细菌生长如何应对温度变化

Bioengineers at the University of California, San Diego have developed a computational model of 1,366 genes¹ in E. coli that includes 3D protein structures and has enabled them to compute² the temperature sensitivity of the bacterium's proteins. The study, published June 7 in the journal Science, opens the door for engineers to create heat-tolerant microbial strains for production of commodity chemicals, therapeutic³ proteins and other industrial applications. Students of microbiology learn early that bacterial⁴ growth is temperature sensitive. For most pathogens, the optimum（最适宜的） growth temperature is approximately the same as the body temperature of humans, or 37 C, but some bacteria, called thermophiles, grow well at high temperatures. Determining what precisely⁵ causes some bacteria to be more heat sensitive than others has eluded⁶ scientists thus far.   "Evidence has accumulated over several decades that proteins are what limit the heat tolerance⁷ of cells, but pinpointing⁸ the weak points represented by specific proteins has never before been accomplished⁹ except when researchers have engineered certain proteins to be sensitive to temperature," said Roger Chang, the first author on the paper who earned his Ph.D. in bioinformatics and systems biology at UC San Diego in 2012. "Not only have we predicted some of these weak points in E. coli but we did so through an unprecedented¹⁰ integrative computational approach drawing from both three-dimensional protein structure analysis and genome-scale cellular¹¹ network modeling."   Chang completed his Ph.D. in the Systems Biology Research Group of Professor Bernhard Palsson and is currently a postdoctoral fellow at Harvard Medical School.   Chang said the predictions about thermosensitivity of specific proteins in E. coli have been overcome by nutrient¹² supplementation experiments, as predicted by the computational model. The next step is to engineer or evolve thermostabilizing mutations in these proteins to yield genetically¹³ thermotolerant strains. The results thus far demonstrate the potential capabilities¹⁴ offered by the emerging field of systems biology, which leverages¹⁵ the power of high-performance computing¹⁶ and an enormous amount of available data from the life sciences to simulate biological activities.   "Broadly speaking, this study demonstrates how fundamental understanding of biology can be revealed by integrating network and structural#p#分页标题#e#¹⁷ biology at the genome-scale," said Professor Palsson. "Representing cellular functions in chemically accurate terms enables quantitative¹⁸ computation of cellular behavior. It is quite remarkable¹⁹ how far this field has come in just the past couple of years, and it appears that we can look forward to continuing advances in the near future."