Metabolism Basics
Metabolism refers to the set of chemical reactions, catalyzed by enzymes in a cell, that is required for its survival; namely, to generate energy and to build up cellular components. The breakdown of materials to produce energy is called catabolism, whereas the building of components is called anabolism. Both catabolic and anabolic processes are carried out in a series of pathways catalyzed by enzymes. The energy released from catabolic reactions is often consumed in anabolic reactions through the use of universal high-energy currencies (ATP, and to a lesser extent, NAD, PEP, and acetyl-CoA).
Amongst the domains of life, organisms metabolism can be categorized into four strategies:
- photoautotrophs
- photoheterotrophs
- chemoautotrophs
- chemoheterotrophs
Cellular respiration is the core metabolic process that occurs in all organisms (except viruses…) where ATP is generated with the use of three things: 1. an energy source; 2. a carbon source; 3. an electron donor.
Autotrophs use CO2 as their carbon source, while heterotrophic organisms use organic molecules (usually from other organisms). Photoautotrophs use light energy from the sun as their energy source (plants, algae, and some bacteria), while chemoautotrophs gain their energy from the oxidation of certain inorganic compounds (for example, hydrogen-, sulfur-, and iron-reducing bacteria). Because chemoautotrophic metabolisms release relatively small amounts of energy compared to photoautotrophs, they must oxidize large amounts of substance for growth and survival. Hence a lot of these microbes are important environmentally for biogeochemical cycling.
Photoheterotrophic metabolisms are very rare, limited to a few extremophiles. But chemoheterotrophs include most bacteria, fungi, yeast, and animals. It is therefore the metabolism type most extensively studied in the rapidly expanding metabolomics field.
In aerobic prokaryotes and eukaryotes, the basic steps of cellular respiration are the same: glycolysis (converting glucose into two pyruvate molecules), pyruvate oxidation (converting pyruvate to acetyl CoA and carbon dioxide), the TCA cycle (generating NADH and FADH2 electron carriers from acetyl CoA cycling), and oxidative phosphorylation (using electrons from NADH and FADH2 to generate a proton gradient to synthesize ATP). Oxygen is directly required by oxidative phosphorylation as the final electron acceptor, where it splits and gains protons to form H20. Hence, aerobic respiration requires O2 and glucose and produces H2O and CO2 as waste. In us, the TCA cycle takes place in the mitochondrial matrix, and the electron transport chain is in the inner mitochondrial membrane. As mitochondria are an evolutionary prokaryotic relic, in prokaryotes these steps occur in the cytosol and plasma membrane respectively.
Though the TCA cycle and pyruvate oxidation steps don’t directly require oxygen, they cannot function without it. Therefore, the concentration of O2 greatly determines the biomass yield of aerobic heterotrophic organisms. However, glycolysis can take place without oxygen (it actually evolved in anaerobic conditions), in the process of fermentation. This involves glycolysis with one or two additional steps bolted onto the end in order to regenerate the NAD+ electron carrier required in glycolysis. Therefore, during fermentation microbes use the products of metabolism as final electron acceptors instead of O2. Fermentation (2 ATP net gain per glucose) produces a lot less ATP than the aerobic pathways (32 ATP net gain per glucose) and produces much more waste than aerobic respiration. As well as the better known lactic acid and alcoholic fermentation, there is a variety of additional fermentation pathway bolt-ons that are used by specific bacteria to break down glucose; the characteristic end products of these pathways can help assist in the identification of the bacteria. Anaerobes are microbes that can grow in the absence of oxygen through fermentation. E. coli and S. cerevisiae yeast are both facultative anaerobes so can switch between fermentation and aerobic respiration processes dependent on environmental conditions. In fact, E. coli can undergo multiple fermentation pathways to produce products including lactic acid, hydrogen gas, acetic acid, formic acid, succinic acid, carbon dioxide, and ethyl alcohol.
Metabolic Flux
Metabolic flux is the movement of matter through an organism’s metabolic network; say a carbon atom’s movement from starch-form through catabolic and anabolic reactions within metabolites, to an end product of metabolism, be that CO2 waste or newly built organic compound. Microorganisms metabolisms are very diverse, and therefore are ideal catalysts for a whole range of standard and new chemical reactions, often to generate a metabolite of interest. The engineering of microbes for the purpose of producing a particular product can be done by introducing a heterologous pathway from a different organism, by enhancing a native pathway, or both. The principle aim of metabolic engineering is to modify the metabolic flux of a wild-type organism to create whole microbial cell factories. To achieve this, it is important to choose a metabolically feasible microorganism with which to begin.
Measuring Metabolism
To undergo metabolic engineering, analytics are necessary to interpret the fluxes within a microbe. Metabolism flux can be predicted theoretically with mathematical modeling using flux and stoichiometric parameters, though practical measurements are also necessary to confirm the initial predictions. This includes working out how much substrate will be turned into the desired product, versus how much will be used to generate byproducts like biomass and waste. This is a very new field in which we know little, and at the moment there are a few ways to go about this. Targeted analysis involves measuring only the analyte of interest, which allows greater sensitivity. On the other hand, (moderately) untargeted analyses allow the monitoring of as many analytes of a particular class as possible (for example, the whole proteome), increasing the chances of uncovering unexpected changes in flux from different candidate analytes. However, truly untargeted analyses of a whole organism’s set of metabolic reactions are not yet possible, as they require access to all possible analytes a cellular chassis may produce.
One cell’s metabolic flux is incredibly complex and approaches to reconstructing flux maps of different microbes are still being innovated. Measuring fluxes within heterotrophic organisms can be done with isotopic 13-C labeling of glucose, and following the movement of the isotopic label into the metabolism reactions. For this to work, the label must not totally saturate it — it needs to be in high enough concentrations to be incorporated, but low enough that not all glucose molecules being metabolized are labeled, else you cannot follow which one is which! By measuring the incorporation of the label into different biological molecules, one can study the fundamental connections and metabolomics of a microbe of interest.
This technique is more difficult with autotrophic organisms because it’s harder to dilute the carbon label down — you can label just 1 out of 6 of glucoses’ carbons, but you must label 1 out of 1 of CO2’s carbons. This creates a saturation of 13-C in the central carbon system which is insensitive to fluxes. A group has undergone interesting work to attempt to overcome this issue — instead of examining positional labeling of amino acids, Young et al. 2011 follow the label’s temporal distribution into the central carbon metabolism before and after a step change from unlabelled to labeled CO2 feeding to autotrophic cyanobacteria. This involves the very rapid sampling of the culture and extraction of the metabolites from the cells before the metabolites become saturated with 13C (see figure below). It was the first demonstration of a metabolic flux analysis on the autotroph cyanobacteria. Hopefully, innovations such as these for measuring autotrophic metabolic fluxes will lead to a higher selection of autotrophs as biotechnological chasses in the future.
Though flux analysis may read like a boring and incredibly niche topic, these kinds of studies allow understanding of cellular metabolism, in order to identify strategies to improve things like photosynthetic efficiency or to re-route the main carbo fluxes to high-value products. In particular, mapping intracellular carbon fluxes in a quantitative manner is necessary to determine where the pathway bottlenecks (representing metabolite build-ups or shortages) are in the cellular system of interest. Omics technologies, including whole-cell proteomics, metabolomics, and fluxomics, are key for the development of successful metabolic engineering.
Controlling Metabolic Flux
The metabolic flux of a microbe has evolved to be maintained at an equilibrium, which can change dynamically in response to biotic and abiotic triggers. Metabolic flux is determined by metabolite concentration, product concentration, and the number of active enzymes acting in the flux pathway (which itself is determined by the enzymes’ gene transcription regulation and post-translational modifications for their activation). Both the substrates and products of a reaction can provide allosteric effects for the enzyme, as well as influence the thermodynamics of the reaction (see figure below). These regulatory mechanisms are necessary to tightly control pathway balance inside a microbe, to prevent overaccumulation of a particular intermediate in the broader network of flux pathways. All of these mechanisms must be taken into account when attempting to change a certain reaction’s output in a microbial metabolism network.
Metabolic Rigidity
Another concept emerging in flux analysis models is the rigidity of a microbial core metabolism as being important in engineering. If a metabolism is soft and flexible, it means that if at a certain point in time the system needs more precursor to maintain a homeostatic state at one reaction, more precursor will be provided by the core metabolism. In contrast, if the core metabolism is rigid and unresponsive, no more precursor will be provided to a particular flux at that time. A rigid core metabolism is unideal for metabolic engineering. This concept is seen in Savakis et al 2013 work, where they analyzed a heterologous pathway of lactic acid production in cyanobacterial strains under different CO2 supplies. In certain strains, the cells started fixing lots more CO2 due to the new metabolic pathway — in the top producing strain over 50% of the carbon fixed was going into the desired product lactic acid. This shows the potential of flexible core metabolisms in generating economically appropriate levels of desirable product. Even within one metabolic network, some pathways may be more rigid than others, which will need to be taken into account when engineering whole-cell factories for high-value products.
Cofactor Balance
Ultimately, it is crucial to balance the supply and demand of key cofactors ATP and electron carriers (NADH) within microbial metabolism. This translates to a balance between anabolic synthesis (which uses ATP and NADH for product, biomass, and waste excretion), and catabolic breakdown (generating ATP and NADH from cellular respiration). Say you want a microbe to produce a particular product from a substrate (see figure below). An excess of ATP in the microbe will promote biomass formation to regenerate more NADH and NAD (from glycolysis and the TCA cycle), which results in a loss of the substrate to byproducts. A lack of ATP drives the redirection of some substrate flux to make more ATP, so this also results in substrate loss. On the other hand, excess electron carriers (NADH, etc.) results in the generation of waste products such as ethanol, and other acids, as your substrate must be used as an electron acceptor in fermentation. Finally, an insufficient supply of electron carriers drives an increase in substrate oxidation (glycolysis), resulting in a loss of substrate carbon as CO2. This co-factor balance can be used to influence the biotechnological performance of metabolically engineered bacteria.
Shen et al. 2011 demonstrated the impact of cofactor balance by creating coupled microbial strains, where microbial growth was directly coupled to an introduced pathway, by first engineering a strain with an imbalance of NADH, then introducing a heterologous pathway to recover the cofactor imbalance. This artificial intervention in the cofactor balance invokes evolutionary pressures on the pathway, to drive improved flux, and the selection of essential enzymes with better catalytic efficiency within the pathway. In this way, cofactor balance can be utilized to drive the efficient production of non-native products. In Shen et al.’s case, the heterologous pathway, which drove E. coli production of butanol, increased in productivity tenfold with the coupling. There is real potential in applying this knowledge to generate more carbon-neutral second-generation biofuels with higher efficiency, as well as for generating high-value products.
Conclusions of Metabolic Flux Control
Microbial metabolisms have evolved to achieve homeostasis, in order to be better prepared for perturbations in their environment in terms of energy sources, food sources, etc. Therefore, increasing enzyme concentration for the catalysis of a substrate to a product only works to enhance product output to a certain extent — the threshold balance must be investigated to prevent problematic metabolite build-ups or insufficiencies in other parts of the pathway. Manipulation of the dynamism imparted to metabolisms from evolutionary pressure has been demonstrated in recent research to enable generating a pull to the product metabolite of interest. However, some core pathways are rigid and prevent this possibility. A key role of the metabolism is to replenish ATP and NADH cofactors, and so modulating their concentrations to find the optimal balance can drive optimization in product/byproduct ratios. Interestingly, some papers have shown it is possible to exploit cofactor balance by inducing an imbalance to couple a pathway of interest into growth when rescuing the balance.
References
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