A community resource for paired genomic and metabolomic data mining

Genomics and metabolomics are widely used to explore specialized metabolite diversity. The Paired Omics Data Platform is a community initiative to systematically document links between metabolome and (meta)genome data, aiding identification of natural product biosynthetic origins and metabolite structures.Peer reviewe

Vertical Inheritance Facilitates Interspecies Diversification in Biosynthetic Gene Clusters and Specialized Metabolites.

While specialized metabolites are thought to mediate ecological interactions, the evolutionary processes driving chemical diversification, particularly among closely related lineages, remain poorly understood. Here, we examine the evolutionary dynamics governing the distribution of natural product biosynthetic gene clusters (BGCs) among 118 strains representing all nine currently named species of the marine actinobacterial genus Salinispora. While much attention has been given to the role of horizontal gene transfer (HGT) in structuring BGC distributions, we find that vertical descent facilitates interspecies BGC diversification over evolutionary timescales. Moreover, we identified a distinct phylogenetic signal among Salinispora species at both the BGC and metabolite level, indicating that specialized metabolism represents a conserved phylogenetic trait. Using a combination of genomic analyses and liquid chromatography-high-resolution tandem mass spectrometry (LC-MS/MS) targeting nine experimentally characterized BGCs and their small molecule products, we identified gene gain/loss events, constrained interspecies recombination, and other evolutionary processes associated with vertical inheritance as major contributors to BGC diversification. These evolutionary dynamics had direct consequences for the compounds produced, as exemplified by species-level differences in salinosporamide production. Together, our results support the concept that specialized metabolites, and their cognate BGCs, can represent phylogenetically conserved functional traits with chemical diversification proceeding in species-specific patterns over evolutionary time frames. IMPORTANCE Microbial natural products are traditionally exploited for their pharmaceutical potential, yet our understanding of the evolutionary processes driving BGC evolution and compound diversification remain poorly developed. While HGT is recognized as an integral driver of BGC distributions, we find that the effects of vertical inheritance on BGC diversification had direct implications for species-level specialized metabolite production. As such, understanding the degree of genetic variation that corresponds to species delineations can enhance natural product discovery efforts. Resolving the evolutionary relationships between closely related strains and specialized metabolism can also facilitate our understanding of the ecological roles of small molecules in structuring the environmental distribution of microbes

The Alleviation of Dextran Sulfate Sodium (DSS)-Induced Colitis Correlate with the logP Values of Food-Derived Electrophilic Compounds

Food-derived electrophilic compounds (FECs) are small molecules with electrophilic groups with potential cytoprotective effects. This study investigated the differential effects of six prevalent FECs on colitis in dextran sodium sulfate (DSS)-induced mice and the underlying relationship with molecular characteristics. Fumaric acid (FMA), isoliquiritigenin (ISO), cinnamaldehyde (CA), ferulic acid (FA), sulforaphane (SFN), and chlorogenic acid (CGA) exhibited varying improvements in colitis on clinical signs, colonic histopathology, inflammatory and oxidative indicators, and Nrf2 pathway in a sequence of SFN, ISO > FA, CA > FMA, CGA. Representative molecular characteristics of the “penetration-affinity–covalent binding” procedure, logP value, Keap1 affinity energy, and electrophilic index of FECs were theoretically calculated, among which logP value revealed a strong correlation with colitis improvements, which was related to the expression of Nrf2 and its downstream proteins. Above all, SFN and ISO possessed high logP values and effectively improving DSS-induced colitis by activating the Keap1–Nrf2 pathway to alleviate oxidative stress and inflammatory responses

Statistical Machines for Trauma Hospital Outcomes Research: Application to the PRospective, Observational, Multi-Center Major Trauma Transfusion (PROMMTT) Study

<div><p>Improving the treatment of trauma, a leading cause of death worldwide, is of great clinical and public health interest. This analysis introduces flexible statistical methods for estimating center-level effects on individual outcomes in the context of highly variable patient populations, such as those of the PRospective, Observational, Multi-center Major Trauma Transfusion study. Ten US level I trauma centers enrolled a total of 1,245 trauma patients who survived at least 30 minutes after admission and received at least one unit of red blood cells. Outcomes included death, multiple organ failure, substantial bleeding, and transfusion of blood products. The centers involved were classified as either large or small-volume based on the number of massive transfusion patients enrolled during the study period. We focused on estimation of parameters inspired by causal inference, specifically estimated impacts on patient outcomes related to the volume of the trauma hospital that treated them. We defined this association as the change in mean outcomes of interest that would be observed if, contrary to fact, subjects from large-volume sites were treated at small-volume sites (the effect of treatment among the treated). We estimated this parameter using three different methods, some of which use data-adaptive machine learning tools to derive the outcome models, minimizing residual confounding by reducing model misspecification. Differences between unadjusted and adjusted estimators sometimes differed dramatically, demonstrating the need to account for differences in patient characteristics in clinic comparisons. In addition, the estimators based on robust adjustment methods showed potential impacts of hospital volume. For instance, we estimated a survival benefit for patients who were treated at large-volume sites, which was not apparent in simpler, unadjusted comparisons. By removing arbitrary modeling decisions from the estimation process and concentrating on parameters that have more direct policy implications, these potentially automated approaches allow methodological standardization across similar comparativeness effectiveness studies.</p></div

Heatmap of matched data set with hierarchical clustering.

<p>A visualization of the scaled covariate values in the matched data set with hierarchical clustering of the individual revealed little clustering of the individuals by site type, indicated in the bar on the left, suggesting that balance in the covariates was achieved. The dendrogram on the right is the result of hierarchical clustering of the individuals based on their covariate values. The color bar on the left indicates the site size where each individual was treated (purple corresponds to small-volume sites and blue to large-volume sites).</p

Summary statistics.

<p>^{<b>^</b>}<b>p</b>-values derived from Mann-Whitney U and Z-tests for continuous and binary variables respectively.</p><p>* <b>p</b>-value significant (α = 0.05).</p><p>BMI: body mass index; ISS: injury severity score; BP: blood pressure; BPM: beats per minute; INR: international normalized ratio; RBC: red blood cell; U: units.</p><p>Summaries are presented as percent where indicated, and mean (standard deviation) otherwise.</p

“Counterfactual” residual plot for binary outcomes.

<p>Residuals (see <i>Diagnostics</i>) for each outcome were plotted against probabilities of overall mortality for large (dotted line) and small-volume (solid line) site patients for binary outcomes using loess smooths.</p

Difference in means, and adjusted ETT estimates (simple substitution, TMLE, and propensity score matching).

<p>95% confidence intervals are included in parentheses after each estimate. Asymptotic (normal-based) confidence intervals were calculated using the standard error of the Unadjusted, Targeted Maximum-Likelihood, and Matching estimators. The nonparametric bootstrap was used to generate 95% confidence intervals in the case of the Simple Substitution estimator.</p

Transfusion of Plasma, Platelets, and Red Blood Cells in a 1:1:1 vs a 1:1:2 Ratio and Mortality in Patients With Severe Trauma: The PROPPR Randomized Clinical Trial

ImportanceSeverely injured patients experiencing hemorrhagic shock often require massive transfusion. Earlier transfusion with higher blood product ratios (plasma, platelets, and red blood cells), defined as damage control resuscitation, has been associated with improved outcomes; however, there have been no large multicenter clinical trials.ObjectiveTo determine the effectiveness and safety of transfusing patients with severe trauma and major bleeding using plasma, platelets, and red blood cells in a 1:1:1 ratio compared with a 1:1:2 ratio.Design, setting, and participantsPragmatic, phase 3, multisite, randomized clinical trial of 680 severely injured patients who arrived at 1 of 12 level I trauma centers in North America directly from the scene and were predicted to require massive transfusion between August 2012 and December 2013.InterventionsBlood product ratios of 1:1:1 (338 patients) vs 1:1:2 (342 patients) during active resuscitation in addition to all local standard-of-care interventions (uncontrolled).Main outcomes and measuresPrimary outcomes were 24-hour and 30-day all-cause mortality. Prespecified ancillary outcomes included time to hemostasis, blood product volumes transfused, complications, incidence of surgical procedures, and functional status.ResultsNo significant differences were detected in mortality at 24 hours (12.7% in 1:1:1 group vs 17.0% in 1:1:2 group; difference, -4.2% [95% CI, -9.6% to 1.1%]; P = .12) or at 30 days (22.4% vs 26.1%, respectively; difference, -3.7% [95% CI, -10.2% to 2.7%]; P = .26). Exsanguination, which was the predominant cause of death within the first 24 hours, was significantly decreased in the 1:1:1 group (9.2% vs 14.6% in 1:1:2 group; difference, -5.4% [95% CI, -10.4% to -0.5%]; P = .03). More patients in the 1:1:1 group achieved hemostasis than in the 1:1:2 group (86% vs 78%, respectively; P = .006). Despite the 1:1:1 group receiving more plasma (median of 7 U vs 5 U, P &lt; .001) and platelets (12 U vs 6 U, P &lt; .001) and similar amounts of red blood cells (9 U) over the first 24 hours, no differences between the 2 groups were found for the 23 prespecified complications, including acute respiratory distress syndrome, multiple organ failure, venous thromboembolism, sepsis, and transfusion-related complications.Conclusions and relevanceAmong patients with severe trauma and major bleeding, early administration of plasma, platelets, and red blood cells in a 1:1:1 ratio compared with a 1:1:2 ratio did not result in significant differences in mortality at 24 hours or at 30 days. However, more patients in the 1:1:1 group achieved hemostasis and fewer experienced death due to exsanguination by 24 hours. Even though there was an increased use of plasma and platelets transfused in the 1:1:1 group, no other safety differences were identified between the 2 groups.Trial registrationclinicaltrials.gov Identifier: NCT01545232