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UCSD Team Wins $9.5M NIH Grant to Use Systems Biology to Tackle Antibiotic Resistance


NEW YORK (GenomeWeb) – With the support of a five-year, $9.5 million grant from the National Institutes of Health, the University of California, San Diego has begun organizing a new research center that will use systems biology to study antibiotic resistance in high-priority pathogens.

Work at the center is expected to not only yield new insights into how drug resistance develops, but also lead to the development of treatment regimens that match specific antibiotics with susceptible pathogen strains.

"We always think of personalized medicine as based on [a patient's] genome," Bernhard Palsson, principal investigator of the Systems Biology Research Group at UCSD, told GenomeWeb. But in this case, treatments could be tailored to the infecting bacterial strain's genome.

"This many become the first example of real personalized therapy, but it's personal to [a patient's] strain," he said.

Research at the center will build on previous studies by Palsson and colleagues at UCSD in which they used genome-scale models — essentially computer simulations — to uncover the shared and unique metabolic capabilities of different strains of the same bacteria. 

In 2015, for instance, the scientists reported in Proceedings of the National Academy of Sciences on the use of genome-scale models to identify the minimal set of genes required to support life in Escherichia coli across 333 different environments. Together, these genes were dubbed the "core proteome" because they code for the portion of the proteome that is consistent in the bacteria across all environments tested. 

And earlier this month, Palsson and collaborators published a study in PNAS that used genome-scale models to 64 strains of Staphylococcus aureus, revealing a total of 7,457 genes across all of the strains. Only 1,441 genes — 19 percent of the total — were part of the staph core genome and essential to life, with the remaining genes variable across strains and in some cases unique to only one particular strain. Notably, many of the genes identified are linked to pathogenesis and virulence, providing clues about why certain strains are more dangerous than others. 

Through the new UCSD research center, the researchers plan to use a cyclical iterative systems biology workflow — which combines computational approaches such as genome-scale modeling with experimental approaches — to study antibiotic resistance in high-priority pathogens including methicillin­resistant S. aureus, carbapenem­resistant Enterobacteriaceae Klebsiella pneumoniae and Acinetobacter baumannii, and Pseudomonas aeruginosa.

According to Palsson, the workflow begins by growing clinically isolated strains of the pathogens in various conditions such as in the presence of antimicrobial peptides to test for the gain of activity advantageous to the bacteria and to generate DNA-seq, RNA-seq, and metabolomics data.

These data will then be analyzed to generate hypotheses about the antibiotic resistance mechanisms, he said. These hypotheses will then be validated using animal models; the laboratory evolution of non-virulent pathogen strains under different conditions; cytology; gene expression alteration; and structural protein analysis of putative targets.

Computational predictions will then be compared with experimental outcomes, and false­negative and false­positive predictions will be analyzed by a hypothesis-generating family of algorithms to make decisions about what conditions will be evaluated next.

"That leads to a new set of experiments, and around and around we go," Palsson said. 

The center is currently in the planning stages, he added, but is expected to be organized with studies underway by the fall.