TY - JOUR
T1 - Resource-allocation constraint governs structure and function of microbial communities in metabolic modeling
AU - Kim, Minsuk
AU - Sung, Jaeyun
AU - Chia, Nicholas
N1 - Publisher Copyright:
© 2021
PY - 2022/3
Y1 - 2022/3
N2 - Predictive modeling tools for assessing microbial communities are important for realizing transformative capabilities of microbiomes in agriculture, ecology, and medicine. Constraint-based community-scale metabolic modeling is unique in its potential for making mechanistic predictions regarding both the structure and function of microbial communities. However, accessing this potential requires an understanding of key physicochemical constraints, which are typically considered on a per-species basis. What is needed is a means of incorporating global constraints relevant to microbial ecology into community models. Resource-allocation constraint, which describes how limited resources should be distributed to different cellular processes, sets limits on the efficiency of metabolic and ecological processes. In this study, we investigate the implications of resource-allocation constraints in community-scale metabolic modeling through a simple mechanism-agnostic implementation of resource-allocation constraints directly at the flux level. By systematically performing single-, two-, and multi-species growth simulations, we show that resource-allocation constraints are indispensable for predicting the structure and function of microbial communities. Our findings call for a scalable workflow for implementing a mechanistic version of resource-allocation constraints to ultimately harness the full potential of community-scale metabolic modeling tools.
AB - Predictive modeling tools for assessing microbial communities are important for realizing transformative capabilities of microbiomes in agriculture, ecology, and medicine. Constraint-based community-scale metabolic modeling is unique in its potential for making mechanistic predictions regarding both the structure and function of microbial communities. However, accessing this potential requires an understanding of key physicochemical constraints, which are typically considered on a per-species basis. What is needed is a means of incorporating global constraints relevant to microbial ecology into community models. Resource-allocation constraint, which describes how limited resources should be distributed to different cellular processes, sets limits on the efficiency of metabolic and ecological processes. In this study, we investigate the implications of resource-allocation constraints in community-scale metabolic modeling through a simple mechanism-agnostic implementation of resource-allocation constraints directly at the flux level. By systematically performing single-, two-, and multi-species growth simulations, we show that resource-allocation constraints are indispensable for predicting the structure and function of microbial communities. Our findings call for a scalable workflow for implementing a mechanistic version of resource-allocation constraints to ultimately harness the full potential of community-scale metabolic modeling tools.
KW - Gut microbiome
KW - Metabolic modeling
KW - Microbial communities
KW - Resource allocation
UR - http://www.scopus.com/inward/record.url?scp=85122519659&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85122519659&partnerID=8YFLogxK
U2 - 10.1016/j.ymben.2021.12.011
DO - 10.1016/j.ymben.2021.12.011
M3 - Article
C2 - 34990848
AN - SCOPUS:85122519659
SN - 1096-7176
VL - 70
SP - 12
EP - 22
JO - Metabolic Engineering
JF - Metabolic Engineering
ER -