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Record W3007224813 · doi:10.1093/jcag/gwz047.098

A99 IMPACT OF OSMOTIC PERTURBATIONS ON THE GUT MICROBIOTA AND HOST HEALTH

2020· article· en· W3007224813 on OpenAlexaff
Deanna M. Pepin, Carolina Tropini

Bibliographic record

VenueJournal of the Canadian Association of Gastroenterology · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGut microbiota and health
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsOsmotic shockDiarrheaBiologyPEG ratioImmune systemMicrobiologyOsmotic concentrationGut floraImmunologyInternal medicineMedicineGeneBiochemistry

Abstract

fetched live from OpenAlex

Abstract Background Osmotic diarrhea is a prevalent condition concurrent with diverse pathologies such as Crohn’s disease and is due to unabsorbed solutes in the gastrointestinal contents inhibiting normal water absorption. Osmotic laxatives such as polyethylene glycol (PEG) take advantage of this process to counteract constipation. However, short-term PEG treatment impacts the gut microbial community, and in humanized and conventional mice leads to disappearance of the abundant and prevalent bacterial family S24-7, while increasing the relative abundance of a related family, Bacteroidaceae. Excitingly, despite community re-equilibration over weeks, S24-7 is capable of superseding other bacterial members and reach its original levels when reintroduced into the environment. My central hypothesis is that the depletion of S24-7 during osmotic diarrhea is due to its deficiency of stress response pathways required to counteract increased osmolality. However, in the absence of this stress, S24-7 is capable of exploiting a unique interaction with the immune system to successfully recolonize. Aims To shed light on this, I will pursue the following two aims: Aim 1: Compare the growth, survival and expression profiles of S24-7 and B. thetaiotaomicron in a bi-colonized gnotobiotic mouse model before, during and after osmotic perturbation to identify candidate genes involved in response to osmotic perturbation. Aim 2: Identify changes in S24-7 gene expression during recolonization and evaluate the host immune response. Methods Gnotobiotic mice were first colonized with S24-7 and then B. thetaiotaomicron, treated with PEG for 6 days and monitored during recovery and recolonization for 20 days. Fecal pellets were used to quantify bacterial abundances via qPCR and bacterial gene expression analysis through metatranscriptomics. Mouse serum was used for ELISA immunoassays to compare adaptive immune responses through serum IgG as well as to quantify glycine betaine levels. Results During PEG treatment S24-7 became undetectable and recolonized to pre-treatment levels during recovery. Using genomic and metagenomic annotation we have identified that S24-7 isolates do not possess the glycine betaine transport system, which is present in B. thetaiotaomicron (Figure 1). B. thetaiotaomicron reduced host serum glycine betaine levels, unlike S24-7. In S24-7 mono-colonized mice, S24-7 specific serum IgG was not detectable. However, once mice were co-colonized with B. thetaiotaomicron, both S24-7 and B. thetaiotaomicron specific IgG is detected, identifying an interesting relationship between S24-7 and the adaptive immune system that may shed light on its unique recolonization. Conclusions By studying S24-7 sensitivity to osmotic stress and its robust colonization abilities we are shedding light on the mechanisms of microbiota response to perturbations that are commonly experienced by the human gut. Funding Agencies None

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.010
GPT teacher head0.240
Teacher spread0.230 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2020
Admission routes1
Has abstractyes

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