Evidence map›Paper›PMID 36072290›Full record

ArticleFrontiers in bioengineering and biotechnology2022

A rapid and standardized workflow for functional assessment of bacterial biosensors in fecal samples.

Ana Zúñiga, Geisler Muñoz-Guamuro, Lucile Boivineau, Pauline Mayonove, Ismael Conejero, Georges-Philippe Pageaux, Romain Altwegg, Jerome Bonnet

Abstract read
In one paragraph

Article in Frontiers in bioengineering and biotechnology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
–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

5 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Review
  4. Article
  5. Review
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

8 authors.

Ana ZúñigaCentre de Biologie Structurale (CBS), INSERM U1054, CNRS UMR5048, University of Montpellier, Montpellier, France.
Geisler Muñoz-GuamuroCentre de Biologie Structurale (CBS), INSERM U1054, CNRS UMR5048, University of Montpellier, Montpellier, France.
Lucile BoivineauHepatogastroenterology and Bacteriology Service at CHU Montpellier, University of Montpellier, Montpellier, France.
Pauline MayonoveCentre de Biologie Structurale (CBS), INSERM U1054, CNRS UMR5048, University of Montpellier, Montpellier, France.
Ismael ConejeroDepartment of Psychiatry, CHU Nimes, University of Montpellier, Montpellier, France.
Georges-Philippe PageauxHepatogastroenterology and Bacteriology Service at CHU Montpellier, University of Montpellier, Montpellier, France.
Romain AltweggHepatogastroenterology and Bacteriology Service at CHU Montpellier, University of Montpellier, Montpellier, France.
Jerome BonnetCentre de Biologie Structurale (CBS), INSERM U1054, CNRS UMR5048, University of Montpellier, Montpellier, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Gut metabolites are pivotal mediators of host-microbiome interactions and provide an important window on human physiology and disease. However, current methods to monitor gut metabolites rely on heavy and expensive technologies such as liquid chromatography-mass spectrometry (LC-MS). In that context, robust, fast, field-deployable, and cost-effective strategies for monitoring fecal metabolites would support large-scale functional studies and routine monitoring of metabolites biomarkers associated with pathological conditions. Living cells are an attractive option to engineer biosensors due to their ability to detect and process many environmental signals and their self-replicating nature. Here we optimized a workflow for feces processing that supports metabolite detection using bacterial biosensors. We show that simple centrifugation and filtration steps remove host microbes and support reproducible preparation of a physiological-derived media retaining important characteristics of human feces, such as matrix effects and endogenous metabolites. We measure the performance of bacterial biosensors for benzoate, lactate, anhydrotetracycline, and bile acids, and find that they are highly sensitive to fecal matrices. However, encapsulating the bacteria in hydrogel helps reduce this inhibitory effect. Sensitivity to matrix effects is biosensor-dependent but also varies between individuals, highlighting the need for case-by-case optimization for biosensors' operation in feces. Finally, by detecting endogenous bile acids, we demonstrate that bacterial biosensors could be used for future metabolite monitoring in feces. This work lays the foundation for the optimization and use of bacterial biosensors for fecal metabolites monitoring. In the future, our method could also allow rapid pre-prototyping of engineered bacteria designed to operate in the gut, with applications to

Indexed as

diagnosticsengineered bacteriagut microbiomemetabolite detectionsynthetic biologywhole-cell biosensor

Identifiers

PMID36072290
PMCPMC9444133

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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.