Evidence map›Paper›PMID 34220728›Full record

ArticleFrontiers in microbiology2021

Using Structural Equation Modeling to Understand Interactions Between Bacterial and Archaeal Populations and Volatile Fatty Acid Proportions in the Rumen.

Veronica Kaplan-Shabtai, Nagaraju Indugu, Meagan Leslie Hennessy, Bonnie Vecchiarelli, Joseph Samuel Bender, Darko Stefanovski, Camila Flavia De Assis Lage, Susanna Elisabeth Räisänen, Audino Melgar, Krum Nedelkov and 5 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in microbiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
12.8field-weighted citation impact, top 1% 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

14 citing papers in PubMed, 50 citations in OpenAlex.

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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

15 authors at 2 institutions in 1 country.

Veronica Kaplan-ShabtaiDepartment of Clinical Studies, School of Veterinary Medicine, University of Pennsylvania, Kennett Square, PA, United States.
Nagaraju InduguDepartment of Clinical Studies, School of Veterinary Medicine, University of Pennsylvania, Kennett Square, PA, United States.
Meagan Leslie HennessyDepartment of Clinical Studies, School of Veterinary Medicine, University of Pennsylvania, Kennett Square, PA, United States.
Bonnie VecchiarelliDepartment of Clinical Studies, School of Veterinary Medicine, University of Pennsylvania, Kennett Square, PA, United States.
Joseph Samuel BenderDepartment of Clinical Studies, School of Veterinary Medicine, University of Pennsylvania, Kennett Square, PA, United States.
Darko StefanovskiDepartment of Clinical Studies, School of Veterinary Medicine, University of Pennsylvania, Kennett Square, PA, United States.
Camila Flavia De Assis LageDepartment of Animal Science, The Pennsylvania State University, University Park, PA, United States.
Susanna Elisabeth RäisänenDepartment of Animal Science, The Pennsylvania State University, University Park, PA, United States.
Audino MelgarDepartment of Animal Science, The Pennsylvania State University, University Park, PA, United States.
Krum NedelkovDepartment of Animal Science, The Pennsylvania State University, University Park, PA, United States.
Molly Elizabeth FetterDepartment of Animal Science, The Pennsylvania State University, University Park, PA, United States.
Andrea FernandezDepartment of Clinical Studies, School of Veterinary Medicine, University of Pennsylvania, Kennett Square, PA, United States.
Addison SpitzerDepartment of Clinical Studies, School of Veterinary Medicine, University of Pennsylvania, Kennett Square, PA, United States.
Alexander Nikolov HristovDepartment of Animal Science, The Pennsylvania State University, University Park, PA, United States.
Dipti Wilhelmina PittaDepartment of Clinical Studies, School of Veterinary Medicine, University of Pennsylvania, Kennett Square, PA, United States.
University of Pennsylvania · USPennsylvania State University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Microbial syntrophy (obligate metabolic mutualism) is the hallmark of energy-constrained anaerobic microbial ecosystems. For example, methanogenic archaea and fermenting bacteria coexist by interspecies hydrogen transfer in the complex microbial ecosystem in the foregut of ruminants; however, these synergistic interactions between different microbes in the rumen are seldom investigated. We hypothesized that certain bacteria and archaea interact and form specific microbial cohorts in the rumen. To this end, we examined the total (DNA-based) and potentially metabolically active (cDNA-based) bacterial and archaeal communities in rumen samples of dairy cows collected at different times in a 24 h period. Notably, we found the presence of distinct bacterial and archaeal networks showing potential metabolic interactions that were correlated with molar proportions of specific volatile fatty acids (VFAs). We employed hypothesis-driven structural equation modeling to test the significance of and to quantify the extent of these relationships between bacteria-archaea-VFAs in the rumen. Furthermore, we demonstrated that these distinct microbial networks were host-specific and differed between cows indicating a natural variation in specific microbial networks in the rumen of dairy cows. This study provides new insights on potential microbial metabolic interactions in anoxic environments that have broader applications in methane mitigation, energy conservation, and agricultural production.

Indexed as

dairy cowshost-microbe interactionsinter-species hydrogen transfermetabolically- active microbesmicrobial syntrophyrumen microbiota

Identifiers

PMID34220728
PMCPMC8248675
OpenAlexW3170194594

What OpenQuestion holds

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LicenceCC BY
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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.