Sensory Systems and Transcriptional Regulation in Escherichia coli

Abstract

In free-living bacteria, the ability to regulate gene expression is at the core of adapting and interacting with the environment. For these systems to have a logic, a signal must trigger a genetic change that helps the cell to deal with what implies its presence in the environment; briefly, the response is expected to include a feedback to the signal. Thus, it makes sense to think of genetic sensory mechanisms of gene regulation. Escherichia coli K-12 is the bacterium model for which the largest number of regulatory systems and its sensing capabilities have been studied in detail at the molecular level. In this special issue focused on biomolecular sensing systems, we offer an overview of the transcriptional regulatory corpus of knowledge for E. coli that has been gathered in our database, RegulonDB, from the perspective of sensing regulatory systems. Thus, we start with the beginning of the information flux, which is the signal’s chemical or physical elements detected by the cell as changes in the environment; these signals are internally transduced to transcription factors and alter their conformation. Signals transduced to effectors bind allosterically to transcription factors, and this defines the dominant sensing mechanism in E. coli. We offer an updated list of the repertoire of known allosteric effectors, as well as a list of the currently known different mechanisms of this sensing capability. Our previous definition of elementary genetic sensory-response units, GENSOR units for short, that integrate signals, transport, gene regulation, and the biochemical response of the regulated gene products of a given transcriptional factor fit perfectly with the purpose of this overview. We summarize the functional heterogeneity of their response, based on our updated collection of GENSORs, and we use them to identify the expected feedback as part of their response. Finally, we address the question of multiple sensing in the regulatory network of E. coli. This overview introduces the architecture of sensing and regulation of native components in E.coli K-12, which might be a source of inspiration to bioengineering applications.

Inferring causal gene regulatory network via GreyNet: From dynamic grey association to causation

“…Reconstructing the causal gene regulatory network is a preliminary step to finding out the internal mechanism of the biological procedure and facilitating our understanding of the basic pathology of tumors and other diseases ( Lesage et al, 2018 ; Femerling et al, 2022 ). However, current biological datasets generated by the facilities are usually accompanied by a low rate of signal-to-noise ratio.…”

Regulatory transcription factor (CooA)-driven carbon monoxide partial pressure sensing whole-cell biosensor

“…, CO) detection system based on regulatory transcription factor ( i.e ., CooA), indicating that the development of a CO-sensing whole-cell biosensor is possible by utilizing CO-sensing transcriptional regulatory mechanisms and reporter proteins [ 12 ]. A CooA-based CO-sensing mechanism allows cells to recognize and respond to the presence of CO and trigger the expression of a GUS reporter protein (β-glucuronidase) [ 13 , 14 , 15 ]. As a visual indicator of CO exposure, CO-sensing whole-cell biosensors have the potential to elucidate intracellular regulatory mechanisms directly involving CO [ 16 ].…”

“…As a visual indicator of CO exposure, CO-sensing whole-cell biosensors have the potential to elucidate intracellular regulatory mechanisms directly involving CO [ 16 ]. This type of biosensor, which incorporates a living cell, provides an accurate representation of a cell's complex and dynamic environment and allows investigation of the interplay between CO and cellular processes [ 13 , 17 ]. In particular, the occurrence of CO sensing and regulation of regulation intensity could be identified.…”

“…This knowledge may inform the development of more efficient and effective CO-utilizing microorganisms [ 19 ]. Second, identifying CO-sensing transcriptional regulatory mechanisms is crucial for developing CO-sensing biosensors with potential applications in industrial biotechnology, environmental monitoring, and human health [ 13 ]. Finally, by understanding how microorganisms sense and respond to CO, it is possible to develop more effective strategies for using CO as a renewable energy source by controlling and optimizing CO utilization in microorganisms [ 20 ].…”

Overview of the Molecular Mechanism of Bacterial Environmental Adaptation by Comprehensive Analysis

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