Evidence map›Paper›PMID 35606844›Full record

ArticleAnimal microbiome2022

Fine scale transitions of the microbiota and metabolome along the gastrointestinal tract of herbivorous fishes.

Wesley J Sparagon, Emily C Gentry, Jeremiah J Minich, Lisa Vollbrecht, Lieve M L Laurens, Eric E Allen, Neil A Sims, Pieter C Dorrestein, Linda Wegley Kelly, Craig E Nelson

Open access · goldAbstract read
In one paragraph

Article in Animal microbiome, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
3.4field-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

18 citing papers in PubMed, 44 citations in OpenAlex.

  1. Article
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  6. Review
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  8. Hindguts ofmSystems · 2025
    Article
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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

10 authors at 6 institutions in 1 country.

Wesley J SparagonDaniel K. Inouye Center for Microbial Oceanography: Research and Education, Department of Oceanography and Sea Grant College Program, University of Hawai'i at Mānoa, 1950 East West Road, Honolulu, HI, 96822, USA. sparagon@hawaii.edu.ORCID http://orcid.org/0000-0002-9627-4174
Emily C GentrySkaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, USA.
Jeremiah J MinichThe Plant Molecular and Cellular Biology Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA.
Lisa VollbrechtOcean Era, Natural Energy Laboratory of Hawai'i, Kailua-Kona, HI, USA.
Lieve M L LaurensBiosciences Center, Bioenergy Science and Technology Directorate, National Renewable Energy Laboratory, Golden, CO, USA.
Eric E AllenMolecular Biology Section, Division of Biological Sciences, University of California San Diego, La Jolla, CA, USA.
Neil A SimsOcean Era, Natural Energy Laboratory of Hawai'i, Kailua-Kona, HI, USA.
Pieter C DorresteinSkaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, USA.
Linda Wegley KellyThe Plant Molecular and Cellular Biology Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA.
Craig E NelsonDaniel K. Inouye Center for Microbial Oceanography: Research and Education, Department of Oceanography and Sea Grant College Program, University of Hawai'i at Mānoa, 1950 East West Road, Honolulu, HI, 96822, USA.
Ocean Era (United States) · USSalk Institute for Biological Studies · USUniversity of California San Diego · USUniversity of Hawaiʻi at Mānoa · USNational Laboratory of the Rockies · USScripps Institution of Oceanography · US

Funding

Advanced Research Projects Agency - Energy ARPA-E DE-FOA-0001858
6 · The paper itself

Abstract

backgroundGut microorganisms aid in the digestion of food by providing exogenous metabolic pathways to break down organic compounds. An integration of longitudinal microbial and chemical data is necessary to illuminate how gut microorganisms supplement the energetic and nutritional requirements of animals. Although mammalian gut systems are well-studied in this capacity, the role of microbes in the breakdown and utilization of recalcitrant marine macroalgae in herbivorous fish is relatively understudied and an emerging priority for bioproduct extraction. Here we use a comprehensive survey of the marine herbivorous fish gut microbial ecosystem via parallel 16S rRNA gene amplicon profiling (microbiota) and untargeted tandem mass spectrometry (metabolomes) to demonstrate consistent transitions among 8 gut subsections across five fish of the genus of Kyphosus.

resultsIntegration of microbial phylogenetic and chemical diversity data reveals that microbial communities and metabolomes covaried and differentiated continuously from stomach to hindgut, with the midgut containing multiple distinct and previously uncharacterized microenvironments and a distinct hindgut community dominated by obligate anaerobes. This differentiation was driven primarily by anaerobic gut endosymbionts of the classes Bacteroidia and Clostridia changing in concert with bile acids, small peptides, and phospholipids: bile acid deconjugation associated with early midgut microbiota, small peptide production associated with midgut microbiota, and phospholipid production associated with hindgut microbiota.

conclusionsThe combination of microbial and untargeted metabolomic data at high spatial resolution provides a new view of the diverse fish gut microenvironment and serves as a foundation to understand functional partitioning of microbial activities that contribute to the digestion of complex macroalgae in herbivorous marine fish.

Indexed as

Fish gastrointestinal tract microbiota metabolome transitions

Identifiers

PMID35606844
PMCPMC9128220
OpenAlexW4281400052

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.