E.coli aerobic/anaerobic switch study Chao Wang, Mar

The bacterium E. coli possesses a large number of sensing/regulation systems for rapid response to environmental changes. Those regulation systems allow variation in the way electrons are channeled from donor to terminal acceptors such that the overall potential difference is maximized for any given growth condition. The adaptive responses are coordinated by a group of global regulators, which includes the one component furmarate & nitrate reduction (FNR) protein, and the two-component anoxic redox control (Arc) system. With the initial onset of anaerobiosis ArcA is activated, and if these conditions persist or become more anaerobic, FNR is activated leading in turn to the upregulation of ArcA and amplification of its effect

Fnr Modulon Fnr is a global transcription regulator with similarity to CRP; it has 4 Cys residues that have been shown to bind a 4Fe-4S cluster under some conditions and 2 [2Fe-2S] centers under other conditions. Hence, a redox-sensitive confirmational change can occur that mediates control of transcription of ~30 transcription units and >70 genes. For nitrate reductase, Fnr only potentiates expression. Nitrate must be present to relieve repression by NarX/NarL two component sensor-regulator system.

ArcA/B Modulon In this system, ArcB is the sensor kinase, and is a membrane- bound protein found in the cytoplasmic membrane. ArcA is the response regulator of the system and is a DNA-binding transcriptional regulator. The signal that causes autophosphorylation of ArcB and phosphotransfer to ArcA is not known, but is presumed to be either the proton motive force or a redox signal, possibly the redox state of the quinone pool. Target genes include those encoding quinol oxidase, succinate dehydrogenase, superoxide dismutase and many others involved in aerobic metabolism and energy production.

Metabolic network This system of connected chemical reactions is a metabolic network. The raw metabolic data collected at KEGG consist of a detailed list of biochemical reactions. Besides annotations for genes and genomes, KEGG contains comprehensive information on biochemical reactions, enzymes, and pathways. Transcriptional Regulation Network Transcriptional regulation is the mechanism that coordinates the expression of genetic information coded on the DNA with the needs of various life processes. The regulation of transcription factors and non-TF transcription units form a network of transcriptional regulation. Gene Expression Data The genome-scale cDNA microarray experiment measures the expression differences under different conditions for virtually all genes of an organism.

To understand metabolic and transcriptional regulation networks in term of their function in the organism. One proper example in this respect is the transcription regulated response of an E. coli cell to oxygen availability.

Flux Balance Analysis of Metabolic Network Flux balance analysis or FBA, is to find the flux for each reaction in the network by linear programming. Mass balance equations accounting for all reactions and transport mechanisms are written for each species. These equations are then rewritten in matrix form. At steady state, this reduces to S · V=0.

Genetic network assisted flux balance analysis

Xoygen and redox sensing pathways in E.coli

Major central metabolic pathways

Main constituents of the Fnr ArcA/B regulon that impact major metabolites

Major anaerobic and aerobic pathways

Fnr and AcrA have a set of overlapping target genes. Mapping out this set of genes on the metabolic net and combining some experimental knowledge from literatures, we may learn more about the crucial pathways. In San’s study, only two state (+O2 and –O2) were investigated. With glucose and oxygen as the controlling variables, we want to characterize a continuous activity of target enzymes, metabolites and reactions. And using PhPP analysis, we may reveal some phases about the changes in flux pattern. With varying oxygen content, which are different conditions, genes have different expressions. We can map these involved genes to proposed pathways. We can study the relation among the expression, transcription regulation and metabolic activities.

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