In PLOS Genetics, researchers from the University of Cambridge, the University of Edinburgh, and University of Melbourne describe a culture-free "Hi-C assisted metagenomics for antimicrobial resistance tracking" (HAM-ART) bioinformatic pipeline for unearthing antimicrobial resistance (AMR) genes with genomes and extra-chromosomal AMR genes gleaned from metagenomic sequence data. With this approach, the team detected distinct AMR levels in pig farms with higher or lower levels of antibiotic use when it applied HAM-ART to 100 fecal microbiome samples collected at the farms. "Our method provides a novel approach to resistance gene tracking," the authors write, "that also leads to the generation of high quality metagenomic assembled genomes that includes genes on mobile genetic elements, such as plasmids, that would not otherwise be included in these assembled genomes."
A team from France, Israel, and the Czech Republic present findings from a multi-omic analysis of factors influencing fitness in Leishmania donovani parasites, known for their role in visceral leishmaniasis. As they report in PLOS Pathogens, the researchers used whole-genome sequencing-based copy number analyses, RNA sequencing, and proteomic analyses to compare early- and late-stage L. donovani parasite cultures undergoing adaptation in the lab. "Leishmania parasites lack transcriptional control and instead exploit genome instability to adapt to their host environment," they report. "Analyzing in vitro adaptation of hamster-derived parasites via gene copy number (genomic level) and gene expression changes (transcriptomic and proteomic levels), we show that these parasites likely exploit small nucleolar RNAs (snoRNAs) to mitigate toxic effects of genome instability by post-transcriptional regulation and the establishment of modified ribosomes."
For a paper appearing in PLOS One, investigators in China consider APC gene expression, mutation, and methylation features across many cancer types with the help of available bioinformatic tools and data from the Cancer Genome Atlas project and the Gene Expression Omnibus database. While APC gene expression tended to be relatively low in most tumor samples, the team's pan-cancer analyses pointed to potential ties between APC expression, immune cell infiltration, patient outcomes, and other tumor or clinical features. "[O]ur first pan-cancer analysis of APC shows that increased APC expression … is statistically correlated with clinical prognosis, cancer pathological staging, DNA methylation, protein phosphorylation, immune cell infiltration, and genetic alteration in various tumors," the authors write, "which is helpful to understand the role of APC in tumorigenesis based on clinical tumor samples combined with clinical parameters."