Accounting for epistatic interactions improves the functional analysis of protein structures

Motivation: The constraints under which sequence, structure and function coevolve are not fully understood. Bringing this mutual relationship to light can reveal the molecular basis of binding, catalysis and allostery, thereby identifying function and rationally guiding protein redesign. Underlying these relationships are the epistatic interactions that occur when the consequences of a mutation to a protein are determined by the genetic background in which it occurs. Based on prior data, we hypothesize that epistatic forces operate most strongly between residues nearby in the structure, resulting in smooth evolutionary importance across the structure. Methods and Results: We find that when residue scores of evolutionary importance are distributed smoothly between nearby residues, functional site prediction accuracy improves. Accordingly, we designed a novel measure of evolutionary importance that focuses on the interaction between pairs of structurally neighboring residues. This measure that we term pair-interaction Evolutionary Trace yields greater functional site overlap and better structure-based proteome-wide functional predictions. Conclusions: Our data show that the structural smoothness of evolutionary importance is a fundamental feature of the coevolution of sequence, structure and function. Mutations operate on individual residues, but selective pressure depends in part on the extent to which a mutation perturbs interactions with neighboring residues. In practice, this principle led us to redefine the importance of a residue in terms of the importance of its epistatic interactions with neighbors, yielding better annotation of functional residues, motivating experimental validation of a novel functional site in LexA and refining protein function prediction. Contact: [email protected] Supplementary information: Supplementary data are available at Bioinformatics online

Heating Injection Drug Preparation Equipment Used for Opioid Injection May Reduce HIV Transmission Associated with Sharing Equipment

London, Canada, experienced an HIV outbreak among persons who inject drugs despite widespread distribution of harm reduction equipment. Hydromorphone controlled-release (HMC) is the local opioid of choice. Injection drug preparation equipment (IDPE; ie, cookers and filters) is often shared and reused because of the perception that there is residual HMC in the IDPE after use. The purpose of this study was to investigate the mechanisms of HIV transmission in this context.Methods:Residual hydromorphone, (controlled-release or immediate-release), remaining in the IDPE, was measured with liquid chromatography-tandem mass spectrometry, in conditions replicating persons who inject drug use. HIV was added to IDPE in the presence HMC, hydromorphone immediate-release, or microcrystalline cellulose (an HMC drug excipient). HIV viral persistence was measured by reverse transcriptase activity and infectivity of indicator Tzm-bl cells.Results:Forty-five percent of HMC remained in the IDPE after the first aspiration of solution, with no change after heating. HIV persistence and infectivity were preserved in the presence of HMC, and less so with microcrystalline cellulose. Heating the IDPE rapidly inactivated HIV.Conclusions:Sharing of IDPE is a potential means of HIV transmission. HMC encourages IDPE sharing because of the residual drug in the IDPE, and the HMC excipients preserve HIV viability. Heating IDPE before aspiration of the opioid may be a harm reduction strategy

Artificial Intelligence and Cardiovascular Genetics

Polygenic diseases, which are genetic disorders caused by the combined action of multiple genes, pose unique and significant challenges for the diagnosis and management of affected patients. A major goal of cardiovascular medicine has been to understand how genetic variation leads to the clinical heterogeneity seen in polygenic cardiovascular diseases (CVDs). Recent advances and emerging technologies in artificial intelligence (AI), coupled with the ever-increasing availability of next generation sequencing (NGS) technologies, now provide researchers with unprecedented possibilities for dynamic and complex biological genomic analyses. Combining these technologies may lead to a deeper understanding of heterogeneous polygenic CVDs, better prognostic guidance, and, ultimately, greater personalized medicine. Advances will likely be achieved through increasingly frequent and robust genomic characterization of patients, as well the integration of genomic data with other clinical data, such as cardiac imaging, coronary angiography, and clinical biomarkers. This review discusses the current opportunities and limitations of genomics; provides a brief overview of AI; and identifies the current applications, limitations, and future directions of AI in genomics.</jats:p

Accurate Protein Structure Annotation through Competitive Diffusion of Enzymatic Functions over a Network of Local Evolutionary Similarities

High-throughput Structural Genomics yields many new protein structures without known molecular function. This study aims to uncover these missing annotations by globally comparing select functional residues across the structural proteome. First, Evolutionary Trace Annotation, or ETA, identifies which proteins have local evolutionary and structural features in common; next, these proteins are linked together into a proteomic network of ETA similarities; then, starting from proteins with known functions, competing functional labels diffuse link-by-link over the entire network. Every node is thus assigned a likelihood z-score for every function, and the most significant one at each node wins and defines its annotation. In high-throughput controls, this competitive diffusion process recovered enzyme activity annotations with 99% and 97% accuracy at half-coverage for the third and fourth Enzyme Commission (EC) levels, respectively. This corresponds to false positive rates 4-fold lower than nearest-neighbor and 5-fold lower than sequence-based annotations. In practice, experimental validation of the predicted carboxylesterase activity in a protein from Staphylococcus aureus illustrated the effectiveness of this approach in the context of an increasingly drug-resistant microbe. This study further links molecular function to a small number of evolutionarily important residues recognizable by Evolutionary Tracing and it points to the specificity and sensitivity of functional annotation by competitive global network diffusion. A web server is at http://mammoth.bcm.tmc.edu/networks

Genetic risk and its role in primary prevention of CAD

Coronary artery disease (CAD) is a pandemic disease and the number one cause of death in the world. Predisposition to CAD is about 50% acquired and 50% genetic. CAD prevention has been proven in randomized clinical trials with statin therapy. However, primary prevention is limited by the lack of biomarkers to detect asymptomatic young individuals at risk. Traditional risk factors (TRFs) such as hypertension or Type 2 Diabetes are age-dependent and often not present until the sixth or seventh decade. In contrast, genetic risk determined at conception is potentially a biomarker to detect young individuals at risk for CAD. The first genetic risk variant for CAD (9p21) was discovered in 2007, and subsequently, over 200 risk variants for CAD were discovered. A genetic risk score (GRS) based on the genetic risk variants for CAD was evaluated in over one million individuals. Retrospective analysis of clinical trials assessing the effect of statin therapy showed that individuals with the highest GRS had the highest risk for cardiac events and also the most benefit from lowering cholesterol. In a recent study of 55,685 individuals, those with the highest GRS (20%) had a 91% higher risk for cardiac events. Furthermore, those with high genetic risk on a favorable lifestyle had 46% fewer cardiac events than those with an unfavorable lifestyle. The GRS is superior and independent of TRFs. Incorporation into clinical practice will be a paradigm shift in preventing this pandemic

Per-pathogen virulence of HIV-1 subtypes A, C and D

HIV-1 subtypes differ in their clinical manifestations and the speed in which they spread. In particular, the frequency of subtype C is increasing relative to subtypes A and D. We investigate whether HIV-1 subtypes A, C and D differ in their per-pathogen virulence and to what extend this explains the difference in spread between these subtypes. We use data from the hormonal contraception and HIV-1 genital shedding and disease progression among women with primary HIV infection study. For each study participant, we determine the set-point viral load value, CD4 + T cell level after primary infection and CD4 + T cell decline. Based on both the CD4 + T cell count after primary infection and CD4 + T cell decline, we estimate the time until AIDS. We then obtain our newly introduced measure of virulence as the inverse of the estimated time until AIDS. After fitting a model to the measured virulence and set-point viral load values, we tested if this relation varies per subtype. We found that subtype C has a significantly higher per-pathogen virulence than subtype A. Based on an evolutionary model, we then hypothesize that differences in the primary length of infection period cause the observed variation in the speed of spread of the subtypes.ISSN:1471-295

The ground plot counting method: A valid and reliable assessment tool for quantifying seed production in temperate oak forests?

International audienceMasting, or mast-seeding, defined as a synchronized and highly variable seed production from year-to-year within a population of plants, is one of the most common example of pulsed resources in terrestrial ecosystems. In oaks, the dramatic fluctuations of acorn production impact its reproductive success and regeneration, the dynamics of a large diversity of seed consumers that rely on it, and, by cascade effects, the dynamics of the entire forest community. However, reproductive effort is difficult to quantify and there is therefore an urgent need of a reliable assessment of the dynamic of acorn production based on a low-cost, unbiased, and robust tool. One of the most commonly used method, the “visual on-tree” method, is very easy and quick to carry out, but is biased under high seed production or when branches are difficult to see. We here assessed the robustness of an alternative method, the “ground plot” (GP), based on a unique annual ground survey after peak of acorn fall, which has not been tested so far. We compared this method at tree and site levels (10 forests throughout France) with the costly and time-consuming trap acorn collection (TNR) method (used here as a reference method). We show that results from the GP method closely matched with those obtained using the TNR method, which demonstrates the efficiency and robustness of the GP method at both tree and forest site levels. Despite some limitations in specific environmental contexts we review, this GP method offers a powerful tool to quantify acorn production and should be deployed to understand mechanisms underlying oak masting and/or to assess its ecological or economic consequences