Evidence map›Paper›PMID 40103612›Full record

ArticleComputational and structural biotechnology journal2025

Comparative analysis of amino acid auxotrophies and peptidase profiles in non-dysbiotic and dysbiotic small intestinal microbiomes.

Svenja Starke, Danielle M M Harris, Amandine Paulay, Konrad Aden, Silvio Waschina

Abstract read
In one paragraph

Article in Computational and structural biotechnology journal, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
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

2 citing papers in PubMed.

  1. Article
  2. Article
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

5 authors.

Svenja StarkeInstitute of Human Nutrition and Food Science, Department of Nutriinformatics, Kiel University, Kiel, 24118, Germany.
Danielle M M HarrisInstitute of Human Nutrition and Food Science, Department of Nutriinformatics, Kiel University, Kiel, 24118, Germany.
Amandine PaulayUniversité Paris-Saclay, INRAE, AgroParisTech, Micalis Institute, Jouy-en-Josas 78350, France.
Konrad AdenInstitute of Clinical Molecular Biology, Kiel University, Rosalind-Franklin-Straße 12, Kiel, 24118, Germany.
Silvio WaschinaInstitute of Human Nutrition and Food Science, Department of Nutriinformatics, Kiel University, Kiel, 24118, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Small Intestinal Bacterial Overgrowth (SIBO) is linked to various diseases and has been associated with altered serum amino acid levels. However, the direct role of the gut microbiome in these changes remains unconfirmed. This study employs genome-scale metabolic modeling to predict amino acid auxotrophy and peptidase gene profiles in the small intestinal microbiomes of SIBO and non-SIBO subjects. Auxotrophy and peptidase gene profiles were further examined in the large intestinal microbiome under non-dysbiotic conditions to assess their similarity to the microbial SIBO profile. Our analysis revealed that the abundance of auxotrophic bacteria is higher in the microbiota of the small intestine than in the large intestine in non-dysbiotic controls. In patients with SIBO, the abundance of auxotrophies in the small intestine decreased compared to non-SIBO subjects. Peptidase gene profiles in non-dysbiotic individuals were distinct between small and large intestinal microbiomes, with fewer extracellular peptidase genes in small intestine microbiomes. In SIBO, extracellular peptidase genes increased compared to non-SIBO subjects. Further, there were more significant associations between the abundance of auxotrophies and peptidase genes in microbiomes of the small intestine compared to the large intestine. In conclusion, the auxotrophy and peptidase gene profiles of the small and large intestinal microbiomes were distinct. In SIBO, the small intestinal microbiome shifts towards a metabolic state resembling that of the large intestine, particularly in its increased abundance of extracellular peptidase genes. This highlights the potential of genome-scale metabolic modeling in identifying metabolic disruptions associated with SIBO, which could inform the development of targeted interventions.

Indexed as

Amino acidsAuxotrophiesPeptidasesSIBOSmall intestinal microbiome

Identifiers

PMID40103612
PMCPMC11914904

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.