Funded Grants


The Importance of Understanding the Complex System of a Living Cell

As we enter the 21st century, a high standard of living is enjoyed by much of society as a result of technological advances made thorough out our history. We have healthcare, agriculture, communication and labor-saving devices that our forefathers could only dream about. It is humbling however, to realize that in spite of these sophisticated technological advances, a living cell remains more complex and efficient than any system designed by man. Implicit in this statement is the fact that if we understood the complexity of a living cell, we would be in a better position to harness biological systems for the economic, environmental and medicinal benefit of society. Research in my laboratory focuses on this goal by using a bacterial cell as a model of biological complexity. By removing individual components and assessing the effect of a specific change on function of the whole system we are uncovering rules that govern the complex interactions in a living cell. This approach is fundamentally distinct from one that utilizes experimental and theoretical predictions to generate model complex systems for analysis. The latter approach is limited to what is known or can be predicted. In contrast, dissecting an existing system, while it requires a long term investment, allows one to learn what is possible without bias generated by previous dogma.

Diversity among life forms is a reflection of the breath of solutions that have evolved in response to problems faced by organisms in environments that undergo constant physical and chemical changes. Although it has long been accepted that visible differences are the result of biochemical diversity, it is now accepted that despite structural and functional differences, each living cell carries out a core set of biochemical reactions/processes that comprise its basic metabolism. The features unique to each organism are then integrated into the core metabolic properties. Effective coordination of these metabolic processes is essential for the function of each living cell. The realization that living systems are "more similar than different" in terms of metabolic strategies justifies our use of the relatively simple and technically amenable bacterial cell as a model system for biological complexity. My research is directed at understanding the rules that govern the integration of metabolism in a bacterial cell, and in the process designing theoretical approaches to complexity that will be applicable to other systems.

A simple analogy I use to emphasize the significance of coordinating biochemical processes in a cell is that of a spider web. A spider is able to detect movement in a distant part of the web when a fly lands. This is possible because of links between threads that transmit movement in one area as a signal that can be detected anywhere on the web. I work with the assumption that disruption of a component in one metabolic process has consequences in many, if not all, remaining processes. Therefore, metabolic processes in a living cell must be integrated such that changes in one part of the network can be compensated for without compromising overall function of the system. Research in my lab is based on the premise that probing the integration of cellular processes will result in a profound understanding of the rules that govern a highly efficient complex system.

The general strategy of my research has been to eliminate the ability of the complex system (in our case a bacterial cell) to compensate for perturbations. In doing so we ensure that disruption of one component will result in effects on function of the overall system that we can detect. This approach has allowed us to identify metabolic connections that would normally be masked by the inherent elasticity of the system. The design of our experiments is such that metabolic processes connected to a central point in the network are identified. In other words, we are identifying connections that radiate outward from a single fixed point. Continuation of this approach will result in a vision of the metabolic network in the cell where each point has its own radial network that is integrated with the whole.

The use of sophisticated genetic analyses has been invaluable in my studies of the integration of bacterial metabolism. In theory a genetic approach removes components of a complex system (by mutation) and analyzes the resulting behavior (phenotype) of the system. From such an approach, one can make conclusions about how the system functions that are based on logical, deductive reasoning. When used rigorously this is an extremely powerful technique for dissecting complex systems in an unbiased way and is in many ways analogous to the deductive reasoning we all use to solve problems on a daily basis. The significant difference in our system is that we can remove components (i.e., make mutations) at will, allowing us to uncover interconnections in the bacterial cell. The continuing advances in molecular biology, sequencing and protein purification now make it feasible to extend these analyses to the molecular level. Thus, inferences from a global genetic approach can now be followed by modern biochemical and molecular techniques to define details of the metabolic interactions. The work in my laboratory is unique in its global goal of identifying pathway connections, and as a result expanding our knowledge of the complex interactions in a living cell. This is distinct from the work of many biological researchers who take a focused, reductionist approach to understanding a specific component within metabolism. Research of the global nature preformed in my laboratory will ultimately allow us to trace the movement of all metabolites through the maze of biochemical processes in a living system.

Bacteria are clonal organisms, which means that the behavior of a population can be used to approximate that of an individual. This feature of bacteria make them well suited for addressing questions common to all life forms, such as the study of metabolism discussed here. Thus while a single bacterial cell is the relevant unit in this work, the actual experiments are preformed with populations of from 107 to 109 individual cells. The rapid generation time of bacteria allows us to obtain large populations (i.e., >109 individuals) in relatively short times (<12 hr). This property makes it possible to identify and manipulate the large numbers of rare events that are implied by the genetic approaches described above. Currently, using large populations is both feasible and informative, however, in the not too distant future a more sophisticated type of analyses will be required. At present, the generalization from population to individual behavior is sufficient since many features of biological systems have yet to be uncovered. At some point in the future, results of work like that carried out in my lab will have defined the majority of general parameters of metabolic interactions in the cell. At that time, techniques to eliminate the any remaining heterogeneity in the population will be required. We are confident that technology will be poised to solve this problem when it becomes necessary. Our engineering collaborators are in the final stages of designing micro devices that will allow us to analyze the behavior of <100 cells, as opposed to the current 109 cells. The potential of this micro-fluidics technology to further our understanding of the interactions occurring in a single cell is quite exciting.

It is hard to imagine a field of research that will be more critical in the future than that resulting in a better fundamental understanding of the living cell! The significance of understanding biological complexity in the 21st century is epitomized by the realization that nature is full of diverse systems that function with an efficiency man has never matched. Hidden in biological systems are the solutions to problems that technology will be asked to solve in the future. In the last seven years my laboratory has pioneered a novel approach to dissecting biological complexity with a bacterial model system. It is anticipated that data generated from this work will be used to derive computer programs with predictive value for other complex systems. Significant precedence exists for the use of bacterial systems to address problems of general importance. The ability to manipulate a bacterial system allows one to address problems of wide interest with a rapid, direct and detailed analysis. By understanding biological complexity society will be better prepared to derive solutions to various problems faced by society in the future.