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COMMENTARY: The Need for Metabolic Mapping in Living Cells and Tissues

Posted on: Thursday, 1 July 2004, 06:00 CDT

KEYWORDS Metabolic mapping; Enzyme histochemistry; Live cells; Image analysis; Biocomplexity

Summary

The ultimate activity of an enzyme depends on many regulatory steps from transcription of the gene up to complex formation of the enzyme. Therefore, gene expression (mRNA levels) or protein expression (protein levels) are not reliable parameters to predict the functional activity of an enzyme. Activity measurements in cell homogenates or in frozen or fixed (and thus dead) cell preparations are not appropriate either because post-translational regulation mechanisms that exist in living cells may be lost by homogenization or freezing or chemical fixation of cells. Therefore, metabolic mapping in living cells or, in other words, visualization and quantification using microscopy and image analysis of enzyme reactions in living cells is the approach of choice to understand the functional role of enzymes in vivo as is demonstrated here with a number of examples in recent literature.

2004 Elsevier GmbH. All rights reserved.

Introduction

Complex scientific questions concerning functioning of biological systems are usually approached as a series of subquestions that are easier to define and to investigate. When these subquestions have been solved, they provide insights, which illuminate the complexity of the entire organism. This approach has been successful so far and has led to the identification of the function of many proteins and other macromolecules. However, this approach does not allow elucidation of the complex interactions that occur in living cells and tissues and what the meaning of these interactions is for the functioning of the entire organism. The genome of man and other organisms has been sequenced, and we know in principle how many and which genes are involved, but this information does not give us a total functional map of all existing proteins. Additionally, alternative splicing of mRNA resulting in protein variations encoded by one gene and directed proteolysis for activation or degradation of proteins increases the multitude of functional proteins. The human genome comprises of approximately 30,000 genes encoding for, as is estimated now, 80,000 different proteins (Ravesloot, 2002). Furthermore, many macromolecules in cells are not encoded for, such as lipids and sugars. These molecules play essential but often unknown roles in cellular processes as well. Finally, the intact biocomplex entity of a cell functions by virtue of a multitude of interacting molecular events (Hehre, 2001; Miklos and Maleszka, 2001; Schwule and Kettling, 2001; Gavin et al., 2002; Gavin and Superti-Furga, 2003). External stimuli or intracellular changes in gene expression, post-transcriptional and post-translational modifications modulate these interactions. On top of that it becomes more and more evident that proteins are multifunctional. These are all aspects that have to be taken into consideration as part of the complex regulation of the activity of proteins in general, and enzymes in particular.

Multifunctional or moonlighting proteins

Multifunctionality of proteins may be caused by the fusion of genes, thereby limiting the number of genes, but maintaining the different functions (Davidson et al., 1993). Multifunctionality of proteins may be a common phenomenon. Molecular integration of metabolic and structural functions has many implications for cellular physiology such as cytoplasmic organization and cell motility and for the integration of structure and metabolism at the cellular level. Multifunctionality of proteins is called moonlighting (Jeffery, 1999), and adds another dimension to cellular complexity, from which cells can benefit in various ways. Therefore, elucidation of the functional roles of moonlighting proteins and their regulation is becoming a pertinent issue in cell biology as part of the functional proteomics approach (Perham, 2000; Miklos and Maleszka, 2001; Amsterdam, 2003). The function of a moonlighting protein (Jeffery, 1999; Ejiri, 2002) can vary as a consequence of changes in cellular localization of a protein, cell type in which the protein is expressed, the oligomeric or polymeric state of a protein, and intracellular concentrations of ligand, substrate, cofactor or product of the protein. Moonlighting proteins can switch between functions in a number of ways as is demonstrated here with a few examples.

Example 1

The Escherichia coli PutA protein has both proline dehydrogenase activity and pyrroline-5-carboxylate dehydrogenase activity when it is associated with the plasma membrane, but lacks enzymatic activity when it binds to DNA as a transcriptional repressor (Ostrovsky de Spicer and Maloy, 1993; Muro-Pastor et al., 1997). Its localization switches on the basis of the amount of available substrate, ligand or cofactor. The PutA protein binds to the plasma membrane when substrate concentrations are high, but binds to DNA when substrate concentrations are low.

Example 2

A protein can perform different functions when it is expressed in different cell types. Neuropilin is a receptor on endothelial cells for vascular endothelial growth factor (Soker et al., 1998). In axons, it serves as a receptor for another ligand, semaphorin III, which guides axons to find their destination during outgrowth.

Example 3

Proteins can have different functions when they are present intracellularly or extracellularly. For instance, phosphoglucose isomerase is a ubiquitous cytosolic enzyme and catalyzes the second step of glycolysis. However, it is also secreted by cells and then it has at least four additional functions. Phosphoglucose isomerase can act as neuroleukin, which is both a cytokine that causes B cells to mature into antibody-secreting cells and a nerve growth factor that promotes survival of embryonic spinal neurons and sensory nerves (Gurney et al., 1986; Li and Chirgwin, 2000; Amraei and Nabi, 2002; Amraei et al., 2003). In addition, phosphoglucose isomerase/ neuroleukin is also known as an autocrine motility factor, which is a cytokine that stimulates cell migration. Finally, the enzyme is a differentiation and maturation mediator that induces differentiation of human myeloid leukemia cells.

Example 4

Some proteins have different functions when they are present as monomer or as multimer (Rettig et al., 1993, 1994; Scanlan et al., 1994; Mazzola and Sirover, 2003). For example, the monomer 37-kDa subunit of human glyceraldehyde-3-phosphate dehydrogenase acts as uracil-DNA glycolase in the nucleus (Meyer-Siegler et al., 1991), whereas the tetramer converts glyceraldehyde-3-phosphate into 1,3- diphosphoglycerate.

Protein complexes

Complex interactions between enzymes and other macromolecules play important roles in regulating metabolic activity in vivo. Enzymes which were generally considered to be soluble and freely diffusable may be organized in multienzyme complexes or so-called molecular machines (Perham, 2000; Gavin and Superti-Furga, 2003). It has become clear that well-defined intracellular compartments, such as cytosol and mitochondrial matrix, cannot simply be regarded as bags containing homogeneous solutions of enzymes, but are rather well organized. Furthermore, the role of water in metabolic processes is an interesting but largely ignored aspect in cell biology. Usually, enzyme reactions are measured in dilute solutions of cell or tissue extracts, whereas enzymes in vivo function in high (protein) concentrations in cells (Srere, 1967, 1980; Fulton, 1982; Srivastava and Bernhard, 1987; Aragon and Sols, 1991). Cells contain 20-40% proteins by weight. In this rich solution, interactions between enzymes and their cellular microenvironment are completely different from those in dilute solutions (Masters, 1981; Fulton, 1982). Homologous (Hulme and Tipton, 1971; Minton and Wilf, 1981) and heterologous (Wiame, 1971; Srivastava and Bernhard, 1987; Gavin and Superti-Furga, 2003) molecular interactions have been described to occur in vivo. Homologous interactions are considered to be changes in enzymes from a monomer form to a polymer form. Heterologous interactions are associations between enzymes and other proteins such as structural elements of the cell, e.g. membrane- associated structures or cytoskeletal components (Pette and Brandau, 1962; Arnold and Pette, 1968; Sigel and Pette, 1969; Swezey and Epel, 1986; Rogalski et al., 1989; Minaschek et al., 1992). These interactions may affect the catalytic activity considerably.

Example 5

Studies by Wang et al. (1997) and Kusakabe et al. (1997) have shown that specific molecular interactions between aldolase, a glycolytic enzyme, and actin is responsible for the functioning of aldolase. Most of the aldolase is preferentially localized on stress fibers and in close vicinity of active ruffles of cells (Kusakabe et al., 1997). This relative subcellular enrichment of aldolase is explained by its interactions with actin that can be modulated by physiological effectors such as insulin, calcium and anoxia. In the turtle brain, increased aldolase binding has been observed during anoxia-induced metabolic arrest (Duncan and Storey, 1992). The physiological relevance of binding of aldolase to the cytoskeleton is still not clear, but it has been postulated that aldolase has a dual role as enzyme and as structural part of the cytoskeleton. Binding of a\ldolase to the F-actin core of microfilaments inhibits competitively the enzymatic conversion of the substrate of aldolase, fructose-1, 6-biphosphate.

Example 6

Post-translational regulation of metabolism by macromolecular interactions is distinctly involved in the activity of glucose-6- phosphate dehydrogenase (G6PDH). Swezey and Epel (1986) described the enzyme G6PDH in sea urchin eggs and found that in the unfertilized sea urchin eggs, 60% of G6PDH is bound to structural elements and then has a relatively low V^sub max^ and high K^sub m^ whereas, within a few seconds after fertilization, G6PDH is largely released from its bound state and acquires a distinctly higher V^sub max^ and lower K^sub m^. G6PDH is then able to produce large quantities of NADPH at the same physiological substrate and coenzyme concentrations that also existed before fertilization. NADPH is needed for hardening of the membrane (synthesis of the fertilization membrane) to prevent polyspermy and thus a lethal embryo, underlining the importance of rapid post-translational metabolic regulation in living cells (Shapiro, 1991; Rees et al., 1996). See example 10 for visualization of the immediate increase in NADPH production upon fertilization of sea urchin eggs.

Enzymes may switch partners and are then involved in different functions when their aggregation state or intracellular and/or extracellular localization is changed (Jeffery, 1999; Ejiri, 2002).

Metabolic channeling

Enzyme complexes enable the product of the first enzyme to be utilized by a second enzyme of a metabolic pathway. Channeling of metabolic intermediates within these complexes has been postulated to lead to increased efficiency of substrate fluxes by coupling of reactions in a metabolic pathway. Channeling can also lead to sequestration of intermediates, so that flux into other pathways that compete for the same substrates and/or intermediate products is restricted (Ovadi and Srere, 2000). We like to introduce the term preferential pathway for this type of substrate channeling because it explains how a substrate that can be used in different pathways is directed in one that is relevant for an organism at a certain point in time.

Example 7

The need of NADPH in various metabolic pathways in livers of flatfish explains why female flatfish and not male flatfish develop liver cancer when living in a chemically-polluted environment (Koehler and Van Noorden, 2003). NADPH is a major metabolite in livers used in detoxification processes and biosynthetic processes such as the production of vitellogenin needed for oocytes. In females, NADPH is channeled in the preferential pathway of biosynthesis when oocytes are generated and is thus not available for detoxification at that time. As a consequence, females are exposed to toxicants in periods of vitellogenin synthesis and may develop liver cancer. It is an example of evolutionary laws that the offspring and not the individual is important for a species to survive.

Metabolic mapping of living cells

Pathological alterations in enzymatic activity may have many causes. An enzyme can be either absent, inactive, overexpressed or located in a wrong cellular subcompartment. When the activity is normal but its location is wrong, deviations are hard to detect when using a biochemical approach for the detection of enzyme activity. On the other hand, when localizing an enzyme protein by immunohistochemistry, it does not give any information on whether the enzyme is active or not. Moreover, activity of enzymes is often regulated by the microenvironment of the enzyme. Therefore, detection of both enzyme protein and its activity in living cells provides a better understanding of cellular functioning (Van Noorden and Jonges, 1995; Stoward et al., 1998; Amsterdam, 2003). For this purpose, novel tools are being developed to detect the activity of enzymes in living cells (Haugland, 1995; Sameni et al., 2000; Boonacker and Van Noorden, 2001, 2003; Hahn and Toutchkine, 2002; Patton and Beechem, 2002; Boonacker et al., 2003b; Lee et al., 2003), because most existing techniques to demonstrate activity of enzymes are not compatible with fragile living cells. They are based on the use of compounds or methods that are toxic or damaging, and are thus not appropriate to study enzymatic activity and its regulation in living cells. Furthermore, membranes may be a limiting factor when detecting activity of intracellular enzymes in living cells. Traditionally, cells are permeabilized to enable compounds of the incubation medium to reach the site of the enzyme but this is not allowed when using living cells. Micro-injection of (caged) substrates (Rees et al., 1996), bead loading, scrape loading, scratch loading and pinocytotic cell loading are techniques to overcome the problem (Okada and Rechsteiner, 1982; McNeil, 1989), but they remain cumbersome techniques for various reasons. Selectivity of substrates to demonstrate activity of enzymes may be a limiting factor as well. Homologue enzymes may convert a substrate that is used for visualization of the activity of a particular enzyme, thus interfering with selectivity (Boonacker et al., 2003a).

Table 1. Receptor function as demonstrated immunohistochemically with anti-CD26 antibodies and proteolytic activity as demonstrated with Ala Pro-cresyl violet fluorescent substrate of CD26/DPPIV on human Th1 and Th2 cells in relation with aging.

Studies with the use of intact biological systems have taught us thus far that metabolic processes are heavily regulated post- translationally by molecular interactions (Van Noorden and Jonges, 1995; Ovadi and Srere, 2000). Enzymes are liable to rapid variations in kinetic parameters, that are regulated by interactions with other (macro)molecules (Swezey and Epel, 1986; Rees et al., 1996).

Example 8

Kinetic parameters of the protease CD26/dipeptidyl peptidase (DPP)IV have been determined in situ along villi of rat and human jejunum (Gutschmidt and Gossrau, 1981). Differences in V^sub max^ and K^sub m^ were found between basal and apical parts of villi which is related with differentiation of the epithelial cells. These findings suggest that protein degradation by this enzyme differs at the different sites of the villi. CD26/DPPIV shows the lowest V^sub max^ and highest K^sub m^ in the base of villi where epithelial cells start to differentiate. As a consequence, fluxes are much higher in the older cells than in the younger cells.

Example 9

CD26/DPPIV expression and activity are also regulated on T helper (Th) cells. Th1 cells possess more CD26/DPPIV molecules after differentiation than Th2 cells (Table 1). The receptor and co- stimulatory (CD26) functions of the moonlighting protein CD26/DPPIV are directly related with the number of CD26/DPPIV molecules on Th cells and are thus more pronounced in Th1 cells (Boonacker et al., 2002). Surprisingly, the proteolytic DPPIV function of CD26/DPPIV is not related to the number of molecules present on Th cells because of a similar variation in kinetic parameters as shown in Example 8 (Table 1). DPPIV-dependent proteolysis per CD26/DPPIV molecule (flux/ CD26) is relatively higher on Th2 cells due to this kinetic variability. It may explain how two different functions of one molecule are separately regulated: the receptor/co-stimulatory function transcriptionally and the proteolytic DPPIV function post- translationally. To investigate whether glycosylation and/or sialylation plays a role in this post-translational regulation, we investigated CD26/DPPIV function of Th1 and Th2 cells obtained from post-natal blood, blood of young men and blood of old men because the glycosylation and sialylation grade of CD26/DPPIV increases with the number of immunological challenges a person has had and thus, more or less, with age. Table 1 shows that the proteolytic activity per CD26/DPPIV molecule decreases with age but remains relatively higher on Th2 cells. These data suggest that glycosylation and/or sialylation or other age-dependent parameters of CD26/DPPIV affects proteolytic activity of CD26/DPPIV but that these post- translational modifications do not explain the differences in DPPIVactivity per CD26/DPPIV molecule on Th1 and Th2 cells in each individual.

Figure 1. Advantages of direct visualization of enzyme reactions using quantitative light microscopy.

Conclusions

Spatial crowding of enzymes in living cells has definitive advantages over an at-random distribution of enzymes in a cellular organelle or the cytoplasm, but our understanding of the formation of these complexes, its regulation and the metabolic consequences of these molecular interactions, is limited due to our lack of understanding of the intracellular environment of enzymes including (free) substrate and effector concentrations and the interactions with other enzymes and macromolecules (Aragon and Sols, 1991). Interactions are often transient and based on weak protein-protein interactions. These interactions have been implicated to be important in metabolic flux control (Cascante et al., 2002) but are most of the time ignored in any model based on the kinetic properties of purified enzymes. Besides in vitro experiments to study flux control in metabolic pathways (Groen et al., 1983; Westerhoff et al., 1984; Ovadi, 1988; Cascante et al., 2002), there is a need to determine activity of enzymes directly in functionally intact living cells to address questions concerning the relevance of enzyme complexes and interactions with other molecules for metabolic processes and other functional processes and the multifunctionality or moonlighting of proteins.

An approach that is very attractive for this purpose is the quantitative microscopical analysis of enzyme reactions in time and space (4D analysis) in living cells using fluorogenic or chromogenic substrates and digital microscopy (Haugland, 1995; Boonacker and Van Noorden, 2001; Patton and Beechem, 2002).

Exampl\e 10

An example of the advantages of direct visualization of enzyme reactions using quantitative light microscopy is shown in Fig. 1A and B. Here, metabolic mapping in living oocytes is performed to determine G6PDH activity around fertilization. In Fig. 1A, two living sea urchin eggs are shown in time (s) while they are incubated in sea water in the presence of sea urchin sperm and chromogenic compounds to visualize G6PDH activity in living cells (Boonacker and Van Noorden, 2001; Winzer et al., 2001). The arrow indicates the moment that one of the two oocytes is fertilized; the other one remains unfertilized. Accumulation of coloured end product is clearly increased upon fertilization as is visualized in time in Fig. 1A and determined quantitatively as absorbance per oocyte in time in Fig. 1B (arrow, moment of fertilization; __, fertilized egg; - - -, unfertilized egg). Unpublished data of A. Koehler.

The approach of metabolic mapping in living cells and tissues is developing rapidly because it is realized that the microenvironment plays a distinct role in regulating metabolic processes in cells as is shown in this commentary.

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Emil Boonacker(a), Jan Stap(a), Angela Koehler(b), Cornell's J.F. Van Noorden(a),*

a Department of Cell Biology and Histology, Academic Medical Center, University of Amsterdam, Meibergdreef 15, 1105 AZ Amsterdam, The Netherlands

(b) Alfred Wegener Institute for Marine and Polar Research, Bremerhaven, Germany

Received 23 July 2003; received in revised form 16 January 2004; accepted 27 January 2004

* Corresponding author. Tel.: + 31-20-566-4970/4966; fax: +31-20- 697-4156.

E-mail address: c.j.vannoorden@amc.uva.nl (C.J.F. Van Noorden).

Copyright Urban & Fischer Verlag 2004

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