Evidence map›Paper›PMID 34584635›Full record

ReviewComputational and structural biotechnology journal2021

Modelling microbial communities: Harnessing consortia for biotechnological applications.

Maziya Ibrahim, Lavanya Raajaraam, Karthik Raman

Abstract readReview
In one paragraph

Review in Computational and structural biotechnology journal, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.

0numbers the graph read from it
0cells of the map it votes in
28citing 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

28 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
  4. Review
  5. Review
  6. Recent trends in microbial production of alkanes.World journal of microbiology & biotechnology · 2025
    Review
  7. COmmunity and Single Microbe Optimisation System (COSMOS).NPJ systems biology and applications · 2025
    Article
  8. mSystems · 2025
    Article
  9. Article
  10. Article
  11. Construction of a syntrophicSynthetic biology (Oxford, England) · 2025
    Article
  12. Review
  13. Deciphering and designing microbial communities by genome-scale metabolic modelling.Computational and structural biotechnology journal · 2024
    Review
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Review
  20. 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

3 authors.

Maziya IbrahimBhupat and Jyoti Mehta School of Biosciences, Department of Biotechnology, Indian Institute of Technology (IIT) Madras, Chennai 600 036, India.
Lavanya RaajaraamBhupat and Jyoti Mehta School of Biosciences, Department of Biotechnology, Indian Institute of Technology (IIT) Madras, Chennai 600 036, India.
Karthik RamanBhupat and Jyoti Mehta School of Biosciences, Department of Biotechnology, Indian Institute of Technology (IIT) Madras, Chennai 600 036, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Microbes propagate and thrive in complex communities, and there are many benefits to studying and engineering microbial communities instead of single strains. Microbial communities are being increasingly leveraged in biotechnological applications, as they present significant advantages such as the division of labour and improved substrate utilisation. Nevertheless, they also present some interesting challenges to surmount for the design of efficient biotechnological processes. In this review, we discuss key principles of microbial interactions, followed by a deep dive into genome-scale metabolic models, focussing on a vast repertoire of constraint-based modelling methods that enable us to characterise and understand the metabolic capabilities of microbial communities. Complementary approaches to model microbial communities, such as those based on graph theory, are also briefly discussed. Taken together, these methods provide rich insights into the interactions between microbes and how they influence microbial community productivity. We finally overview approaches that allow us to generate and test numerous synthetic community compositions, followed by tools and methodologies that can predict effective genetic interventions to further improve the productivity of communities. With impending advancements in high-throughput omics of microbial communities, the stage is set for the rapid expansion of microbial community engineering, with a significant impact on biotechnological processes.

Indexed as

Constraint-based modellingGenome-scale modelsMetabolic engineeringMetabolic modellingMicrobial consortiaMicrobiome

Identifiers

PMID34584635
PMCPMC8441623

What OpenQuestion holds

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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.