3 research outputs found
Putative antimicrobial peptides within bacterial proteomes affect bacterial predominance: a network analysis perspective
The predominance of bacterial taxa in the gut, was examined in view of the putative antimicrobial peptide sequences (AMPs) within their proteomes. The working assumption was that compatible bacteria would share homology and thus immunity to their putative AMPs, while competing taxa would have dissimilarities in their proteome-hidden AMPs. A network–based method (“Bacterial Wars”) was developed to handle sequence similarities of predicted AMPs among UniProt-derived protein sequences from different bacterial taxa, while a resulting parameter (“Die” score) suggested which taxa would prevail in a defined microbiome. T he working hypothesis was examined by correlating the calculated Die scores, to the abundance of bacterial taxa from gut microbiomes from different states of health and disease. Eleven publicly available 16S rRNA datasets and a dataset from a full shotgun metagenomics served for the analysis. The overall conclusion was that AMPs encrypted within bacterial proteomes affected the predominance of bacterial taxa in chemospheres
miRNATissueAtlas2: an update to the human miRNA tissue atlas
Small non-coding RNAs (sncRNAs) are pervasive
regulators of physiological and pathological processes. We previously developed the human miRNA
Tissue Atlas, detailing the expression of miRNAs
across organs in the human body. Here, we present
an updated resource containing sequencing data of
188 tissue samples comprising 21 organ types retrieved from six humans. Sampling the organs from
the same bodies minimizes intra-individual variability and facilitates the making of a precise highresolution body map of the non-coding transcriptome. The data allow shedding light on the organ- and
organ system-specificity of piwi-interacting RNAs
(piRNAs), transfer RNAs (tRNAs), microRNAs (miRNAs) and other non-coding RNAs. As use case of
our resource, we describe the identification of highly
specific ncRNAs in different organs. The update also
contains 58 samples from six tissues of the Tabula Muris collection, allowing to check if the tissue specificity is evolutionary conserved between
Homo sapiens and Mus musculus. The updated resource of 87 252 non-coding RNAs from nine noncoding RNA classes for all organs and organ systems
is available online without any restrictions (https:
//www.ccb.uni-saarland.de/tissueatlas2)
Systematic Cross-biospecimen Evaluation of DNA Extraction Kits for Long- and Short-read Multi-metagenomic Sequencing Studies
High-quality DNA extraction is a crucial step in metagenomic studies. Bias by different isolation kits impairs the comparison across datasets. A trending topic is, however, the analysis of multiple metagenomes from the same patients to draw a holistic picture of microbiota associated with diseases. We thus collected bile, stool, saliva, plaque, sputum, and conjunctival swab samples and performed DNA extraction with three commercial kits. For each combination of the specimen type and DNA extraction kit, 20-gigabase (Gb) metagenomic data were generated using short-read sequencing. While profiles of the specimen types showed close proximity to each other, we observed notable differences in the alpha diversity and composition of the microbiota depending on the DNA extraction kits. No kit outperformed all selected kits on every specimen. We reached consistently good results using the Qiagen QiAamp DNA Microbiome Kit. Depending on the specimen, our data indicate that over 10 Gb of sequencing data are required to achieve sufficient resolution, but DNA-based identification is superior to identification by mass spectrometry. Finally, long-read nanopore sequencing confirmed the results (correlation coefficient > 0.98). Our results thus suggest using a strategy with only one kit for studies aiming for a direct comparison of multiple microbiotas from the same patients