7. A Great University engaged in Drug Discovery: University of Pittsburgh

Larry H. Bernstein, MD, FCAP, Reporter and Curator

http://pharmaceuticalintelligence.com/2014/07/15/a-great-university-engaged-in-drug-discovery/

8. microRNA called miRNA-142 involved in the process by which the immature cells in the bone  marrow give                              rise to all the types of blood cells, including immune cells and the oxygen-bearing red blood cells

Aviva Lev-Ari, PhD, RN, Author and Curator

http://pharmaceuticalintelligence.com/2014/07/24/microrna-called-mir-142-involved-in-the-process-by-which-the-                   immature-cells-in-the-bone-marrow-give-rise-to-all-the-types-of-blood-cells-including-immune-cells-and-the-oxygen-             bearing-red-blood-cells/

9. Genes, proteomes, and their interaction

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

http://pharmaceuticalintelligence.com/2014/07/28/genes-proteomes-and-their-interaction/

10. Regulation of somatic stem cell Function

Larry H. Bernstein, MD, FCAP, Writer and Curator    Aviva Lev-Ari, PhD, RN, Curator

http://pharmaceuticalintelligence.com/2014/07/29/regulation-of-somatic-stem-cell-function/

11. Scientists discover that pluripotency factor NANOG is also active in adult organisms

Larry H. Bernstein, MD, FCAP, Reporter

http://pharmaceuticalintelligence.com/2014/07/10/scientists-discover-that-pluripotency-factor-nanog-is-also-active-in-           adult-organisms/

12. Bzzz! Are fruitflies like us?

Larry H Bernstein, MD, FCAP, Author and Curator

http://pharmaceuticalintelligence.com/2014/07/07/bzzz-are-fruitflies-like-us/

13. Long Non-coding RNAs Can Encode Proteins After All

Larry H Bernstein, MD, FCAP, Reporter

http://pharmaceuticalintelligence.com/2014/06/29/long-non-coding-rnas-can-encode-proteins-after-all/

14. Michael Snyder @Stanford University sequenced the lymphoblastoid transcriptomes and developed an
allele-specific full-length transcriptome

Aviva Lev-Ari, PhD, RN, Author and Curator

http://pharmaceuticalintelligence.com/014/06/23/michael-snyder-stanford-university-sequenced-the-lymphoblastoid-            transcriptomes-and-developed-an-allele-specific-full-length-transcriptome/

15. Commentary on Biomarkers for Genetics and Genomics of Cardiovascular Disease: Views by Larry H                                     Bernstein, MD, FCAP

Author: Larry H Bernstein, MD, FCAP

http://pharmaceuticalintelligence.com/2014/07/16/commentary-on-biomarkers-for-genetics-and-genomics-of-                        cardiovascular-disease-views-by-larry-h-bernstein-md-fcap/

16. Observations on Finding the Genetic Links in Common Disease: Whole Genomic Sequencing Studies

Author an curator: Larry H Bernstein, MD, FCAP

http://pharmaceuticalintelligence.com/2013/05/18/observations-on-finding-the-genetic-links/

17. Silencing Cancers with Synthetic siRNAs

Larry H. Bernstein, MD, FCAP, Reviewer and Curator

http://pharmaceuticalintelligence.com/2013/12/09/silencing-cancers-with-synthetic-sirnas/

18. Cardiometabolic Syndrome and the Genetics of Hypertension: The Neuroendocrine Transcriptome Control Points

Reporter: Aviva Lev-Ari, PhD, RN

http://pharmaceuticalintelligence.com/2013/12/12/cardiometabolic-syndrome-and-the-genetics-of-hypertension-the-neuroendocrine-transcriptome-control-points/

19. Developments in the Genomics and Proteomics of Type 2 Diabetes Mellitus and Treatment Targets

Larry H. Bernstein, MD, FCAP, Reviewer and Curator

http://pharmaceuticalintelligence.com/2013/12/08/developments-in-the-genomics-and-proteomics-of-type-2-diabetes-           mellitus-and-treatment-targets/

20. Loss of normal growth regulation

Larry H Bernstein, MD, FCAP, Curator

http://pharmaceuticalintelligence.com/2014/07/06/loss-of-normal-growth-regulation/

21. CT Angiography & TrueVision™ Metabolomics (Genomic Phenotyping) for new Therapeutic Targets to Atherosclerosis

Reporter: Aviva Lev-Ari, PhD, RN

http://pharmaceuticalintelligence.com/2013/11/15/ct-angiography-truevision-metabolomics-genomic-phenotyping-for-           new-therapeutic-targets-to-atherosclerosis/

22.  CRACKING THE CODE OF HUMAN LIFE: The Birth of BioInformatics & Computational Genomics

Genomics Curator, Larry H Bernstein, MD, FCAP

http://pharmaceuticalintelligence.com/2014/08/30/cracking-the-code-of-human-life-the-birth-of-bioinformatics-                      computational-genomics/

23. Big Data in Genomic Medicine

Author and Curator, Larry H Bernstein, MD, FCAP

http://pharmaceuticalintelligence.com/2012/12/17/big-data-in-genomic-medicine/

24. From Genomics of Microorganisms to Translational Medicine

Author and Curator: Demet Sag, PhD

http://pharmaceuticalintelligence.com/2014/03/20/without-the-past-no-future-but-learn-and-move-genomics-of-                      microorganisms-to-translational-medicine/

25. Summary of Genomics and Medicine: Role in Cardiovascular Diseases

Author and Curator, Larry H Bernstein, MD, FCAP

http://pharmaceuticalintelligence.com/2014/01/06/summary-of-genomics-and-medicine-role-in-cardiovascular-diseases/

 26. Genomic Promise for Neurodegenerative Diseases, Dementias, Autism Spectrum, Schizophrenia, and Serious                      Depression

Author and Curator, Larry H Bernstein, MD, FCAP

http://pharmaceuticalintelligence.com/2013/02/19/genomic-promise-for-neurodegenerative-diseases-dementias-autism-        spectrum-schizophrenia-and-serious-depression/

 27.  BRCA1 a tumour suppressor in breast and ovarian cancer – functions in transcription, ubiquitination and DNA repair

Sudipta Saha, PhD

http://pharmaceuticalintelligence.com/2012/12/04/brca1-a-tumour-suppressor-in-breast-and-ovarian-cancer-functions-         in-transcription-ubiquitination-and-dna-repair/

28. Personalized medicine gearing up to tackle cancer

Ritu Saxena, PhD

http://pharmaceuticalintelligence.com/2013/01/07/personalized-medicine-gearing-up-to-tackle-cancer/

29. Differentiation Therapy – Epigenetics Tackles Solid Tumors

Stephen J Williams, PhD

      http://pharmaceuticalintelligence.com/2013/01/03/differentiation-therapy-epigenetics-tackles-solid-tumors/

30. Mechanism involved in Breast Cancer Cell Growth: Function in Early Detection & Treatment

     Aviva Lev-Ari, PhD, RN

http://pharmaceuticalintelligence.com/2013/01/17/mechanism-involved-in-breast-cancer-cell-growth-function-in-early-          detection-treatment/

31. The Molecular pathology of Breast Cancer Progression

Tilde Barliya, PhD

http://pharmaceuticalintelligence.com/2013/01/10/the-molecular-pathology-of-breast-cancer-progression

32. Gastric Cancer: Whole-genome reconstruction and mutational signatures

Aviva Lev-Ari, PhD, RN

http://pharmaceuticalintelligence.com/2012/12/24/gastric-cancer-whole-genome-reconstruction-and-mutational-                   signatures-2/

33. Paradigm Shift in Human Genomics – Predictive Biomarkers and Personalized Medicine –                                                       Part 1 (pharmaceuticalintelligence.com)

Aviva  Lev-Ari, PhD, RN

http://pharmaceuticalntelligence.com/2013/01/13/paradigm-shift-in-human-genomics-predictive-biomarkers-and-personalized-medicine-part-1/

34. LEADERS in Genome Sequencing of Genetic Mutations for Therapeutic Drug Selection in Cancer                                         Personalized Treatment: Part 2

A Lev-Ari, PhD, RN

http://pharmaceuticalintelligence.com/2013/01/13/leaders-in-genome-sequencing-of-genetic-mutations-for-therapeutic-       drug-selection-in-cancer-personalized-treatment-part-2/

35. Personalized Medicine: An Institute Profile – Coriell Institute for Medical Research: Part 3

Aviva Lev-Ari, PhD, RN

http://pharmaceuticalintelligence.com/2013/01/13/personalized-medicine-an-institute-profile-coriell-institute-for-medical-        research-part-3/

36. Harnessing Personalized Medicine for Cancer Management, Prospects of Prevention and Cure: Opinions of                           Cancer Scientific Leaders @http://pharmaceuticalintelligence.com

Aviva Lev-Ari, PhD, RN

http://pharmaceuticalintelligence.com/2013/01/13/7000/Harnessing_Personalized_Medicine_for_ Cancer_Management-      Prospects_of_Prevention_and_Cure/

37.  GSK for Personalized Medicine using Cancer Drugs needs Alacris systems biology model to determine the in silico
effect of the inhibitor in its “virtual clinical trial”

Aviva Lev-Ari, PhD, RN

http://pharmaceuticalintelligence.com/2012/11/14/gsk-for-personalized-medicine-using-cancer-drugs-needs-alacris-             systems-biology-model-to-determine-the-in-silico-effect-of-the-inhibitor-in-its-virtual-clinical-trial/

38. Personalized medicine-based cure for cancer might not be far away

Ritu Saxena, PhD

  http://pharmaceuticalintelligence.com/2012/11/20/personalized-medicine-based-cure-for-cancer-might-not-be-far-away/

39. Human Variome Project: encyclopedic catalog of sequence variants indexed to the human genome sequence

Aviva Lev-Ari, PhD, RN

http://pharmaceuticalintelligence.com/2012/11/24/human-variome-project-encyclopedic-catalog-of-sequence-variants-         indexed-to-the-human-genome-sequence/

40. Inspiration From Dr. Maureen Cronin’s Achievements in Applying Genomic Sequencing to Cancer Diagnostics

Aviva Lev-Ari, PhD, RN

http://pharmaceuticalintelligence.com/2013/01/10/inspiration-from-dr-maureen-cronins-achievements-in-applying-                genomic-sequencing-to-cancer-diagnostics/

41. The “Cancer establishments” examined by James Watson, co-discoverer of DNA w/Crick, 4/1953

Aviva Lev-Ari, PhD, RN

http://pharmaceuticalintelligence.com/2013/01/09/the-cancer-establishments-examined-by-james-watson-co-discover-         of-dna-wcrick-41953/

42. What can we expect of tumor therapeutic response?

Author and curator: Larry H Bernstein, MD, FACP

http://pharmaceuticalintelligence.com/2012/12/05/what-can-we-expect-of-tumor-therapeutic-response/

43. Directions for genomics in personalized medicine

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

http://pharmaceuticalintelligence.com/2013/01/27/directions-for-genomics-in-personalized-medicine/

44. How mobile elements in “Junk” DNA promote cancer. Part 1: Transposon-mediated tumorigenesis.

Stephen J Williams, PhD

http://pharmaceuticalintelligence.com/2012/10/31/how-mobile-elements-in-junk-dna-prote-cancer-part1-transposon-            mediated-tumorigenesis/

45. mRNA interference with cancer expression

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

 http://pharmaceuticalintelligence.com/2012/10/26/mrna-interference-with-cancer-expression/

46. Expanding the Genetic Alphabet and linking the genome to the metabolome

Aviva Lev-Ari, PhD, RD

http://pharmaceuticalintelligence.com/2012/09/24/expanding-the-genetic-alphabet-and-linking-the-genome-to-the-               metabolome/

47. Breast Cancer, drug resistance, and biopharmaceutical targets

Author and Curator: Larry H Bernstein, MD, FCAP

http://pharmaceuticalintelligence.com/2012/09/18/breast-cancer-drug-resistance-and-biopharmaceutical-targets/

48.  Breast Cancer: Genomic profiling to predict Survival: Combination of Histopathology and Gene Expression                            Analysis

Aviva Lev-Ari, PhD, RD

http://pharmaceuticalintelligence.com/2012/12/24/breast-cancer-genomic-profiling-to-predict-survival-combination-of-           histopathology-and-gene-expression-analysis

49. Gastric Cancer: Whole-genome reconstruction and mutational signatures

Aviva  Lev-Ari, PhD, RD

http://pharmaceuticalintelligence.com/2012/12/24/gastric-cancer-whole-genome-reconstruction-and-mutational-                   signatures-2/

50. Genomic Analysis: FLUIDIGM Technology in the Life Science and Agricultural Biotechnology

Aviva Lev-Ari, PhD, RD

http://pharmaceuticalintelligence.com/2012/08/22/genomic-analysis-fluidigm-technology-in-the-life-science-and-                   agricultural-biotechnology/

51. 2013 Genomics: The Era Beyond the Sequencing Human Genome: Francis Collins, Craig Venter, Eric Lander, et al.

Aviva Lev-Ari, PhD, RD

http://pharmaceuticalintelligence.com/2013_Genomics

52. Paradigm Shift in Human Genomics – Predictive Biomarkers and Personalized Medicine – Part 1

Aviva Lev-Ari, PhD, RD

http://pharmaceuticalintelligence.com/Paradigm Shift in Human Genomics_/

Signaling Pathways

  1. Proteins and cellular adaptation to stress

Larry H Bernstein, MD, FCAP, Curator

http://pharmaceuticalintelligence.com/2014/07/08/proteins-and-cellular-adaptation-to-stress/

  1. A Synthesis of the Beauty and Complexity of How We View Cancer:
    Cancer Volume One – Summary

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

http://pharmaceuticalintelligence.com/2014/03/26/a-synthesis-of-the-beauty-and-complexity-of-how-we-view-cancer/

  1. Recurrent somatic mutations in chromatin-remodeling and ubiquitin ligase complex genes in
    serous endometrial tumors

Sudipta Saha, PhD

http://pharmaceuticalintelligence.com/2012/11/19/recurrent-somatic-mutations-in-chromatin-remodeling-ad-ubiquitin-           ligase-complex-genes-in-serous-endometrial-tumors/

4.  Prostate Cancer Cells: Histone Deacetylase Inhibitors Induce Epithelial-to-Mesenchymal Transition

Stephen J Williams, PhD

http://pharmaceuticalintelligence.com/2012/11/30/histone-deacetylase-inhibitors-induce-epithelial-to-mesenchymal-              transition-in-prostate-cancer-cells/

5. Ubiquinin-Proteosome pathway, autophagy, the mitochondrion, proteolysis and cell apoptosis

Author and Curator: Larry H Bernstein, MD, FCAP

http://pharmaceuticalintelligence.com/2012/10/30/ubiquinin-proteosome-pathway-autophagy-the-mitochondrion-                   proteolysis-and-cell-apoptosis/

6. Signaling and Signaling Pathways

Larry H. Bernstein, MD, FCAP, Reporter and Curator

http://pharmaceuticalintelligence.com/2014/08/12/signaling-and-signaling-pathways/

7.  Leptin signaling in mediating the cardiac hypertrophy associated with obesity

Larry H. Bernstein, MD, FCAP, Reporter and Curator

http://pharmaceuticalintelligence.com/2013/11/03/leptin-signaling-in-mediating-the-cardiac-hypertrophy-associated-            with-obesity/

  1. Sensors and Signaling in Oxidative Stress

Larry H. Bernstein, MD, FCAP, Reporter and Curator

http://pharmaceuticalintelligence.com/2013/11/01/sensors-and-signaling-in-oxidative-stress/

  1. The Final Considerations of the Role of Platelets and Platelet Endothelial Reactions in Atherosclerosis and Novel
    Treatments

Larry H. Bernstein, MD, FCAP, Reporter and Curator

http://pharmaceuticalintelligence.com/2013/10/15/the-final-considerations-of-the-role-of-platelets-and-platelet-                      endothelial-reactions-in-atherosclerosis-and-novel-treatments

10.   Platelets in Translational Research – Part 1

Larry H. Bernstein, MD, FCAP, Reporter and Curator

http://pharmaceuticalintelligence.com/2013/10/07/platelets-in-translational-research-1/

11.  Disruption of Calcium Homeostasis: Cardiomyocytes and Vascular Smooth Muscle Cells: The Cardiac and
Cardiovascular Calcium Signaling Mechanism

Author and Curator: Larry H Bernstein, MD, FCAP, Author, and Content Consultant to e-SERIES A:
Cardiovascular Diseases: Justin Pearlman, MD, PhD, FACC and Curator: Aviva Lev-Ari, PhD, RN

http://pharmaceuticalintelligence.com/2013/09/12/disruption-of-calcium-homeostasis-cardiomyocytes-and-vascular-             smooth-muscle-cells-the-cardiac-and-cardiovascular-calcium-signaling-mechanism/

12. The Centrality of Ca(2+) Signaling and Cytoskeleton Involving Calmodulin Kinases and
Ryanodine Receptors in Cardiac Failure, Arterial Smooth Muscle, Post-ischemic Arrhythmia,
Similarities and Differences, and Pharmaceutical Targets

     Author and Curator: Larry H Bernstein, MD, FCAP, Author, and Content Consultant to
e-SERIES A: Cardiovascular Diseases: Justin Pearlman, MD, PhD, FACC and
Curator: Aviva Lev-Ari, PhD, RN

http://pharmaceuticalintelligence.com/2013/09/08/the-centrality-of-ca2-signaling-and-cytoskeleton-involving-calmodulin-       kinases-and-ryanodine-receptors-in-cardiac-failure-arterial-smooth-muscle-post-ischemic-arrhythmia-similarities-and-           differen/

13.  Nitric Oxide Signalling Pathways

Aviral Vatsa, PhD, MBBS

http://pharmaceuticalintelligence.com/2012/08/22/nitric-oxide-signalling-pathways/

14. Immune activation, immunity, antibacterial activity

Larry H. Bernstein, MD, FCAP, Curator

http://pharmaceuticalintelligence.com/2014/07/06/immune-activation-immunity-antibacterial-activity/

15.  Regulation of somatic stem cell Function

Larry H. Bernstein, MD, FCAP, Writer and Curator    Aviva Lev-Ari, PhD, RN, Curator

http://pharmaceuticalintelligence.com/2014/07/29/regulation-of-somatic-stem-cell-function/

16. Scientists discover that pluripotency factor NANOG is also active in adult organisms

Larry H. Bernstein, MD, FCAP, Reporter

http://pharmaceuticalintelligence.com/2014/07/10/scientists-discover-that-pluripotency-factor-nanog-is-also-active-in-adult-organisms/

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Myocardial Damage in Cardiovascular Disease: Circulating MicroRNA-208b and MicroRNA-499

Reporter: Aviva Lev-Ari, PhD, RN

Circulating MicroRNA-208b and MicroRNA-499 Reflect Myocardial Damage in Cardiovascular Disease

Maarten F. Corsten, MD, Robert Dennert, MD, Sylvia Jochems, BSc, Tatiana Kuznetsova, MD, PhD, Yvan Devaux, PhD, Leon Hofstra, MD, PhD, Daniel R. Wagner, MD, PhD, Jan A. Staessen, MD, PhD, Stephane Heymans, MD, PhD and Blanche Schroen, PhD

Author Affiliations

From the Center for Heart Failure Research (M.F.C., R.D., S.J., S.H., B.S.), Cardiovascular Research Institute, Maastricht, The Netherlands; the Division of Hypertension and Cardiovascular Rehabilitation (T.K., J.A.S.), Department of Cardiovascular Diseases, University of Leuven, Leuven, Belgium and Department of Epidemiology, Maastricht University Medical Center, Maastricht, The Netherlands; Centre de Recherche Public–Santé, Luxembourg (Y.D., D.R.W.), Luxembourg; Maastricht University Medical Center (L.H.), Maastricht, The Netherlands; and Centre Hospitalier Luxembourg (D.R.W.), Luxembourg.

Correspondence to Blanche Schroen, PhD, Center for Heart Failure Research, Cardiovascular Research Institute Maastricht, Universiteitssingel 50, 6229 ER Maastricht, The Netherlands. E-mail b.schroen@cardio.unimaas.nl

Drs Heymans and Schroen contributed equally to this work.

Abstract

Background— Small RNA molecules, called microRNAs, freely circulate in human plasma and correlate with varying pathologies. In this study, we explored their diagnostic potential in a selection of prevalent cardiovascular disorders.

Methods and Results— MicroRNAs were isolated from plasmas from well-characterized patients with varying degrees of cardiac damage:

(1) acute myocardial infarction,

(2) viral myocarditis,

(3) diastolic dysfunction, and

(4) acute heart failure.

Plasma levels of selected microRNAs, including heart-associated (miR-1, -133a, -208b, and -499), fibrosis-associated (miR-21 and miR-29b), and leukocyte-associated (miR-146, -155, and -223) candidates, were subsequently assessed using real-time polymerase chain reaction. Strikingly, in plasma from acute myocardial infarction patients, cardiac myocyte–associated miR-208b and -499 were highly elevated, 1600-fold (P<0.005) and 100-fold (P<0.0005), respectively, as compared with control subjects. Receiver operating characteristic curve analysis revealed an area under the curve of 0.94 (P<1010) for miR-208b and 0.92 (P<109) for miR-499. Both microRNAs correlated with plasma troponin T, indicating release of microRNAs from injured cardiomyocytes. In viral myocarditis, we observed a milder but significant elevation of these microRNAs, 30-fold and 6-fold, respectively. Plasma levels of leukocyte-expressed microRNAs were not significantly increased in acute myocardial infarction or viral myocarditis patients, despite elevated white blood cell counts. In patients with acute heart failure, only miR-499 was significantly elevated (2-fold), whereas no significant changes in microRNAs studied could be observed in diastolic dysfunction. Remarkably, plasma microRNA levels were not affected by a wide range of clinical confounders, including age, sex, body mass index, kidney function, systolic blood pressure, and white blood cell count.

Conclusions— Cardiac damage initiates the detectable release of cardiomyocyte-specific microRNAs-208b and -499 into the circulation.

SOURCE:

Circulation: Cardiovascular Genetics. 2010; 3: 499-506

Published online before print October 4, 2010,

doi: 10.1161/ CIRCGENETICS.110.957415

 

 

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Reporter: Aviva Lev-Ari, PhD, RN

The 6/13/2013 Supreme Court Decision is covered on this Open Access Online Scientific Journal

Genomics & Ethics: DNA Fragments are Products of Nature or Patentable Genes?

Geneticist Ricki Lewis, PhD: Genetics Errors in Supreme Court Decision of 6/13/2013

DNA Science BlogDNA Science Blog

http://blogs.plos.org/dnascience/2013/06/13/genetics-errors-in-supreme-court-decision/

Earlier today, my “in” box began to fill with info from everyone I’ve ever met letting me know that the Supreme Court had ruled on the Myriad case about patenting the breast cancer genes BRCA1 and BRCA2. I also received a dozen pitches from PR people offering me all manner of instant interviews with lawyers, doctors, bioethicists, and health care analysts.

No one offered me an interview with a geneticist – a person who knows something about DNA. So being such a person myself, I decided to take a look at the decision. And I found errors – starting right smack in the opening paragraph.

“Scientists can extract DNA from cells to isolate specific segments for study. They can also synthetically create exons-only strands of nucleotides known as composite DNA (cDNA). cDNA contains only the exons that occur in DNA, omitting the intervening exons.”

The definition is correct, the terminology, not. “cDNA” does not stand for “composite DNA.” It stands for “complementary DNA.”

cDNA came into fashion when I was in grad school, circa 1977. Like many genetics terms, it has a very precise meaning, something I pay attention to because I write human genetics books, including 10 editions of a textbook.

A cDNA is termed “complementary” because it is complementary in nucleotide base sequence to the messenger RNA (mRNA) that is made from the gene. Enzymes cut from the mRNA the sequences (introns) that do not encode amino acids and retains those (exons) that do encode protein. So a cDNA represents the part of a gene that is actually used to tell the cell to make protein. End of biology lesson.

A cDNA is created in the laboratory, and it is not a DNA sequence that occurs in nature. Hence, the Supreme Court’s part 2 of the decision, which acknowledges Myriad’s right to use a test based on a complementary, or cDNA.

I did a google search for “composite DNA” and just found the media parroting of today’s decision, and a few old forensics uses. So a caveat: my conclusion that the term is incorrect and invented is based on negative evidence. If I’m wrong, mea culpa in advance and I will feel like an idiot.

But cDNA isn’t the only error. I soon found another. On page 16, footnote #8 discusses a pseudogene as resulting from “random incorporation of fragments of cDNA.” That’s not even close to what a pseudogene is.

A pseudogene results from a DNA replication error that makes an extra copy of a gene. Over time, one copy mutates itself into a form that can’t do its job. The pseudogene remains in the genome like a ghost of a functional gene. The mutations occur at random because the pseudogene, not being used, isn’t subject to natural selection – that’s probably what the Court means by “random.” The globin gene locus on chromosome 11 is chock full of pseudogenes. This is such a classic example of basic genetics that my head is about to explode.

And how on earth is the Supreme Court’s definition of a pseudogene supposed to happen, in nature or otherwise? A cDNA exists in a lab dish. A gene exists in a cell that is part of an organism. How does the cDNA “randomly incorporate” itself inside the cell? Jump in from the dish? Part of the footnote states, “… given pseudogenes’ apparently random origins … ” Pseudogenes’ origins aren’t random at all. They happen in specific genes that tend to have repeats in the sequence, “confusing” the replication enzymes.

Today’s decision is undoubtedly a wonderful leap forward for patients, their families, and researchers. And some may think I am nitpicking. But these two errors jumped right out at me — I’d troll for more but I want to post this. What else is wrong? How can we trust the decision if the science is wrong? And what is the background of the people who research the decisions?

I know nothing about the law, zero, which is why I’m not writing about that. But the science in something as important as a Supreme Court decision should accurately use the language of the field under discussion.

http://blogs.plos.org/dnascience/2013/06/13/genetics-errors-in-supreme-court-decision/

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The Development of siRNA-Based Therapies for Cancer

Author: Ziv Raviv, PhD

Background

The use of gene regulation technology in research and medicine had evolved rapidly since the discovery of post transcriptional gene silencing using RNA interference (RNAi). RNAi was first described in C. elegance in the 90s of the previous century. RNAi post transcriptional gene regulation is carried out by small non-coding RNA double strand RNA (dsRNA) molecules such as microRNA (miRNA; miR) and small interference RNA (siRNA), and has an important role in defending cells against parasitic nucleotide sequences (e.g. viruses) as well as in gene expression regulation.

In RNAi-mediated gene regulation, short dsRNA molecules are being transcribed in the nucleus (in the case of miRs) or introduced exogenously into the cell (in the case of synthetic siRNA or viruses), and are processed in the cytoplasm by an enzyme called Dicer that cleaves long dsRNA and pre-microRNA to produce short double-stranded RNA fragments of 21 base pairs long. The 21 nucleotides long double strand RNA is then being incorporated into the RNA-induced silencing complex (RISC) where it is unwound into two single strands RNA (ssRNA). The “guide” strand is then paired with its complementary targeted messenger RNA (mRNA) that is subsequently cleaved by Argonaute RISC-associated endonuclease. Consequently, the targeted gene protein expression is blocked, leading to its substantial reduced levels in the cell. This so called gene silencing or gene knockdown, hitting the message not the gene itself, will last as long as RNAi molecules are present. The mechanism of action of RNAi is illustrated in the following Video.

RNAi technology was then massively adapted for research allowing the evaluation of functional involvement of genes in various cellular processes because introducing synthetic siRNA into cells can selectively suppress any specific gene of interest.  Not only that RNAi serves as a valuable research tool both in cell culture and in vivo, RNAi has an extremely high potential for specific gene-targeting therapy, as many diseases consist gene deregulation. Synthetic siRNAs are perfectly and completely base pairing to a target (in contrast to endogenous miRs), leading to mRNA-induced cleavage in a single-specific manner that allows treatment without non-specific off-target side effects.

RNAi as therapeutic tool for cancer

All malignant conditions consist of gene deregulations in the form of mutations causing protein misfunction that lead to loss of cell growth regulation and consequently to cancer. Therefore, the fact that siRNA can selectively and specifically target any gene of interest creates a powerful tool to downregulate cancer-associated genes, that eventually will lead to a decrease and even abolishment of the malignant condition.

The advantages of using siRNA for therapy thus are:

  • RNAi technology represents a 3rd revolutionary step for pharmaceutics after small molecules and monoclonal antibodies (mAb), and has a strong commercial potential similar to mAb and even beyond.
  • The ability to target any gene of interest, by blocking specifically the message from DNA to protein consequently the protein is not allowed to be expressed and thus is not functioning.
  • Specificity – siRNA have strong potential to bind specifically to target mRNA, thus lowering unwanted side effects.
  • siRNAs are double stranded oligonucleotides, which are resistant to nucleases.
  • Fast pre-clinical development

General considerations for developing anti-cancer RNAi-based treatment

Given the great potential of siRNA as a therapeutic tool for cancer, one should bring into consideration some general aspects for the development of a siRNA anti-cancer drug:

  • Choosing the gene of interest to be silenced – A wide spectrum of genes could be considered as targets based upon gene of interest role in the cancer cell, type of cancer, and condition of the disease: (i) Oncogenes or central signaling molecules that are crucial for cancer cell growth (ii) Anti-apoptotic deregulated genes (iii) Cancer metabolism associated genes (iv) Angiogenic related genes (v) Metastatic condition related genes.
  • Considering the option of hitting combined target genes consist of different functions (e.g. an oncogene and an anti-apoptotic gene).
  • Basic research evaluation – To examine the effect of silencing the gene of interest in cancer cell based assays and in animal models.
  • Chemical modifications of the siRNA molecule – Modifications such as 2′OMe to increase protection from nuclease, decrease the immunogenicity, lower the incidence of off-target effects, and improve pharmacodynamics of the siRNA.
  • Drug delivery formulation – For an efficient transport of the siRNA. Such delivery system could be formulated using liposome-based nanoparticles (NP) or other nanocarriers to facilitate the siRNA effective systemic distribution.
  • PEGylation – PEGylation of the NPs carriers to reduce non-specific tissue interactions, increase serum stability and half life, and reduce immunogenicity of the siRNA molecule.
  • Site specific targeting – Target tissue-specific distribution of the siRNA drug could be performed by attaching on the outer surface of the nanocarrier a ligand that will direct the siRNA drug to the tumor site.
  • Preclinical – Efficiency and validity, as well as toxicity and pharmacokinetic studies for the siRNA-transporter formulation should be evaluated in animal models.
  • Personalized treatment – In first stages clinical trials, biomarkers should be developed and detected to direct the selection criteria for further treatment of patients with the selected siRNA.
  • Combined therapy – Conduct clinical trials using a combination of the siRNA drug together with a chemotherapy drug that is in-clinical use. Such combined therapy can result in synergism actions of the two combined drugs, and could lower the dosage and thus the side effects of the drugs. In addition, the use of established contemporary agents has practical industrial-related advantages as it is much easier to introduce a new mode of treatment on the background of an existing one.

Development of transport methods for siRNA

As mentioned above, an important aspect in applying siRNA-based therapy is the development of a suitable delivery method that should carry the siRNA molecule systemically to the site of the tumor. In addition, the siRNA-transporter formulation should provide protection from serum nucleases to the siRNA and should decrease its immunogenicity by blocking response of the innate immune system. Examples of such NPs are illustrated in Figure 1. Indeed, several clinical trials were conducted to evaluate the efficacy, validity, and safety use of such transporters for clinical use (Table I).

Figure 1: Various types of nanoparticles for siRNA delivery

Taken from: Cho K et al. Clin Cancer Res 2008;14:1310-1316

Table IClinical trials examining siRNA delivery methods

T1Click on table to enlarge

Table resources: nmOK drug database and clinicaltrials.gov

Download table with active links: Development of siRNA-Based Therapies for Cancer_Table I

Current development status of RNAi-based cancer therapies  

The potential use of RNAi technology to treat cancer is versatile as for any gene of interest it is easy to synthesize a siRNA molecule and the pre-clinical development of siRNA agent is fast. Several companies specialized in siRNA technology have begun recently developing RNAi-based therapies to various cancer associated genes (as well as to other diseases) and to conduct clinical trials. Table II summaries the current clinical trials status of such siRNA-based anti-cancer agents.

Table II: Current clinical trials of siRNA therapies for cancer

T2Click on table to enlarge

Table resources: nmOK drug database, clinicaltrials.gov, and World Health Organization (WHO)

Download table with active links: Development of siRNA-Based Therapies for Cancer_Table II

Conclusion remarks

The power of siRNA-based therapeutics resides in the ability to target and silence any desired gene. Pharmaceutical and biotech companies have started to conduct clinical trials of siRNA therapies for cancer. Most of these clinical trials are in the early preclinical and phase I stages. The results expected from these experiments should further direct the development of siRNA-based anti-cancer therapies and phase II and III trials should consequently emerge. Other target genes should be evaluated as well for siRNA-anti cancer therapy in addition to those that are currently in evaluation, and accelerated efforts should be made in the direction of combining existing chemotherapy with the technology of siRNA. The next future to come will tell us if the potential of siRNA therapy for cancer had been fulfilled.

Related references:

  1. RNAi-Based Therapies for Cancer in Development. Anna Azvolinsky, PhD. Cancernetwork, March 3, 2011.
  2. siRNA-based approaches in cancer therapy. GR Devi. Cancer Gene Therapy (2006) 13, 819–829
  3. Therapeutic Effect of RNAi Gene Silencing Effective in Cancer Treatment, Study Suggests. Sciencedaily, Feb. 11, 2013.
  4. Kinesin Spindle Protein SiRNA Slows Tumor Progression. Marra E, Palombo F, Ciliberto G, Aurisicchio L. J Cell Physiol. 2013 Jan;228(1):58-64.
  5. First-in-Humans Trial of an RNA Interference Therapeutic Targeting VEGF and KSP in Cancer Patients with Liver Involvement. Josep Tabernero et al. Cancer Discov. 2013 Apr;3(4):406-417.

Chemical modification:

  1. Chemical Modification of siRNAs for In Vivo Use. Behlke MA. Oligonucleotides. 2008 Dec; 18(4):305-19.

Delivery Technology:

  1. Cancer siRNA therapy by tumor selective delivery with ligand-targeted sterically stabilized nanoparticle. Schiffelers RM et al. Nucleic Acids Res. 2004 Nov 1;32(19):e149.
  2. Therapeutic Nanoparticles for Drug Delivery in Cancer.  Kwangjae Cho, Xu Wang, Shuming Nie, et al. Clin Cancer Res 2008;14:1310-1316.
  3. Liposomes and nanoparticles: nanosized vehicles for drug delivery in cancer. Malam Y, Loizidou M, Seifalian AM. Trends Pharmacol Sci. 2009 Nov; 30(11):592-9.
  4. Silence-therapeutics delivery platform

Related articles on this Open Access Online Scientific Journal:

  1. MIT Team: Microfluidic-based approach – A Vectorless delivery of Functional siRNAs into Cells. Reporter: Aviva Lev-Ari, Ph.D., RN
  2. Targeted Tumor-Penetrating siRNA Nanocomplexes for Credentialing the Ovarian Cancer Oncogene ID4. Reporter and Curator: Sudipta Saha, Ph.D.
  3. Targeted delivery of therapeutics to bone and connective tissues: current status and challenges- Part II. Curator and Reporter: Aviral Vatsa Ph.D., MBBS
  4. Nanotechnology and HIV/AIDS treatment. Author: Tilda Barliya, PhD

To download tables of this post (with active links) :

  1. Development of siRNA-Based Therapies for Cancer_Table I
  2. Development of siRNA-Based Therapies for Cancer_Table II

Databases:

http://www.nmok.net

http://www.clinicaltrials.gov/

http://apps.who.int/trialsearch/

Related Videos:

RNA interference mechanism of action

RNA interference (RNAi): by Nature video

RNAi Therapeutics and Cancer Treatment

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Reporter: Aviva Lev-Ari, PhD, RN

 

Brain Development Is Guided by Junk DNA that Isn’t Really Junk

By Jeffrey Norris on April 15, 2013

Fluorescent dyes track the presence of the RNA molecules and the genes they  affect in the developing mouse brain.

UCSF researchers have uncovered a role in brain development and in neurological

disease for little appreciated molecules called long noncoding RNA. In this image,

fluorescent dyes track the presence of the RNA molecules and the genes they

affect in the developing mouse brain. Image courtesy of Alexander Ramos

Specific DNA once dismissed as junk plays an important role in brain development and might be involved in several devastating neurological diseases, UC San Francisco scientists have found.

Their discovery in mice is likely to further fuel a recent scramble by researchers to identify roles for long-neglected bits of DNA within the genomes of mice and humans alike.

While researchers have been busy exploring the roles of proteins encoded by the genes identified in various genome projects, most DNA is not in genes. This so-called junk DNA has largely been pushed aside and neglected in the wake of genomic gene discoveries, the UCSF scientists said.

In their own research, the UCSF team studies molecules called long noncoding RNA (lncRNA, often pronounced as “link” RNA), which are made from DNA templates in the same way as RNA from genes.

“The function of these mysterious RNA molecules in the brain is only beginning to be discovered,” said Daniel Lim, MD, PhD, assistant professor of neurological surgery, a member of the Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research at UCSF, and the senior author of the study, published online April 11 in the journal Cell Stem Cell.

Daniel Lim, MD, PhD

Alexander Ramos, a student enrolled in the MD/PhD program at UCSF and first author of the study, conducted extensive computational analysis to establish guilt by association, linking lncRNAs within cells to the activation of genes.

Ramos looked specifically at patterns associated with particular developmental pathways or with the progression of certain diseases. He found an association between a set of 88 long noncoding RNAs and Huntington’s disease, a deadly neurodegenerative disorder. He also found weaker associations between specific groups of long noncoding RNAs and Alzheimer’s disease, convulsive seizures, major depressive disorder and various cancers.

“Alex was the team member who developed this new research direction, did most of the experiments, and connected results to the lab’s ongoing work,” Lim said. The study was mostly funded through Lim’s grant – a National Institutes of Health (NIH) Director’s New Innovator Award, a competitive award for innovative projects that have the potential for unusually high impact.

LncRNA versus Messenger RNA

Unlike messenger RNA, which is transcribed from the DNA in genes and guides the production of proteins, lncRNA molecules do not carry the blueprints for proteins. Because of this fact, they were long thought to not influence a cell’s fate or actions.

Alexander Ramos

Nonetheless, lncRNAs also are transcribed from DNA in the same way as messenger RNA, and they, too, consist of unique sequences of nucleic acid building blocks.

Evidence indicates that lncRNAs can tether structural proteins to the DNA-containing chromosomes, and in so doing indirectly affect gene activation and cellular physiology without altering the genetic code. In other words, within the cell, lncRNA molecules act “epigenetically” — beyond genes — not through changes in DNA.

The brain cells that the scientists focused on the most give rise to various cell types of the central nervous system. They are found in a region of the brain called the subventricular zone, which directly overlies the striatum. This is the part of the brain where neurons are destroyed in Huntington’s disease, a condition triggered by a single genetic defect.

Ramos combined several advanced techniques for sequencing and analyzing DNA and RNA to identify where certain chemical changes happen to the chromosomes, and to identify lncRNAs on specific cell types found within the central nervous system. The research revealed roughly 2,000 such molecules that had not previously been described, out of about 9,000 thought to exist in mammals ranging from mice to humans.

In fact, the researchers generated far too much data to explore on their own. The UCSF scientists created a website through which their data can be used by others who want to study the role of lncRNAs in development and disease.

“There’s enough here for several labs to work on,” said Ramos, who has training grants from the California Institute for Regenerative Medicine (CIRM) and the NIH.

“It should be of interest to scientists who study long noncoding RNA, the generation of new nerve cells in the adult brain, neural stem cells and brain development, and embryonic stem cells,” he said.

Other co-authors who worked on the study include UCSF postdoctoral fellows Aaron Diaz, PhD, Abhinav Nellore, PhD, Michael Oldham, PhD, Jun Song, PhD, Ki-Youb Park, PhD, andGabriel Gonzales-Roybal, PhD; and MD/PhD student Ryan Delgado. Additional funders of the study included the Sontag Foundation and the Sandler Foundation.

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Modulating Stem Cells with Unread Genome: microRNAs

Author, Demet Sag, PhD

Life is simple but complicated. Both simple specific sequences and the big picture approach as a system are necessary in applications for a coherent outcome. Thus, providing an engineered whole cell as a system of correction for “Stem Cell Therapy” may resolve unmet health problems.  Only 1% of the genome is read and the remaining 99% is not a junk but useful. The energy is never getting lost and there is a tight conservation economy in living organisms.  As an example microRNAs that are one of the families of untranslated sequences can be utilized for a stem cell therapy for cancer.  Their power lies at transcription control that may direct the cell expression at exact time, and place for diagnosing, imaging and treatment.  The development of cell biology and understanding of genetic data from model organisms will assist to design a well-working mechanism.

In 1964, after their elegant experiment Till et. al demonstrated that special stimulating factors caused the differentiation and made new colonies. They suggested that “…since stem cells are responsible for continued cell production, it would appear probable that such stem cells are the sites of action for control mechanisms.”  They also pointed out simply that some cells do continue to be stem cells and some do loose the plasticity as they differentiate. Regardless of the two major unescapable events, “the birth” and “the death”, even though can be less predictable than the other, life must go on.  This nature brought an attention to regenerate the cells for our need.

One of the main issues in stem cell biology is figuring out how to re-activate once upon a time fast dividing cells, while the rest of the cells were not even active. The short answer is escaping the control gates with the precise keys without creating any immune responses or toxicity. The easiest and safest method is to re-write instructions of the cells for making a function based on comparative system biology and development. These retrained, resensitized and reprogrammed cells make possible changes to produce right amount of protein(s) on time and its place.

Functional genomics approach to a system within conserved life mechanisms of organisms (C elegans, D. melanogaster, A. nidulans, S. cerevisiae and M. musculus) is necessary for sound principles development.

The first resolution comes from the worm, C. elegans.  The early founding fathers of these special 20-22 bp untranslated specific sequences that control time in development and possible mRNA regulation are called microRNAs. This significant signature sequences and biomarkers control gene regulation for a proper protein expression even though these whistles and bells are not even expressed. Since they are included in 99% of the genome, they must have a voice in the system.  These miRNAs are shown first time in C.elegans were lin4 and let7.  When they were mutated, the cells went onto extra cell proliferation like it would in cancer. Later, in many metazoans it was discovered and shown that these special RNAs negatively regulate specific gene expression during important developmental stages of life such as cell proliferation, apoptosis and stress response.  For example the famous Drosha and Dicer, members of the RNA H III family, is acting sequentially in Drosophila bind to un-translated region of mRNA that either preventing the expression of the protein or causing to be degraded by RISC (He and Hannon 2004).

Dicer is important in biogenesis of miRNA pathway and Drosophila ovary is a great tool to study embryonic stem cells.   Analysis of Dicer-1 (dcr-1) germline mutants showed that these mutants have fewer cysts because at G1/S checkpoint the activity of Decapo, a cyclin kinase inhibitor, depends on Dicer-1.  As a result, cell division mechanisms require functional miRNA. In addition, these miRNAs also make the cells “insensitive” to the environmental influences. The new epigenetic studies  include their function for oncology RD to increase efficacy and survival rate of the treatment along with personalized genomic data.

The new technologies screening of the genome or doing chromosome walk became less labor intense and more informative like miccroarray technology, faster sequencing. Lu’s group designed a microarray analysis on comparative differential expression of miRNAs between healthy and tumor in human.  Their data show that there is a difference between these populations besides having specific loci for miRNAs in the genome (Lu et al. 2005).  The study by O’Dennel’s group reaffirmed their finding. Microarray screening showed several miRNAs are residing at the chromosome 13 region.  These miRNAs are also interacting specifically with MYC to modulate the cell genesis during cancer development (O’Dennel et al. 2005).

Yet, recent evidences show that miRNAs also manipulate regulation of transcription and epigenetics (Wang et. al 2013).  As a result, nanomolecules without affecting the cellular life with specific miRNAs help us to imagine of this complexity and to receive the snapshot of the condition (Conde et al. 2013).

Furthermore, there is a complexity to be included in the design of molecules.  The system mechanism may bring solutions for human health.  Thus, modulated stem cells with engineered special future based on not only one gene-one enzyme theory but also many/one gene, one/many enzyme. For example, Schwartz group showed that polycomb group of genes made up of several hundred genes manipulate a complete function in the system of organism (Schwartz et al. 2007). First polycombs were found in fruit flies (Drosophila), but they are recognized that they function to regulate homeotic genes both in mammals and insects. Now, it is known that these polycomb complexes play a huge global role in organizing epigenetics by enforcing repressed states, but balanced by Trithorax.  Interestingly, even same genes function in both germline and somatic sex determination pathway, there are different cell-cell communications, signal transductions and players in regulation mechanisms of Drosophila (Salz 2013; Ng et al. 2013).

Therefore, the studies modulating cells by engineering oligos may fix a health problem. Immunomodulation of immune cells APC (antigen presenting cells) / DC (dentritic cells) / T (T/B), reprogramming stem cells and restructuring of the membrane receptors for increased sensitivity to protect/locate/activate are few examples of possible platforms to develop products.

Life is simple but complex, also there is a simple solution, since human is the most resilient living who will answer how to cure what is broken to survive.

References:

  1. A Stochastic model of stem cell proliferation,based on th egrowth of spleen xcolony-forming cells. J. E. Till, E. A. McCulloch, L. Siminovitch Proc Natl Acad Sci U S A. 1964 January; 51(1): 29–36.  PMCID: PMC300599. (http://www.ncbi.nlm.nih.gov/pmc/articles/PMC300599/)
  2. MicroRNAs: Small RNAs with a big role in gene regulation L. He, G.J. Hannon Nat. Rev. Genet., 5 (2004), pp. 522–531 (http://www.nature.com/nrg/journal/v5/n7/full/nrg1379.html)
  3. Stem cell division is regulated by the microRNA pathway.  S.D. Hatfield, H.R. Shcherbata, K.A. Fischer, K. Nakahara, R.W. Carthew, H. Ruohola-Baker Nature, 435 (2005), pp. 974–978 (http://www.nature.com/nature/journal/v435/n7044/full/nature03816.html)
  4. MicroRNA expression profiles classify human cancers. J. Lu, G. Getz, E.A. Miska, E. Alvarez-Saavedra, J. Lamb, D. Peck, A. Sweet-Cordero, B.L. Ebert, R.H. Mak, A.A. Ferrando et al. Nature, 435 (2005), pp. 834–838 (http://www.nature.com/nature/journal/v435/n7043/full/nature03702.html)
  5. c-Myc-regulated microRNAs modulate E2F1 expression. K.A. O’Donnell, E.A. Wentzel, K.I. Zeller, C.V. Dang, J.T. Mendell Nature, 435 (2005), pp. 839–843 (http://www.nature.com/nature/journal/v435/n7043/full/nature03677.html)
  6. Gold-nanobeacons for simultaneous gene specific silencing and intracellular tracking of the silencing events. J. Conde, J, Rosa, J. M. la Fuente, P. V. Baptista.  Biomaterials, Vol. 34, issue 10, March 2013, pp. 2516-2523 (http://www.sciencedirect.com/science/article/pii/S0142961212013956)
  7. Transcriptional and epigenetic regulation of human microRNAs.
  8. Zifeng Wang,Hong Yao, Sheng Lin, Xiao Zhu, Zan Shen, Gang Lu, Wai Sang Poon, Dan Xie, Marie Chia-mi Lin, Hsiang-fu KungCancer Letters Volume 331, Issue 1 , Pages 1-10, 30 April 2013. (http://www.cancerletters.info/article/S0304-3835(12)00723-9/abstract)
  9. The MSC: An Injury Drugstore. A. I. Caplan and D. Correa Cell Stem Cell. 2011 July 8; 9(1): 11–15. doi:10.1016/j.stem.2011.06.008.
  10. Polycomb silencing mechanisms and the management of genomic programmes. Schwartz YB, Pirrotta V (January 2007). Nat. Rev. Genet. 8 (1): 9–22. doi:10.1038/nrg1981. PMID 17173055. (http://www.ncbi.nlm.nih.gov/pubmed/17173055)
  11. Sex, stem cells and tumors in the Drosophila ovary. HK Salz, Fly, 2013 (http://www.landesbioscience.com/journals/fly/article/22687/)
  12. In Vivo Epigenomic Profiling of Germ Cells Reveals Germ Cell Molecular Signatures. J. Ng, V. Kumar, M. Muratani, P. Kraus, JC. Yeo, L-P. Yaw, K. XUe, T. Lufkin, S. Prabhakar, H-H, Ng. Developmental Cell, Vol. 24, Issue 3, 11 February 2013, Pages 324–333. (http://www.sciencedirect.com/science/article/pii/S1534580712005850)

Other related article appeared on this Open Access Online Scientific Journal, including:

 

When Clinical Application of miRNAs?

Larry H Bernstein, MD, FACP, 3/3/2013

 

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Curator: Aviva Lev-Ari, PhD, RN

On 3/13/2013 Forbes Science Writer, Metthew Herper, presented a curated article about the protein Cas9. With a compelling title like 

This Protein Could Change Biotech Forever, we drew over 40 comments. 

A tiny molecular machine used by bacteria to kill attacking viruses could change the way that scientists edit the DNA of plants, animals and fungi, revolutionizing genetic engineering. The protein, called Cas9, is quite simply a way to more accurately cut a piece of DNA.

“This could significantly accelerate the rate of discovery in all areas of biology, including gene therapy in medicine, the generation of improved agricultural goods, and the engineering of energy-producing microbes,” says Luciano Marraffini of Rockefeller University.

The ability to make modular changes in the DNA of bacteria and primitive algae has resulted in drug and biofuel companies such as Amyris and LS9. But figuring out how to make changes in the genomes of more complicated organisms has been tough.

http://www.forbes.com/sites/matthewherper/2013/03/19/the-protein-that-could-change-biotech-forever/?goback=.gde_48920_member_227143277

In this article we bring all the pieces to one place, telling the evolution of a series of discoveries, which together may have the Protein, Cas9,  changing the Biotech Industry forever with its contributions to Diagnosing Diseases and Gene Therapy by Precision Genome Editing and Cost-effective microRNA Profiling. 

MicroRNA detection on the cheap

MIT alumni’s startup provides rapid, cost-effective microRNA profiling, which is beneficial for diagnosing diseases.
Rob Matheson, MIT News Office
March 28, 2013
Current methods of detecting microRNA (miRNA) — gene-regulating molecules implicated in the onset of various diseases — can be time-consuming and costly: The custom equipment used in such tests costs more than $100,000, and the limited throughput of these systems further hinders progress.
Two MIT alumni are helping to rectify these issues through their fast-growing, Cambridge-headquartered startup, Firefly BioWorks Inc., which provides technology that allows for rapid miRNA detection in a large number of samples using standard lab equipment. This technology has helped the company thrive — and also has the potential to increase the body of research on miRNA, which could help lead to better disease diagnosis and screening.The company’s core technology, called Optical Liquid Stamping (OLS) — which was invented at MIT by Firefly co-founder and Chief Technical Officer Daniel C. Pregibon PhD ’08 — works by imprinting (or stamping) microparticle structures onto photosensitive fluids. The resulting three-dimensional hydrogel particles, encoded with unique “barcodes,” can be used for the detection of miRNAs across large numbers of samples. These particles are custom-designed for readout in virtually any flow cytometer, a cost-effective device that’s accessible to most scientists.“Our manufacturing process allows us to make very sophisticated particles that can be read on the most basic instruments,” says co-founder and CEO Davide Marini PhD ’03.The company’s first commercial product, FirePlex miRSelect, an miRNA-detection kit that uses an assay based on OLS-manufactured particles and custom software, began selling about a year ago. Since then, the company has drawn a steady influx of customers (primarily academic and clinical scientists) while seeing rapid revenue growth.

To date, most of the company’s revenue has come from backers who see value in Firefly’s novel technology. In addition to a cumulative $2.5 million awarded through Small Business Innovation Research grants — primarily from the National Cancer Institute — the company has attracted $3 million from roughly 20 independent investors. Its most recent funding came from a $500,000 grant from the Massachusetts Life Sciences Center.

Pregibon developed the technology in the lab of MIT chemical engineering professorPatrick Doyle, a Firefly co-founder who serves on the company’s scientific advisory board. Firefly’s intellectual property is partially licensed through the Technology Licensing Office at MIT, along with several other Firefly patents. Firefly’s technology, from OLS to miRNA detection, has been described in papers published in several leading journals, including ScienceNature MaterialsNature Protocols and Analytical Chemistry.

Shifting complexity from equipment to particle

The success of the technology, Marini says, derives from an early business decision to focus attention on the development of the hydrogel particle instead of the equipment needed. Essentially, this allowed the co-founders to focus on developing a high-quality miRNA assay and hit the market quickly with particles that are universally readable on basic lab instrumentation.

“Imagine sticking a microscopic barcode on a microscopic product,” Marini says. “How do you scan it? At the beginning we thought we would have to build our own scanner. This would have been an expensive proposition. Instead, by using a few clever tricks, we redesigned the barcode to make it readable by existing instruments. You can write these ‘barcodes,’ and all you need is one scanner to read different codes. To quote an investor: ‘It shifts the complexity from the equipment to the particle.’”

Firefly’s particles appear to a standard flow cytometer as a series of closely spaced cells; these data are recorded and the company’s FireCode software then regroups them into particle information, including miRNA target identification and quantity.

But why, specifically, did the company choose a flow cytometer as its primary “scanner”? Pregibon answers: “To start, there are nearly 100,000 cytometers worldwide. In addition, we are now seeing a trend where flow cytometers are getting smaller and closer to the bench — closer to the actual researcher. We’re finding that people are tight for money because of the economy and are trying to conserve capital as much as possible. In order to use our products, they can either buy a very inexpensive bench-top flow cytometer or use one that already exists in their core facility.”

In turn, opting out of equipment development and manufacturing costs has helped the company stay financially sound, says Marini, who worked in London’s financial sector before coming to MIT. As an additional perk, the manufacturers of flow cytometers have begun “courting” Firefly, Marini says, because “our products help expand the capability of their systems, which are now exclusively used to analyze cells.”

The company’s FirePlex kit allows researchers to assay (or analyze) roughly 70 miRNA targets simultaneously across 96 samples of a wide variety — including serum, plasma and crude cell digests — in approximately three hours.

This is actually a “middle-ground” assaying technique, Pregibon says, and saves researchers time and money: Until now, scientists were forced to use separate techniques to look at a few miRNA targets over thousands of samples, or vice versa.

Marini adds that if a scientist suspects a number of miRNAs, perhaps 50 or so, could be involved in a pancreatic-cancer pathway, the only way to know for sure is to test those 50 targets over hundreds of samples. “There’s nowhere to do this today in a cost-effective, timely manner. Our tech now allows that,” he says.

‘Over the bridge of validation’

Because miRNAs are so important in the regulation of genes, and ultimately proteins, they have implications in a broad range of diseases, from cancer to Alzheimer’s disease. Several studies have suggested these relationships, but the field currently lacks the validation required to definitively demonstrate clinical utility.

With that in mind, Pregibon hopes that Firefly’s technology will help push miRNA-based diagnoses “over the bridge of validation,” giving scientists the means to validate miRNA signatures they discover in diagnosing diseases such as cancer. “That’s where we want to fit in,” he says. “With the help of a technology like ours, you’ll start to see more tests hitting the market and ultimately, more people benefitting from early cancer detection.”

Firefly’s aim is to strengthen preventive medicine in the United States. “In the long term, we see these products helping in the shift from reactive to preventative medicine,” Marini says. “We believe we will see a proliferation of tools for detection of diseases. We want to move away from the system we have now, which is curing before it’s too late.”

Pregibon says Firefly’s technology can be used across several molecule classes that are important in development and disease research: proteins, messenger RNA and DNA, among many others. “Essentially, the possibilities are endless,” Pregibon says.

Editing the genome with high precision

New method allows scientists to insert multiple genes in specific locations, delete defective genes.
Anne Trafton, MIT News Office
 
Researchers at MIT, the Broad Institute and Rockefeller University have developed a new technique for precisely altering the genomes of living cells by adding or deleting genes. The researchers say the technology could offer an easy-to-use, less-expensive way to engineer organisms that produce biofuels; to design animal models to study human disease; and  to develop new therapies, among other potential applications.To create their new genome-editing technique, the researchers modified a set of bacterial proteins that normally defend against viral invaders. Using this system, scientists can alter several genome sites simultaneously and can achieve much greater control over where new genes are inserted, says Feng Zhang, an assistant professor of brain and cognitive sciences at MIT and leader of the research team.“Anything that requires engineering of an organism to put in new genes or to modify what’s in the genome will be able to benefit from this,” says Zhang, who is a core member of the Broad Institute and MIT’s McGovern Institute for Brain Research.Zhang and his colleagues describe the new technique in the Jan. 3 online edition ofScience. Lead authors of the paper are graduate students Le Cong and Ann Ran.Early effortsThe first genetically altered mice were created in the 1980s by adding small pieces of DNA to mouse embryonic cells. This method is now widely used to create transgenic mice for the study of human disease, but, because it inserts DNA randomly in the genome, researchers can’t target the newly delivered genes to replace existing ones.

In recent years, scientists have sought more precise ways to edit the genome. One such method, known as homologous recombination, involves delivering a piece of DNA that includes the gene of interest flanked by sequences that match the genome region where the gene is to be inserted. However, this technique’s success rate is very low because the natural recombination process is rare in normal cells.

More recently, biologists discovered that they could improve the efficiency of this process by adding enzymes called nucleases, which can cut DNA. Zinc fingers are commonly used to deliver the nuclease to a specific location, but zinc finger arrays can’t target every possible sequence of DNA, limiting their usefulness. Furthermore, assembling the proteins is a labor-intensive and expensive process.

Complexes known as transcription activator-like effector nucleases (TALENs) can also cut the genome in specific locations, but these complexes can also be expensive and difficult to assemble.

Precise targeting

The new system is much more user-friendly, Zhang says. Making use of naturally occurring bacterial protein-RNA systems that recognize and snip viral DNA, the researchers can create DNA-editing complexes that include a nuclease called Cas9 bound to short RNA sequences. These sequences are designed to target specific locations in the genome; when they encounter a match, Cas9 cuts the DNA.

This approach can be used either to disrupt the function of a gene or to replace it with a new one. To replace the gene, the researchers must also add a DNA template for the new gene, which would be copied into the genome after the DNA is cut.

Each of the RNA segments can target a different sequence. “That’s the beauty of this — you can easily program a nuclease to target one or more positions in the genome,” Zhang says.

The method is also very precise — if there is a single base-pair difference between the RNA targeting sequence and the genome sequence, Cas9 is not activated. This is not the case for zinc fingers or TALEN. The new system also appears to be more efficient than TALEN, and much less expensive.

The new system “is a significant advancement in the field of genome editing and, in its first iteration, already appears comparable in efficiency to what zinc finger nucleases and TALENs have to offer,” says Aron Geurts, an associate professor of physiology at the Medical College of Wisconsin. “Deciphering the ever-increasing data emerging on genetic variation as it relates to human health and disease will require this type of scalable and precise genome editing in model systems.”

The research team has deposited the necessary genetic components with a nonprofit called Addgene, making the components widely available to other researchers who want to use the system. The researchers have also created a website with tips and tools for using this new technique.

Engineering new therapies

Among other possible applications, this system could be used to design new therapies for diseases such as Huntington’s disease, which appears to be caused by a single abnormal gene. Clinical trials that use zinc finger nucleases to disable genes are now under way, and the new technology could offer a more efficient alternative.

The system might also be useful for treating HIV by removing patients’ lymphocytes and mutating the CCR5 receptor, through which the virus enters cells. After being put back in the patient, such cells would resist infection.

This approach could also make it easier to study human disease by inducing specific mutations in human stem cells. “Using this genome editing system, you can very systematically put in individual mutations and differentiate the stem cells into neurons or cardiomyocytes and see how the mutations alter the biology of the cells,” Zhang says.

In the Science study, the researchers tested the system in cells grown in the lab, but they plan to apply the new technology to study brain function and diseases.

The research was funded by the National Institute of Mental Health; the W.M. Keck Foundation; the McKnight Foundation; the Bill & Melinda Gates Foundation; the Damon Runyon Cancer Research Foundation; the Searle Scholars Program; and philanthropic support from MIT alumni Mike Boylan and Bob Metcalfe, as well as the newscaster Jane Pauley.

SOURCE:
Published online 2012 September 4. doi:  10.1073/pnas.1208507109
PMCID: PMC3465414
PNAS Plus

Cas9–crRNA ribonucleoprotein complex mediates specific DNA cleavage for adaptive immunity in bacteria

ABSTRACT

Clustered, regularly interspaced, short palindromic repeats (CRISPR)/CRISPR-associated (Cas) systems provide adaptive immunity against viruses and plasmids in bacteria and archaea. The silencing of invading nucleic acids is executed by ribonucleoprotein complexes preloaded with small, interfering CRISPR RNAs (crRNAs) that act as guides for targeting and degradation of foreign nucleic acid. Here, we demonstrate that the Cas9–crRNA complex of the Streptococcus thermophilus CRISPR3/Cas system introduces in vitro a double-strand break at a specific site in DNA containing a sequence complementary to crRNA. DNA cleavage is executed by Cas9, which uses two distinct active sites, RuvC and HNH, to generate site-specific nicks on opposite DNA strands. Results demonstrate that the Cas9–crRNA complex functions as an RNA-guided endonuclease with RNA-directed target sequence recognition and protein-mediated DNA cleavage. These findings pave the way for engineering of universal programmable RNA-guided DNA endonucleases.

Keywords: nuclease, site-directed mutagenesis, RNA interference, DNA interference

Comparison with Other RNAi Complexes

The mechanism proposed here for the cleavage of dsDNA by the Cas9–crRNA complex differs significantly from that for the type I-E (former “Ecoli”) system (7). In the E. coli type I-E system crRNA and Cas proteins assemble into a large ribonucleoprotein complex, Cascade, that facilitates target recognition by enhancing sequence-specific hybridization between the crRNA and complementary target sequences (7). Target recognition is dependent on the PAM and governed by the seed crRNA sequence located at the 5′ end of the spacer region (24). However, although the Cascade–crRNA complex alone is able to bind dsDNA containing a PAM and a protospacer, it requires an accessory Cas3 protein for DNA cleavage. Cas3 is an ssDNA nuclease and helicase that is able to cleave ssDNA, producing multiple cuts (10). It has been demonstrated recently that Cas3 degrades E. coli plasmid DNA in vitro in the presence of the Cascade–crRNA complex (25). Thus, current data clearly show that the mechanistic details of the interference step for the type I-E system differ from those of type II systems, both in the catalytic machinery involved and the nature of the molecular mechanisms.

In type IIIB CRISPR/Cas systems, present in many archaea and some bacteria, Cmr proteins and cRNA assemble into an effector complex that targets RNA (612). In Pyrococcus furiosus the RNA-silencing complex, comprising six proteins (Cmr1–Cmr6) and crRNA, binds to the target RNA and cleaves it at fixed distance from the 3′ end. The cleavage activity depends on Mg2+ ions; however, individual Cmr proteins responsible for target RNA cleavage have yet to be identified. The effector complex of Sulfolobus solfataricus, comprising seven proteins (Cmr1–Cmr7) and crRNA, cuts invading RNA in an endonucleolytic reaction at UA dinucleotides (13). Importantly, these two archaeal Cmr–crRNA complexes perform RNA cleavage in a PAM-independent manner.

Overall, we have shown that the Cas9–crRNA complex in type II CRISPR/Cas systems is a functional homolog of Cascade in type I systems and represents a minimal DNAi complex. The simple modular organization of the Cas9–crRNA complex, in which specificity for DNA targets is encoded by crRNAs and the cleavage enzymatic machinery is brought by a single, multidomain Cas protein, provides a versatile platform for engineering universal RNA-guided DNA endonucleases. Indeed, by altering the RNA sequence within the Cas9–crRNA complex, programmable endonucleases can be designed both for in vitro and in vivo applications. To provide proof of principle of such a strategy, we engineered de novo into a CRISPR locus a spacer targeted to a specific sequence on a plasmid and demonstrated that such a plasmid is cleaved by the Cas9–crRNA complex at a sequence specified by the designed crRNA. Experimental demonstration that RuvC and HNH active-site mutants of Cas9 are functional as strand-specific nicking enzymes opens the possibility of generating programmed DNA single-strand breaks de novo. Taken together, these findings pave the way for the development of unique molecular tools for RNA-directed DNA surgery.

SOURCE:

Cheap and easy technique to snip DNA could revolutionize gene therapy

By Robert Sanders, Media Relations | January 7, 2013

BERKELEY —A simple, precise and inexpensive method for cutting DNA to insert genes into human cells could transform genetic medicine, making routine what now are expensive, complicated and rare procedures for replacing defective genes in order to fix genetic disease or even cure AIDS.

Cas9 protein on DNA
The bacterial enzyme Cas9 is the engine of RNA-programmed genome engineering in human cells. Graphic by Jennifer Doudna/UC Berkeley.
IMAGE SOURCE:

Discovered last year by Jennifer Doudna and Martin Jinek of the Howard Hughes Medical Institute and University of California, Berkeley, and Emmanuelle Charpentier of the Laboratory for Molecular Infection Medicine-Sweden, the technique was labeled a “tour de force” in a 2012 review in the journal Nature Biotechnology.

That review was based solely on the team’s June 28, 2012, Science paper, in which the researchers described a new method of precisely targeting and cutting DNA in bacteria.

Two new papers published last week in the journal Science Express demonstrate that the technique also works in human cells. A paper by Doudna and her team reporting similarly successful results in human cells has been accepted for publication by the new open-access journal eLife.

“The ability to modify specific elements of an organism’s genes has been essential to advance our understanding of biology, including human health,” said Doudna, a professor of molecular and cell biology and of chemistry and a Howard Hughes Medical Institute Investigator at UC Berkeley. “However, the techniques for making these modifications in animals and humans have been a huge bottleneck in both research and the development of human therapeutics.

“This is going to remove a major bottleneck in the field, because it means that essentially anybody can use this kind of genome editing or reprogramming to introduce genetic changes into mammalian or, quite likely, other eukaryotic systems.”

“I think this is going to be a real hit,” said George Church, professor of genetics at Harvard Medical School and principal author of one of the Science Express papers. “There are going to be a lot of people practicing this method because it is easier and about 100 times more compact than other techniques.”

“Based on the feedback we’ve received, it’s possible that this technique will completely revolutionize genome engineering in animals and plants,” said Doudna, who also holds an appointment at Lawrence Berkeley National Laboratory. “It’s easy to program and could potentially be as powerful as the Polymerase Chain Reaction (PCR).”

The latter technique made it easy to generate millions of copies of small pieces of DNA and permanently altered biological research and medical genetics.

Cruise missiles

Two developments – zinc-finger nucleases and TALEN (Transcription Activator-Like Effector Nucleases) proteins – have gotten a lot of attention recently, including being together named one of the top 10 scientific breakthroughs of 2012 by Science magazine. The magazine labeled them “cruise missiles” because both techniques allow researchers to home in on a particular part of a genome and snip the double-stranded DNA there and there only.

Researchers can use these methods to make two precise cuts to remove a piece of DNA and, if an alternative piece of DNA is supplied, the cell will plug it into the cut instead. In this way, doctors can excise a defective or mutated gene and replace it with a normal copy. Sangamo Biosciences, a clinical stage biospharmaceutical company, has already shown that replacing one specific gene in a person infected with HIV can make him or her resistant to AIDS.

Both the zinc finger and TALEN techniques require synthesizing a large new gene encoding a specific protein for each new site in the DNA that is to be changed. By contrast, the new technique uses a single protein that requires only a short RNA molecule to program it for site-specific DNA recognition, Doudna said.

In the new Science Express paper, Church compared the new technique, which involves an enzyme called Cas9, with the TALEN method for inserting a gene into a mammalian cell and found it five times more efficient.

“It (the Cas9-RNA complex) is easier to make than TALEN proteins, and it’s smaller,” making it easier to slip into cells and even to program hundreds of snips simultaneously, he said. The complex also has lower toxicity in mammalian cells than other techniques, he added.

“It’s too early to declare total victory” over TALENs and zinc-fingers, Church said, “but it looks promising.”

Based on the immune systems of bacteria

Doudna discovered the Cas9 enzyme while working on the immune system of bacteria that have evolved enzymes that cut DNA to defend themselves against viruses. These bacteria cut up viral DNA and stick pieces of it into their own DNA, from which they make RNA that binds and inactivates the viruses.

UC Berkeley professor of earth and planetary science Jill Banfield brought this unusual viral immune system to Doudna’s attention a few years ago, and Doudna became intrigued. Her research focuses on how cells use RNA (ribonucleic acids), which are essentially the working copies that cells make of the DNA in their genes.

Doudna and her team worked out the details of how the enzyme-RNA complex cuts DNA: the Cas9 protein assembles with two short lengths of RNA, and together the complex binds a very specific area of DNA determined by the RNA sequence. The scientists then simplified the system to work with only one piece of RNA and showed in the earlier Science paper that they could target and snip specific areas of bacterial DNA.

“The beauty of this compared to any of the other systems that have come along over the past few decades for doing genome engineering is that it uses a single enzyme,” Doudna said. “The enzyme doesn’t have to change for every site that you want to target – you simply have to reprogram it with a different RNA transcript, which is easy to design and implement.”

The three new papers show this bacterial system works beautifully in human cells as well as in bacteria.

“Out of this somewhat obscure bacterial immune system comes a technology that has the potential to really transform the way that we work on and manipulate mammalian cells and other types of animal and plant cells,” Doudna said. “This is a poster child for the role of basic science in making fundamental discoveries that affect human health.”

Doudna’s coauthors include Jinek and Alexandra East, Aaron Cheng and Enbo Ma of UC Berkeley’s Department of Molecular and Cell Biology.

Doudna’s work was sponsored by the Howard Hughes Medical Institute.

RELATED INFORMATION

SOURCE:
http://newscenter.berkeley.edu/2013/01/07/cheap-and-easy-technique-to-snip-dna-could-revolutionize-gene-therapy/

Matthew Herper, Forbes Staff on 3/24/2013

 A Cancer Patient’s Quest Hits DNA Pay Dirt

 

Kathy Giusti

Kathy Giusti has faced her cancer with the verve of an entrepreneur. Now her fight with multiple myeloma has moved to a new front: DNA.

Giusti was a 37-year-old marketing executive at Searle (now part of Pfizer) when she was diagnosed in 1996 with myeloma, a deadly blood and bone marrow cancer. She had a 1-year-old daughter. Sixty percent of myeloma patients die within five years, but Giusti beat the odds, living for a decade and a half through multiple rounds of drug therapy and a bone marrow transplant from her twin sister.

She has also changed the way her disease is treated. Giusti founded an advocacy group, the Multiple Myeloma Research Foundation, that works with companies like NovartisCelgene, and Merck to develop new treatments. It played a key role in the development of Velcade and Revlimid, two of the biggest advances in treating the disease, which is diagnosed in 20,000 patients a year.

Now a new research effort, funded with $14 million of MMRF money, has revealed new hints at what causes the disease and potential avenues for treating it. “This is going to be the next wave of how health care gets changed over time,” Giusti says. The results are published in the current issue of Nature.

Working with patient samples collected by the MMRF and using DNA sequencers made by Illumina of San Diego, researchers at the Broad Institute of MIT and Harvard sequenced the genes of 38 myeloma tumors and the DNA of the patients in whom they were growing. Tumors are twisted versions of the people in which they are growing; their DNA is mutated and disfigured, turning them deadly. By comparing DNA from healthy cells with malignant ones, researchers can find genetic differences that might be what led the tumors to go bad in the first place.

This experiment would have been unthinkable just a few years ago, when sequencing a human being was so expensive that all the people whose DNA had been read out could fit in a small room. In 2005, the idea of producing 38 DNA sequences was laughable. Now it’s par for the course, and researchers expect thousands of genomes will be sequenced by the end of the year – and experiments like this are expected to become commonplace.

What’s so exciting is that sometimes the DNA changes scientists find are completely unexpected. “There were genes we found to be recurrently mutated and yet no one had any clue that they had anything to do with multiple myeloma or any other cancer,” says Todd Golub, the Broad researcher who led the study. He splits his time with the Dana-Farber Cancer Institute.

One gene, called FAM46C, was mutated in 13% of the cancers, but has never been studied in humans. “It appears no one had been working on it,” says Golub, but from studies in yeast and bacteria it appears that it has to do with how the recipes in genes are used to make proteins, the building blocks of just about everything in the body.

Another surprise gene, called BRAF, is generating excitement because it is the target of a skin cancer drug developed by Plexxikon, a small biotech firm that is partnered with Roch and is being purchased by Daiichi Sankyo. For the 4% of myeloma patients who have this mutation, this drug might be an option. The challenge will be testing it: it will be difficult to find enough of these patients to conduct a clinical trial. The MMRF says early discussions on such a study are moving forward. Giusti imagines that in the future, the MMRF may fund studies not of myeloma, but of a mix of different cancers caused by similar genetic mutations.

Several of the genes seem involved in the proteins that help guide epigenetics, a kind of molecular code written on DNA that may represent another kind of genetic code. The MMRF is already supporting some small drug companies that hope to create cancer drugs that target this second code.

Golub, the Broad scientist, says that right now it doesn’t make sense for most multiple myeloma patients to get their full DNA sequences outside of clinical trials, although he can imagine that for patients who have failed every available treatment it might make sense as a way to come up with another drug to try.

Giusti says, however, that the kinds of genetic tests that are done are changing the way that patients understand their disease. “Patients like me are starting to know, ‘I have this DNA translocation, maybe a proteasome inhibitor [a type of drug] is better for me.’ We become forerunners in the role patient can plan and the importance it has in drug development.”

Moving past old ways of thinking about inventing new medicines to a new path that is based on genetics and a flood of biological data is going to be difficult. But Giusti has never been afraid of hard — and she is sure there will be ways to drive the science forward.

SOURCE:

http://www.forbes.com/sites/matthewherper/2011/03/24/a-cancer-patients-quest-hits-dna-pay-dirt/

REFERENCES

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3465414/

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Ca2+ Signaling: Transcriptional Control

Reporter: Larry H. Bernstein, MD, FCAP

Cardiac Physiology (excitation-transcription coupling)(transient receptor potential channels canonical; TRPCs)
The other side of cardiac Ca2+ signaling: transcriptional control
Domínguez-Rodríguez A, Ruiz-Hurtado G, Benitah J-P and Gómez AM
Front. Physio.2012; 3:452.    http://dx.doi.org/10.3389/fphys.2012.00452
 http://www.FrontPhysiol.com/The_other_side_of_cardiac_Ca2+_signaling:_transcriptional_control
http://www.frontiersin.org/Computational_Physiology_and_Medicine/10.3389/fphys.2012.00299/full

Integration of expression data in genome-scale metabolic network reconstructions
Anna S. Blazier and Jason A. Papin*
Department of Biomedical Engineering, University of Virginia, Charlottesville, VA, USA
Front. Physiol., 06 August 2012 |          http://dx.doi.org/10.3389/fphys.2012.00299
http://

The other side of cardiac Ca2+ signaling: transcriptional control
Alejandro Domínguez-Rodríguez1, Gema Ruiz-Hurtado2, Jean-Pierre Benitah1 and Ana M. Gómez1*
Ca2+ is probably the most versatile signal transduction element used by all cell types. In the heart, it is essential to activate cellular contraction in each heartbeat. Nevertheless Ca2+ is not only a key element in excitation-contraction coupling (EC coupling), but it is also

  • a pivotal second messenger in cardiac signal transduction, being able to control processes such as
    • excitability, metabolism, and transcriptional regulation.

Regarding the latter, Ca2+ activates Ca2+-dependent transcription factors by a process called excitation-transcription coupling (ET coupling). ET coupling is an integrated process by which

  • the common signaling pathways that regulate EC coupling
    • activate transcription factors.

In studies on the development of cardiac hypertrophy, two Ca2+-dependent enzymes are key actors:

  1. Ca2+/Calmodulin kinase II (CaMKII) and
  2. phosphatase calcineurin,
    • both of which are activated by the complex Ca2+/Calmodulin.

The question now is how ET coupling occurs in cardiomyocytes, where intracellular Ca2+ is continuously oscillating. We draw attention to location of Ca2+ signaling:

  1. intranuclear ([Ca2+]n) or cytoplasmic ([Ca2+]c), and
  2. the specific ionic channels involved in the activation of cardiac ET coupling.

We highlight the role of the 1,4,5 inositol triphosphate receptors (IP3Rs) in the elevation of [Ca2+]n levels, which are important to

  • locally activate CaMKII, and
  • the role of transient receptor potential channels canonical (TRPCs) in [Ca2+]c,
    • needed to activate calcineurin (Cn).

Keywords: heart, calcium, excitation-transcription coupling, TRPC, nuclear calcium
Citation: Domínguez-Rodríguez A, Ruiz-Hurtado G, Benitah J-P and Gómez AM (2012) The other side of cardiac Ca2+ signaling: transcriptional control.
Front. Physio. 3:452.   http://dx.doi.org/10.3389/fphys.2012.00452       Published online: 28 November 2012.
Edited by:Eric A. Sobie, Mount Sinai School of Medicine, USA; Reviewed by: Jeffrey Varner, Cornell University, USA; Ravi Radhakrishnan, University of Pennsylvania, USA

Integration of expression data in genome-scale metabolic network reconstructions
Anna S. Blazier and Jason A. Papin*
Front. Physiol., 06 August 2012 | doi: 10.3389/fphys.2012.00299

With the advent of high-throughput technologies, the field of systems biology has amassed an abundance of “omics” data,

  • quantifying thousands of cellular components across a variety of scales,
    • ranging from mRNA transcript levels to metabolite quantities.

Methods are needed to not only

  • integrate this omics data but to also
  • use this data to heighten the predictive capabilities of computational models.

Several recent studies have successfully demonstrated how flux balance analysis (FBA), a constraint-based modeling approach, can be used

  • to integrate transcriptomic data into genome-scale metabolic network reconstructions
    • to generate predictive computational models.

We summarize such FBA-based methods for integrating expression data into genome-scale metabolic network reconstructions, highlighting their advantages as well as their limitations.

Introduction
  1. Genomics provides data on a cell’s DNA sequence,
  2. transcriptomics on the mRNA expression of cells,
  3. proteomics on a cell’s protein composition, and
  4. metabolomics on a cell’s metabolite abundance.

Computational methods are needed to reduce this dimensionality across the wide spectrum of omics data to improve understanding of the underlying biological processes (Cakir et al., 2006Pfau et al., 2011).

Metabolic network reconstructions are an advantageous platform for the integration of omics data (Palsson, 2002). Assembled in part from

  • annotated genomes as well as
    • biochemical, genetic, and cell phenotype data,
  • a metabolic network reconstruction is a manually-curated, computational framework that

Numerous studies have demonstrated how such reconstructions of metabolism can guide the development of biological hypotheses and discoveries (Oberhardt et al., 2010Sigurdsson et al., 2010Chang et al., 2011).

Flux balance analysis (FBA), a constraint-based modeling approach, can be used to probe these network reconstructions by

  • predicting physiologically relevant growth rates as a function of the underlying biochemical networks (Gianchandani et al., 2009).

To do so, FBA involves delineating constraints on the network according to

After applying constraints, the solution space of possible phenotypes narrows, allowing for more accurate characterization of the reconstructed metabolic network,

  • Omics data can be used to further constrain the possible solution space and
  • enhance the model’s predictive powers

Given the wealth of transcriptomic data, efforts to integrate mRNA expression data with metabolic network reconstructions, have, in particular, made significant progress when using FBA as an analytical platform (Covert and Palsson, 2002Akesson et al., 2004Covert et al., 2004). However, despite this abundance of data, the integration of expression data faces unique challenges such as

  • experimental and inherent biological noise,
  • variation among experimental platforms,
  • detection bias, and the
  • unclear relationship between gene expression and reaction flux

The past few years have witnessed several advances in the integration of transcriptomic data with genome-scale metabolic network reconstructions. Specifically, numerous FBA-driven algorithms have been introduced that use experimentally derived mRNA transcript levels to modify the network’s reactions either by

  • inactivating them entirely or
  • by constraining their activity levels.

Such algorithms have demonstrated their applicability by, for example,

  1. We give an overview of the formulation of FBA.
  2. We summarize various FBA-driven methods for integrating expression data into genome-scale metabolic network reconstructions.
  3. We survey the limitations of these algorithms as well as look to the future of
    • multi-omics data integration using genome-scale metabolic network reconstructions as the scaffold.

Flux balance analysis

FBA is a constraint-based modeling approach that characterizes and predicts aspects of an organism’s metabolism (Gianchandani et al., 2009) To use FBA, the user supplies a metabolic network reconstruction in the form of a stoichiometric matrix, S, where

  1. the rows in S correspond to the metabolites of the reconstruction and
  2. the columns in S represent reactions in the reconstruction.
  3.  a stoichiometric coefficient sij conveys the molecularity of a certain metabolite in a particular reaction, with
    • sij ≥ 1 indicating that the metabolite is a product of the reaction,
    • sij ≤ −1 a reactant, and
    • sij = 0 signifies that the metabolite is not involved.

A system of linear equations is established by multiplying the matrix by a column vector, v, which contains the unknown fluxes through each of the reactions of the S matrix. Under the assumption that the system operates at steady-state, that is to say there is no net production or consumption of mass within the system, the product of this matrix multiplication must equal zero, S · v = 0 (Gianchandani et al., 2009). Because the resulting system is underdetermined (i.e., too few equations, too many unknowns), linear programming (LP) is used to optimize for a particular flux,Z, the objective function, subject to underlying constraints. The objective function typically takes on the form of:    Z = c ⋅ v
where c is a row vector of weights for each of the fluxes in column vector v, indicating how much each reaction in v contributes to the objective function,Z (Lee et al., 2006; Orth et al., 2010). Examples of objective functions include maximizing biomass, ATP production, and the production of a metabolite of interest (Lewis et al., 2012).

equation M2     (1)

subject to

S ⋅ v = 0
(2)
lb ≤ v ≤ ub                     
(3)

(1) outlines the objective function to be optimized,

(2) the steady state assumption, and

(3) describes the upper and lower bounds, ub and lb, of each of the fluxes in v according to such constraints as

  • enzyme capacities,
  • maximum uptake and secretion rates, and
  • thermodynamic constraints
    • (Price et al., 2003; Jensen and Papin, 2011).

Through this application of constraints, the solution space of physiologically feasible flux distributions for v shrinks. Thus, the task of FBA is to find a solution to v that lies within the bounded solution space and that optimizes the objective function at the same time.

Several recently developed algorithms have demonstrated how expression data can be incorporated into FBA models to further constrain the flux distribution solution space in genome-scale metabolic network reconstructions .
Summary of the algorithms for the integration of expression data.     Table 1 image URL  http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3429070/table/T1/?report=thumb

List of Methods:

GIMME guarantees to both produce a functioning metabolic model based on gene expression levels and quantify the agreement between the model and the data is called the Gene Inactivity Moderated by Metabolism and Expression (GIMME) algorithm (Becker and Palsson, 2008).

iMAT Similar to GIMME, the Integrative Metabolic Analysis Tool (iMAT) results in a functioning model in which the fluxes of reactions correlated with high mRNA levels are maximized and the fluxes of reactions associated with low mRNA levels are minimized (Shlomi et al., 2008; Zur et al., 2010). A key difference is that iMAT does not require a priori knowledge of a defined metabolic functionality. Briefly, this method establishes a tri-valued gene-to-reaction mapping for each reaction in the model according to the level of gene expression in the data. iMAT requires that reactions catalyzed by the products of highly expressed genes are able to carry a minimum flux. By removing this need for user-specified objective functions, iMAT bypasses assumptions about metabolic functionalities of a particular network, which proves advantageous for models where there is no clear objective function, as in models of mammalian cells.

MADE While both GIMME and iMAT rely on user-specified threshold values to determine which reactions are highly expressed and which reactions are lowly expressed, Metabolic Adjustment by Differential Expression (MADE) uses statistically significant changes in gene expression measurements to determine sequences of highly and lowly expressed reactions (Jensen and Papin, 2011). The lack of correlation between mRNA levels and protein levels makes it difficult to accurately determine when genes are “turned on,” and when they are “turned off.” Therefore, in eliminating this need for thresholding, MADE removes significant user-bias from the system.

E-Flux Whereas GIMME, iMAT, and MADE incorporate gene expression data into their models by reducing gene expression levels to binary states, the method E-Flux attempts to more directly incorporate gene expression data into FBA optimization problems by constraining the maximum possible flux through the reactions (Colijn et al., 2009). Rather than setting the upper bounds of a reaction to some large constant or 0, mirroring the implementation of binary-based algorithms, E-Flux constrains the upper bound of a reaction according to its respective gene expression level relative to a particular threshold. In cases where the gene expression data is below a certain threshold, tight constraints are placed on the flux through the corresponding reactions in the reconstruction; conversely, in cases where the gene expression is above a certain threshold, loose constraints are placed on the flux through the corresponding reactions.

PROM In contrast to the other methods discussed, which focused solely on integrating gene expression data into genome-scale metabolic network reconstructions, Probabilistic Regulation of Metabolism (PROM) aims to fuse together metabolic networks and transcription regulatory networks with expression data (Chandrasekaran and Price, 2010). To run PROM, the user supplies a genome-scale metabolic network reconstruction, a regulatory network structure describing transcription factors and their targets, and a range of expression data from various environmental and genetic perturbations. Given this expression data, PROM binarizes the genes with respect to a user-supplied threshold to evaluate the likelihood of the expression of a target gene given the expression of that gene’s transcription factor.

 Challenges facing the integration of expression data

Each of the methods discussed hinges on the assumption that mRNA transcript levels are a strong indicator for the level of protein activity. For instance, GIMME and iMAT assume that mRNA levels below a certain threshold suggest that the corresponding reactions are inactive. MADE follows a similar logic, turning reactions on and off depending on the changes in mRNA transcript levels. E-Flux and PROM assume that transcript levels indicate the degree to which reactions are active, evident in the constraining of the upper bounds in the FBA optimization problems associated with these methods.

Rather than requiring that the reconstruction mirror the expression data exactly, the methods allow for deviations in the FBA flux solution space in order to generate a functioning model that adheres to the specified constraints. In the case of GIMME, highly expressed reactions are prioritized relative to lowly expressed reactions; however, in the event that an optimal, functioning solution cannot be found, the assumption can be violated and lowly expressed reactions can be added back into the reconstruction. Thus, this assumption that mRNA transcript levels correlate to protein levels serves as a cue rather than a mandate.

Conclusion

The above methods have been used to not only integrate expression data from a variety of sources but to also make progress toward overcoming key challenges in the field of systems biology. For instance, iMAT, highlighting its applicability in multi-cellular organisms, was used to curate the human metabolic network reconstruction and predict tissue-specific gene activity levels in ten human tissues (Duarte et al., 2007; Shlomi et al., 2008). Additionally, both E-Flux and PROM have been used to discover novel drug targets in Mycobacterium tuberculosis (Colijn et al., 2009; Chandrasekaran and Price, 2010).

Given the recent success with using genome-scale metabolic network reconstructions as a platform for integrating expression data, efforts should focus on multi-omics data integration. A handful of methods have already been introduced that integrate two or more types of omics data into genome-scale metabolic network reconstructions. For example, despite the current dearth of quantitative metabolomics data, a method has been developed that demonstrates how semi-quantitative metabolomics data can be used with transcriptomic data to curate genome-scale metabolic network reconstructions and identify key reactions involved in the production of certain metabolites (Cakir et al., 2006). Another algorithm, called Integrative Omics-Metabolic Analysis (IOMA), integrates metabolomics data and proteomics data into a genome-scale metabolic network reconstruction by evaluating kinetic rate equations subject to quantitative omics measurements (Yizhak et al., 2010). Furthermore, Mass Action Stoichiometric Simulation (MASS) uses metabolomic, fluxomic, and proteomic data to transform a static stoichiometric reconstruction of an organism into a large-scale dynamic network model (Jamshidi and Palsson, 2010). And finally, building off of iMAT, the Model-Building Algorithm (MBA) utilizes literature-based knowledge, transcriptomic, proteomic, metabolomic, and phenotypic data to curate the human metabolic network reconstruction to derive a more complete picture of tissue-specific metabolism (Jerby et al., 2010). Such algorithms show promise in their ability to easily integrate high-throughput data into genome-scale metabolic network reconstructions to generate phenotypically accurate and predictive computational models.

calcium release calmodulin

calcium release calmodulin

Ca(2+) and contraction

Ca(2+) and contraction

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Phosphatidyl-5-Inositol Signaling by Pin1

 

Reporter: Larry H Bernstein, MD, FCAP

 

Regulation of Phosphatidylinositol-5-Phosphate Signaling by Pin1 Determines Sensitivity to Oxidative Stress

Willem-Jan Keune et al.
Increasing the abundance of the phospholipid PtdIns5P protects cells from oxidative stress.
Science Signaling   27 nov 2012; 5:252.
  1. T cell receptor (TCR) and costimulatory molecule mediated signaling
  2. culminate in maximal cytokine mRNA production and stability.
The transcriptional responses to co-stimulatory T cell signaling involve calcineurin and NF-AT, which
    • can be antagonized by interference with the cis-trans peptidyl-prolyl isomerases (PPIase), cyclophilin A and FKBP.
Signaling molecules downstream of CD28
    • which are essential for the stabilization of cytokine mRNAs are largely unknown.

Pin1, a third member of the PPIase family

    • mediates the post-transcriptional regulation of Th1 cytokines by activated T cells.

Blockade of Pin1 by pharmacologic or genetic means

  • greatly attenuated IFN-γ, IL-2 and CXCL-10 mRNA
    • stability,
    • accumulation and
    • protein expression after cell activation.

In vivo, Pin1 blockade prevented

  • both the acute and chronic rejection of MHC mismatched, orthotopic rat lung transplants by
  • reducing the expression of IFN-γ and CXCL-10.

Combined transcriptional and post-transcriptional blockade with

    • cyclosporine A and the Pin1 inhibitor, juglone, was synergistic.

These data suggest Pin1 inhibitors should be explored for use as immunosuppressants and employed with available calcineurin inhibitors to reduce toxicity and enhance effectiveness.
Esnault S, Braun RK, Shen Z-J, Xiang Z, Heninger E, et al. (2007)
Pin1 Modulates the Type 1 Immune Response. PLoS ONE 2(2): e226.  http://dx. doi.org/10.1371/journal.pone.0000226

Mixed-lineage kinase 3 phosphorylates prolyl-isomerase Pin1 to regulate its nuclear translocation and cellular function
Velusamy Rangasamya,1, Rajakishore Mishraa,1, Gautam Sondarvaa, Subhasis Dasa, et al.
Loyola University Chicago, Maywood, IL 60153;  Beth Israel Deaconess Medical Center, Boston, MA 02115; University of Mississippi Medical Center, Jackson, MS 39216;
University of Wisconsin, Madison, WI 53705; Hines Veterans Affairs Medical Center, Hines, IL 60141; and College of Veterinary Medicine, Iowa State University, Ames, IA 50011
Edited* by Michael Karin, University of California, San Diego School of Medicine, La Jolla, CA, and approved April 11, 2012
Nuclear protein peptidyl-prolyl isomerase Pin1-mediated prolyl isomerization is

  • an essential and novel regulatory mechanism for protein phosphorylation.

Therefore, tight regulation of Pin1 localization and catalytic activity is

  • crucial for its normal nuclear functions.

Pin1 is commonly dysregulated during oncogenesis and likely contributes to these pathologies; The mechanism by which Pin1 catalytic activity and nuclear localization are increased is unknown.
Here we demonstrate that

  1. mixed-lineage kinase 3 (MLK3), a MAP3K family member,
  2. phosphorylates Pin1 on a Ser138 site
  3. to increase its catalytic activity and nuclear translocation.
This phosphorylation event

  1. drives the cell cycle and
  2. promotes cyclin D1 stability and centrosome amplification.

Pin1 pSer138 is significantly

  • up-regulated in breast tumors and
  • is localized in the nucleus.

These findings collectively suggest that the MLK3-Pin1 signaling cascade plays a critical role

  1. in regulating the cell cycle,
  2. centrosome numbers, and
  3. oncogenesis. breast cancer

JNK Peptidyl-prolyl isomerase Pin1 plays a critical role in

  • regulating cellular homeostasis by
  • isomerizing the prolyl bond preceded by
  • a phosphorylated Ser or Thr residue (pSer/Thr-Pro) (1).

This isomerization by Pin1 regulates the biological function of several target proteins, including

  • cell-cycle regulators,
  • protooncogenes,
  • tumor suppressors, and
  • transcription factors (2).
Due to its role in controlling the cell cycle, apoptosis, growth, and stress responses, Pin1 has been linked to the pathogenesis of human diseases, including
  • cancer (3, 4),
  • asthma (5),
  • Alzheimer’s disease (AD) (6), and
  • Parkinson disease (PD) (7).

It is thus quite likely that tight regulation of Pin1 catalytic activity or expression is important for normal physiology. It is reported that Pin1 is

  • overexpressed in most types of cancer (8), whereas
  • its expression is diminished in AD brains (2).

Accumulating evidence suggests that Pin1 isomerase activity

  • and thus function are regulated by posttranslational modifications (2).

Pin1 function is also dependent on its

  • predominant nuclear localization (2),
    • consistent with its substrates being involved in transcription and cell-cycle progression.

It was recently reported that Pin1 nuclear import is regulated by a novel nuclear localization sequence in the PPIase domain, composed of basic amino acids (9). Nonetheless, the detailed mechanism that regulates Pin1 nuclear translocation is still not known. It also remains unknown whether any posttranslational modification of Pin1 can regulate its nuclear translocation or catalytic activity, and therefore directly affect its function.

Stereospecific gating of functional motions in Pin1
Andrew T. Namanjaa, Xiaodong J. Wangb, Bailing Xub, et al.
University of Notre Dame, Notre Dame, IN 46556; Virginia Tech, Blacksburg, VA 24061
Edited by Peter E. Wright, The Scripps Research Institute, La Jolla, CA, and approved June 2, 2011
Pin1 is a modular enzyme that

  • accelerates the cis-trans isomerization of phosphorylated-Ser/Thr-Pro (pS/T-P) motifs
  • found in numerous signaling proteins regulating cell growth and neuronal survival.

We have used NMR to investigate the interaction of Pin1 with three related ligands that include

  1. a pS-P substrate peptide, and
  2. two pS-P substrate analogue inhibitors
    • locked in the cis and trans conformations.

We compared the

  • ligand binding modes and
  • binding-induced changes
    • in Pin1 side-chain flexibility.

The cis and trans binding modes differ, and

  • produce different mobility in Pin1.

The cis-locked inhibitor and substrate produced a

  • loss of side-chain flexibility
    • along an internal conduit of conserved hydrophobic residues,
    • connecting the domain interface with the isomerase active site.

The trans-locked inhibitor

  • produces a weaker conduit response.

Thus, the conduit response is stereoselective. We further show

  • interactions between the peptidyl-prolyl isomerase and
  • Trp-Trp (WW) domains
    • amplify the conduit response, and
    • alter binding properties at the remote peptidyl-prolyl isomerase active site.

These results suggest that

  • specific input conformations can gate dynamic changes that support intraprotein communication.

Such gating may help control the propagation of chemical signals by Pin1, and other modular signaling proteins.

allostery ∣ protein dynamics ∣ ligand dynamics ∣ protein evolution
Phospho-serine/threonine-proline (pS/T-P) motifs are
signaling motifs within
intrinsically disordered loops of cell cycle proteins (1).
The imide bond between the pS/T and P residues can adopt

  • either the cis or trans conformation.

These conformations differ

  • in their susceptibility to kinases and phosphatases

that propagate the chemical signals governing the cell cycle.
Accordingly, the cell must regulate the cis/trans populations of these pS/T-P motifs

  • to ensure proper signal routing.

In this context, the peptidyl-prolyl isomerase Pin1 has emerged as a critical regulator (2, 3). Pin1 is a reversible enzyme that

  • catalyzes the cis-trans isomerization of the pS/T-P imide linkages (2, 3) of other signaling proteins, such as
  1. CDC25C,
  2. p53,
  3. c-Myc,
  4. NF-kB,
  5. cyclin D1, and
  6. tau (3).

Pin1 engages when external events, such as

  • S/T (de)-phosphorylation, change the cis-trans equilibrium.

Pin1 then

  1. catalyzes the cis-trans isomerization, thereby
  2. accelerating the approach to the new equilibrium (1).

Pin1 is a modular protein of 163 residues consisting of a

  • WW domain (1–39) and a larger
  • peptidyl-prolyl isomerase (PPIase) domain (50–163) (Fig. 1).

A flexible linker connects the two domains.

  1. Both domains are specific for pS/T-P motifs (1).
  2. The WW domain serves as a docking module, whereas
  3. catalysis is the sole province of the PPIase domain.

Earlier structural studies of Pin1 revealed

  1. conformational changes upon substrate interaction, thus
  2. motivating flexibility-function studies of Pin1 (4–6).
Peptidyl-prolyl Isomerase Pin1 Controls Down-regulation of Conventional Protein Kinase C Isozymes
JBC Papers in Press, Feb 8, 2012.       http://dx.doi.org/10.1074/jbc.M112.349753

H Abrahamsen, AK O’Neill, N Kannan, N Kruse¶, et al.
From the University of California, San Diego, La Jolla, California 92093
Background: Conventional PKC isozymes have a putative Pin1

  • isomerization sequence at their turn motif phosphorylation site.
Results: Pin1 binds conventional PKCs and

    • promotes their activation-induced down-regulation.
Conclusion: Pin1 isomerizes the phosphorylated turn motif of conventional PKC isozymes,

    • priming them for subsequent down-regulation.
Significance: Pin1 provides a switch regulating the lifetime of conventional PKCs. The down-regulation or cellular depletion of protein kinase C (PKC)
  • attendant to prolonged activation by phorbol esters is a
  • widely described property of this key family of signaling enzymes.

However, neither the mechanism of down-regulation nor whether this mechanism occurs following stimulation by physiological agonists is known.
**the peptidylprolyl isomerase Pin1 provides a timer for the lifetime of conventional PKC isozymes,

  • converting the enzymes into a species that can be dephosphorylated and ubiquitinated
  • following activation induced by either phorbol esters or natural agonists.

The regulation by Pin1 requires both the catalytic activity of the isomerase and the presence of a Pro immediately following the phosphorylated Thr of
the turn motif phosphorylation site,

  • one of two C-terminal sites that is phosphorylated during the maturation of PKC isozymes.
  • the second C-terminal phosphorylation site, the hydrophobic motif, docks
    • Pin1 to PKC.

Our data are consistent with a model in which Pin1

  • binds the hydrophobic motif of conventional PKC isozymes to catalyze the isomerization of the phospho-Thr-Pro peptide bond at the turn motif, thus
  • converting these PKC  isozymes into species that can be efficiently down-regulated following activation.

The peptidyl-prolyl cis-trans isomerase Pin1 is emerging as an important regulator of signal transduction pathways (1).

Pin1-catalyzed isomerization plays a key role in the control of normal cellular functions, most notably proliferation where

    • Pin1 is essential for cell cycle progression (2).

Pin1 belongs to the Parvulin family of peptidyl-prolyl cis-trans isomerases and is the only member that

  • specifically isomerizes phospho-(Ser/Thr)-Pro ((Ser(P)/Thr(P))-Pro) motifs (3):
  1. the enzyme displays an 1000-fold selectivity for peptides phosphorylated on the
  2. Ser/Thr preceding the Pro compared with unphosphorylated peptides (3).
Pin1induced conformational changes in target proteins

  • affect a variety of protein properties from
    • folding to
    • regulation of activity and stability.

As a consequence, deregulation of phosphorylation steps and their attendant conformational changes often lead to disease (4). For example, Pin1 is
downregulated in degenerating neurons from Alzheimer disease patients, correlating with age-dependent neurodegeneration (5).
Pin1 has also been implicated in cancer progression:
levels of this protein are increased in many cancers, including those of the

    • breast,
    • prostate,
    • brain,
    • lung, and
    • colon (6–9).

Thus, Pin1 has been proposed to function as a catalyst for oncogenic pathways (10). The molecular mechanisms that lead to disease progression

  • most likely involve postphosphorylation conformational changes
    • catalyzed by Pin1
    • that are required for downstream effects.
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The human immunophilin protein FKBP12 colored ...

The human immunophilin protein FKBP12 colored by hydrophobicity (white = hydrophobic) with bound FK506, an immunosuppressant used in treating organ transplant patients to prevent rejection. FKBP also has unrelated prolyl isomerase activity. (Photo credit: Wikipedia)

The human immunophilin protein FKBP12 colored ...

The human immunophilin protein FKBP12 colored by secondary structure with bound FK506, an immunosuppressant used in treating organ transplant patients to prevent rejection. FKBP also has unrelated prolyl isomerase activity. (Photo credit: Wikipedia)

 

 

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RNA Virus Genome as Bacterial Chromosome

Reporter: Larry H Bernstein, MD, FCAP

 

Engineering the largest RNA virus genome as an infectious bacterial artificial chromosome
F Almazan, JM Gonzalez, Z Penzes, A Izeta, E Calvo, J Plana-Duran, and L Enjuanes

PNAS  May 9, 2000; 97(10): 5516–5521.

the application of two strategies,

  • cloning of the cDNAs into a bacterial artificial chromosome and
  • nuclear expression of RNAs that are typically produced within the cytoplasm

is useful for the engineering of large RNA molecules.
A cDNA encoding an infectious coronavirus RNA genome

  • has been cloned as a bacterial artificial chromosome.

The rescued coronavirus

  • conserved all of the genetic markers introduced throughout the sequence and
  • showed a standard mRNA pattern and

the antigenic characteristics expected for the synthetic virus.
The cDNA was transcribed

  • within the nucleus, and
  • the RNA translocated to the cytoplasm.
Interestingly, the recovered virus had
  • essentially the same sequence as the original one, and
      • no splicing was observed.

During the engineering of the infectious cDNA,

  • the spike gene of the virus was replaced by
  • the spike gene of an enteric isolate.

The synthetic virus

  • replicated abundantly in the enteric tract and was fully virulent, demonstrating that
  • the tropism and virulence of the recovered coronavirus can be modified.

the application of two strategies,

  • cloning of the cDNAs into a bacterial artificial chromosome and
  • nuclear expression of RNAs that are typically produced within the cytoplasm,
    • is useful for the engineering of large RNA molecules.

A cDNA encoding an infectious coronavirus RNA genome has been cloned as a bacterial artificial chromosome. The rescued coronavirus

  • conserved all of the genetic markers introduced throughout the sequence and
  • showed a standard mRNA pattern and
  • the antigenic characteristics expected for the synthetic virus.
    • The cDNA was transcribed within the nucleus, and
    • the RNA translocated to the cytoplasm.

Interestingly, the recovered virus had essentially the same sequence as the original one, and no splicing was observed. During the engineering of the infectious cDNA, the spike gene of the virus was replaced by the spike gene of an enteric isolate. The synthetic virus

  • replicated abundantly in the enteric tract and
  • was fully virulent,

demonstrating that the tropism and virulence of the recovered coronavirus can be modified.}
http://www.PNAS.org/Engineering_the_largest_RNAvirus_genome_as_an_infectious_bacterial_artificial_chromosome/

Description: The interaction of mRNA in a cell...

Description: The interaction of mRNA in a cell. Source: http://www.genome.gov/Pages/Hyperion/DIR/VIP/Glossary/Illustration/mrna.shtml (file) License: “All of the illustrations in the Talking Glossary of Genetics are freely available and may be used without special permission.” http://www.genome.gov/page.cfm?pageID=10003803 (Photo credit: Wikipedia)

RNA Protein Virus

RNA Protein Virus (Photo credit: Wikipedia)

This image was created as part of the Philip G...

This image was created as part of the Philip Greenspun illustration project. (Photo credit: Wikipedia)

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