ReviewArchives of microbiology2026
Regulation of Escherichia coli fermentation processes: from molecular mechanisms to smart industrial practice.
Review in Archives of microbiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
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.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
Escherichia coli remains the premier microbial chassis in industrial biotechnology; yet, translating laboratory-scale metabolic successes into robust, hundred-ton-scale manufacturing presents persistent multidimensional bottlenecks. This review systematically elucidates a contemporary paradigm shift in E. coli fermentation regulation, transitioning from isolated, empirical process adjustments to cross-scale, deeply coupled intelligent cybernetic frameworks. We first deconstruct the precise cross-scale links between macroscopic physicochemical parameters and intracellular biological regulatory networks, detailing how fluctuations in temperature, pH, and dissolved oxygen fundamentally reshape intracellular molecular cascades alongside transmembrane proton motive forces. To mitigate spatial heterogeneity, substrate mixing delays, and carbon catabolite repression common in large-volume bioreactors, we comprehensively evaluate advanced mitigation strategies that integrate process-level model predictive control (MPC) with dynamic synthetic biology circuits, including quorum-sensing-based growth-production decoupling, metabolite-responsive feedback loops, and optogenetic switches. Critically, we highlight the convergence of multi-scale modeling and digital twins as a frontier simulation-driven tool, which dynamically couples computational fluid dynamics (CFD) with genome-scale metabolic models (GEMs) to render the industrial fermentation "black box" transparent. Finally, we outline the evolutionary trajectory of E. coli biomanufacturing toward a digitized, intelligent, and sustainable paradigm, leveraging low-carbon C1 feedstocks and paving the way for next-generation green biomanufacturing.
Indexed as
Identifiers
42565891What OpenQuestion holds
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.