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Posts Tagged ‘Stephen J. Williams’


Synthetic Biology: On Advanced Genome Interpretation for Gene Variants and Pathways: What is the Genetic Base of Atherosclerosis and Loss of Arterial Elasticity with Aging

Curator: Aviva Lev-Ari, PhD, RN

UPDATED on 11/6/2018

Which biological systems should be engineered?

To solve real-world problems using emerging abilities in synthetic biology, research must focus on a few ambitious goals, argues Dan Fletcher, Professor of bioengineering and biophysics, and chair of the Department of Bioengineering at the University of California, Berkeley, USA. He is also a Chan Zuckerberg Biohub Investigator.
Start Quote

Artificial blood cells. Blood transfusions are crucial in treatments for everything from transplant surgery and cardiovascular procedures to car accidents, pregnancy-related complications and childhood malaria (see go.nature.com/2ozbfwt). In the United States alone, 36,000 units of red blood cells and 7,000 units of platelets are needed every day (see go.nature.com/2ycr2wo).

But maintaining an adequate supply of blood from voluntary donors can be challenging, especially in low- and middle-income countries. To complicate matters, blood from donors must be checked extensively to prevent the spread of infectious diseases, and can be kept for only a limited time — 42 days or 5 days for platelets alone. What if blood cells could be assembled from purified or synthesized components on demand?

In principle, cell-like compartments could be made that have the oxygen-carrying capacity of red blood cells or the clotting ability of platelets. The compartments would need to be built with molecules on their surfaces to protect the compartments from the immune system, resembling those on a normal blood cell. Other surface molecules would be needed to detect signals and trigger a response.

In the case of artificial platelets, that signal might be the protein collagen, to which circulating platelets are exposed when a blood vessel ruptures5. Such compartments would also need to be able to release certain molecules, such as factor V or the von Willebrand clotting factor. This could happen by building in a rudimentary form of exocytosis, for example, whereby a membrane-bound sac containing the molecule would be released by fusing with the compartment’s outer membrane.

It is already possible to encapsulate cytoplasmic components from living cells in membrane compartments6,7. Now a major challenge is developing ways to insert desired protein receptors into the lipid membrane8, along with reconstituting receptor signalling.

Red blood cells and platelets are good candidates for the first functionally useful synthetic cellular system because they lack nuclei. Complex functions such as nuclear transport, protein synthesis and protein trafficking wouldn’t have to be replicated. If successful, we might look back with horror on the current practice of bleeding one person to treat another.

Micrograph of red blood cells, 3 T-lymphocytes and activated platelets

Human blood as viewed under a scanning electron microscope.Credit: Dennis Kunkel Microscopy/SPL

Designer immune cells. Immunotherapy is currently offering new hope for people with cancer by shaping how the immune system responds to tumours. Cancer cells often turn off the immune response that would otherwise destroy them. The use of therapeutic antibodies to stop this process has drastically increased survival rates for people with multiple cancers, including those of the skin, blood and lung9. Similarly successful is the technique of adoptive T-cell transfer. In this, a patient’s T cells or those of a donor are engineered to express a receptor that targets a protein (antigen) on the surface of tumour cells, resulting in the T cells killing the cancerous cells (called CAR-T therapies)10. All of this has opened the door to cleverly rewiring the downstream signalling that results in the destruction of tumour cells by white blood cells11.

What if researchers went a step further and tried to create synthetic cells capable of moving towards, binding to and eliminating tumour cells?

In principle, untethered from evolutionary pressures, such cells could be designed to accomplish all sorts of tasks — from killing specific tumour cells and pathogens to removing brain amyloid plaques or cholesterol deposits. If mass production of artificial immune cells were possible, it might even lessen the need to tailor treatments to individuals — cutting costs and increasing accessibility.

To ensure that healthy cells are not targeted for destruction, engineers would also need to design complex signal-processing systems and safeguards. The designer immune cells would need to be capable of detecting and moving towards a chemical signal or tumour. (Reconstituting the complex process of cell motility is itself a major challenge, from the delivery of energy-generating ATP molecules to the assembly of actin and myosin motors that enable movement.)

Researchers have already made cell-like compartments that can change shape12, and have installed signalling circuits within them13. These could eventually be used to control movement and mediate responses to external signals.

Smart delivery vehicles. The relative ease of exposing cells in the lab to drugs, as well as introducing new proteins and engineering genomes, belies how hard it is to deliver molecules to specific locations inside living organisms. One of the biggest challenges in most therapies is getting molecules to the right place in the right cell at the right time.

Harnessing the natural proclivity of viruses to deliver DNA and RNA molecules into cells has been successful14. But virus size limits cargo size, and viruses don’t necessarily infect the cell types researchers and clinicians are aiming at. Antibody-targeted synthetic vesicles have improved the delivery of drugs to some tumours. But getting the drug close to the tumour generally depends on the vesicles leaking from the patient’s circulatory system, so results have been mixed.

Could ‘smart’ delivery vehicles containing therapeutic cargo be designed to sense where they are in the body and move the cargo to where it needs to go, such as across the blood–brain barrier?

This has long been a dream of those in drug delivery. The challenges are similar to those of constructing artificial blood and immune cells: encapsulating defined components in a membrane, incorporating receptors into that membrane, and designing signal-processing systems to control movement and trigger release of the vehicle’s contents.

The development of immune-cell ‘backpacks’ is an exciting step in the right direction. In this, particles containing therapeutic molecules are tethered to immune cells, exploiting the motility and targeting ability of the cells to carry the molecules to particular locations15.

A minimal chassis for expression. In each of the previous examples, the engineered cell-like system could conceivably be built to function over hours or days, without the need for additional protein production and regulation through gene expression. For many other tasks, however, such as the continuous production of insulin in the body, it will be crucial to have the ability to express proteins, upregulate or downregulate certain genes, and carry out functions for longer periods.

Engineering a ‘minimal chassis’ that is capable of sustained gene expression and functional homeostasis would be an invaluable starting point for building synthetic cells that produce proteins, form tissues and remain viable for months to years. This would require detailed understanding and incorporation of metabolic pathways, trafficking systems and nuclear import and export — an admittedly tall order.

It is already possible to synthesize DNA in the lab, whether through chemically reacting bases or using biological enzymes or large-scale assembly in a cell16. But we do not yet know how to ‘boot up’ DNA and turn a synthetic genome into a functional system in the absence of a live cell.

Since the early 2000s, biologists have achieved gene expression in synthetic compartments loaded with cytoplasmic extract17. And genetic circuits of increasing complexity (in which the expression of one protein results in the production or degradation of another) are now the subject of extensive research. Still to be accomplished are: long-lived gene expression, basic protein trafficking and energy production reminiscent of live cells.

End Quote

SOURCE

https://www.nature.com/articles/d41586-018-07291-3?utm_source=briefing-dy&utm_medium=email&utm_campaign=briefing&utm_content=20181106

 

UPDATED on 10/14/2013

Genetics of Atherosclerotic Plaque in Patients with Chronic Coronary Artery Disease

372/3:15 Genetic influence on LpPLA2 activity at baseline as evaluated in the exome chip-enriched GWAS study among ~13600 patients with chronic coronary artery disease in the STABILITY (STabilisation of Atherosclerotic plaque By Initiation of darapLadIb TherapY) trial. L. Warren, L. Li, D. Fraser, J. Aponte, A. Yeo, R. Davies, C. Macphee, L. Hegg, L. Tarka, C. Held, R. Stewart, L. Wallentin, H. White, M. Nelson, D. Waterworth.

Genetic influence on LpPLA2 activity at baseline as evaluated in the exome chip-enrichedGWASstudy among ~13600 patients with chronic coronary artery disease in the STABILITY (STabilisation of Atherosclerotic plaque By Initiation of darapLadIb TherapY) trial.

L. Warren1, L. Li1, D. Fraser1, J. Aponte1, A. Yeo2, R. Davies3, C. Macphee3, L. Hegg3,

L. Tarka3, C. Held4, R. Stewart5, L. Wallentin4, H. White5, M. Nelson1, D.

Waterworth3.

1) GlaxoSmithKline, Res Triangle Park, NC;

2) GlaxoSmithKline, Stevenage, UK;

3) GlaxoSmithKline, Upper Merion, Pennsylvania, USA;

4) Uppsala Clinical Research Center, Department of Medical Sciences, Uppsala University, Uppsala, Sweden;

5) 5Green Lane Cardiovascular Service, Auckland Cty Hospital, Auckland, New Zealand.

STABILITY is an ongoing phase III cardiovascular outcomes study that compares the effects of darapladib enteric coated (EC) tablets, 160 mg versus placebo, when added to the standard of care, on the incidence of major adverse cardiovascular events (MACE) in subjects with chronic coronary heart disease (CHD). Blood samples for determination of the LpPLA2 activity level in plasma and for extraction of DNA was obtained at randomization. To identify genetic variants that may predict response to darapladib, we genotyped ~900K common and low frequency coding variations using Illumina OmniExpress GWAS plus exome chip in advance of study completion. Among the 15828 Intent-to-Treat recruited subjects, 13674 (86%) provided informed consent for genetic analysis. Our pharmacogenetic (PGx) analysis group is comprised of subjects from 39 countries on five continents, including 10139 Whites of European heritage, 1682 Asians of East Asian or Japanese heritage, 414 Asians of Central/South Asian heritage, 268 Blacks, 1027 Hispanics and 144 others. Here we report association analysis of baseline levels of LpPLA2 to support future PGx analysis of drug response post trial completion. Among the 911375 variants genotyped, 213540 (23%) were rare (MAF < 0.5%).

Our analyses were focused on the drug target, LpPLA2 enzyme activity measured at baseline. GWAS analysis of LpPLA2 activity adjusting for age, gender and top 20 principle component scores identified 58 variants surpassing GWAS-significant threshold (5e-08).

Genome-wide stepwise regression analyses identified multiple independent associations from PLA2G7, CELSR2, APOB, KIF6, and APOE, reflecting the dependency of LpPLA2 on LDL-cholesterol levels. Most notably, several low frequency and rare coding variants in PLA2G7 were identified to be strongly associated with LpPLA2 activity. They are V279F (MAF=1.0%, P= 1.7e-108), a previously known association, and four novel associations due to I1317N (MAF=0.05%, P=4.9e-8), Q287X (MAF=0.05%, P=1.6e-7), T278M (MAF=0.02%, P=7.6e-5) and L389S (MAF=0.04%, P=4.3e-4).

All these variants had enzyme activity lowering effects and each appeared to be specific to certain ethnicity. Our comprehensive PGx analyses of baseline data has already provided great insight into common and rare coding genetic variants associated with drug target and related traits and this knowledge will be invaluable in facilitating future PGx investigation of darapladib response.

SOURCE

http://www.ashg.org/2013meeting/pdf/46025_Platform_bookmark%20for%20Web%20Final%20from%20AGS.pdf

Synthetic Biology: On Advanced Genome Interpretation for

  • Gene Variants and
  • Pathways,
  • Inversion Polymorphism,
  • Passenger Deletions,
  • De Novo Mutations,
  • Whole Genome Sequencing w/Linkage Analysis

What is the Genetic Base of Atherosclerosis and Loss of Arterial Elasticity with Aging?

In a recent publication by my colleague, Stephen J. Williams, Ph.D. on  5/15/2013 titled

Finding the Genetic Links in Common Disease:  Caveats of Whole Genome Sequencing Studies

https://pharmaceuticalintelligence.com/2013/05/15/finding-the-genetic-links-in-common-disease-caveats-of-whole-genome-sequencing-studies/

we learned that:

  • Groups of variants in the same gene confirmed link between APOC3 and higher risk for early-onset heart attack
  • No other significant gene variants linked with heart disease

APOC3 – apolipoprotein C-III – Potential Relevance to the Human Aging Process

Main reason for selection
Entry selected based on indirect or inconclusive evidence linking the gene product to ageing in humans or in one or more model systems
Description
APOC3 is involved in fat metabolism and may delay the catabolism of triglyceride-rich particles. Changes in APOC3 expression levels have been reported in aged mice [1754]. Results from mice suggest that FOXO1 may regulate the expression of APOC3 [1743]. Polymorphisms in the human APOC3 gene and promoter have been associated with lipoprotein profile, cardiovascular health, insulin (INS) sensitivity, and longevity [1756]. Therefore, APOC3 may impact on some age-related diseases, though its exact role in human ageing remains to be determined.

Cytogenetic information

Cytogenetic band
11q23.1-q2
Location
116,205,833 bp to 116,208,997 bp
Orientation
Plus strand

Display region using the UCSC Genome Browser

Protein information

Gene Ontology
Process: GO:0006869; lipid transport
GO:0016042; lipid catabolic process
GO:0042157; lipoprotein metabolic process
Function: GO:0005319; lipid transporter activity
Cellular component: GO:0005576; extracellular region
GO:0042627; chylomicron

Protein interactions and network

No interactions in records.

Retrieve sequences for APOC3

Promoter
Promoter
ORF
ORF
CDS
CDS

Homologues in model organisms

Bos taurus
APOC3_BOVI
Mus musculus
Apoc3
Pan troglodytes
APOC3

In other databases

AnAge
This species has an entry in AnAge

Selected references

  • [2125] Pollin et al. (2008) A null mutation in human APOC3 confers a favorable plasma lipid profile and apparent cardioprotection.PubMed
  • [1756] Atzmon et al. (2006) Lipoprotein genotype and conserved pathway for exceptional longevity in humansPubMed
  • [1755] Araki and Goto (2004) Dietary restriction in aged mice can partially restore impaired metabolism of apolipoprotein A-IV and C-IIIPubMed
  • [1743] Altomonte et al. (2004) Foxo1 mediates insulin action on apoC-III and triglyceride metabolismPubMed
  • [1754] Araki et al. (2004) Impaired lipid metabolism in aged mice as revealed by fasting-induced expression of apolipoprotein mRNAs in the liver and changes in serum lipidsPubMed
  • [1753] Panza et al. (2004) Vascular genetic factors and human longevityPubMed
  • [1752] Anisimov et al. (2001) Age-associated accumulation of the apolipoprotein C-III gene T-455C polymorphism C 

http://genomics.senescence.info/genes/entry.php?hgnc=APOC3

Apolipoprotein C-III is a protein component of very low density lipoprotein (VLDL). APOC3 inhibitslipoprotein lipase and hepatic lipase; it is thought to inhibit hepatic uptake[1] of triglyceride-rich particles. The APOA1, APOC3 and APOA4 genes are closely linked in both rat and human genomes. The A-I and A-IV genes are transcribed from the same strand, while the A-1 and C-III genes are convergently transcribed. An increase in apoC-III levels induces the development of hypertriglyceridemia.

Clinical significance

Two novel susceptibility haplotypes (specifically, P2-S2-X1 and P1-S2-X1) have been discovered in ApoAI-CIII-AIV gene cluster on chromosome 11q23; these confer approximately threefold higher risk ofcoronary heart disease in normal[2] as well as non-insulin diabetes mellitus.[3]Apo-CIII delays the catabolism of triglyceride rich particles. Elevations of Apo-CIII found in genetic variation studies may predispose patients to non-alcoholic fatty liver disease.

  1. ^ Mendivil CO, Zheng C, Furtado J, Lel J, Sacks FM (2009). “Metabolism of VLDL and LDL containing apolipoprotein C-III and not other small apolipoproteins – R2”.Arteriosclerosis, Thrombosis and Vascular Biology 30 (2): 239–45. doi:10.1161/ATVBAHA.109.197830PMC 2818784PMID 19910636.
  2. ^ Singh PP, Singh M, Kaur TP, Grewal SS (2007). “A novel haplotype in ApoAI-CIII-AIV gene region is detrimental to Northwest Indians with coronary heart disease”. Int J Cardiol 130 (3): e93–5. doi:10.1016/j.ijcard.2007.07.029PMID 17825930.
  3. ^ Singh PP, Singh M, Gaur S, Grewal SS (2007). “The ApoAI-CIII-AIV gene cluster and its relation to lipid levels in type 2 diabetes mellitus and coronary heart disease: determination of a novel susceptible haplotype”. Diab Vasc Dis Res 4 (2): 124–29. doi:10.3132/dvdr.2007.030PMID 17654446.

In 2013 we reported on the discovery that there is a

Genetic Associations with Valvular Calcification and Aortic Stenosis

N Engl J Med 2013; 368:503-512

February 7, 2013DOI: 10.1056/NEJMoa1109034

METHODS

We determined genomewide associations with the presence of aortic-valve calcification (among 6942 participants) and mitral annular calcification (among 3795 participants), as detected by computed tomographic (CT) scanning; the study population for this analysis included persons of white European ancestry from three cohorts participating in the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium (discovery population). Findings were replicated in independent cohorts of persons with either CT-detected valvular calcification or clinical aortic stenosis.

CONCLUSIONS

Genetic variation in the LPA locus, mediated by Lp(a) levels, is associated with aortic-valve calcification across multiple ethnic groups and with incident clinical aortic stenosis. (Funded by the National Heart, Lung, and Blood Institute and others.)

SOURCE:

N Engl J Med 2013; 368:503-512

Related Research by Author & Curator of this article:

Artherogenesis: Predictor of CVD – the Smaller and Denser LDL Particles

Cardiovascular Biomarkers

Genetics of Conduction Disease: Atrioventricular (AV) Conduction Disease (block): Gene Mutations – Transcription, Excitability, and Energy Homeostasis

Genomics & Genetics of Cardiovascular Disease Diagnoses: A Literature Survey of AHA’s Circulation Cardiovascular Genetics, 3/2010 – 3/2013

Hypertriglyceridemia concurrent Hyperlipidemia: Vertical Density Gradient Ultracentrifugation a Better Test to Prevent Undertreatment of High-Risk Cardiac Patients

Hypertension and Vascular Compliance: 2013 Thought Frontier – An Arterial Elasticity Focus

Personalized Cardiovascular Genetic Medicine at Partners HealthCare and Harvard Medical School

Genomics Orientations for Individualized Medicine Volume One

Market Readiness Pulse for Advanced Genome Interpretation and Individualized Medicine

We present below the MARKET LEADER in Interpretation of the Genomics Computations Results in the emerging new ERA of Medicine:  Genomic Medicine, Knome.com and its home grown software power house.

A second Case study in the  Advanced Genome Interpretation and Individualized Medicine presented following the Market Leader, is the Genome-Phenome Analyzer by SimulConsult, A Simultaneous Consult On Your Patient’s Diagnosis, Chestnut Hill, MA

 

2012: The Year When Genomic Medicine Started Paying Off

Luke Timmerman

An excerpt of an interesting article mentioning Knome [emphasis ours]…

Remember a couple of years ago when people commemorated the 10-year anniversary of the first draft human genome sequencing? The storyline then, in 200, was that we all went off to genome camp and only came home with a lousy T-shirt. Society, we were told, invested huge scientific resources in deciphering the code of life, and there wasn’t much of a payoff in the form of customized, personalized medicine.

That was an easy conclusion to reach then, when personalized medicine advocates could only point to a couple of effective targeted cancer drugs—Genentech’s Herceptin and Novartis’ Gleevec—and a couple of diagnostics. But that’s changing. My inbox the past week has been full of analyst reports from medical meetings, which mostly alerted readers to mere “incremental” advances with a number of genomic-based medicines and diagnostics. But that’s a matter of focusing on the trees, not the forest. This past year, we witnessed some really impressive progress from the early days of “clinical genomics” or “medical genomics.” The investment in deep understanding of genomics and biology is starting to look visionary.

The movement toward clinical genomics gathered steam back in June at the American Society of Clinical Oncology annual meeting. One of the hidden gem stories from ASCO was about little companies like Cambridge, MA-based Foundation Medicine and Cambridge, MA-based Knome that started seeing a surprising surge in demand from physicians for their services to help turn genomic data into medical information. The New York Times wrote a great story a month later about a young genomics researcher at Washington University in St. Louis who got cancer, had access to incredibly rich information about his tumors, and—after some wrestling with his insurance company—ended up getting a targeted drug nobody would have thought to prescribe without that information. And last month, I checked back on Stanford University researcher Mike Snyder, who made headlines this year using a smorgasbord of “omics” tools to correctly diagnose himself early with Type 2 diabetes, and then monitor his progress back into a healthy state–read the entire article

http://www.knome.com/knome-blog/2012-the-year-when-genomic-medicine-started-paying-off/

Knome and Real Time Genomics Ink Deal to Integrate and Sell the RTG Variant Platform on knoSYS™100 System

Partnership to bring accurate and fast genome analysis to translational researchers

CAMBRIDGE, MA –  May 6, 2013 – Knome Inc., the genome interpretation company, and Real Time Genomics, Inc., the genome analytics company, today announced that the Real Time Genomics (RTG) Variant platform will be integrated into every shipment of the knoSYS™100 interpretation system. The agreement enables customers to easily purchase the RTG analytics engine as an upgrade to the system. The product will combine two world-class commercial platforms to deliver end-to-end genome analytics and interpretation with superior accuracy and speed. Financial terms of the agreement were not disclosed.

“In the past year demand for genome interpretation has surged as translational researchers and clinicians adopt sequencing for human disease discovery and diagnosis,” said Wolfgang Daum, CEO of Knome. “Concomitant with that demand is the need for accurate and easy-to-use industrial grade analysis that meets expectations of clinical accuracy. The RTG platform is both incredibly fast and truly differentiating to customers doing family studies, and we are excited to add such a powerful platform to the knoSYS ecosystem.”

The partnership simplifies the purchasing process by allowing knoSYS customers to purchase the RTG platform directly from Knome sales representatives.

“The Knome system is a perfect complementary channel to further expand our commercial effort to bring the RTG platform to market,” said Steve Lombardi, CEO of Real Time Genomics. “Knome has built a recognizable brand around human clinical genome interpretation, and by delivering the RTG platform within their system, both companies are simplifying genomics to help customers understand human disease and guide clinical actions.”

About Knome

Knome Inc. (www.knome.com) is a leading provider of human genome interpretation systems and services. We help clients in two dozen countries identify the genetic basis of disease, tumor growth, and drug response. Designed to accelerate and industrialize the process of interpreting whole genomes, Knome’s big data technologies are helping to pave the healthcare industry’s transition to molecular-based, precision medicine.

About Real Time Genomics

Real Time Genomics (www.realtimegenomics.com) has a passion for genomics.  The company offers software tools and applications for the extraction of unique value from genomes.  Its competency lies in applying the combination of its patented core technology and deep computational expertise in algorithms to solve problems in next generation genomic analysis.  Real Time Genomics is a private San Francisco based company backed by investment from Catamount Ventures, Lightspeed Venture Partners, and GeneValue Ltd.

http://www.knome.com/knome-blog/knome-and-real-time-genomics-ink-deal-to-integrate-and-sell-the-rtg-variant-platform-on-knosys100-system/

Direct-to-Consumer Genomics Reinvents Itself

Malorye Allison

An excerpt of an interesting article mentioning Knome [emphasis ours]:

Cambridge, Massachusetts–based Knome made one of the splashiest entries into the field, but has now turned entirely to contract research. The company began providing DTC whole-genome sequencing to independently wealthy individuals at a time when the price was still sky high. The company’s first client, Dan Stoicescu, was a former biotech entrepreneur who paid $350,000 to have his genome sequenced in 2008 so he could review it “like a stock portfolio” as new genetic discoveries unfolded4. About a year later, the company was auctioning off a genome, with such frills as a dinner with renowned Harvard genomics researcher George Church, at a starting price of $68,000; at the time, a full-genome sequence came at the price of $99,000, indicating that the cost of genome sequencing has been plummeting steadily.

Now, the company’s model is very different. “We stopped working with the ‘wealthy healthy’ in 2010,” says Jonas Lee, Knome’s chief marketing officer. “The model changed as sequencing changed.” The new emphasis, he says, is now on using Knome’s technology and technical expertise for genome interpretation. Knome’s customers are researchers, pharmaceutical companies and medical institutions, such as Johns Hopkins University School of Medicine in Baltimore, which in January signed the company up to interpret 1,000 genomes for a study of genetic variants underlying asthma in African American and African Caribbean populations.

Knome is trying to advance the clinical use of genomics, working with groups that “want to be prepared for what’s ahead,” Lee says. “We work with at least 50 academic institutions and 20 pharmaceutical companies looking at variants and drug response.” Cancer and idiopathic genetic diseases are the first sweet spots for genomic sequencing, he says. Although cancer genomics has been hot for a while, a recent string of discoveries of Mendelian diseases5 made by whole-genome sequencing has lit up that field, too. Lee is also confident, however, that “chronic diseases like heart disease are right behind those.” The company also provides software tools. The price for its KnomeDiscovery sequencing and analysis service starts at about $12,000 per sample–read the entire article here.

http://www.knome.com/knome-blog/direct-to-consumer-genomics-reinvents-itself/

Regenesis: How Synthetic Biology Will Reinvent Nature and Ourselves

VIEW VIDEO

http://www.colbertnation.com/the-colbert-report-videos/419824/october-04-2012/george-church

 

Knome Software Makes Sense of the Genome

The startup’s software takes raw genome data and creates a usable report for doctors.

DNA decoder: Knome’s software can tease out medically relevant changes in DNA that could disrupt individual gene function or even a whole molecular pathway, as is highlighted here—certain mutations in the BRCA2 gene, which affects the function of many other genes, can be associated with an increased risk of breast cancer.

A genome analysis company called Knome is introducing software that could help doctors and other medical professionals identify genetic variations within a patient’s genome that are linked to diseases or drug response. This new product, available for now only to select medical institutions, is a patient-focused spin on Knome’s existing products aimed at researchers and pharmaceutical companies. The Knome software turns a patient’s raw genome sequence into a medically relevant report on disease risks and drug metabolism. The software can be run within a clinic’s own network—rather than in the cloud, as is the case with some genome-interpretation services—which keeps the information private.

Advances in DNA sequencing technology have sharply reduced the amount of time and money required to identify all three billion base pairs of DNA in a person’s genome. But the use of genomic information for medical decisions is still limited because the process creates such large volumes of data. Less than five years ago, Knome, based in Cambridge, Massachusetts, made headlines by offering what seemed then like a low price—$350,000—for a genome sequencing and profiling package. The same service now costs just a few thousand dollars.

Today, genome profiling has two main uses in the clinic. It’s part of the search for the cause of rare genetic diseases, and it generates tumor-specific profiles to help doctors discover the weaknesses of a patient’s particular cancer. But within a few years, the technique could move beyond rare diseases and cancer. The information gleaned from a patient’s genome could explain the origin of specific disease, could help save costs by allowing doctors to pretreat future diseases, or could improve the effectiveness and safety of medications by allowing doctors to prescribe drugs that are tuned to a person’s ability to metabolize drugs.

But teasing out the relevant genetic information from a patient’s genome is not trivial. To find the particular genetic variant that causes a specific disease or drug response can require expertise from many disciplines—from genetics to statistics to software engineering—and a lot of time. In any given patient’s genome, millions of places in that genome will differ from the standard of reference. The vast majority of these differences, or variants, will be unrelated to a patient’s medical condition, but determining that can take between 20 minutes and two hours for each variant, says Heidi Rehm, a clinical geneticist who directs the Laboratory for Molecular Medicine at Partners Healthcare Center for Personalized Genetic Medicine in Boston, and who will soon serve on the clinical advisory board of Knome. “If you scale that to … millions of variants, it becomes impossible.”

A software package like Knome’s can help whittle down the list based on factors such as disease type, the pattern of inheritance in a family, and the effects of given mutations on genes. Other companies have introduced Web- or cloud-based services to perform such an analysis, but Knome’s software suite can operate within a hospital’s network, which is critically important for privacy-concerned hospitals.

The greatest benefit of the widespread adoption of genomics in the clinic will come from the “clinical intelligence” doctors gain from networks of patient data, says Martin Tolar, CEO of Knome. Information about the association between certain genetic variants and disease or drug response could be anonymized—that is, no specific patient could be tied to the data—and shared among large hospital networks. Knome’s software will make it easy to share that kind of information, says Tolar.

“In the future, you could be in the situation where your physician will be able to pull the most appropriate information for your specific case that actually leads to recommendations about drugs and so forth,” he says.

http://www.technologyreview.com/news/428179/knome-software-makes-sense-of-the-genome/

An End-to-end Human Genome Interpretation System

The knoSYS™100 seamlessly integrates an interpretation application (knoSOFT) and informatics engine (kGAP) with a high-performance grid computer. Designed for whole genome, exome, and targeted NGS data, the knoSYS™100 helps labs quickly go “from reads to reports.”


 


Advanced Interpretation and Reporting Software

The knoSYS™100 ships with knoSOFT, an advanced application for managing sequence data through the informatics pipeline, filtering variants, running gene panels, classifying/interpreting variants, and reporting results.

knoSOFT has powerful and scalable multi-sample comparison features–capable of performing family studies, tumor/normal studies, and large case-control comparisons of hundreds of whole genomes.

Multiple simultaneous users (10) are supported, including technicians running sequence data through informatics pipeline, developers creating next-generation gene panels, geneticists researching causal variants, and production staff processing gene panels.

http://www.knome.com/knosys-100-overview/

Publications

View our collection of journal articles and genome research papers written by Knome employees, Knome board members, and other industry experts.

Publications by Knome employees and board members

The Top Two Axes of Variation of the Combined Dataset (MS, BD, PD, and IBD)

21 Aug 2012

Discerning the Ancestry of European Americans in Genetic Association Studies

Co-authored by Dr. David Goldstein, Clinical and Scientific board member for Knome

Author summary: Genetic association studies analyze both phenotypes (such as disease status) and genotypes (at sites of DNA variation) of a given set of individuals. … more

Pedigree and genetic risk prediction workflow

20 Aug 2012

Phased Whole-Genome Genetic Risk in a Family Quartet Using a Major Allele Reference Sequence

Co-authored by Dr. George Church and Dr. Heidi Rehm, Clinical and Scientific Board Members for Knome

Author summary: An individual’s genetic profile plays an important role in determining risk for disease and response to medical therapy. The development of technologies that facilitate rapid whole-genome sequencing will provide unprecedented power in the estimation of disease risk. Here we develop methods to characterize genetic determinants of disease risk and … more

20 Aug 2012

A Genome-Wide Investigation of SNPs and CNVs in Schizophrenia

Co-authored by Dr. David Goldstein, Clinical and Scientific board member for Knome

Author summary: Schizophrenia is a highly heritable disease. While the drugs commonly used to treat schizophrenia offer important relief from some symptoms, other symptoms are not well treated, and the drugs cause serious adverse effects in many individuals. This has fueled intense interest over the years in identifying genetic contributors to … more

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20 Aug 2012

Whole-Genome Sequencing of a Single Proband Together with Linkage Analysis Identifies a Mendelian Disease Gene

Co-authored by Dr. David Goldstein, Clinical and Scientific board member for Knome

Author summary: Metachondromatosis (MC) is an autosomal dominant condition characterized by exostoses (osteochondromas), commonly of the hands and feet, and enchondromas of long bone metaphyses and iliac crests. MC exostoses may regress or even resolve over time, and short stature … more

19 Aug 2012

Exploring Concordance and Discordance for Return of Incidental Findings from Clinical Sequencing Co-authored by Dr. Heidi Rehm, Clinical and Scientific board member for Knome

Introduction: There is an increasing consensus that whole-exome sequencing (WES) and whole-genome sequencing (WGS) will continue to improve in accuracy and decline in price and that the use of these technologies will eventually become an integral part of clinical medicine.1–7 … more

Publications by industry experts and thought-leaders

22 Aug 2012

Rate of De Novo Mutations and the Importance of Father’s Age to Disease Risk

Augustine Kong, Michael L. Frigge, Gisli Masson, Soren Besenbacher, Patrick Sulem, Gisli Magnusson, Sigurjon A. Gudjonsson, Asgeir Sigurdsson, Aslaug Jonasdottir, Adalbjorg Jonasdottir, Wendy S. W. Wong, Gunnar Sigurdsson, G. Bragi Walters, Stacy Steinberg, Hannes Helgason, Gudmar Thorleifsson, Daniel F. Gudbjartsson, Agnar Helgason, Olafur Th. Magnusson, Unnur Thorsteinsdottir, & Kari Stefansson

Abstract: Mutations generate sequence diversity and provide a substrate for selection. The rate of de novo mutations is therefore of major importance to evolution. Here we conduct a study of genome-wide mutation rates by sequencing the entire genomes of 78 … more

15 Aug 2012

Passenger Deletions Generate Therapeutic Vulnerabilities in Cancer

Florian L. Muller, Simona Colla, Elisa Aquilanti, Veronica E. Manzo, Giannicola Genovese, Jaclyn Lee, Daniel Eisenson, Rujuta Narurkar, Pingna Deng, Luigi Nezi, Michelle A. Lee, Baoli Hu, Jian Hu, Ergun Sahin, Derrick Ong, Eliot Fletcher-Sananikone, Dennis Ho, Lawrence Kwong, Cameron Brennan, Y. Alan Wang, Lynda Chin, & Ronald A. DePinho

Abstract: Inactivation of tumour-suppressor genes by homozygous deletion is a prototypic event in the cancer genome, yet such deletions often encompass neighbouring genes. We propose that homozygous deletions in such passenger genes can expose cancer-specific therapeutic vulnerabilities when the collaterally … more

1 Jul 2012

Structural Diversity and African Origin of the 17q21.31 Inversion Polymorphism

Karyn Meltz Steinberg, Francesca Antonacci, Peter H Sudmant, Jeffrey M Kidd, Catarina D Campbell, Laura Vives, Maika Malig, Laura Scheinfeldt, William Beggs, Muntaser Ibrahim, Godfrey Lema, Thomas B Nyambo, Sabah A Omar, Jean-Marie Bodo, Alain Froment, Michael P Donnelly, Kenneth K Kidd, Sarah A Tishkoff, & Evan E Eichler

Abstract: The 17q21.31 inversion polymorphism exists either as direct (H1) or inverted (H2) haplotypes with differential predispositions to disease and selection. We investigated its genetic diversity in 2,700 individuals, with an emphasis on African populations. We characterize eight structural haplotypes … more

http://www.knome.com/publications/

knome’s Systems & Software

Technical specifications

Connections and communications

Two networks: 40-Gigabit Infiniband QDR via a Mellanox Switch for storage traffic and HP ProCurve switch for network traffic

High performance computing cluster

Four nodes, each node with two 8-core/16 thread, 2.4Ghz, 64 bit Intel® Xeon® E5-2660 processor with 20MB cache, 128GB of DDR3 ECC 1600 memory; 2x2TB SATA drives (7,200RPM)

Metadata server

2x2TB 3.5″ drives with 6GB/sec SATA, RAID 1 and 2x300GB SSD (RAID 1)

Object storage server

Lustre array: Two 12x4TB arrays of 12 3.5″ drives with 6GB/sec serial SATA channels, each OSS powered by a 6-core Intel Xeon 64-bit processor running at 20GHz with 32GB RAM.

knoSYS_server

96TB total, 64TB useable storage (redundancy for failure tolerance). Expandable 384TB total.

Data sources

Reference genome GRCh37 (HG19)

dbSNP, v137

Condel (SIFT and PolyPhen-2)

HPO

OMIM

Exome Variant server, with allelisms and allele frequencies

1000 Genomes, with allelisms and allele frequencies

Human Gene Mutation db (HGMD)

Phastcons 46, mammalian conservation

PhyloP

Input/output formats

Input formats: kGAP accepts Illumina FASTQ and VCF 4.1 files as inputs

Output formats: annotated VCF files

Electrical and operating requirements

Line voltage: 110V to 120V AC, 200-240V (single phase)

Frequency: 50Hz to 60Hz

Current: 30A, RoSH compliant

Connection: NEMA L5-30

Operating temperature: 50° to 95° F

UPS included

Maximum operating altitude: 10,000 feet

Power consumption: 2,800 VA (peak)

Size and weight

Height 49.2 Inches (1250 mm)
Width 30.7 Inches (780 mm)
Depth 47.6 Inches (1210 mm)
Weight 394 lbs (179 kg)

Noise generation and heat dissipation

Enclosure provides 28dB of acoustic noise reduction; system suitable for placing in working lab environment

7200w of active heat dissipation

Included in the package

knoSYS™100 hardware

Knome software: knoSOFT, kGAP

Operating system: Linux (CentOS 6.3)

http://www.knome.com/knosys-100-specifications/

Our research services group uses a set of advanced software tools designed for whole genome and exome interpretation. These tools are also available to our clients through our knomeBASE informatics service. In addition to various scripts, libraries, and conversion utilities, these tools include knomeVARIANTS and knomePATHWAYS.

knomeVARIANTS

Genome_software_knomeVARIANTS

knome VARIANTS is a query kit that lets users search for candidate causal variants in studied genomes. It includes a query interface (see above), scripting libraries, and data conversion utilities.

Users select cases and controls, input a putative inheritance mode, and add sensible filter criteria (variant functional class, rarity/novelty, location in prior candidate regions, etc.) to automatically generate a sorted short-list of leading candidates. The application includes a SQL query interface to let users query the database as they wish, including by complex or novel sets of criteria.

In addition to querying, the application lets users export subsets of the database for viewing in MS Excel. Subsets can be output that target common research foci, including the following:

  • Sites implicated in phenotypes, regardless of subject genotypes
  • Sites where at least one studied genome mismatches the reference
  • Sites where a particular set of one or more genomes, but no other genomes, show a novel variant
  • Sites in phenotype-implicated genes
  • Sites with nonsense, frameshift, splice-site, or read-through variants, relative to reference
  • Sites where some but not all subject genome were called

knomePATHWAYS

Genome_software_knomePATHWAYS

knomePATHWAYS is a visualization tool that overlays variants found in each sample genome onto known gene interaction networks in order to help spot functional interactions between variants in distinct genes, and pathways enriched for variants in cases versus controls, differential drug responder groups, etc.

knomePATHWAYS integrates reference data from many sources, including GO, HPRD, and MsigDB (which includes KEGG and Reactome data). The application is particularly helpful in addressing higher-order questions, such as finding candidate genes and protein pathways, that are not readily addressed from tabular annotation data alone.

http://www.knome.com/interpretation-toolkit/

Genome-Phenome Analyzer by SimulConsult

A Simultaneous Consult On Your Patient’s Diagnosis

Clinicians can get a “simultaneous consult” about their patient’s diagnosis using SimulConsult’s diagnostic decision support software.

Using the free “phenome” version, medical professionals can enter patient findings into the software and get an initial differential diagnosis and suggestions about other useful findings, including tests.  The database used by the software has > 4,000 diagnoses, most complete for genetics and neurology.  It includes all genes in GeneTests and all diseases in GeneReviews.  The information about diseases is entered by clinicians, referenced to the literature and peer-reviewed by experts.  The software takes into account pertinent negatives, temporal information, and cost of tests, information ignored in other diagnostic approaches.  It transforms medical diagnosis by lowering costs, reducing errors and eliminating the medical diagnostic odysseys experienced by far too many patients and their families.

http://www.simulconsult.com/index.html

Using the “genome-phenome analyzer” version, a lab can combine a genome variant table with the phenotypic data entered by the referring clinician, thereby using the full power of genome + phenome to arrive at a diagnosis in seconds.  An innovative measure of pertinence of genes focuses attention on the genes accounting for the clinical picture, even if more than one gene is involved.  The referring clinician can use the results in the free phenome version of the software, for example adding information from confirmatory tests or adding new findings that develop over time.  For details, click here.

http://www.simulconsult.com/genome/index.html

Michael M. Segal MD, PhD, Founder,Chairman and Chief Scientist.  Dr. Segal did his undergraduate work at Harvard and his MD and PhD at Columbia, where his thesis project outlined rules for the types of chemical synapses that will form in a nervous system.  After his residency in pediatric neurology at Columbia, he moved to Harvard Medical School, where he joined the faculty and developed the microisland system for studying small numbers of brain neurons in culture.  Using this system, he developed a simplified model of epilepsy, work that won him national and international young investigator awards, and set the stage for later work on the molecular mechanism of attention deficit disorder.  Dr. Segal has a long history of interest in computers, and patterned the SimulConsult software after the way that experienced clinicians actually think about diagnosis.  He is on the Electronic Communication Committee of the Child Neurology Society and the Scientific Program Committee of the American Medical Informatics Association.

http://www.simulconsult.com/company/management.html

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Stephen J. Williams, Ph.D. Writer, Curator

Rational Design of Allosteric Inhibitors and Activators Using the Population-Shift Model: In Vitro Validation and Application to an Artificial Biosensor.(1)

The population-shift mechanism allows for the re-engineering of biosensors utilizing the concept of allosterism to allow for a structure-based switching on/off capacity into biosensors, “smart-biomaterials, and other artificial biotechnologies.  A fundamental problem in the design of valuable biosensors has been limited number of biomolecules that produce enough signal (for example emission of light, etc.) upon binding to its target.  However this issue has been resolved with the development of biosensors in which target binding is transduced into a quantifiable optical or electrochemical signal after coupling with conformational changes in the receptor (for review see (2)).

There are a few advantages to this biosensor design:

  • Works well in complex samples, such as blood, serum; Low background noise from nonspecific adsorption from interfering biomolecules
  • Supports real-time monitoring- allosteric biosensors do not rely on additional reagents and are rapidly reversible
  • Binding of the receptors is dependent on an unfavorable conformational change, so there is possibility to fine tune this conformational switch.

Concept of allosterism

Allosterism is generally defined as a change in the activity and conformation of an enzyme/protein resulting from the binding of a compound at a site on the enzyme other than the active binding site.  Allosterism plays a critical role in the control and integration of molecular events in biological systems.  Frequently, allosterism is seen with multisubunit proteins/enzymes, where subunit interaction is necessary for allosteric effects, and is distal to the binding site.  Examples of allosteric systems include hemoglobin, phosphofructose kinase and many

NAD+ -dependent dehydrogenases.  For example, the binding of O2 to hemoglobin is enhanced the binding of addition O2, the Bohr effect (the affinity of hemoglobin to O2 depends on H+), and the metabolic product diphosphoglycerate regulates O2 binding.

Types of DNA Biosensors

DNA-based biosensors rely on the hybridization of complementary DNA.  Many optical biosensors based on the phenomenon of surface plasmon resonance (SPR) utilize a property of and other materials; specifically that a thin layer of gold on a high refractive index glass surface can absorb laser light, producing electron waves (surface plasmons) on the gold surface. This occurs only at a specific angle and wavelength of incident light and is highly dependent on the surface of the gold, such that binding of a target analyte to a receptor on the gold surface produces a measurable signal.

Electrochemical biosensors are normally based on enzymatic catalysis of a reaction that produces or consumes electrons (such enzymes are rightly called redox enzymes). The sensor substrate usually contains three electrodes; a reference electrode, a working electrode and a counter electrode. The target analyte is involved in the reaction that takes place on the active electrode surface, and the reaction may cause either electron transfer across the double layer (producing a current) or can contribute to the double layer potential (producing a voltage). We can either measure the current (rate of flow of electrons is now proportional to the analyte concentration) at a fixed potential or the potential can be measured at zero current (this gives a logarithmic response). The label-free and direct electrical detection of small peptides and proteins is possible by their intrinsic charges using bio-functional ion-sensitive field-effect transistors.

Piezoelectric sensors utilize crystals which undergo an elastic deformation when an electrical potential is applied to them. An alternating potential produces a standing wave in the crystal at a characteristic frequency. This frequency is highly dependent on the elastic properties of the crystal, such that if a crystal is coated with a biological recognition element the binding of a (large) target analyte to a receptor will produce a change in the resonance frequency, which gives a binding signal. In a mode that uses surface acoustic waves (SAW), the sensitivity is greatly increased.

Type Biological Element Transducer
OpticalFiber Optics

Surface plasmon resonance

Biomolecular interactionAnalysis

Raman spectroscopy

DNA Optical fiberResonant mirror

BIAcore

SERG probe

Electrochemical DNA Carbon paste electrodes
Piezoelectric     FrequencyAcoustics DNA CrystalsCrystals

The most popular of optical DNA biosensors is molecular beacons, DNA probes containing a fluorescent moiety and a quencher of on the same DNA strand. This probe has an internal complementary sequence so as the DNA folds into a secondary structure, most likely a stem-loop or hairpin structure, so the fluor and quencher are held in close proximity, quenching the fluorescent signal.  Target hybridization opens up the stem-loop structure, thereby emitting the fluorescent signal. A typical molecular beacon probe is 25 nucleotides long. A typical molecular beacon structure can be divided in 4 parts:

  • Loop: This is the 18–30 base pair region of the molecular beacon which is complementary to the target sequence.
  • Stem: The beacon stem is formed by the attachment, to both termini of the loop, of two short (5 to 7 nucleotide residues) oligonucleotides that are complementary to each other.
  • 5′ fluorophore: At the 5′ end of the molecular beacon, a fluorescent dye is covalently attached.
  • 3′ quencher (non fluorescent): The quencher dye is covalently attached to the 3′ end of the molecular beacon. When the beacon is in closed loop shape, the quencher resides in proximity to the fluorophore, which results in quenching the fluorescent emission of the latter.

Structure of a molecular beacon. Description and figure from Wikipedia (5).

Common applications of DNA biosensors include cDNA microarray and Affymetrix GeneChip™ technology.

Ricci et al. provide a proof-of –principle paper to demonstrate how allosteric switching can be introduced into biosensors(1). The authors engineered allosteric inhibition into a molecular beacon by the addition of two single-stranded tails that serve as an allosteric site where binding of an inhibitor sequence would bridge the two tails and prevent target binding (holding the probe in the inactivated state).  Using this approach the authors demonstrated over a three-fold increase in the dynamic range of the beacon.

The authors also demonstrated this effect, with an allosterically activated biosensor in which “allosteric activation was engineered into a molecular beacon using one single-stranded tail as an allosteric binding site.  The activator sequence binding to this tail partially invades the stem, destabilizing the nonbinding state and thus improving the target affinity.”  Thus this population-shift mechanism allows for the design of sensors that can be allosterically activated using activators that destabilize the beacon’s nonbinding conformation, increasing the beacon’s dynamic range without compromising target specificity. Finally the authors suggest that population-shift mechanisms can be engineered into many different types of “switching” biosensors including aptamer-based and protein-based sensors (3,4).

1.            Ricci, F., Vallee-Belisle, A., Porchetta, A., and Plaxco, K. W. (2012) Journal of the American Chemical Society 134, 15177-15180

2.            Vallee-Belisle, A., and Plaxco, K. W. (2010) Current opinion in structural biology 20, 518-526

3.            White, R. J., Rowe, A. A., and Plaxco, K. W. (2010) The Analyst 135, 589-594

4.            Kohn, J. E., and Plaxco, K. W. (2005) Proceedings of the National Academy of Sciences of the United States of America 102,   10841-10845

5.            http://en.wikipedia.org/wiki/Molecular_beacon

Other research papers on Biosensors were published on this Scientific Web site as follows:

Measuring glucose without needle pricks: nano-sized biosensors made the test easy

New Definition of MI Unveiled, Fractional Flow Reserve (FFR)CT for Tagging Ischemia

New Drug-Eluting Stent Works Well in STEMI

Sensor detects glucose in saliva, tears for diabetes testing

Synthesizing Synthetic Biology: PLOS Collections

Competition in the Ecosystem of Medical Devices in Cardiac and Vascular Repair: Heart Valves, Stents, Catheterization Tools and Kits for Open Heart and Minimally Invasive Surgery (MIS)

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Author: Stephen J. Williams, PhD

     The finding that a substance, derived from vascular endothelium, that could control vascular tone and induce smooth muscle relaxation, led to the discovery of nitric oxide (NO) as a major physiological mediator (1) in many cell types and processes.  Other investigators, working with platelets, determined that nitric oxide is a potent inhibitor, via an autocrine pathway, of platelet aggregation and adhesion to the vessel wall (2).  Nitric oxide is also an important regulator of neurotransmission in the nonadrenergic-noncholinergic system in gastric tissue (3,4).   In addition nitric oxide is involved in macrophage-mediated cytotoxicity, (5)based on the observation the cytotoxic action of macrophages required external arginine, which summarily was converted to citrulline, releasing  the nitric oxide involved in the cell-killing process.  The above physiological responses represent highly regulated, short-term responses that, as seen with classical receptor-based agonists such as epinephrine, terminate once the agonist (NO) is removed.   Given the short half-life of nitric oxide and these rapid physiologic responses, nitric oxide has been given the role of a second messenger within the cell.

However nitric oxide also produces some physiologically, pharmacologically, and pathologically relevant changes, lasting longer time periods, which is the main focus of this article.  For example, nitric oxide is important in the development of long term potentiation (a model of learning and memory), neural plasticity, and neurite outgrowth, revealing nitric oxide can induce more permanent changes in cellular and tissue reorganization (6-9).  Other pathologic and toxicological responses to nitric oxide include cell death from excitotoxic amino acids (glutamate, kainite), oxidative stress, DNA and protein damage, and disease progression in Alzheimer’s disease, epilepsy, aging, apoptosis and Huntington’s chorea (10-12).  These effects persist over longer time frames than the effects which most second messenger systems occur.  These cellular changes can be described by biochemical changes on protein and nucleic acid modification, metabolism (13-15), DNA synthesis and replication, and molecular and organelle reorganization.  The pharmacological and toxicological implications of such cellular changes are inherent in the persistent effects of nitric oxide on biological systems.  The mechanism of nitric oxide-induced physiology and toxicology had been assumed to involve the stimulation of soluble guanylate cyclase, raising intracellular cGMP levels.  As discussed further, this mechanism of action does not account for all the actions of nitric oxide, especially in nitric oxide-induced pathologies.  Other mechanisms of action include post-translational modifications of proteins such as S-nitrosylations, ADP-ribosylations, and a unique nonenzymatic covalent attachment of NAD+ to the regulatory site of glyceraldehyde 3-phosphate dehydrogenase (GAPDH), a reaction specific to this dehydrogenase.  GAPDH is a true multifunctional protein involved in diverse cellular functions such as glycolysis, endocytosis, RNA processing and stability, DNA replication and repair, and involved in apoptosis.  GAPDH has been implicated in trinucleotide repeat neurodegenerative disorders such as Huntington’s disease, spinocerebellar ataxia, via binding to the polyglutamated forms of huntingtin and ataxin, protein modifications only seen in these respective diseases. GAPDH has also been implicated in Alzheimer’s disease as well, in genetic linkage studies as well as a β-amyloid precursor protein binding partner (for reviews see (16-20)).

Next to phosphorylation, ADP ribosylation and NAD+ modifications are the second most  common enzymatic  protein modifications in nature and regulates many cellular processes in nervous tissue, tumoral cell growth, cytoskeletal function, cell death and apoptosis, immune function, and bacterial cytotoxicity(21,22). These include poly ADP-ribosylations such as histones in the apoptotic process, and ADP-ribosylation of G-proteins by pertussis and cholera toxin. Interestingly, nitric oxide and other oxidants promote nonenzymatic ribosylation of proteins such as GAPDH.  Unlike the enzymatic reactions, this modification is covalent and generally considered irreversible and either involves nitrosylation of critical reactive cysteine residues or nitric oxide-mediated attachment of the whole NAD+ moiety, a reaction akin to aging of enzymes by reactive oxygen species.  There have been multiple intracellular targets of nitric oxide, with the result of inhibiting activity and/or protein interactions.  These include mitochondrial enzymes such as aconitase (23) and cytochrome oxidase (24), cytosolic enzymes such as cyclooxygenase and affect heme-containing proteins hemoglobin and myoglobin.  Such nitric oxide mediated effects on these systems were cGMP-independent, therefore independent of nitric oxide synthase.  The inhibition of GAPDH glycolytic activity by nitric oxide and NO-mediated NAD+ modification has been widely studied (21,25) and widely accepting to be important in nitric oxide mediated pathology (16,26-33).

So can this NO-NAD+ modification of GAPDH be useful as a therapeutic target for diseases such as Huntington’s, Alzheimer’s or other nitric oxide associated pathologies?   This is as much an intriguing idea as one fraught with caveats and technical issues.   First there is ample evidence that alterations of GAPDH structure/function exist in these neurodegenerative diseases and evidence that this type of modification may be important in the etiology of such diseases(34-41).

Second, as mentioned before, this modification is unique for GAPDH and would offer a disease-specific target(42).  Third, and most interesting, is the multifunctionality of GAPDH, therefore such modification has the possibility for affecting many processes involved in the disease progression.    However there is the big caveat and problem.  Such NO-NAD+ modifications are a covalent reaction, thought to be irreversible.  Studies on purified GAPDH reveal such modification is released by chemicals that can reduce the cysteine covalent bond such as HgCl2 or NaOH treatment(17).  However such treatment would be impractical for in-vivo use.  The ideal situation would be the discovery of an enzyme activity comparable to phosphatases which could enzymatically release the NO-NAD+ modification from GAPDH. A proof of concept experiment could involve creation of a genetically engineered enzyme capable of this reaction.  Therapeutic use of such an enzyme would depend of course on bioavailability.  Interestingly there has been evidence of cellular NO reductase activities, capable of removing the S-nitrosylation on reactive thiols.  Enzymes with denitrosylation activities include the thioredoxin system, superoxide dismutase, and xanthine oxidoreductase (34-40).  Possible therapeutic strategies may include regulation of these intracellular reductase activities.

1.            Furchgott, R. F., and Vanhoutte, P. M. (1989) FASEB journal : official publication of the Federation of American Societies for Experimental Biology 3, 2007-2018

2.            Radomski, M. W., Zakar, T., and Salas, E. (1996) Methods in enzymology 269, 88-107

3.            Barbier, A. J., and Lefebvre, R. A. (1993) The Journal of pharmacology and experimental therapeutics 266, 172-178

4.            Dick, J. M., and Lefebvre, R. A. (1997) Naunyn-Schmiedeberg’s archives of pharmacology 356, 488-494

5.            Hibbs, J. B., Jr., Taintor, R. R., Vavrin, Z., and Rachlin, E. M. (1988) Biochemical and biophysical research communications 157, 87-94

6.            Sunico, C. R., Portillo, F., Gonzalez-Forero, D., and Moreno-Lopez, B. (2005) The Journal of neuroscience : the official journal of the Society for Neuroscience 25, 1448-1458

7.            Koriyama, Y., Takagi, Y., Chiba, K., Yamazaki, M., Arai, K., Matsukawa, T., Suzuki, H., Sugitani, K., Kagechika, H., and Kato, S. (2011) Journal of neurochemistry 119, 1232-1242

8.            Sen, N., and Snyder, S. H. (2011) Proceedings of the National Academy of Sciences of the United States of America 108, 20178-20183

9.            Zoubovsky, S. P., Pogorelov, V. M., Taniguchi, Y., Kim, S. H., Yoon, P., Nwulia, E., Sawa, A., Pletnikov, M. V., and Kamiya, A. (2011) Biochemical and biophysical research communications 408, 707-712

10.          Brune, B., and Lapetina, E. G. (1995) Genetic engineering 17, 149-164

11.          Brune, B., and Mohr, S. (2001) Current protein & peptide science 2, 61-72

12.          Brune, B., Mohr, S., and Messmer, U. K. (1996) Reviews of physiology, biochemistry and pharmacology 127, 1-30

13.          Galli, F., Rossi, R., Di Simplicio, P., Floridi, A., and Canestrari, F. (2002) Nitric oxide : biology and chemistry / official journal of the Nitric Oxide Society 6, 186-199

14.          Rudkouskaya, A., Sim, V., Shah, A. A., Feustel, P. J., Jourd’heuil, D., and Mongin, A. A. (2010) Free radical biology & medicine 49, 757-769

15.          Borderie, D., Le Marechal, H., Ekindjian, O. G., and Hernvann, A. (2000) Cell biology international 24, 285-289

16.          Mazzola, J. L., and Sirover, M. A. (2002) Neurotoxicology 23, 603-609

17.          Williams, S. J., and Sirover, M. A. (1999) Mechanism of Nitric Oxide-Protein Interactions: Species Specific NO-NAD+ Modification and Kinetic Alteration of the Glycolytic Protein Glyceraldehyde 3-Phosphate Dehydrogenase. Temple University, Temple University Press

18.          Sirover, M. A. (2005) Journal of cellular biochemistry 95, 45-52

19.          Sirover, M. A. (2011) Biochimica et biophysica acta 1810, 741-751

20.          Sirover, M. A. (2012) Journal of cellular biochemistry 113, 2193-2200

21.          McDonald, L. J., and Moss, J. (1993) Proceedings of the National Academy of Sciences of the United States of America 90, 6238-6241

22.          McDonald, L. J., and Moss, J. (1994) Molecular and cellular biochemistry 138, 201-206

23.          Drapier, J. C., and Hibbs, J. B., Jr. (1996) Methods in enzymology 269, 26-36

24.          Torres, J., Cooper, C. E., and Wilson, M. T. (1998) The Journal of biological chemistry 273, 8756-8766

25.          Dimmeler, S., and Brune, B. (1993) FEBS letters 315, 21-24

26.          Mazzola, J. L., and Sirover, M. A. (2001) Journal of neurochemistry 76, 442-449

27.          Mazzola, J. L., and Sirover, M. A. (2002) Brain research. Molecular brain research 100, 95-101

28.          Mazzola, J. L., and Sirover, M. A. (2003) Biochimica et biophysica acta 1622, 50-56

29.          Mazzola, J. L., and Sirover, M. A. (2003) Journal of neuroscience research 71, 279-285

30.          Mazzola, J. L., and Sirover, M. A. (2004) Journal of neuroscience methods 137, 241-246

31.          Mazzola, J. L., and Sirover, M. A. (2005) Biochimica et biophysica acta 1722, 168-174

32.          Nakaizumi, A., Horie, T., Kida, T., Kurimoto, T., Sugiyama, T., Ikeda, T., and Oku, H. (2012) Cellular and molecular neurobiology 32, 95-106

33.          Nakamura, T., and Lipton, S. A. (2009) Neuron 63, 3-6

34.          Beigi, F., Gonzalez, D. R., Minhas, K. M., Sun, Q. A., Foster, M. W., Khan, S. A., Treuer, A. V., Dulce, R. A., Harrison, R. W., Saraiva, R. M., Premer, C., Schulman, I. H., Stamler, J. S., and Hare, J. M. (2012) Proceedings of the National Academy of Sciences of the United States of America 109, 4314-4319

35.          Benhar, M., Forrester, M. T., Hess, D. T., and Stamler, J. S. (2008) Science 320, 1050-1054

36.          Benhar, M., Forrester, M. T., and Stamler, J. S. (2009) Nature reviews. Molecular cell biology 10, 721-732

37.         Duan, S., and Chen, C. (2007) Cellular & molecular immunology 4, 353-358

38.          Straub, A. C., Billaud, M., Johnstone, S. R., Best, A. K., Yemen, S., Dwyer, S. T., Looft-Wilson, R., Lysiak, J. J., Gaston, B., Palmer, L., and Isakson, B. E. (2011) Arteriosclerosis, thrombosis, and vascular biology 31, 399-407

39.          Wu, C., Parrott, A. M., Fu, C., Liu, T., Marino, S. M., Gladyshev, V. N., Jain, M. R., Baykal, A. T., Li, Q., Oka, S., Sadoshima, J., Beuve, A., Simmons, W. J., and Li, H. (2011) Antioxidants & redox signaling 15, 2565-2604

40.          Zheng, W., Liu, Y., Pan, S., Yuan, W., Dai, Y., and Wei, J. (2011) Applied microbiology and biotechnology 90, 1763-1772

41.          Knott, A. B., and Bossy-Wetzel, E. (2009) Antioxidants & redox signaling 11, 541-554

42.          Hara, M. R., Thomas, B., Cascio, M. B., Bae, B. I., Hester, L. D., Dawson, V. L., Dawson, T. M., Sawa, A., and Snyder, S. H. (2006) Proceedings of the National Academy of Sciences of the United States of America 103, 3887-3889

Other research paper on Nitric Oxide were published on this Scientific Web site as follows:

Discovery of nitric oxide and its role in vascular biology

Nitric Oxide and Platelet Aggregation

Inhaled NO in Pulmonary Artery Hypertension and Right Sided Heart Failure

Cardiovascular Disease (CVD) and the Role of agent alternatives in endothelial Nitric Oxide Synthase (eNOS) Activation and Nitric Oxide Production

Nitric Oxide in bone metabolism

Nitric oxide and signalling pathways

Rationale of NO use in hypertension and heart failure

Interaction of Nitric Oxide and Prostacyclin in Vascular Endothelium

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

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