Zoltán N. Oltvai

NETWORK BIOLOGY: UNDERSTANDING THE CELL'S FUNCTIONAL ORGANIZATION

A key aim of postgenomic biomedical research is to systematically catalogue all molecules and their interactions within a living cell. There is a clear need to understand how these molecules and the interactions between them determine the function of this enormously complex machinery, both in isolation and when surrounded by other cells. Rapid advances in network biology indicate that cellular networks are governed by universal laws and offer a new conceptual framework that could potentially revolutionize our view of biology and disease pathologies in the twenty-first century.

The large-scale organization of metabolic networks.

In a cell or microorganism, the processes that generate mass, energy, information transfer and cell-fate specification are seamlessly integrated through a complex network of cellular constituents and reactions. However, despite the key role of these networks in sustaining cellular functions, their large-scale structure is essentially unknown. Here we present a systematic comparative mathematical analysis of the metabolic networks of 43 organisms representing all three domains of life. We show that, despite significant variation in their individual constituents and pathways, these metabolic networks have the same topological scaling properties and show striking similarities to the inherent organization of complex non-biological systems. This may indicate that metabolic organization is not only identical for all living organisms, but also complies with the design principles of robust and error-tolerant scale-free networks, and may represent a common blueprint for the large-scale organization of interactions among all cellular constituents.

Lethality and centrality in protein networks.

Proteins are traditionally identified on the basis of their individual actions as catalysts, signalling molecules, or building blocks in cells and microorganisms. But our post-genomic view is expanding the proteins role into an element in a network of protein–protein interactions as well, in which it has a contextual or cellular function within functional modules. Here we provide quantitative support for this idea by demonstrating that the phenotypic consequence of a single gene deletion in the yeast Saccharomyces cerevisiae is affected to a large extent by the topological position of its protein product in the complex hierarchical web of molecular interactions.

Hierarchical Organization of Modularity in Metabolic Networks

Spatially or chemically isolated functional modules composed of several cellular components and carrying discrete functions are considered fundamental building blocks of cellular organization, but their presence in highly integrated biochemical networks lacks quantitative support. Here, we show that the metabolic networks of 43 distinct organisms are organized into many small, highly connected topologic modules that combine in a hierarchical manner into larger, less cohesive units, with their number and degree of clustering following a power law. Within Escherichia coli, the uncovered hierarchical modularity closely overlaps with known metabolic functions. The identified network architecture may be generic to system-level cellular organization.

CHECKPOINTS OF DUELING DIMERS FOIL DEATH WISHES

Zoltan N. Oitvai* and Stanley 3. Korsmeyefl *Department of Pathology Northwestern University School of Medicine Chicago, Illinois 60610 tHoward Hughes Medical institute Division of Molecular Oncology Departments of Medicine and Pathology Washington University School of Medicine St. Louis, Missouri 63110 Recent evidence has emphasized the indispensibie role of programmed cell death in the development and mainte- nance of homeostasis within ail multicellular organisms. Genetic and molecular analysis from nematodes to hu- mans has indicated that cellular suicide is highly con- sewed (Hengartner and Horvitz, 1994, and references therein). Thus, it appears that the evolutionary switch from a unicellular to a multicellular existence hinged in part upon the creation of a regulated cell suicide response. A Cell-Autonomous Susceptibility to Dying From an individual cell’ s point of view, signals received from its environment can prompt the ultimate sacrifice: its own demise. The capacity to carry out apoptosis appears to be inherent to most (if not ail) ceils that depend upon an extracellular milieu of survival factors or cell-ceil contact molecules for their viability (Raff, 1992). Yet it is increasingly evident that the decision to die is not solely determined by extraceiluiar signals. in a number of biological systems, the degree of sensitivity to a given death stimulus is cell-type specific. For example, CD4+CD6+ cortical thymocytes are exquisitely sensitive to a wide vari- ety of apoptotic stimuli, while the more mature meduliary thymocytes are resistant. Similarly, in the Drosophila eye, a given signal can effectively rescue cells from apoptosis at one developmental stage, but not at another (Bonini et al., 1993). These observations imply the existence of an autonomous regulation of the apoptotic program. intracellular Checkpoints: The f3cM/Bax Rheostat The resistance of mature meduliary thymocytes to apop- totic signals correlates with a high expression level of the Bcl-2 protein. Bcl-2, originally identified at the t(l4;16) breakpoint in foilicular B cell lymphoma, can counter some but not ail stimuli known to induce cell death (Vaux et al., 1968). Bcl-2 is the founding member of an expanding family of proteins, whose principle homology is clustered within two conserved motifs called the Bcl-2 homology 1 (BHl) and homology 2 (BH2) domains (reviewed by Wii- liams and Smith, 1993). This family includes Bax, a homo- log that dimerizes with itself or with Bcl-2 and that, when overproduced, promotes apoptosis (Korsmeyer et al., 1993). Of note, Bax itself cannot trigger cell death, but requires a cell death signal (Figure 1). Selected mutations

Evolutionary conservation of motif constituents in the yeast protein interaction network

Understanding why some cellular components are conserved across species but others evolve rapidly is a key question of modern biology. Here we show that in Saccharomyces cerevisiae, proteins organized in cohesive patterns of interactions are conserved to a substantially higher degree than those that do not participate in such motifs. We find that the conservation of proteins in distinct topological motifs correlates with the interconnectedness and function of that motif and also depends on the structure of the overall interactome topology. These findings indicate that motifs may represent evolutionary conserved topological units of cellular networks molded in accordance with the specific biological function in which they participate.

The implications of human metabolic network topology for disease comorbidity

Most diseases are the consequence of the breakdown of cellular processes, but the relationships among genetic/epigenetic defects, the molecular interaction networks underlying them, and the disease phenotypes remain poorly understood. To gain insights into such relationships, here we constructed a bipartite human disease association network in which nodes are diseases and two diseases are linked if mutated enzymes associated with them catalyze adjacent metabolic reactions. We find that connected disease pairs display higher correlated reaction flux rate, corresponding enzyme-encoding gene coexpression, and higher comorbidity than those that have no metabolic link between them. Furthermore, the more connected a disease is to other diseases, the higher is its prevalence and associated mortality rate. The network topology-based approach also helps to uncover potential mechanisms that contribute to their shared pathophysiology. Thus, the structure and modeled function of the human metabolic network can provide insights into disease comorbidity, with potentially important consequences for disease diagnosis and prevention.

Intracellular crowding defines the mode and sequence of substrate uptake by Escherichia coli and constrains its metabolic activity.

The influence of the high intracellular concentration of macromolecules on cell physiology is increasingly appreciated, but its impact on system-level cellular functions remains poorly quantified. To assess its potential effect, here we develop a flux balance model of Escherichia coli cell metabolism that takes into account a systems-level constraint for the concentration of enzymes catalyzing the various metabolic reactions in the crowded cytoplasm. We demonstrate that the models predictions for the relative maximum growth rate of wild-type and mutant E. coli cells in single substrate-limited media, and the sequence and mode of substrate uptake and utilization from a complex medium are in good agreement with subsequent experimental observations. These results suggest that molecular crowding represents a bound on the achievable functional states of a metabolic network, and they indicate that models incorporating this constraint can systematically identify alterations in cellular metabolism activated in response to environmental change.

Aggregation of topological motifs in the Escherichia coli transcriptional regulatory network

BackgroundTranscriptional regulation of cellular functions is carried out through a complex network of interactions among transcription factors and the promoter regions of genes and operons regulated by them.To better understand the system-level function of such networks simplification of their architecture was previously achieved by identifying the motifs present in the network, which are small, overrepresented, topologically distinct regulatory interaction patterns (subgraphs). However, the interaction of such motifs with each other, and their form of integration into the full network has not been previously examined.ResultsBy studying the transcriptional regulatory network of the bacterium, Escherichia coli, we demonstrate that the two previously identified motif types in the network (i.e., feed-forward loops and bi-fan motifs) do not exist in isolation, but rather aggregate into homologous motif clusters that largely overlap with known biological functions. Moreover, these clusters further coalesce into a supercluster, thus establishing distinct topological hierarchies that show global statistical properties similar to the whole network. Targeted removal of motif links disintegrates the network into small, isolated clusters, while random disruptions of equal number of links do not cause such an effect.ConclusionIndividual motifs aggregate into homologous motif clusters and a supercluster forming the backbone of the E. coli transcriptional regulatory network and play a central role in defining its global topological organization.

Catabolic efficiency of aerobic glycolysis: The Warburg effect revisited

BackgroundCancer cells simultaneously exhibit glycolysis with lactate secretion and mitochondrial respiration even in the presence of oxygen, a phenomenon known as the Warburg effect. The maintenance of this mixed metabolic phenotype is seemingly counterintuitive given that aerobic glycolysis is far less efficient in terms of ATP yield per moles of glucose than mitochondrial respiration.ResultsHere, we resolve this apparent contradiction by expanding the notion of metabolic efficiency. We study a reduced flux balance model of ATP production that is constrained by the glucose uptake capacity and by the solvent capacity of the cells cytoplasm, the latter quantifying the maximum amount of macromolecules that can occupy the intracellular space. At low glucose uptake rates we find that mitochondrial respiration is indeed the most efficient pathway for ATP generation. Above a threshold glucose uptake rate, however, a gradual activation of aerobic glycolysis and slight decrease of mitochondrial respiration results in the highest rate of ATP production.ConclusionsOur analyses indicate that the Warburg effect is a favorable catabolic state for all rapidly proliferating mammalian cells with high glucose uptake capacity. It arises because while aerobic glycolysis is less efficient than mitochondrial respiration in terms of ATP yield per glucose uptake, it is more efficient in terms of the required solvent capacity. These results may have direct relevance to chemotherapeutic strategies attempting to target cancer metabolism.