We show how metagenomic analysis of the human gut antibiotic resistome, compared across large populations and against environmental or agricultural resistomes, suggests a strong anthropogenic cause behind increasing antibiotic resistance in bacteria. This area has been the subject of intense and polarized debate driven by economic and political concerns; therefore such recently available insights address an important need. We derive and compare antibiotic resistomes of human gut microbes from 832 individuals from ten different countries. We observe and describe significant differences between samples from these countries in the gut resistance potential, in line with expectations from antibiotic usage and exposure in medical and food production contexts. Our results imply roles for both of these sources in increased resistance among pathogens in recent history. In contrast, other available metadata such as age, body mass index, sex, or health status have little effect on the antibiotic resistance potential of human gut microbes. Also watch the Video Abstract.

The increasing number of sequenced genomes has prompted the development of several automated orthology prediction methods. Tests to evaluate the accuracy of predictions and to explore biases caused by biological and technical factors are therefore required. We used 70 manually curated families to analyze the performance of five public methods in Metazoa. We analyzed the strengths and weaknesses of the methods and quantified the impact of biological and technical challenges. From the latter part of the analysis, genome annotation emerged as the largest single influencer, affecting up to 30% of the performance. Generally, most methods did well in assigning orthologous group but they failed to assign the exact number of genes for half of the groups. The publicly available benchmark set (http://eggnog.embl.de/orthobench/) should facilitate the improvement of current orthology assignment protocols, which is of utmost importance for many fields of biology and should be tackled by a broad scientific community.

Protein complexes perform many important functions in the cell. Large-scale studies of protein-protein interactions have not only revealed new complexes but have also placed many proteins into multiple complexes. Whilst the advocates of hypothesis-free research touted the discovery of these shared components as new links between diverse cellular processes, critical commentators denounced many of the findings as artefacts, thus questioning the usefulness of large-scale approaches. Here, we survey proteins known to be shared between complexes, as established in the literature, and compare them to shared components found in high-throughput screens. We discuss the various challenges to the identification and functional interpretation of bona fide shared components, namely contaminants, variant and megacomplexes, and transient interactions, and suggest that many of the novel shared components found in high-throughput screens are neither the results of contamination nor central components, but appear to be primarily regulatory links in cellular processes.

Alternative splicing is a critical post-transcriptional event leading to an increase in the transcriptome diversity. Recent bioinformatics studies revealed a high frequency of alternative splicing. Although the extent of AS conservation among mammals is still being discussed, it has been argued that major forms of alternatively spliced transcripts are much better conserved than minor forms. It suggests that alternative splicing plays a major role in genome evolution allowing new exons to evolve with less constraint.