Highlights of B/D‐HPP and HPP Resource Pillar Workshops at 12th Annual HUPO World Congress of Proteomics

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/106985/1/pmic7698.pd

MAID : An effect size based model for microarray data integration across laboratories and platforms

<p>Abstract</p> <p>Background</p> <p>Gene expression profiling has the potential to unravel molecular mechanisms behind gene regulation and identify gene targets for therapeutic interventions. As microarray technology matures, the number of microarray studies has increased, resulting in many different datasets available for any given disease. The increase in sensitivity and reliability of measurements of gene expression changes can be improved through a systematic integration of different microarray datasets that address the same or similar biological questions.</p> <p>Results</p> <p>Traditional effect size models can not be used to integrate array data that directly compare treatment to control samples expressed as log ratios of gene expressions. Here we extend the traditional effect size model to integrate as many array datasets as possible. The extended effect size model (MAID) can integrate any array datatype generated with either single or two channel arrays using either direct or indirect designs across different laboratories and platforms. The model uses two standardized indices, the standard effect size score for experiments with two groups of data, and a new standardized index that measures the difference in gene expression between treatment and control groups for one sample data with replicate arrays. The statistical significance of treatment effect across studies for each gene is determined by appropriate permutation methods depending on the type of data integrated. We apply our method to three different expression datasets from two different laboratories generated using three different array platforms and two different experimental designs. Our results indicate that the proposed integration model produces an increase in statistical power for identifying differentially expressed genes when integrating data across experiments and when compared to other integration models. We also show that genes found to be significant using our data integration method are of direct biological relevance to the three experiments integrated.</p> <p>Conclusion</p> <p>High-throughput genomics data provide a rich and complex source of information that could play a key role in deciphering intricate molecular networks behind disease. Here we propose an extension of the traditional effect size model to allow the integration of as many array experiments as possible with the aim of increasing the statistical power for identifying differentially expressed genes.</p

In Situ Proteolysis to Generate Crystals for Structure Determination: An Update

For every 100 purified proteins that enter crystallization trials, an average of 30 form crystals, and among these only 13–15 crystallize in a form that enables structure determination. In 2007, Dong et al reported that the addition of trace amounts of protease to crystallization trials—in situ proteolysis—significantly increased the number of proteins in a given set that produce diffraction quality crystals. 69 proteins that had previously resisted structure determination were subjected to crystallization with in situ proteolysis and ten crystallized in a form that led to structure determination (14.5% success rate). Here we apply in situ proteolysis to over 270 new soluble proteins that had failed in the past to produce crystals suitable for structure determination. These proteins had produced no crystals, crystals that diffracted poorly, or produced twinned and/or unmanageable diffraction data. The new set includes yeast and prokaryotic proteins, enzymes essential to protozoan parasites, and human proteins such as GTPases, chromatin remodeling proteins, and tyrosine kinases. 34 proteins yielded deposited crystal structures of 2.8 Å resolution or better, for an overall 12.6% success rate, and at least ten more yielded well-diffracting crystals presently in refinement. The success rate among proteins that had previously crystallized was double that of those that had never before yielded crystals. The overall success rate is similar to that observed in the smaller study, and appears to be higher than any other method reported to rescue stalled protein crystallography projects

Open drug discovery in Alzheimer\u27s disease.

Alzheimer\u27s disease (AD) drug discovery has focused on a set of highly studied therapeutic hypotheses, with limited success. The heterogeneous nature of AD processes suggests that a more diverse, systems-integrated strategy may identify new therapeutic hypotheses. Although many target hypotheses have arisen from systems-level modeling of human disease, in practice and for many reasons, it has proven challenging to translate them into drug discovery pipelines. First, many hypotheses implicate protein targets and/or biological mechanisms that are under-studied, meaning there is a paucity of evidence to inform experimental strategies as well as high-quality reagents to perform them. Second, systems-level targets are predicted to act in concert, requiring adaptations in how we characterize new drug targets. Here we posit that the development and open distribution of high-quality experimental reagents and informatic outputs-termed target enabling packages (TEPs)-will catalyze rapid evaluation of emerging systems-integrated targets in AD by enabling parallel, independent, and unencumbered research

Study protocol: cross-national comparative case study of recovery-focused mental health care planning and coordination (COCAPP).

BACKGROUND: The collaborative care planning study (COCAPP) is a cross-national comparative study of care planning and coordination in community mental healthcare settings. The context and delivery of mental health care is diverging between the countries of England and Wales whilst retaining points of common interest, hence providing a rich geographical comparison for research. Across England the key vehicle for the provision of recovery-focused, personalised, collaborative mental health care is the care programme approach (CPA). The CPA is a form of case management introduced in England in 1991, then revised in 2008. In Wales the CPA was introduced in 2003 but has now been superseded by The Mental Health (Care Co-ordination and Care and Treatment Planning) (CTP) Regulations (Mental Health Measure), a new statutory framework. In both countries, the CPA/CTP requires providers to: comprehensively assess health/social care needs and risks; develop a written care plan (which may incorporate risk assessments, crisis and contingency plans, advanced directives, relapse prevention plans, etc.) in collaboration with the service user and carer(s); allocate a care coordinator; and regularly review care. The overarching aim of this study is to identify and describe the factors that ensure CPA/CTP care planning and coordination is personalised, recovery-focused and conducted collaboratively. METHODS/DESIGN: COCAPP will employ a concurrent transformative mixed methods approach with embedded case studies. Phase 1 (Macro-level) will consider the national context through a meta-narrative mapping (MNM) review of national policies and the relevant research literature. Phase 2 (Meso-level and Micro-level) will include in-depth micro-level case studies of everyday 'frontline' practice and experience with detailed qualitative data from interviews and reviews of individual care plans. This will be nested within larger meso-level survey datasets, senior-level interviews and policy reviews in order to provide potential explanations and understanding. DISCUSSION: COCAPP will help identify the key components that support and hinder the provision of personalised, recovery-focused care planning and provide an informed rationale for a future planned intervention and evaluation

Structural and Chemical Profiling of the Human Cytosolic Sulfotransferases

The human cytosolic sulfotransfases (hSULTs) comprise a family of 12 phase II enzymes involved in the metabolism of drugs and hormones, the bioactivation of carcinogens, and the detoxification of xenobiotics. Knowledge of the structural and mechanistic basis of substrate specificity and activity is crucial for understanding steroid and hormone metabolism, drug sensitivity, pharmacogenomics, and response to environmental toxins. We have determined the crystal structures of five hSULTs for which structural information was lacking, and screened nine of the 12 hSULTs for binding and activity toward a panel of potential substrates and inhibitors, revealing unique “chemical fingerprints” for each protein. The family-wide analysis of the screening and structural data provides a comprehensive, high-level view of the determinants of substrate binding, the mechanisms of inhibition by substrates and environmental toxins, and the functions of the orphan family members SULT1C3 and SULT4A1. Evidence is provided for structural “priming” of the enzyme active site by cofactor binding, which influences the spectrum of small molecules that can bind to each enzyme. The data help explain substrate promiscuity in this family and, at the same time, reveal new similarities between hSULT family members that were previously unrecognized by sequence or structure comparison alone

Target 2035-update on the quest for a probe for every protein

Twenty years after the publication of the first draft of the human genome, our knowledge of the human proteome is still fragmented. The challenge of translating the wealth of new knowledge from genomics into new medicines is that proteins, and not genes, are the primary executers of biological function. Therefore, much of how biology works in health and disease must be understood through the lens of protein function. Accordingly, a subset of human proteins has been at the heart of research interests of scientists over the centuries, and we have accumulated varying degrees of knowledge about approximately 65% of the human proteome. Nevertheless, a large proportion of proteins in the human proteome (∼35%) remains uncharacterized, and less than 5% of the human proteome has been successfully targeted for drug discovery. This highlights the profound disconnect between our abilities to obtain genetic information and subsequent development of effective medicines. Target 2035 is an international federation of biomedical scientists from the public and private sectors, which aims to address this gap by developing and applying new technologies to create by year 2035 chemogenomic libraries, chemical probes, and/or biological probes for the entire human proteome

The Structural Basis of Gas-Responsive Transcription by the Human Nuclear Hormone Receptor REV-ERBβ

Heme is a ligand for the human nuclear receptors (NR) REV-ERBα and REV-ERBβ, which are transcriptional repressors that play important roles in circadian rhythm, lipid and glucose metabolism, and diseases such as diabetes, atherosclerosis, inflammation, and cancer. Here we show that transcription repression mediated by heme-bound REV-ERBs is reversed by the addition of nitric oxide (NO), and that the heme and NO effects are mediated by the C-terminal ligand-binding domain (LBD). A 1.9 Å crystal structure of the REV-ERBβ LBD, in complex with the oxidized Fe(III) form of heme, shows that heme binds in a prototypical NR ligand-binding pocket, where the heme iron is coordinately bound by histidine 568 and cysteine 384. Under reducing conditions, spectroscopic studies of the heme-REV-ERBβ complex reveal that the Fe(II) form of the LBD transitions between penta-coordinated and hexa-coordinated structural states, neither of which possess the Cys384 bond observed in the oxidized state. In addition, the Fe(II) LBD is also able to bind either NO or CO, revealing a total of at least six structural states of the protein. The binding of known co-repressors is shown to be highly dependent upon these various liganded states. REV-ERBs are thus highly dynamic receptors that are responsive not only to heme, but also to redox and gas. Taken together, these findings suggest new mechanisms for the systemic coordination of molecular clocks and metabolism. They also raise the possibility for gas-based therapies for the many disorders associated with REV-ERB biological functions

The promise and peril of chemical probes

Chemical probes are powerful reagents with increasing impacts on biomedical research. However, probes of poor quality or that are used incorrectly generate misleading results. To help address these shortcomings, we will create a community-driven wiki resource to improve quality and convey current best practice