Evidence map›Paper›PMID 32282794›Full record

ArticlePLoS computational biology2020

Enhanced production of heterologous proteins by a synthetic microbial community: Conditions and trade-offs.

Marco Mauri, Jean-Luc Gouzé, Hidde de Jong, Eugenio Cinquemani

Abstract read
In one paragraph

Article in PLoS computational biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. Global dynamics of the chemostat with overflow metabolism.Journal of mathematical biology · 2021
    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

4 authors.

Marco MauriUniv. Grenoble Alpes, Inria, 38000 Grenoble, France.ORCID 0000-0001-6345-5369
Jean-Luc GouzéUniversity Côte d'Azur, Inria, INRAE, CNRS, Sorbonne Université, Biocore Team, 06902 Sophia-Antipolis, France.ORCID 0000-0001-7156-7934
Hidde de JongUniv. Grenoble Alpes, Inria, 38000 Grenoble, France.ORCID 0000-0002-2226-650X
Eugenio CinquemaniUniv. Grenoble Alpes, Inria, 38000 Grenoble, France.ORCID 0000-0003-3353-6525

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Synthetic microbial consortia have been increasingly utilized in biotechnology and experimental evidence shows that suitably engineered consortia can outperform individual species in the synthesis of valuable products. Despite significant achievements, though, a quantitative understanding of the conditions that make this possible, and of the trade-offs due to the concurrent growth of multiple species, is still limited. In this work, we contribute to filling this gap by the investigation of a known prototypical synthetic consortium. A first E. coli strain, producing a heterologous protein, is sided by a second E. coli strain engineered to scavenge toxic byproducts, thus favoring the growth of the producer at the expense of diverting part of the resources to the growth of the cleaner. The simplicity of the consortium is ideal to perform an in depth-analysis and draw conclusions of more general interest. We develop a coarse-grained mathematical model that quantitatively accounts for literature data from different key growth phenotypes. Based on this, assuming growth in chemostat, we first investigate the conditions enabling stable coexistence of both strains and the effect of the metabolic load due to heterologous protein production. In these conditions, we establish when and to what extent the consortium outperforms the producer alone in terms of productivity. Finally, we show in chemostat as well as in a fed-batch scenario that gain in productivity comes at the price of a reduced yield, reflecting at the level of the consortium resource allocation trade-offs that are well-known for individual species.

Indexed as

MicrobiotaRecombinant ProteinsEscherichia coliMetabolic EngineeringModels, BiologicalSynthetic BiologyRecombinant Proteins

Identifiers

PMID32282794
PMCPMC7179936

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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.