ArticlemSystems2024
Kinetics-based inference of environment-dependent microbial interactions and their dynamic variation.
Article in mSystems, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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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.
The trial behind it
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Who cites it
6 citing papers in PubMed.
- Quartet: Disentangling positive and negative components of microbial interactions.PLoS computational biology · 2026Article
- A survey of computational approaches for characterizing microbial interactions in microbial mats.Genome biology · 2025Review
- Diversity in chemical subunits and linkages: a key molecular determinant of microbial richness, microbiota interactions, and substrate utilization.Microbiology spectrum · 2025Article
- Directing microbial co-culture composition using cybernetic control.Cell reports methods · 2025Article
- 3D imaging-driven assembly of multispecies biofilms with antagonistic activity against undesirable bacteria.ISME communications · 2025Article
- Effect of microbial interactions on performance of community metabolic modeling algorithms: flux balance analysis (FBA), community FBA (cFBA) and SteadyCom.Bioprocess and biosystems engineering · 2024Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
Microbial communities in nature are dynamically evolving as member species change their interactions subject to environmental variations. Accounting for such context-dependent dynamic variations in interspecies interactions is critical for predictive ecological modeling. In the absence of generalizable theoretical foundations, we lack a fundamental understanding of how microbial interactions are driven by environmental factors, significantly limiting our capability to predict and engineer community dynamics and function. To address this issue, we propose a novel theoretical framework that allows us to represent interspecies interactions as an explicit function of environmental variables (such as substrate concentrations) by combining growth kinetics and a generalized Lotka-Volterra model. A synergistic integration of these two complementary models leads to the prediction of alterations in interspecies interactions as the outcome of dynamic balances between positive and negative influences of microbial species in mixed relationships. The effectiveness of our method was experimentally demonstrated using a synthetic consortium of two
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Registered trials
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.