Evidence map›Paper›PMID 42565891›Full record

ReviewArchives of microbiology2026

Regulation of Escherichia coli fermentation processes: from molecular mechanisms to smart industrial practice.

Haoni Luan, Wenhan Qiu, Rui Yang, Kaiyue Feng, Wei Xu, Fei Wang, Wei Feng, Peng Song

Abstract readReview
PubMed Publisher
In one paragraph

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.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

8 authors.

Haoni LuanSchool of Pharmaceutical Sciences and Food Engineering, Liaocheng University, Liaocheng, 252000, China.
Wenhan QiuSchool of Pharmaceutical Sciences and Food Engineering, Liaocheng University, Liaocheng, 252000, China.
Rui YangSchool of Pharmaceutical Sciences and Food Engineering, Liaocheng University, Liaocheng, 252000, China.
Kaiyue FengCollege of Agriculture and Biology, Liaocheng University, Liaocheng, 252000, China.
Wei XuSchool of Pharmaceutical Sciences and Food Engineering, Liaocheng University, Liaocheng, 252000, China.
Fei WangSchool of Pharmaceutical Sciences and Food Engineering, Liaocheng University, Liaocheng, 252000, China.
Wei FengSchool of Pharmaceutical Sciences and Food Engineering, Liaocheng University, Liaocheng, 252000, China.
Peng SongSchool of Pharmaceutical Sciences and Food Engineering, Liaocheng University, Liaocheng, 252000, China. songpeng@lcu.edu.cn.

Funding

National Natural Science Foundation of China No. 82304838Natural Science Foundation of Shandong Province ZR2022MC159
6 · The paper itself

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

Escherichia coliFermentationIndustrial MicrobiologyBioreactorsGene Expression Regulation, BacterialMetabolic EngineeringModels, BiologicalDynamic regulationEscherichia coliGreen biomanufacturingIndustrial scale-upIntelligent control

Identifiers

What OpenQuestion holds

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Read underepoch 390

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.