DOE OSTI · 3490010
Coarse-grained resource allocation modeling for decoding and rewiring microbial metabolism
Abstract
Microbial metabolism is a complex, emergent system driven by the coordinated interplay of intricate and dynamic molecular processes. To elucidate cellular behavior and enable biotechnological applications, quantitative models that address the inherent complexity of metabolism have been developed from a resource allocation perspective. Here, we synthesize recent advances in coarse-grained resource allocation frameworks and their applications in understanding microbial physiology and guiding gene circuit design. Here, these frameworks reveal global regulatory constraints and predict cellular adaptation to nutrient and environmental changes. In addition, they enable the quantification of metabolic costs, the dissection of circuit–host interactions, and the development of strategies for burden mitigation. Collectively, these modeling frameworks provide a powerful platform for uncovering quantitative principles of microbial growth and engineering robust synthetic biological systems.
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Lai, Yi-Hui [University of Illinois Urbana-Champaign, IL (United States)], Lu, Ting [University of Illinois Urbana-Champaign, IL (United States)] (ORCID:0000000190433253). 2026-08-01. Coarse-grained resource allocation modeling for decoding and rewiring microbial metabolism. https://doi.org/10.1016/j.tim.2026.07.011
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