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Metabolic Pathway Diagram. The microbial proteins
comprise a diverse set of reaction pathways that carry out the cell's
activities. Modeling this complexity is crucial to understanding and utilizing
the cell's capacities. |
Microbial Cell Research Thrusts (Continued) Goal: Determine the physiological and biochemical functions of the gene and specific bioprocesses using standard biochemical techniques and structural/computational biology. Challenges: Although a given microbe possesses a single set of genes, it is the pattern and timing of how these genes are expressed that enables the organism to adapt and survive. One of the challenges in studying a microbe that has been biologically selected to respond quickly to complex environmental cues (such as changes in nutrients, toxins, temperature, salt, or acid conditions) is to understand how it expresses a physiologically appropriate subset of its genes. Adaptation by a microbe to a specific environmental cue is not simply the addition of unrelated, independent responses by individual genes, but rather a synergistic and tightly coordinated network of gene expression. A number of technical advances make it feasible, for the first time, to begin to map out these complex regulatory networks in microbial cells. The advent of microarrays of DNA sequence fragments (one for each expressed gene) and high-resolution protein electrophoresis and mass spectrometry can give scientists the gene expression and protein profile of a microbe as a function of time or experimental condition. Among these are responses to external stimuli (e.g., hormones, nutrients, and toxins), or changes in environmental conditions. Similarly, computational algorithms designed to recognize common pattern elements in gene control regions can provide insight into co-regulated genes. Since, as noted above, about half of the genes in a microbial genome have unknown function, these approaches will be especially useful in linking these novel genes and proteins to a particular physiological regulatory network and potentially in elucidating their function. For these data-intensive gene expression profile and sequence comparisons, computational biology will be critical. published 06/05/00 |
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