Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 487

The DOI matches its Crossref record; 15 of the 15 references it cites were found in a registry or an index.

Metabolite induction via microorganism co-culture: A potential way to enhance chemical diversity for drug discovery

Open access
Bertrand, Samuel, Bohni, Nadine, Schnee, Sylvain, Schumpp, Olivier, Gindro, Katia, Wolfender, Jean-Luc·2014·Biotechnology Advances

Abstract

Microorganisms have a long track record as important sources of novel bioactive natural products, particularly in the field of drug discovery. While microbes have been shown to biosynthesize a wide array of molecules, recent advances in genome sequencing have revealed that such organisms have the potential to yield even more structurally diverse secondary metabolites. Thus, many microbial gene clusters may be silent under standard laboratory growth conditions. In the last ten years, several methods have been developed to aid in the activation of these cryptic biosynthetic pathways. In addition to the techniques that demand prior knowledge of the genome sequences of the studied microorganisms, several genome sequence-independent tools have been developed. One of these approaches is microorganism co-culture, involving the cultivation of two or more microorganisms in the same confined environment. Microorganism co-culture is inspired by the natural microbe communities that are omnipresent in nature. Within these communities, microbes interact through signaling or defense molecules. Such compounds, produced dynamically, are of potential interest as new leads for drug discovery. Microorganism co-culture can be achieved in either solid or liquid media and has recently been used increasingly extensively to study natural interactions and discover new bioactive metabolites. Because of the complexity of microbial extracts, advanced analytical methods (e.g., mass spectrometry methods and metabolomics) are key for the successful detection and identification of co-culture-induced metabolites. This review focuses on co-culture studies that aim to increase the diversity of metabolites obtained from microbes. The various strategies are summarized with a special emphasis on the multiple methods of performing co-culture experiments. The analytical approaches for studying these interaction phenomena are discussed, and the chemical diversity and biological activity observed among the induced metabolites are described.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1016/j.biotechadv.2014.03.001

Cites

15 of 15 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 15 references

Cited by

See all 487

Metadata

Authors
Bertrand, S., Bohni, N., Schnee, S., Schumpp, O., Gindro, K., & Wolfender, J.-L.
Venue
Biotechnology Advances
Publisher
Elsevier BV
Published
2014-11
Volume
32
Issue
6
Pages
1180-1204
ISSN
0734-9750 (ISSN-L)
OpenAlex
W2017343996
Cited by
487
References
15
FWCI
20.35
Type
journal article
Language
en
Open access
green

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Metabolite induction via microorganism co-culture: A potential way to enhance chemical diversity for drug discovery. https://app.cochat.ai/papers/10.1016/j.biotechadv.2014.03.001
The paper
Bertrand, S., Bohni, N., Schnee, S., Schumpp, O., Gindro, K., & Wolfender, J.-L. (2014). Metabolite induction via microorganism co-culture: A potential way to enhance chemical diversity for drug discovery. Biotechnology Advances. https://doi.org/10.1016/j.biotechadv.2014.03.001

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.