A systems biology approach sheds new light on the regulation of acid adaptation in Escherichia coli BW25113 and MG1655 strains

The ability of Escherichia coli to survive in extreme acid conditions is an important component of its physiology. In my study I have profiled the Escherichia coli K-12 BW25113 strain using microarray technology and I have analysed a multi-omics dataset representing the transcriptional and metabolic responses of the MG1655 Escherichia coli strain. An initial high-level model in the BW25113 strain representing the interaction between two component systems regulators and effectors functions was built using the ARACNE methodology. My model supported the view that acid resistance involves a mechanism based on the transcriptional switch between the expression of genes encoding aerobic and anaerobic enzymes and controlled by the two-component system regulator OmpR. Experimental validation of the model confirmed this hypothesis. This model allowed me to predict that the MG1655 strain would be more sensitive to acid than the related BW25113 strain. Acid exposure induced an opposite response in this strain by repressing most of the anaerobic enzymes in favour of the aerobic metabolism. A dynamical model, developed by using State Space Models, revealed three potential regulators of acid adaptation in the MG1655 strain: OmpR, YehT and DcuR. I concluded that OmpR has a key role in acid adaptation in both strains and that the ability to reassess the balance in the expression of bioenergetics genes is more important for survival than proton detoxification

A computational framework for gene regulatory network inference that combines multiple methods and datasets

<p>Abstract</p> <p>Background</p> <p>Reverse engineering in systems biology entails inference of gene regulatory networks from observational data. This data typically include gene expression measurements of wild type and mutant cells in response to a given stimulus. It has been shown that when more than one type of experiment is used in the network inference process the accuracy is higher. Therefore the development of generally applicable and effective methodologies that embed multiple sources of information in a single computational framework is a worthwhile objective.</p> <p>Results</p> <p>This paper presents a new method for network inference, which uses multi-objective optimisation (MOO) to integrate multiple inference methods and experiments. We illustrate the potential of the methodology by combining ODE and correlation-based network inference procedures as well as time course and gene inactivation experiments. Here we show that our methodology is effective for a wide spectrum of data sets and method integration strategies.</p> <p>Conclusions</p> <p>The approach we present in this paper is flexible and can be used in any scenario that benefits from integration of multiple sources of information and modelling procedures in the inference process. Moreover, the application of this method to two case studies representative of bacteria and vertebrate systems has shown potential in identifying key regulators of important biological processes.</p

A systems biology approach sheds new light on Escherichia coli acid resistance

In order to develop an infection, diarrhogenic Escherichia coli has to pass through the stomach, where the pH can be as low as 1. Mechanisms that enable E. coli to survive in low pH are thus potentially relevant for pathogenicity. Four acid response systems involved in reducing the concentration of intracellular protons have been identified so far. However, it is still unclear to what extent the regulation of other important cellular functions may be required for survival in acid conditions. Here, we have combined molecular and phenotypic analysis of wild-type and mutant strains with computational network inference to identify molecular pathways underlying E. coli response to mild and strong acid conditions. The interpretative model we have developed led to the hypothesis that a complex transcriptional programme, dependent on the two-component system regulator OmpR and involving a switch between aerobic and anaerobic metabolism, may be key for survival. Experimental validation has shown that the OmpR is responsible for controlling a sizeable component of the transcriptional programme to acid exposure. Moreover, we found that a ΔompR strain was unable to mount any transcriptional response to acid exposure and had one of the strongest acid sensitive phenotype observed

The return of metabolism: biochemistry and physiology of the pentose phosphate pathway.

The pentose phosphate pathway (PPP) is a fundamental component of cellular metabolism. The PPP is important to maintain carbon homoeostasis, to provide precursors for nucleotide and amino acid biosynthesis, to provide reducing molecules for anabolism, and to defeat oxidative stress. The PPP shares reactions with the Entner-Doudoroff pathway and Calvin cycle and divides into an oxidative and non-oxidative branch. The oxidative branch is highly active in most eukaryotes and converts glucose 6-phosphate into carbon dioxide, ribulose 5-phosphate and NADPH. The latter function is critical to maintain redox balance under stress situations, when cells proliferate rapidly, in ageing, and for the 'Warburg effect' of cancer cells. The non-oxidative branch instead is virtually ubiquitous, and metabolizes the glycolytic intermediates fructose 6-phosphate and glyceraldehyde 3-phosphate as well as sedoheptulose sugars, yielding ribose 5-phosphate for the synthesis of nucleic acids and sugar phosphate precursors for the synthesis of amino acids. Whereas the oxidative PPP is considered unidirectional, the non-oxidative branch can supply glycolysis with intermediates derived from ribose 5-phosphate and vice versa, depending on the biochemical demand. These functions require dynamic regulation of the PPP pathway that is achieved through hierarchical interactions between transcriptome, proteome and metabolome. Consequently, the biochemistry and regulation of this pathway, while still unresolved in many cases, are archetypal for the dynamics of the metabolic network of the cell. In this comprehensive article we review seminal work that led to the discovery and description of the pathway that date back now for 80 years, and address recent results about genetic and metabolic mechanisms that regulate its activity. These biochemical principles are discussed in the context of PPP deficiencies causing metabolic disease and the role of this pathway in biotechnology, bacterial and parasite infections, neurons, stem cell potency and cancer metabolism.We acknowledge funding from the European Commission (Brussels) Role ofMitochondria in Conserved Mechanisms of Aging (MIMAGE) Project (Contract 512020, to M.B.), the Cancer Research Programme Grant (C197/A3514 to K.M.B.), Cancer Research UK and ERC Grants 322842-METABOp53 (supporting E.C.), the Wellcome Trust (RG 093735/Z/10/Z to M.R.), the ERC (Starting grant 260809 to M.R.), the German Research Foundation DFG (PR 1527/1-1 to A.P.), and the Austrian Science Fund (FWF) S9302-B05 (to M.B.). V.O.-S. is supported by Consejo Nacional de Ciencia y Tecnologia (CONACyT) Mexico postdoctoral fellowship 203450, M.A.K. by the FWF (Austria) by an Erwin Schroedinger postdoctoral fellowship (J 3341). M.R. is a Wellcome-Trust Research career development and Wellcome-Beit prize fellow.This is the final published version. It is also available from Wiley at http://onlinelibrary.wiley.com/doi/10.1111/brv.12140/abstract

A Systems Biology Approach Identifies Molecular Networks Defining Skeletal Muscle Abnormalities in Chronic Obstructive Pulmonary Disease

Chronic Obstructive Pulmonary Disease (COPD) is an inflammatory process of the lung inducing persistent airflow limitation. Extensive systemic effects, such as skeletal muscle dysfunction, often characterize these patients and severely limit life expectancy. Despite considerable research efforts, the molecular basis of muscle degeneration in COPD is still a matter of intense debate. In this study, we have applied a network biology approach to model the relationship between muscle molecular and physiological response to training and systemic inflammatory mediators. Our model shows that failure to co-ordinately activate expression of several tissue remodelling and bioenergetics pathways is a specific landmark of COPD diseased muscles. Our findings also suggest that this phenomenon may be linked to an abnormal expression of a number of histone modifiers, which we discovered correlate with oxygen utilization. These observations raised the interesting possibility that cell hypoxia may be a key factor driving skeletal muscle degeneration in COPD patients

"Acid stress in Escherichia coli K12: transcriptomic analysis using Green Fluorescent Protein reporter constructs and Fluorescent activated cell sorter (FACS)"

Many microorganisms have a remarkable adaptability at pH values significantly or relatively lower compared with the optimal values of growth. Between these microorganisms it is possible to include Escherichia coli, which has developed four systems response to acid stress. The two best-studied systems are characterized by the presence of amino acid-dependant decarboxylase: isozymes GadA and GadB, glutamate dependant, belonging to acid stress response system 2, and the decarboxylase AdiA, employee from arginine, and present in the system response 3. The response to stress is governed by a dense network of genes that cooperate with each other through an activation cascade of the promoters. The results of transcriptomic analysis from microaarays made it possible to determine which are the promoters triggered by lower pH. The following step in our experiments was the selection of some of the promoters who have shown this resistance and subsequent analysis by Fluorescence Activated Cell Sorting, assessing the fluorescence of the Green Fluorescence Protein inserted in reporter constructs. Experiments were done on a library of constructs containing the promoters of E. Coli K-12. The assessment of fluorescence was done in the same conditions that occur in a chemostat, using shake flasks, therefore trying to maintain bacterial growth steady and stable through continuous replenishment of the media culture after the acidification. FACS is an investigation method to measure transcriptional activity at the population level, which cannot be done with other transcriptional readouts. The use of this technique in these experiments is just a way to optimize this scientific approach and to obtain even more results and reproducibility with many promoters of the GFP library, trying to understand which are the genes involved in acid stress response that can belong to important metabolic pathways. Future works will be directed towards developing a dataset with a large number of time points and by applying bioiformatics tools, attempting to formulate hypothesis on the regulatory networks underlying this tress response

The self-inhibitory nature of metabolic networks and its alleviation through compartmentalization

Metabolites can inhibit the enzymes that generate them. To explore the general nature of metabolic self-inhibition, we surveyed enzymological data accrued from a century of experimentation and generated a genome-scale enzyme-inhibition network. Enzyme inhibition is often driven by essential metabolites, affects the majority of biochemical processes, and is executed by a structured network whose topological organization is reflecting chemical similarities that exist between metabolites. Most inhibitory interactions are competitive, emerge in the close neighbourhood of the inhibited enzymes, and result from structural similarities between substrate and inhibitors. Structural constraints also explain one-third of allosteric inhibitors, a finding rationalized by crystallographic analysis of allosterically inhibited L-lactate dehydrogenase. Our findings suggest that the primary cause of metabolic enzyme inhibition is not the evolution of regulatory metabolite–enzyme interactions, but a finite structural diversity prevalent within the metabolome. In eukaryotes, compartmentalization minimizes inevitable enzyme inhibition and alleviates constraints that self-inhibition places on metabolism

A systems biology approach identifies Molecular networks defining skeletal muscle abnormalities in chronic obstructive pulmonary disease.

Chronic Obstructive Pulmonary Disease (COPD) is an inflammatory process of the lung inducing persistent airflow limitation. Extensive systemic effects, such as skeletal muscle dysfunction, often characterize these patients and severely limit life expectancy. Despite considerable research efforts, the molecular basis of muscle degeneration in COPD is still a matter of intense debate. In this study, we have applied a network biology approach to model the relationship between muscle molecular and physiological response to training and systemic inflammatory mediators. Our model shows that failure to co-ordinately activate expression of several tissue remodelling and bioenergetics pathways is a specific landmark of COPD diseased muscles. Our findings also suggest that this phenomenon may be linked to an abnormal expression of a number of histone modifiers, which we discovered correlate with oxygen utilization. These observations raised the interesting possibility that cell hypoxia may be a key factor driving skeletal muscle degeneration in COPD patients