The proposal details a novel means of meeting the challenge of antibiotic resistance of pathogenic organisms. It is based on the assumption that genomic information for the pathogen of interest is complete enough to permit useful probabilities of finding weak points to exploit. The goal of the proposal is to determine the sensitivity of the organism to deletion of individual genes or relatively small groups of genes. In this way it is hoped to find deletions which are lethal to the organism but at the same time harmless for the human host. At a more detailed level the proposal lays out mathematical procedures for finding lethal deletions and for putting the results in convenient form for the investigator. Only computer simulations will be made, and it is not expected to find any promising new antibiotics. Rather the proposal is to investigate the feasibility and potential utility of the procedures outlined.
| Brunk, Elizabeth; Chang, Roger L; Xia, Jing et al. (2018) Characterizing posttranslational modifications in prokaryotic metabolism using a multiscale workflow. Proc Natl Acad Sci U S A 115:11096-11101 |
| Latif, Haythem; Federowicz, Stephen; Ebrahim, Ali et al. (2018) ChIP-exo interrogation of Crp, DNA, and RNAP holoenzyme interactions. PLoS One 13:e0197272 |
| Brunk, Elizabeth; Sahoo, Swagatika; Zielinski, Daniel C et al. (2018) Recon3D enables a three-dimensional view of gene variation in human metabolism. Nat Biotechnol 36:272-281 |
| Monk, Jonathan M; Lloyd, Colton J; Brunk, Elizabeth et al. (2017) iML1515, a knowledgebase that computes Escherichia coli traits. Nat Biotechnol 35:904-908 |
| Sastry, Anand; Monk, Jonathan; Tegel, Hanna et al. (2017) Machine learning in computational biology to accelerate high-throughput protein expression. Bioinformatics 33:2487-2495 |
| Fang, Xin; Sastry, Anand; Mih, Nathan et al. (2017) Global transcriptional regulatory network for Escherichia coli robustly connects gene expression to transcription factor activities. Proc Natl Acad Sci U S A 114:10286-10291 |
| Chen, Ke; Gao, Ye; Mih, Nathan et al. (2017) Thermosensitivity of growth is determined by chaperone-mediated proteome reallocation. Proc Natl Acad Sci U S A 114:11548-11553 |
| Yurkovich, James T; Yang, Laurence; Palsson, Bernhard O (2017) Biomarkers are used to predict quantitative metabolite concentration profiles in human red blood cells. PLoS Comput Biol 13:e1005424 |
| Brunk, Elizabeth; George, Kevin W; Alonso-Gutierrez, Jorge et al. (2016) Characterizing Strain Variation in Engineered E. coli Using a Multi-Omics-Based Workflow. Cell Syst 2:335-46 |
| Brunk, Elizabeth; Mih, Nathan; Monk, Jonathan et al. (2016) Systems biology of the structural proteome. BMC Syst Biol 10:26 |
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