Evidence map›Paper›PMID 37961608›Full record

ArticlebioRxiv : the preprint server for biology2023

Metabolic similarity and the predictability of microbial community assembly.

Jean C C Vila, Joshua Goldford, Sylvie Estrela, Djordje Bajic, Alicia Sanchez-Gorostiaga, Alejandro Damian-Serrano, Nanxi Lu, Robert Marsland, Maria Rebolleda-Gomez, Pankaj Mehta and 1 more

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

11 authors.

Jean C C VilaDepartment of Ecology and Evolutionary Biology, Yale University, New Haven, CT USA.ORCID 0000-0003-0499-0200
Joshua GoldfordDivision of Geophysical and Planetary sciences,California Institute of Technology, Pasadena, CA, USA.ORCID 0000-0001-7315-8018
Sylvie EstrelaDepartment of Ecology and Evolutionary Biology, Yale University, New Haven, CT USA.ORCID 0000-0003-1946-3657
Djordje BajicDepartment of Ecology and Evolutionary Biology, Yale University, New Haven, CT USA.ORCID 0000-0002-6716-7898
Alicia Sanchez-GorostiagaDepartment of Ecology and Evolutionary Biology, Yale University, New Haven, CT USA.ORCID 0000-0002-2719-5659
Alejandro Damian-SerranoDepartment of Ecology and Evolutionary Biology, Yale University, New Haven, CT USA.ORCID 0000-0002-2544-0489
Nanxi LuDepartment of Ecology and Evolutionary Biology, Yale University, New Haven, CT USA.ORCID 0000-0003-0277-4782
Robert MarslandDepartment of Physics, Boston University, Boston, MA 02215, USA.ORCID 0000-0002-5007-6877
Maria Rebolleda-GomezDepartment of Ecology and Evolutionary Biology, Yale University, New Haven, CT USA.ORCID 0000-0002-3592-4479
Pankaj MehtaDepartment of Physics, Boston University, Boston, MA 02215, USA.ORCID 0000-0003-1290-5897
Alvaro SanchezDepartment of Ecology and Evolutionary Biology, Yale University, New Haven, CT USA.ORCID 0000-0002-2292-5608

Funding

MODELING EMERGENT BEHAVIORS IN SYSTEMS BIOLOGY: A BIOLOGICAL PHYSICS APPROACHR35GM119461 · NIGMS · BOSTON UNIVERSITY (CHARLES RIVER CAMPUS) · PI Pankaj Mehta · 2016 to 2026
$3.6M
Predicting the assembly and function of microbial consortia: a systems biology approachR35GM133467 · NIGMS · YALE UNIVERSITY · PI SANCHEZ DE ANDRES, ALVARO · 2019 to 2021
$1.3M
NIGMS NIH HHS R35 GM119461NIGMS NIH HHS R35 GM133467
6 · The paper itself

Abstract

When microbial communities form, their composition is shaped by selective pressures imposed by the environment. Can we predict which communities will assemble under different environmental conditions? Here, we hypothesize that quantitative similarities in metabolic traits across metabolically similar environments lead to predictable similarities in community composition. To that end, we measured the growth rate and by-product profile of a library of proteobacterial strains in a large number of single nutrient environments. We found that growth rates and secretion profiles were positively correlated across environments when the supplied substrate was metabolically similar. By analyzing hundreds of in-vitro communities experimentally assembled in an array of different synthetic environments, we then show that metabolically similar substrates select for taxonomically similar communities. These findings lead us to propose and then validate a comparative approach for quantitatively predicting the effects of novel substrates on the composition of complex microbial consortia.

Identifiers

PMID37961608
PMCPMC10634833

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Registered trials

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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.