Evidence map›Paper›PMID 37160919›Full record

ArticleNPJ science of food2023

Evaluating the prebiotic effect of oligosaccharides on gut microbiome wellness using in vitro fecal fermentation.

Dong Hyeon Lee, Hyunbin Seong, Daniel Chang, Vinod K Gupta, Jiseung Kim, Seongwon Cheon, Geonhee Kim, Jaeyun Sung, Nam Soo Han

Open access · goldAbstract read
In one paragraph

Article in NPJ science of food, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 1 pooled it
4.2field-weighted citation impact, top 6% 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

17 citing papers in PubMed, 1 synthesis or guideline pooled it, 27 citations in OpenAlex.

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  15. Determinants of raffinose family oligosaccharide use inbioRxiv : the preprint server for biology · 2024
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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

9 authors at 3 institutions in 2 countries.

Dong Hyeon Lee *Brain Korea 21 Center for Bio-Health Industry, Department of Food Science and Biotechnology, Chungbuk National University, Cheongju, Chungbuk, 28644, Republic of Korea.
Hyunbin Seong *Brain Korea 21 Center for Bio-Health Industry, Department of Food Science and Biotechnology, Chungbuk National University, Cheongju, Chungbuk, 28644, Republic of Korea.
Daniel ChangDepartment of Computer Science and Engineering, University of Minnesota-Twin Cities, Minneapolis, MN, 55455, USA.ORCID http://orcid.org/0000-0003-0076-2833
Vinod K GuptaMicrobiome Program, Center for Individualized Medicine, Mayo Clinic, Rochester, MN, 55905, USA.
Jiseung KimBrain Korea 21 Center for Bio-Health Industry, Department of Food Science and Biotechnology, Chungbuk National University, Cheongju, Chungbuk, 28644, Republic of Korea.
Seongwon CheonBrain Korea 21 Center for Bio-Health Industry, Department of Food Science and Biotechnology, Chungbuk National University, Cheongju, Chungbuk, 28644, Republic of Korea.
Geonhee KimBrain Korea 21 Center for Bio-Health Industry, Department of Food Science and Biotechnology, Chungbuk National University, Cheongju, Chungbuk, 28644, Republic of Korea.
Jaeyun SungMicrobiome Program, Center for Individualized Medicine, Mayo Clinic, Rochester, MN, 55905, USA. Sung.Jaeyun@mayo.edu.ORCID http://orcid.org/0000-0002-3005-2798
Nam Soo HanBrain Korea 21 Center for Bio-Health Industry, Department of Food Science and Biotechnology, Chungbuk National University, Cheongju, Chungbuk, 28644, Republic of Korea. namsoo@cbnu.ac.kr.ORCID http://orcid.org/0000-0002-8460-8165
Chungbuk National University · KRMayo Clinic · USUniversity of Minnesota · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We previously proposed the Gut Microbiome Wellness Index (GMWI), a predictor of disease presence based on a gut microbiome taxonomic profile. As an application of this index for food science research, we applied GMWI as a quantitative tool for measuring the prebiotic effect of oligosaccharides. Mainly, in an in vitro anaerobic batch fermentation system, fructooligosaccharides (FOS), galactooligosaccharides (GOS), xylooligosaccharides (XOS), inulin (IN), and 2'-fucosyllactose (2FL), were mixed separately with fecal samples obtained from healthy adult volunteers. To find out how 24 h prebiotic fermentation influenced the GMWI values in their respective microbial communities, changes in species-level relative abundances were analyzed in the five prebiotics groups, as well as in two control groups (no substrate addition at 0 h and for 24 h). The GMWI of fecal microbiomes treated with any of the five prebiotics (IN (0.48 ± 0.06) > FOS (0.47 ± 0.03) > XOS (0.33 ± 0.02) > GOS (0.26 ± 0.02) > 2FL (0.16 ± 0.06)) were positive, which indicates an increase of relative abundances of microbial species previously found to be associated with a healthy, disease-free state. In contrast, the GMWI of samples without substrate addition for 24 h (-0.60 ± 0.05) reflected a non-healthy, disease-harboring microbiome state. Compared to the original prebiotic index (PI) and α-diversity metrics, GMWI provides a more data-driven, evidence-based indexing system for evaluating the prebiotic effect of food components. This study demonstrates how GMWI can be applied as a novel PI in dietary intervention studies, with wider implications for designing personalized diets based on their impact on gut microbiome wellness.

Identifiers

PMID37160919
PMCPMC10170090
OpenAlexW4376121136

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.