Compositional Changes in the Gut Mucus Microbiota Precede the Onset of Colitis-Induced Inflammation

Glymenaki, Maria; Singh, Gurdeep; Brass, Andy; Warhurst, Geoffrey; McBain, Andrew J.; Else, Kathryn J.; Cruickshank, Sheena M.

doi:10.1097/mib.0000000000001118

Cited by 48 publications

(63 citation statements)

References 54 publications

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“…Sample collection and processing was performed as described by Glymenaki et al (15). In brief, samples were harvested from mice at two time points, 6 and 18 weeks of age.…”

Section: Methodsmentioning

confidence: 99%

“…FISH was performed as described previously (15). In brief, FISH staining was performed using the universal bacterial probe-EUB338 (5′-Cy3-GCTGCCTCCCGTAGGAGT-3′), followed by immunostaining with a rabbit polyclonal MUC2 antibody and goat anti-rabbit Alexa-Fluor 488 antibody (Life Technologies, Paisley, United Kingdom).…”

Section: Methodsmentioning

confidence: 99%

“…Bacteria vary along the length of the gut as well as within specific niches such as the mucus layer overlying the intestinal epithelial cells (13). We and others have shown that the mucus microbiome is discrete from that detected in stools (14, 15) and that changes in the mucus microbiota precede changes in the stool microbiota and onset of disease (15). Host environmental factors such as diet and housing can also impact the microbiota, yet few studies report on how mice are caged and whether they are littermates (16-18).…”

Section: Introductionmentioning

confidence: 98%

“…We use data from an IBD mouse model (colitis-prone, mdr1a -/- ). These mice have been shown by standard analytical techniques to have an altered gut mucus bacteria (15). Importantly, the data come from a carefully controlled experiment, with co-housed mdr1a -/- and wildtype mice.…”

Section: Introductionmentioning

confidence: 99%

“…Importantly, the data come from a carefully controlled experiment, with co-housed mdr1a -/- and wildtype mice. 16S sequencing was ordered to avoid confounding sequencing batches with treatments, enabling robust comparisons, among genotype, niche and age (15). To avoid taxonomic bias, we use the sequences themselves to estimate the phylogenetic relationships amongst organisms and thereby abundances at different phylogenetic scales.…”

Section: Introductionmentioning

confidence: 99%

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Distinct microbial communities in the murine gut are revealed by taxonomy-independent phylogenetic random forests

Singh¹,

Brass

Cruickshank³

et al. 2019

Preprint

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Gut microbiome analysis using 16S rRNA frequently focuses on summary statistics (e.g. diversity) or single taxonomic scales (e.g. Operational Taxonomic units, OTUs). This approach risks misinterpreting the phylogenetic or abundance scales of community differences (e.g. over-emphasising the role of single strains). We therefore constructed a 16S phylogenetic tree from mouse stool and colonic mucus communities. Random forest models, of all 428,234 clades, tested community differences among niches (stool versus mucus), host ages (6 versus 18 weeks), genotypes (wildtype versus colitis prone-mdr1a-/-) and social groups (co-housed siblings). Models discriminated all criteria except host genotype, where no community differences were found. Host social groups differed in abundant, low-level, taxa whereas intermediate phylogenetic and abundance scales distinguished ages and niches. Thus, treating evolutionary clades of microbes equivalently without reference to OTUs or taxonomy, clearly identifies whether and how gut microbial communities are distinct and provides a novel way to define functionally important bacteria.

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“…Sample collection and processing was performed as described by Glymenaki et al (15). In brief, samples were harvested from mice at two time points, 6 and 18 weeks of age.…”

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%