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
structural17 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."