Questioning the Quality of 16S rRNA Gene Sequences Derived From Human Gut Metagenome-Assembled Genomes

The recent introduction of metagenome-assembled genomes (MAGs) has marked a major milestone in the human gut microbiome field (Almeida et al., 2019; Nayfach et al., 2019; Pasolli et al., 2019). Such reference-free, de novo-assembled genomes (Hugerth et al., 2015) have revealed a wide range of hitherto uncultured microbial species in human gut samples. The significance of MAGs in unravelling human gut microbial diversity was supported by their overwhelming representation in a comprehensive human gut prokaryotic collection filtered by metagenome data dereplicated at 97.5% average nucleotide identity (ANI) (Hiseni et al., 2021). More than 90% of the collection consists of MAGs, while the rest of the collection mainly comprises RefSeq genomes (Figure 1A).publishedVersio

HumGut: a comprehensive human gut prokaryotic genomes collection filtered by metagenome data

Background A major bottleneck in the use of metagenome sequencing for human gut microbiome studies has been the lack of a comprehensive genome collection to be used as a reference database. Several recent efforts have been made to re-construct genomes from human gut metagenome data, resulting in a huge increase in the number of relevant genomes. In this work, we aimed to create a collection of the most prevalent healthy human gut prokaryotic genomes, to be used as a reference database, including both MAGs from the human gut and ordinary RefSeq genomes. Results We screened > 5,700 healthy human gut metagenomes for the containment of > 490,000 publicly available prokaryotic genomes sourced from RefSeq and the recently announced UHGG collection. This resulted in a pool of > 381,000 genomes that were subsequently scored and ranked based on their prevalence in the healthy human metagenomes. The genomes were then clustered at a 97.5% sequence identity resolution, and cluster representatives (30,691 in total) were retained to comprise the HumGut collection. Using the Kraken2 software for classification, we find superior performance in the assignment of metagenomic reads, classifying on average 94.5% of the reads in a metagenome, as opposed to 86% with UHGG and 44% when using standard Kraken2 database. A coarser HumGut collection, consisting of genomes dereplicated at 95% sequence identity—similar to UHGG, classified 88.25% of the reads. HumGut, half the size of standard Kraken2 database and directly comparable to the UHGG size, outperforms them both. Conclusions The HumGut collection contains > 30,000 genomes clustered at a 97.5% sequence identity resolution and ranked by human gut prevalence. We demonstrate how metagenomes from IBD-patients map equally well to this collection, indicating this reference is relevant also for studies well outside the metagenome reference set used to obtain HumGut. All data and metadata, as well as helpful code, are available at http://arken.nmbu.no/~larssn/humgut/.publishedVersio

A Feeding Induced Switch from a Variable to a Homogenous State of the Earthworm Gut Microbiota within a Host Population

BACKGROUND: The distribution pattern of the earthworm gut microbiota at the host population level is of fundamental importance to understand host-microbiota interactions. Our current understanding of these interactions is very limited. Since feeding represents a main perturbation of the gut microbiota, we determined the effect of a single dose of feed on the microbiota associated with an earthworm population in a simulated microenvironment. METHODOLOGY: Earthworms were sampled 0, 1 and 7 days after feeding. We determined the overall composition of the earthworm-associated microbiota by 16S rRNA gene cloning and sequencing. Based on the 16S rRNA gene data we constructed quantitative PCR's (Q-PCR) for the seven most dominating bacterial groups. PRINCIPAL FINDINGS: Q-PCR revealed low density and highly variable microbiota among the earthworms before feeding, while a high-density homologous microbiota resulted from feeding. We found that the microbiota 1 day after feeding was more equal to the microbiota after 7 days than before feeding. Furthermore, we found that the gut microbiota was very distinct from that of the bedding and the feed. SIGNIFICANCE: The homogenous population response represents fundamental new knowledge about earthworm gut associated bacteria

Liquid array diagnostics: A novel method for rapid detection of microbial communities in single-tube multiplex reactions

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Diet-dependent modular dynamic interactions of the equine cecal microbiota

Knowledge on dynamic interactions in microbiota is pivotal for understanding the role of bacteria in the gut. We herein present comprehensive dynamic models of the horse cecal microbiota, which include short-chained fatty acids, carbohydrate metabolic networks, and taxonomy. Dynamic models were derived from time-series data in a crossover experiment in which four cecum-cannulated horses were fed a starch-rich diet of hay supplemented with barley (starch intake 2 g kg(−1) body weight per day) and a fiber-rich diet of only hay. Cecal contents were sampled via the cannula each h for 24 h for both diets. We observed marked differences in the microbial dynamic interaction patterns for Fibrobacter succinogenes, Lachnospiraceae, Streptococcus, Treponema, Anaerostipes, and Anaerovibrio between the two diet groups. Fluctuations and microbiota interactions were the most pronounced for the starch rich diet, with Streptococcus spp. and Anaerovibrio spp. showing the largest fluctuations. Shotgun metagenome sequencing revealed that diet differences may be explained by modular switches in metabolic cross-feeding between microbial consortia in which fermentation is linked to sugar alcohols and amino sugars for the starch-rich diet and monosaccharides for the fiber-rich diet. In conclusion, diet may not only affect the composition of the cecal microbiota, but also dynamic interactions and metabolic cross-feeding

Spatial fractionation of phosphorus accumulating biofilm: stratification of polyphosphate accumulation and dissimilatory nitrogen metabolism

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Spatiotemporal succession of phosphorous accumulating biofilms during the first year of establishment

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