Research

Towards a Holistic Understanding of Cellular Metabolism

The 20 th century saw remarkable progress in understanding key biochemical structures and processes, such as the enzymatic pathway by which glucose is used to generate ATP and the mechanism of replication of genetic material. Until very recently, however, chemical biology focused almost exclusively on understanding biological processes in relative isolation, with minimal attention to the mechanisms by which the complete chemical constituents of cells, or even more dauntingly multi-cellular organisms, function together. With newfound knowledge of the full genetic sequences of multiple organisms, chemical biology is for the first time beginning to investigate the means by which the integrated functioning of the full complement of biological chemicals yields life.

To succeed in developing a complete chemical model of even a simple organism, it is necessary to gain a comprehensive understanding of the molecular constituents involved, including their function, production, consumption, and geometrical organization. These constituents can be broadly divided into large molecule biopolymers such as DNA, RNA, and proteins, and small molecules such metabolic intermediates and membrane lipids. Currently, progress towards a complete understanding of biopolymers is progressing with remarkable speed. The full sequence of genomic DNA is known, and the entirety of RNA present in a cell at any given moment can be relatively easily measured using DNA microarrays. As proteins are produced from RNA templates, the ability to quantify all cellular RNA provides valuable insight into which proteins are being manufactured at specific times in specific cell types.

A critical complement to the current holistic studies of cellular large molecules is comparably comprehensive study of the dynamics of the intracellular metabolites. The challenges of holistic study of cellular metabolites differ substantially from those of macromolecules. There is no master code of cellular small molecules comparable to the genomic template that encodes the structure of all biopolymers. In addition, metabolic reactions occur on a timescale much shorter than that of large molecule synthesis or degradation, with substantial swings in small molecule concentrations possible on the time scale of seconds. In part because of these challenges, no methods have yet been developed that allow for comprehensive characterization of small molecule concentrations and fluxes in living cells, analogous to methods such as microarrays that provide global views of biopolymer expression. The overall goal of my lab is to develop a robust means of measuring the concentrations and fluxes of numerous intracellular metabolites in parallel.

Methodology for Metabolite Measurement

Our overall approach to metabolite concentration measurement is shown in the figure below. We first grow cells under carefully defined conditions (Step 1) and then extract the small molecules present inside the cells using organic solvent (Step 2). The metabolites in this extract are then measured by liquid chromatography / tandem mass spectrometry (LC/MS/MS). This technique enables very precise detection of numerous metabolites in parallel, due to its ability to isolate targets of interest by both polarity (Step 3) and molecular weight (Step 4) and to detect the resulting separated ions with exquisite sensitivity (Step 5).

Experimental and Computational Studies of Metabolic Fluxes

An interesting step towards a holistic understanding of metabolism would be to develop a comprehensive, chemical kinetic model of all known metabolic reactions. The model would involve attaching a kinetic rate constant to every metabolic step, as well as a concentration to every metabolite. Cell metabolism could then be reduced to a system of chemical kinetic differential equations. A major barrier towards development of such a model is current lack of knowledge of the intracellular concentration of many metabolic intermediates; hence, our focus on developing the measurement methodology described above. Measurement of intracellular metabolite concentrations would ideally be complemented by measurement of the in vivo rate constants of metabolic reactions, which can be achieved by techniques including mass spectrometry and microphysiometry.

Biomedical Applications

A virtue of improved tools for measuring the chemical constituents of cells is the ability to extract further illumination from classic biological experimental designs, such as the diauxic shift in yeast. In the diauxic shift, yeast switch from anaerobically fermenting glucose to form ethanol to aerobically consuming this ethanol when the glucose is exhausted. Analysis of the diauxic shift using DNA microarrays revealed that very many genes change their expression during this switch in nutrient utilization. The interrelationship between specific gene expression changes and metabolic changes, however, remains unclear, primarily because the temporal course of changes in metabolite concentrations and fluxes has not been studied adequately. A major effort is currently underway in my lab, in collaboration with other groups at the Lewis-Sigler Center, to rectify this deficiency.

A virtue of studying metabolism in systems like yeast is that metabolites are remarkably conserved between species—even more so, in fact, than genes. Thus, lessons learned in unicellular organisms can rapidly inform medical issues, such as the molecular basis of metabolic malfunctioning that occurs in human disease. In certain common diseases, e.g., diabetes and obesity, metabolic dysfunction is a core aspect of the pathophysiology. In others, such as cancer, it is secondary, but nevertheless required for disease progression, with, for example, malignant cells requiring increased glycolytic metabolism and nucleic acid synthesis to be able to divide rapidly in an oxygen-poor tumor environment. Notably, many important drugs (e.g., certain antibiotic and anticancer agents and the leading cholesterol lowering agents) target specific metabolic reactions. Hence, improved understanding of metabolism will likely have great value in developing better drugs and disease treatments.