Evidence map›Paper›PMID 33646814›Full record

ReviewAnnual review of biophysics2021

Directed Evolution of Microbial Communities.

Álvaro Sánchez, Jean C C Vila, Chang-Yu Chang, Juan Diaz-Colunga, Sylvie Estrela, María Rebolleda-Gomez

Abstract readReview
In one paragraph

Review in Annual review of biophysics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers.

0numbers the graph read from it
0cells of the map it votes in
41citing 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

41 citing papers in PubMed.

  1. Article
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  5. Microbial biotechnology meets ecological theory: a unified framework to design industrial microbial consortia.International microbiology : the official journal of the Spanish Society for Microbiology · 2026
    Review
  6. Review
  7. Article
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  11. Article
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  15. Review
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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

6 authors.

Álvaro SánchezDepartment of Ecology & Evolutionary Biology and Microbial Sciences Institute, Yale University, New Haven, Connecticut 06520, USA; email: alvaro.sanchez@yale.edu, jean.vila@yale.edu, chang-yu.chang@yale.edu, juan.diazcolunga@gmail.com, sylvie.estrela@yale.edu, maria.rebolleda-gomez@yale.edu.
Jean C C VilaDepartment of Ecology & Evolutionary Biology and Microbial Sciences Institute, Yale University, New Haven, Connecticut 06520, USA; email: alvaro.sanchez@yale.edu, jean.vila@yale.edu, chang-yu.chang@yale.edu, juan.diazcolunga@gmail.com, sylvie.estrela@yale.edu, maria.rebolleda-gomez@yale.edu.
Chang-Yu ChangDepartment of Ecology & Evolutionary Biology and Microbial Sciences Institute, Yale University, New Haven, Connecticut 06520, USA; email: alvaro.sanchez@yale.edu, jean.vila@yale.edu, chang-yu.chang@yale.edu, juan.diazcolunga@gmail.com, sylvie.estrela@yale.edu, maria.rebolleda-gomez@yale.edu.
Juan Diaz-ColungaDepartment of Ecology & Evolutionary Biology and Microbial Sciences Institute, Yale University, New Haven, Connecticut 06520, USA; email: alvaro.sanchez@yale.edu, jean.vila@yale.edu, chang-yu.chang@yale.edu, juan.diazcolunga@gmail.com, sylvie.estrela@yale.edu, maria.rebolleda-gomez@yale.edu.
Sylvie EstrelaDepartment of Ecology & Evolutionary Biology and Microbial Sciences Institute, Yale University, New Haven, Connecticut 06520, USA; email: alvaro.sanchez@yale.edu, jean.vila@yale.edu, chang-yu.chang@yale.edu, juan.diazcolunga@gmail.com, sylvie.estrela@yale.edu, maria.rebolleda-gomez@yale.edu.
María Rebolleda-GomezDepartment of Ecology & Evolutionary Biology and Microbial Sciences Institute, Yale University, New Haven, Connecticut 06520, USA; email: alvaro.sanchez@yale.edu, jean.vila@yale.edu, chang-yu.chang@yale.edu, juan.diazcolunga@gmail.com, sylvie.estrela@yale.edu, maria.rebolleda-gomez@yale.edu.

Funding

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 GM133467
6 · The paper itself

Abstract

Directed evolution is a form of artificial selection that has been used for decades to find biomolecules and organisms with new or enhanced functional traits. Directed evolution can be conceptualized as a guided exploration of the genotype-phenotype map, where genetic variants with desirable phenotypes are first selected and then mutagenized to search the genotype space for an even better mutant. In recent years, the idea of applying artificial selection to microbial communities has gained momentum. In this article, we review the main limitations of artificial selection when applied to large and diverse collectives of asexually dividing microbes and discuss how the tools of directed evolution may be deployed to engineer communities from the top down. We conceptualize directed evolution of microbial communities as a guided exploration of an ecological structure-function landscape and propose practical guidelines for navigating these ecological landscapes.

Indexed as

MicrobiotaAnimalsBiological EvolutionGenotypeHumansPhenotypeartificial ecosystem selectioncollective community functionsdirected evolutionmicrobial communitiesstructure–function landscape

Identifiers

PMID33646814
PMCPMC8105285

What Socratic holds

Textmetadata
LicenceTDM
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 Socratic graph.