Structural control of metabolic flux

Control Theory and Systems Biology: Potential Applications in Neurodegeneration and Search for Therapeutic Targets

Control theory, a well-established discipline in engineering and mathematics, has found novel applications in systems biology. This interdisciplinary approach leverages the principles of feedback control and regulation to gain insights into the complex dynamics of cellular and molecular networks underlying chronic diseases, including neurodegeneration. By modeling and analyzing these intricate systems, control theory provides a framework to understand the pathophysiology and identify potential therapeutic targets. Therefore, this review examines the most widely used control methods in conjunction with genomic-scale metabolic models in the steady state of the multi-omics type. According to our research, this approach involves integrating experimental data, mathematical modeling, and computational analyses to simulate and control complex biological systems. In this review, we find that the most significant application of this methodology is associated with cancer, leaving a lack of knowledge in neurodegenerative models. However, this methodology, mainly associated with the Minimal Dominant Set (MDS), has provided a starting point for identifying therapeutic targets for drug development and personalized treatment strategies, paving the way for more effective therapies.

In silico study of peculiarities of metabolism of erythrocytes with glucosephosphate isomerase deficiency

Glucose phosphate isomerase (GPI) deficiency, the third most common cause of hereditary nonspherocytic hemolytic anemia, is associated with the mutation of the GPI gene. The results of the GPI deficiency are premature aging of erythrocytes, macrocytosis, reticulocytosis, minor splenomegaly, hyperbilirubinemia and hyperferritinemia, and hemolytic crisis under the influence of exogenous oxidants such as infections or drugs. Regarding the the lack of GPI correction drugs, the theoretical substantiation of supportive therapy based on system biology approaches that would allow the analysis of the relationships between numerical metabolic processes in a cell would be beneficial. The stoichiometric model of erythrocytes’ steady state metabolism, including the pathways of Embden-Meyerhof and pentose phosphate (PPP), purine metabolism cycles and glutathione synthesis, has been developed. To predict the redistribution of metabolic flows in erythrocytes under conditions of GPI deficiency, we used the flux balance analysis (FBA). In this approach, calculations of the elementary flux modes (EFMs) and the control-effective flux (CEF) have been performed. Using the CEF evaluation approach, effective profiles of enzymatic reactions depending on the degree of enzyme deficiency were obtained. It has been shown that these relationships can be the basis for future experimental studies. Analysis of the profiles of enzymatic reactions of metabolic networks suggests that erythrocytes are capable of metabolizing other substrates that contribute to overcoming the effects of energy stress in the case of enzymopathies. So, it is shown that erythrocytes can effectively use SAM and adenosine as alternative energy sources. It has been established that the GPI enzymopathy results in a decrease in the flow through the glycolysis and pentose phosphate pathway, resulting in a decrease in the content of such reducing agents as NADPH and GSH, ATP. The processes of the GSH synthesis from amino acids in the cell are shown to be suppressed. Decreased content of NADPH and GSH cause the premature aging of erythrocytes. The target therapeutic approaches that influence the behaviour of the metabolic network of erythrocytes are discussed.

Extreme pathway analysis reveals the organizing rules of metabolic regulation

Cellular systems shift metabolic states by adjusting gene expression and enzyme activities to adapt to physiological and environmental changes. Biochemical and genetic studies are identifying how metabolic regulation affects the selection of metabolic phenotypes. However, how metabolism influences its regulatory architecture still remains unexplored. We present a new method of extreme pathway analysis (the minimal set of conically independent metabolic pathways) to deduce regulatory structures from pure pathway information. Applying our method to metabolic networks of human red blood cells and Escherichia coli, we shed light on how metabolic regulation are organized by showing which reactions within metabolic networks are more prone to transcriptional or allosteric regulation. Applied to a human genome-scale metabolic system, our method detects disease-associated reactions. Thus, our study deepens the understanding of the organizing principle of cellular metabolic regulation and may contribute to metabolic engineering, synthetic biology, and disease treatment.

An application of the Shapley value to the analysis of co-expression networks

We study the problem of identifying relevant genes in a co-expression network using a (cooperative) game theoretic approach. The Shapley value of a cooperative game is used to asses the relevance of each gene in interaction with the others, and to stress the role of nodes in the periphery of a co-expression network for the regulation of complex biological pathways of interest. An application of the method to the analysis of gene expression data from microarrays is presented, as well as a comparison with classical centrality indices. Finally, making further assumptions about the a priori importance of genes, we combine the game theoretic model with other techniques from cluster analysis.

Experimental strategies to assess the biological ramifications of multiple drivers of global ocean change-A review

Marine life is controlled by multiple physical and chemical drivers and by diverse ecological processes. Many of these oceanic properties are being altered by climate change and other anthropogenic pressures. Hence, identifying the influences of multifaceted ocean change, from local to global scales, is a complex task. To guide policy-making and make projections of the future of the marine biosphere, it is essential to understand biological responses at physiological, evolutionary and ecological levels. Here, we contrast and compare different approaches to multiple driver experiments that aim to elucidate biological responses to a complex matrix of ocean global change. We present the benefits and the challenges of each approach with a focus on marine research, and guidelines to navigate through these different categories to help identify strategies that might best address research questions in fundamental physiology, experimental evolutionary biology and community ecology. Our review reveals that the field of multiple driver research is being pulled in complementary directions: the need for reductionist approaches to obtain process-oriented, mechanistic understanding and a requirement to quantify responses to projected future scenarios of ocean change. We conclude the review with recommendations on how best to align different experimental approaches to contribute fundamental information needed for science-based policy formulation.

How the chemical features of molecules may have addressed the settlement of metabolic steps

INTRODUCTION

While the evolutionary adaptation of enzymes to their own substrates is a well assessed and rationalized field, how molecules have been originally selected in order to initiate and assemble convenient metabolic pathways is a fascinating, but still debated argument.

OBJECTIVES

Aim of the present study is to give a rationale for the preferential selection of specific molecules to generate metabolic pathways.

METHODS

The comparison of structural features of molecules, through an inductive methodological approach, offer a reading key to cautiously propose a determining factor for their metabolic recruitment.

RESULTS

Starting with some commonplaces occurring in the structural representation of relevant carbohydrates, such as glucose, fructose and ribose, arguments are presented in associating stable structural determinants of these molecules and their peculiar occurrence in metabolic pathways.

CONCLUSIONS

Among other possible factors, the reliability of the structural asset of a molecule may be relevant or its selection among structurally and, a priori, functionally similar molecules.

Functional centrality as a predictor of shifts in metabolic flux states

Background

The flux phenotype describes the entirety of biochemical conversions in a cell, which renders it a key characteristic of metabolic function. To quantify the functional relevance of individual biochemical reactions, functional centrality has been introduced based on cooperative game theory and structural modeling. It was shown to be capable to determine metabolic control properties utilizing only structural information. Here, we demonstrate the capability of functional centrality to predict changes in the flux phenotype.

Results

We use functional centrality to successfully predict changes of metabolic flux triggered by switches in the environment. The predictions via functional centrality improve upon predictions using control-effective fluxes, another measure aiming at capturing metabolic control using structural information.

Conclusions

The predictions of flux changes via functional centrality corroborate the capability of the measure to gain a mechanistic understanding of metabolic control from the structure of metabolic networks.

Predictive sulfur metabolism - a field in flux

The key role of sulfur metabolites in response to biotic and abiotic stress in plants, as well as their importance in diet and health has led to a significant interest and effort in trying to understand and manipulate the production of relevant compounds. Metabolic engineering utilizes a set of theoretical tools to help rationally design modifications that enhance the production of a desired metabolite. Such approaches have proven their value in bacterial systems, however, the paucity of success stories to date in plants, suggests that challenges remain. Here, we review the most commonly used methods for understanding metabolic flux, focusing on the sulfur assimilatory pathway. We highlight known issues with both experimental and theoretical approaches, as well as presenting recent methods for integrating different modeling strategies, and progress toward an understanding of flux at the whole plant level.