Evidence map›Paper›PMID 32620143›Full record

ArticleGenome medicine2020

High-resolution temporal profiling of the human gut microbiome reveals consistent and cascading alterations in response to dietary glycans.

Richard Creswell, Jie Tan, Jonathan W Leff, Brandon Brooks, Michael A Mahowald, Ruth Thieroff-Ekerdt, Georg K Gerber

Open access · goldAbstract read
In one paragraph

Article in Genome medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
1.5field-weighted citation impact, top 18% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

16 citing papers in PubMed, 22 citations in OpenAlex.

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  14. Re-evaluation of polydextrose (E 1200) as a food additive.EFSA journal. European Food Safety Authority · 2021
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 4 institutions in 2 countries.

Richard CreswellDepartment of Pathology, Brigham and Women's Hospital, 60 Fenwood Road, Boston, MA, 02115, USA.
Jie TanKaleido Biosciences, Lexington, MA, 02421, USA.
Jonathan W LeffKaleido Biosciences, Lexington, MA, 02421, USA.
Brandon BrooksKaleido Biosciences, Lexington, MA, 02421, USA.
Michael A MahowaldKaleido Biosciences, Lexington, MA, 02421, USA.
Ruth Thieroff-EkerdtKaleido Biosciences, Lexington, MA, 02421, USA.
Georg K GerberDepartment of Pathology, Brigham and Women's Hospital, 60 Fenwood Road, Boston, MA, 02115, USA. ggerber@bwh.harvard.edu.ORCID 0000-0002-9149-5509
Brigham and Women's Hospital · USAssociated Press · USLeo Pharma (Denmark) · DKNeuroMetrix (United States) · US

Funding

Bayesian Machine Learning Tools for Analyzing Microbiome DynamicsR01GM130777 · NIGMS · BRIGHAM AND WOMEN'S HOSPITAL · PI GERBER, GEORG KURT · 2018 to 2022
$1.6M
NIGMS NIH HHS 1R01GM130777NIGMS NIH HHS R01 GM130777
6 · The paper itself

Abstract

backgroundDietary glycans, widely used as food ingredients and not directly digested by humans, are of intense interest for their beneficial roles in human health through shaping the microbiome. Characterizing the consistency and temporal responses of the gut microbiome to glycans is critical for rationally developing and deploying these compounds as therapeutics.

methodsWe investigated the effect of two chemically distinct glycans (fructooligosaccharides and polydextrose) through three clinical studies conducted with 80 healthy volunteers. Stool samples, collected at dense temporal resolution (~ 4 times per week over 10 weeks) and analyzed using shotgun metagenomic sequencing, enabled detailed characterization of participants' microbiomes. For analyzing the microbiome time-series data, we developed MC-TIMME2 (Microbial Counts Trajectories Infinite Mixture Model Engine 2.0), a purpose-built computational tool based on nonparametric Bayesian methods that infer temporal patterns induced by perturbations and groups of microbes sharing these patterns.

resultsOverall microbiome structure as well as individual taxa showed rapid, consistent, and durable alterations across participants, regardless of compound dose or the order in which glycans were consumed. Significant changes also occurred in the abundances of microbial carbohydrate utilization genes in response to polydextrose, but not in response to fructooligosaccharides. Using MC-TIMME2, we produced detailed, high-resolution temporal maps of the microbiota in response to glycans within and across microbiomes.

conclusionsOur findings indicate that dietary glycans cause reproducible, dynamic, and differential alterations to the community structure of the human microbiome.

Indexed as

DietGastrointestinal MicrobiomeMetagenomeMetagenomicsAlgorithmsBayes TheoremBiodiversityComputational BiologyFecesHealthy VolunteersHumansModels, TheoreticalPolysaccharidesSoftwarePolysaccharidesDynamicsGastrointestinalGlycansHumanMicrobiomeTime-series

Identifiers

PMID32620143
PMCPMC7386241
OpenAlexW3039746172

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.