This study demonstrates that BRCA2 expression level is regulated via 5′ UTR splicing variants and that the BRCA2 intron 1 region harbors cis-regulatory elements.

This study demonstrates that BRCA2 expression level is regulated via 5′ UTR splicing variants and that the BRCA2 intron 1 region harbors cis-regulatory elements.

High-throughput sequencing has increased the number of available microbial genomes recovered from isolates, single cells, and metagenomes. Accordingly, fast and comprehensive functional gene annotation pipelines are needed to analyze and compare these genomes. Although several approaches exist for genome annotation, these are typically not designed for easy incorporation into analysis pipelines, do not combine results from different annotation databases or offer easy-to-use summaries of metabolic reconstructions, and typically require large amounts of computing power for high-throughput analysis not available to the average user.

Here, we introduce MicrobeAnnotator, a fully automated, easy-to-use pipeline for the comprehensive functional annotation of microbial genomes that combines results from several reference protein databases and returns the matching annotations together with key metadata such as the interlinked identifiers of matching reference proteins from multiple databases [KEGG Orthology (KO), incorporated into other analysis pipelines while the results of other annotation tools can be seemingly incorporated into MicrobeAnnotator to generate summary plots.

We demonstrated the capabilities of MicrobeAnnotator by annotating 100 Escherichia coli and 78 environmental Candidate Phyla Radiation (CPR) bacterial genomes and comparing the results to those of other popular tools. We showed that the use of multiple annotation databases allows MicrobeAnnotator to recover more annotations per genome compared to faster tools that use reduced databases and is computationally efficient for use in personal computers. The output of MicrobeAnnotator can be easily incorporated into other analysis pipelines while the results of other annotation tools can be seemingly incorporated into MicrobeAnnotator to generate summary plots.Hepatic ischemia/reperfusion (I/R) injury represents a major risk factor for liver transplantation and is related to graft dysfunction and acute/chronic rejection. However, a significant part of these processes remain poorly characterized. To reveal differences in the proteome during liver I/R injury, we collected human liver biopsy samples during hepatectomy before and after the Pringle maneuver and conducted a TMT-based proteomic analysis through quantitative high-throughput mass spectrometry. We used a fold-change threshold of 1.3 and a t-test p-value  less then  0.05 as the criteria to identify 5,257 total quantifiable proteins. The levels of 142 proteins were increased, while the levels of 103 proteins were decreased in response to hepatic I/R treatment. Bioinformatic analysis further revealed that these differentially expressed proteins are mainly involved in multiple biological functions and enzyme-regulated metabolic pathways. Most proteins whose expression was changed are related to the defense, immune and inflammatory responses as well as lipid and steroid metabolic processes. Based on this finding, we developed a panel for targeted proteomic analysis and used the parallel reaction monitoring (PRM) method, qPCR and western blotting experiments to validate alterations in the expression of some of the identified proteins. The upregulated proteins were found to be involved in immunity and inflammatory responses, and downregulated proteins were enriched in metabolic pathways. This study therefore may provide a research direction for the design of new therapeutic strategies for hepatic ischemia/reperfusion injury.

Hydrogen cross-feeding microbes form a functionally important subset of the human colonic microbiota. The three major hydrogenotrophic functional groups of the colon sulphate-reducing bacteria (SRB), methanogens and reductive acetogens, have been linked to wide ranging impacts on host physiology, health and wellbeing.

An existing mathematical model for microbial community growth and metabolism was combined with models for each of the three hydrogenotrophic functional groups. Delamanid The model was further developed for application to the colonic environment via inclusion of responsive pH, host metabolite absorption and the inclusion of host mucins. Predictions of the model, using two existing metabolic parameter sets, were compared to experimental faecal culture datasets. Model accuracy varied between experiments and measured variables and was most successful in predicting the growth of high relative abundance functional groups, such as the Bacteroides, and short chain fatty acid (SCFA) production. Two versions oficrobiota.

Although the model predictions compared well to only some experimental measurements, the important features of the colon environment included make it a novel and useful contribution to modelling the colonic microbiota.

Atrial fibrillation (AF) is the most common cardiac heterogeneous rhythm disorder. It represents a major cause of mortality and morbidity, mainly related to embolic events and heart failure. Mechanisms of AF are complex and remain incompletely understood. Recent evidence suggests exosomes are membrane-coated objects released by many cell-types. Their presence in body fluids and the variable surface composition and content render them attractive as a mechanism for potential biomarkers. However, the content of serum exosomes of AF patients has not been fully delineated.

In this work, the serum exosomes from AF patients and healthy donors were used to compare changes in the exosome protein content. Exosomes were isolated from serum of AF patients and healthy donors and their purity was confirmed by Western blotting assays and transmission electron microscopy (TEM). Label-free LC-MS/MS quantitative proteomic analysis was applied to analyze protein content of serum exosomes.

A total of 440 exosomal protein gt system and protein folding to AF.

Protein inter-residue contact and distance prediction are two key intermediate steps essential to accurate protein structure prediction. Distance prediction comes in two forms real-valued distances and ‘binned’ distograms, which are a more finely grained variant of the binary contact prediction problem. The latter has been introduced as a new challenge in the 14th Critical Assessment of Techniques for Protein Structure Prediction (CASP14) 2020 experiment. Despite the recent proliferation of methods for predicting distances, few methods exist for evaluating these predictions. Currently only numerical metrics, which evaluate the entire prediction at once, are used. These give no insight into the structural details of a prediction. For this reason, new methods and tools are needed.

We have developed a web server for evaluating predicted inter-residue distances. Our server, DISTEVAL, accepts predicted contacts, distances, and a true structure as optional inputs to generate informative heatmaps, chord diagrams, and 3D models.