Pfeiffer, W. | bioRxiv Science

bioRxiv2021

RAxML Grove: An empirical Phylogenetic Tree Database

The assessment of novel phylogenetic models and inference methods is routinely being conducted via experiments on simulated as well as empirical data. When generating synthetic data it is often unclear how to set simulation parameters for the models and generate trees that appropriately reflect empirical model parameter distributions and tree shapes. As a solution, we present and make available a new database called RAxML Grove currently comprising more than 60,000 inferred trees and respective model parameter estimates from fully anonymized empirical data sets that were analyzed using RAxML (1) and RAxML-NG (2) on two web servers. We also describe and make available two simple applications of RAxML Grove to exemplify its usage and highlight its utility for designing realistic simulation studies and analyzing empirical model parameter and tree shape distributions. RAxML Grove is freely available at https://github.com/angtft/RAxMLGrove.

bioinformatics↗

bioRxiv2020

Identification of an N-acetylneuraminic acid-presenting bacteria isolated from a healthy human microbiome

N-acetylneuraminic acid is the most abundant sialic acid in humans and is generally expressed as the terminal sugar on intestinal mucus glycans. Several pathogenic bacterial species harvest sialic acid from the mucus, diet, as well as other intestinal sources and display this sugar on their own surface to evade sialic acid-binding immunoglobulin-type lectin (Siglec)-mediated host immune surveillance. While previous studies have identified bacterial enzymes associated with sialic acid catabolism, no reported methods permit the selective labeling, tracking, and quantitation of sialic acid-presenting microbes within complex multi-microbial systems. Here, we apply an interdisciplinary approach combining metabolic labeling, click chemistry, metagenomic, and whole-genome sequencing to selectively track and identify sialic acid-presenting microbes from a cultured healthy human fecal microbiome. We isolated and identified a new strain of Escherichia coli that incorporates sialic acid onto its own surface. Analysis of the sequence data reveals that this E. coli strain encodes for the NanT, NeuA, and NeuS genes necessary for harvesting environmental sialic acid and generating the capsular polysialic acid. We envision that this method is applicable to the detection and quantitation of sialic acid-presenting bacteria from human, animal, and environmental microbiomes, as well as investigating the importance of other carbohydrates to commensal and pathogenic bacteria.

microbiology↗