Metabolic Pathway Engineering

Analysis and Applications in the Life Sciences

Jean F. Challacombe

• Publisher: Jenny Stanford Publishing
• Year: 2021
• Print ISBN: 9789814877398
• eBook ISBN: 9781000260540
• Topic: Medicine
• Subtopic: Biochemistry in Medicine

Metabolic systems engineering combines the tools and approaches of systems biology, synthetic biology, and evolutionary engineering. This book reviews studies on metabolism, from the earliest work of Lavoisier and Buchner to current cutting-edge research in metabolic systems engineering.

This technology has been used in bioengineering applications to create high-performing microbes and plants that produce important chemicals, pharmaceuticals, crops, and other natural products. Current applications include optimizing metabolic pathways to enhance degradation of biomass for biofuel production and accelerated processing of environmental waste products and contaminants. The book includes examples to illustrate the applications of this technology in the optimization of metabolic pathways to create robust industrial strains as well as in the engineering of biological processes involving health and diseases of humans, animals, and plants.

Written by a seasoned computational biologist with many years of experience in genomics, bioinformatics, and systems biology, this book will appeal to anyone interested in metabolic systems analysis and metabolic pathway engineering.

Chapter 1
Understanding the Biology of Organisms Through Studies of Metabolism

1.1 Introduction

Metabolism refers to the biochemical processes that occur in all living organisms in order to maintain life. An organism’s metabolism consists of interconnected metabolic pathways, where each pathway is essentially a series of linked chemical reactions occurring in individual cells [1]. Each reaction in a metabolic pathway transforms the molecular or ionic structure of one or more compound(s) to form other substance(s). Metabolic reactions can be catabolic, mediating food digestion by converting macronutrients (proteins, lipids, carbohydrates, nucleic acids) into smaller nutrient molecules that can be used for energy and to drive cellular processes; in contrast, anabolic reactions start with small molecules and synthesize larger molecules that can be used as building blocks for cellular components [2]. These transformations are usually mediated by enzymes, which were discovered by Eduard Buchner in 1897 [3]; enzymes can speed up a chemical reaction by lowering the activation energy needed for the reaction to start [1]. Some reactions that have low activation energies can proceed spontaneously, without the involvement of enzymes. Another important component of metabolism is the transport of compounds across cell membranes and between different subcellular compartments such as the nucleus, mitochondria and chloroplasts [1].

1.2 Studies of Metabolism

1.2.1 Early Experiments

As depicted in Figure 1.1, key work by Lavoisier in the 1780s set the stage for subsequent studies of human and animal metabolism. Lavoisier showed that combustion and respiration are the same process, and that the amount of oxygen consumed during respiration changes depending on how active a person is [4]. As metabolism is the source of nutrients that sustain all life forms, it is not surprising that many of the early studies of human metabolism were conducted and reported in the context of nutrition and the production of waste products. A seminal book on the topic of human nutrition and metabolism, The Elements of the Science of Nutrition, was first published by Graham Lusk in 1906 [5], and recently reproduced as a classic reprint in 2017 (https://www.amazon.com/Elements-Science-Nutrition-Classic-Reprint/dp/1330729986). The 1928 edition of Lusk’s book was reviewed by Lafayette B. Mendel, who states in the first paragraph of his review, “When the first edition appeared in 1906, many of the fundamentals of the metabolism of matter in the body had already become well established, and the energy aspects of nutrition were being more accurately formulated” [6]. Another pioneer of research on metabolism was Friedrich Woehler, who performed studies on himself and his dog that focused on the passage of waste products into urine. In 1928, Woehler synthesized urea and speculated on the pathway for conversion of benzoic acid to hippuric acid, but the structure of hippuric acid was not known at the time (https://www.issx.org/page/Woehler#). By one account, following the characterization of hippuric acid in 1929 by Liebig, Alexander Ure observed in 1941 that benzoic acid can be converted to hippuric acid in the human body, and that hippuric acid was excreted in the urine (https://www.issx.org/page/Woehler#). Because of this discovery, Ure mistakenly thought that the administration of benzoic acid could be a treatment for gout, as the symptoms of gout are due to abnormal accumulation of uric acid in the body [7]. Other early works on metabolism and nutrition included studies of nitrogen balance, which is related to protein metabolism and the production of urea and other nitrogenous waste products [8–10].

Figure 1.1 Timeline of technology progression and seminal studies of metabolism.

During the same time frame as the above work, isotopic labeling experiments were used to decipher the flow of carbon, hydrogen, and oxygen through metabolic pathways in living cells. This approach was pioneered by Calvin and his colleagues, who developed metabolite labeling techniques during their pivotal studies of carbon flow during photosynthesis [11–13]. Their labeling technology was adapted to the study of other organisms [14] to trace pathway metabolites and measure metabolite content and enzyme activity in vitro. Other early experimental approaches in metabolomics used gas chromatography and chemical extractions to quantify metabolites and perform metabolic pathway analysis. One example application of this technology resulted in the construction of a hypothetical pathway for citrate accumulation in the yeast Candida lipolytica [15].

1.2.2 Quantitative Metabolic Network Modeling

The first examples of studies involving quantitative metabolic network analyses featured mathematical [16–19] and enzyme kinetic [20, 21] models, as well as discourses and hypotheses on the compartmentalization of metabolic reactions in different parts of cells [22]. The concept of mass balance was used to implement and solve models for the metabolic pathways of citrate production by C. lipolytica starting from glucose. While several possible models were tested, the most plausible model with respect to carbon flux focused on pyruvate carboxylation and the tricarboxylic acid cycle but omitted the glyoxylate cycle. This study was able to report reasonable rates of glucose consumption and citrate and isocitrate production as well as carbon dioxide evolution and cellular protein and carbohydrate synthesis [23].

The detailed requirements for quantitative analysis of metabolic networks were reviewed by Blum and Stein in 1982 [24]. The first steps in this process were critical for success and involved identifying the metabolic pathways of interest, then determining the enzymes involved, their subcellular locations, substrates, and expected products. This information was used to draw a conceptual metabolic scheme for the cell type of interest. However, given the incomplete knowledge of general cellular metabolism at that time, metabolic schemes generated in this way were very approximate. To generate an accurate metabolic model describing fluxes through the pathways of interest required the construction of equations to calculate the specific activity of every carbon atom of every intermediate in every pathway comprising the network [24]. To track metabolic intermediates, investigators measured the amount of a label incorporated into particular molecules or atoms. This approach required more measurements than independent flux parameters in the equations, and also the measurements had to be distributed over all of the pathways of interest [24]. For example, in a study of Tetrahymena pyriformis metabolism, the organisms were grown in defined media containing substrates of interest (glucose, fructose, ribose, glycerol, acetate, pyruvate, bicarbonate, glutamate, and hexanoate), with only one substrate labeled with ¹⁴C in any given flask [25]. Equations and algorithms were devised and used to compute the amount of label expected to be incorporated into any of the products that were measured for any set of steady state flux values in the metabolic network [25]. The fit of the model to actual data was assessed and the model tweaked if necessary until it provided a good fit to the data. Detailed models like this were used to assess metabolite fluxes through pathways and determine utilization rates for substrates that were present in the culture media. In the 1979 study of early stationary phase T. pyriformis cells, a model with three pools of acetyl-CoA was required to fit data on the incorporation of the carbon atoms from acetate, bicarbonate, glutamate, hexanoate, and pyruvate into a variety of metabolic products [25].

1.2.3 Metabolic Pathway Analysis

Metabolic control analysis (MCA), reviewed in Refs. [26–28], was developed and applied to quantitatively determine the degree of control that a given enzyme exerted on flux through a particular metabolic pathway. This approach was also used to determine the concentrations of metabolites that could explain experimental data on enzyme overexpression and downregulation. Results of MCA were used to inform the design of subsequent experiments involving further manipulation of metabolic pathways [28].

To perform MCA, the control structure of a pathway had to be evaluated first. The pathway control structure comprises a flux control coefficient (the degree of control that an enzyme’s rate of activity exerts on a pathway’s flux), a...

Table of contents

• Cover
• Half Title
• Title Page
• Copyright Page
• Contents
• Preface
• 1. Understanding the Biology of Organisms Through Studies of Metabolism
• 2. Computational Tools and Approaches for Metabolic Network Reconstruction and Modeling
• 3. Understanding Microbial Communities
• 4. In silico Identification of Drug and Vaccine Targets Against Human, Animal, and Plant Pathogens
• 5. Metabolic Engineering
• 6. Microbiome Engineering
• 7. The Future of Systems Metabolic Engineering
• Index