Evidence map›Paper›PMID 35337386›Full record

ArticleMicrobiome2022

Metagenomic strain detection with SameStr: identification of a persisting core gut microbiota transferable by fecal transplantation.

Daniel Podlesny, Cesar Arze, Elisabeth Dörner, Sandeep Verma, Sudhir Dutta, Jens Walter, W Florian Fricke

Open access · goldAbstract readVideo-Audio Media
In one paragraph

Article in Microbiome, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
40citing papers in PubMed, 1 pooled it
4.2field-weighted citation impact, top 4% 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

40 citing papers in PubMed, 1 synthesis or guideline pooled it, 53 citations in OpenAlex.

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  16. Human microbiome acquisition and transmission.Nature reviews. Microbiology · 2025
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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 3 institutions in 4 countries.

Daniel PodlesnyDepartment of Microbiome Research and Applied Bioinformatics, University of Hohenheim, Stuttgart, Germany. daniel.podlesny@uni-hohenheim.de.
Cesar ArzeDepartment of Microbiome Research and Applied Bioinformatics, University of Hohenheim, Stuttgart, Germany.
Elisabeth DörnerDepartment of Microbiome Research and Applied Bioinformatics, University of Hohenheim, Stuttgart, Germany.
Sandeep VermaDivision of Gastroenterology, Sinai Hospital of Baltimore, Baltimore, MD, USA.
Sudhir DuttaDivision of Gastroenterology, Sinai Hospital of Baltimore, Baltimore, MD, USA.
Jens WalterAPC Microbiome Ireland, School of Microbiology, and Department of Medicine, University College Cork, Cork, Ireland.
W Florian FrickeDepartment of Microbiome Research and Applied Bioinformatics, University of Hohenheim, Stuttgart, Germany. w.florian.fricke@uni-hohenheim.de.ORCID 0000-0003-1586-0962
University of Hohenheim · DESinai Hospital · USUniversity College Cork · IE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe understanding of how microbiomes assemble, function, and evolve requires metagenomic tools that can resolve microbiota compositions at the strain level. However, the identification and tracking of microbial strains in fecal metagenomes is challenging and available tools variably classify subspecies lineages, which affects their applicability to infer microbial persistence and transfer.

resultsWe introduce SameStr, a bioinformatic tool that identifies shared strains in metagenomes by determining single-nucleotide variants (SNV) in species-specific marker genes, which are compared based on a maximum variant profile similarity. We validated SameStr on mock strain populations, available human fecal metagenomes from healthy individuals and newly generated data from recurrent Clostridioides difficile infection (rCDI) patients treated with fecal microbiota transplantation (FMT). SameStr demonstrated enhanced sensitivity to detect shared dominant and subdominant strains in related samples (where strain persistence or transfer would be expected) when compared to other tools, while being robust against false-positive shared strain calls between unrelated samples (where neither strain persistence nor transfer would be expected). We applied SameStr to identify strains that are stably maintained in fecal microbiomes of healthy adults over time (strain persistence) and that successfully engraft in rCDI patients after FMT (strain engraftment). Taxonomy-dependent strain persistence and engraftment frequencies were positively correlated, indicating that a specific core microbiota of intestinal species is adapted to be competitive both in healthy microbiomes and during post-FMT microbiome assembly. We explored other use cases for strain-level microbiota profiling, as a metagenomics quality control measure and to identify individuals based on the persisting core gut microbiota.

conclusionSameStr provides for a robust identification of shared strains in metagenomic sequence data with sufficient specificity and sensitivity to examine strain persistence, transfer, and engraftment in human fecal microbiomes. Our findings identify a persisting healthy adult core gut microbiota, which should be further studied to shed light on microbiota contributions to chronic diseases. Video abstract.

Indexed as

Clostridium InfectionsGastrointestinal MicrobiomeAdultFecal Microbiota TransplantationFecesHumansMetagenomeMetagenomicsTreatment Outcome

Identifiers

PMID35337386
PMCPMC8951724
OpenAlexW4220990751

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.