With a dearth of new classes of antibiotics in development, hospital infection control is crucial to prevent the rise of untreatable Gram-negative bacterial infections. Whole genome sequencing provides a level of resolution that far exceeds traditional typing methods. This high level resolution enables tracking the spread of pathogens within and between hospitals, thus identifying possible weaknesses in existing practices and points of intervention.
We aim to use genomic information to model outbreaks, monitor evolution of antibiotic resistance and develop risk assessment strategies. The NIH Clinical Center (CC) is a hospital that provides care for critically ill patients. As such, one ongoing concern is the possibility of hospital-acquired infections, particularly with multi-drug resistant (MDR) Gram-negative bacterial infections. Hospital-acquired infections result in 100,000 deaths per year, and represent a tremendous social cost to patients and their families. My laboratorys mission is to use genomic information to model clusters of bacterial infections and transmissions, monitor evolution of antibiotic resistance and develop risk assessment strategies. Acinetobacter baumannii is an emerging human pathogen and a significant cause of nosocomial infections amongst hospital patients worldwide. The enormous increase in multi-drug resistance among hospital isolates and the recent emergence of pan-drug resistant strains underscores the urgency to understand how A. baumannii evolves in hospital environments. To this end, we undertook a genomic study of a polyclonal cluster of infections of multi-drug resistant A. baumannii at the NIH Clinical Center. Comparing the complete genome sequences of the three dominant outbreak strain types enabled us to conclude that despite all belonging to the same epidemic lineage, the three strains diverged prior to their arrival to NIH. The simultaneous presence of three divergent strains from this lineage supports its increasing prevalence in international hospitals, and suggests an ongoing adaptation to the hospital environment. Further genomic comparisons uncovered that that much of the diversification that occurred since the divergence of the three outbreak strains was mediated by homologous recombination across 20% of their genomes. Inspection of recombinant regions revealed that several were associated with either the loss or swapping out of genes encoding proteins that are either exposed to the cell surface or that synthesize cell surface molecules. Extending our analysis to a more diverse set of international clinical isolates revealed a previously unappreciated ability of A. baumannii to vary surface molecules through horizontal gene transfer, with subsequent intra-species dissemination by homologous recombination. Klebsiella pneumoniae is another Gram-negative bacteria, which also represents a major cause of nosocomial infections, primarily among immunocompromised patients. The emergence of strains resistant to carbapenems has left few treatment options, making infection containment critical. In 2011 the National Institutes of Health Clinical Center had a cluster of infections of carbapenem-resistant K. pneumoniae that affected 19 patients, 12 of who died. Whole-genome sequencing was performed on K. pneumoniae isolates to gain insight into why the outbreak progressed in spite of early implementation of infection control procedures. Integrated genomic and epidemiological analysis traced the outbreak to three independent transmissions from a single patient, who was discharged three weeks before the next case became clinically apparent. Additional genomic comparisons provided evidence for unexpected transmission routes, with subsequent mining of epidemiological data providing possible explanations for these transmissions. Our analysis demonstrates that integration of genomic and epidemiological data can yield actionable insights and facilitate the control of nosocomial transmission. With increasing rates of antibiotic resistance, bacterial infections have become more difficult to treat, elevating the importance of surveillance and prevention. Effective surveillance relies on the availability of rapid, cost-effective and informative typing methods to monitor bacterial isolates. PCR based typing assays are fast and inexpensive, but their utility is limited by the lack of targets which are capable of distinguishing between strains within a species. To identify highly informative PCR targets from the growing base of publicly available bacterial genome sequence, we developed a computer algorithm which uses existing genome sequences for isolates of a species of interest and identifies a set of genes whose patterns of presence or absence provides the best discrimination between strains in this species. A set of PCR primers targeting the identified genes is then designed, with each PCR product being of a different size to allow multiplexing. These target DNA regions and PCR primers can then be utilized to type bacterial isolates. Our short-term goal is to produce reference genomes for hospital transmitted pathogens to enable research in this field. Our long-term goal is both to promote hospital infection control and to create drug strategies that capitalize on the bacteriums loss of fitness typically associated with acquisition of antibiotic resistance.
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|Yang, Joy Y; Brooks, Shelise; Meyer, Jennifer A et al. (2013) Pan-PCR, a computational method for designing bacterium-typing assays based on whole-genome sequence data. J Clin Microbiol 51:752-8|
|Snitkin, Evan S; Zelazny, Adrian M; Gupta, Jyoti et al. (2013) Genomic insights into the fate of colistin resistance and Acinetobacter baumannii during patient treatment. Genome Res 23:1155-62|