Evidence map›Paper›PMID 31409662›Full record

ArticlemSystems2019

Engineered Interspecies Amino Acid Cross-Feeding Increases Population Evenness in a Synthetic Bacterial Consortium.

Marika Ziesack, Travis Gibson, John K W Oliver, Andrew M Shumaker, Bryan B Hsu, David T Riglar, Tobias W Giessen, Nicholas V DiBenedetto, Lynn Bry, Jeffrey C Way and 2 more

Abstract read
In one paragraph

Article in mSystems, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.

0numbers the graph read from it
0cells of the map it votes in
33citing 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

33 citing papers in PubMed.

  1. Engineering an asymmetric cross-feeding consortium inSynthetic and systems biotechnology · 2026
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  17. Chaos in synthetic microbial communities.PLoS computational biology · 2022
    Article
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  19. Review
  20. Article
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

12 authors.

Marika ZiesackWyss Institute for Biologically Inspired Engineering, Harvard Medical School, Boston, Massachusetts, USA.ORCID https://orcid.org/0000-0003-0587-6581
Travis GibsonMassachusetts Host-Microbiome Center, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA.
John K W OliverWyss Institute for Biologically Inspired Engineering, Harvard Medical School, Boston, Massachusetts, USA.
Andrew M ShumakerWyss Institute for Biologically Inspired Engineering, Harvard Medical School, Boston, Massachusetts, USA.
Bryan B HsuDepartment of Systems Biology, Harvard Medical School, Boston, Massachusetts, USA.
David T RiglarWyss Institute for Biologically Inspired Engineering, Harvard Medical School, Boston, Massachusetts, USA.
Tobias W GiessenDepartment of Systems Biology, Harvard Medical School, Boston, Massachusetts, USA.
Nicholas V DiBenedettoMassachusetts Host-Microbiome Center, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA.
Lynn BryMassachusetts Host-Microbiome Center, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA.
Jeffrey C Way *Wyss Institute for Biologically Inspired Engineering, Harvard Medical School, Boston, Massachusetts, USA.
Pamela A Silver *Wyss Institute for Biologically Inspired Engineering, Harvard Medical School, Boston, Massachusetts, USA Pamela_Silver@hms.harvard.edu ggerber@bwh.harvard.edu.
Georg K Gerber *Massachusetts Host-Microbiome Center, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA Pamela_Silver@hms.harvard.edu ggerber@bwh.harvard.edu.

Funding

STRUCTURE-FUNCTION RELATIONSHIPS IN THE ALIMENTARY TRACTP30DK034854 · NIDDK · HARVARD UNIVERSITY (MEDICAL SCHOOL) · PI JONATHAN C KAGAN · 1986 to 2026
$32.4M
VASCULAR, PULMONARY AND RENAL INJURYT32HL007627 · NHLBI · BRIGHAM AND WOMEN'S HOSPITAL · PI GIMBRONE, MICHAEL A, MITCHELL, RICHARD N · 1985 to 2019
$12.7M
Bayesian Machine Learning Tools for Analyzing Microbiome DynamicsR01GM130777 · NIGMS · BRIGHAM AND WOMEN'S HOSPITAL · PI GERBER, GEORG KURT · 2018 to 2022
$1.6M
NHLBI NIH HHS T32 HL007627NIDDK NIH HHS P30 DK034854NIGMS NIH HHS R01 GM130777
6 · The paper itself

Abstract

In nature, microbes interact antagonistically, neutrally, or beneficially. To shed light on the effects of positive interactions in microbial consortia, we introduced metabolic dependencies and metabolite overproduction into four bacterial species. While antagonistic interactions govern the wild-type consortium behavior, the genetic modifications alleviated antagonistic interactions and resulted in beneficial interactions. Engineered cross-feeding increased population evenness, a component of ecological diversity, in different environments, including in a more complex gnotobiotic mouse gut environment. Our findings suggest that metabolite cross-feeding could be used as a tool for intentionally shaping microbial consortia in complex environments.

Indexed as

metabolite cross-feedingmicrobial consortiasynthetic biology

Identifiers

PMID31409662
PMCPMC6697442

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.