Evolutionary genomics is a key to controlling emerging infectious diseases by identifying virulence genes in the pathogen genome and by revealing patterns and mechanisms of disease spread. Lyme disease, caused by pathogens belonging to the bacterial species complex Borrelia burgdorferi sensu lato, is the most common vector-borne disease in North America and Europe. Although geographically limited, the Lyme disease endemic has greatly expanded in range in recent decades with little predictability. In the past four years, the PI and his collaborators have sequenced the genomes of twenty-three world-wide representative strains of Lyme disease pathogens. Along with the half dozen genomes previously sequenced by this and other research groups, this large amount of Borrelia genomes usher in a new era of understanding the genomic and ecological basis of Lyme disease endemics through evolutionary and comparative genomics. The SC3 support during 1998- 2012 is behind the PI's leading roles in the phylogeny-based selection of strains for whole-genome sequencing, the discovery of widespread recombination and estimation of its rates, and the development of a computational model of B. burgdorferi genome diversity driven by immune escape at a few major surface antigen loci and the outer-surface protein C (ospC) locus in particular. In addition, the SC3 projects resulted in a mature bioinformatics and analytical infrastructure in the PI's lab including, e.g., a customized genome database, a suite of Perl/BioPerl based software tools (DNATweezers), and a simulator of bacterial genome evolution (SimBac). The latter two tools have been released into public repository SourceForge.net as Open Source projects. The PI's specific aims for the proposed SC1 project are to (i) reveal genome variability associated with B. burgdorferi virulence by tests of positive and purifying natural selection, (ii) launch a new line of research in the phylodynamics of Borrelia for predicting the spread of Lyme endemics, and (iii) modernize comparative genomics studies of pathogens by develop evolutionary bioinformatics tools. The PI will develop non-SCORE research proposals through widening collaboration with Borrelia molecular geneticists and Lyme ecologists and developing translational and innovative research programs in population genomics of Lyme disease. To summarize, the overall goal and expected outcomes of the project will be an elucidation of virulence-associated genomic variations, predictive models of the spread of Lyme disease endemics, and a nationally competitive research program in ecology and evolution of emerging infectious diseases. The project helps to control the spread of Lyme disease by identifying virulence genes and by predicting pathogen spread in nature.

Public Health Relevance

By identifying genes associated with human virulence in the pathogen genome, the proposed project will reveal novel vaccine, treatment, and diagnostic targets of Lyme disease. By elucidating mechanisms of pathogen diversification, the project will monitor and help control the spread of Lyme disease in North America.

Agency
National Institute of Health (NIH)
Institute
National Institute of Allergy and Infectious Diseases (NIAID)
Type
Research Enhancement Award (SC1)
Project #
4SC1AI107955-04
Application #
9014481
Study Section
Special Emphasis Panel (ZGM1)
Program Officer
Ilias, Maliha R
Project Start
2013-03-06
Project End
2018-02-28
Budget Start
2016-03-01
Budget End
2018-02-28
Support Year
4
Fiscal Year
2016
Total Cost
Indirect Cost
Name
Hunter College
Department
Biology
Type
Schools of Arts and Sciences
DUNS #
620127915
City
New York
State
NY
Country
United States
Zip Code
10065
Di, Lia; Wan, Zhenmao; Akther, Saymon et al. (2018) Genotyping and Quantifying Lyme Pathogen Strains by Deep Sequencing of the Outer Surface Protein C (ospC) Locus. J Clin Microbiol 56:
Casjens, Sherwood R; Di, Lia; Akther, Saymon et al. (2018) Primordial origin and diversification of plasmids in Lyme disease agent bacteria. BMC Genomics 19:218
Hernández, Yözen; Bernstein, Rocky; Pagan, Pedro et al. (2018) BpWrapper: BioPerl-based sequence and tree utilities for rapid prototyping of bioinformatics pipelines. BMC Bioinformatics 19:76
Yan, Jinyuan; Deforet, Maxime; Boyle, Kerry E et al. (2017) Bow-tie signaling in c-di-GMP: Machine learning in a simple biochemical network. PLoS Comput Biol 13:e1005677
Casjens, Sherwood R; Gilcrease, Eddie B; Vujadinovic, Marija et al. (2017) Plasmid diversity and phylogenetic consistency in the Lyme disease agent Borrelia burgdorferi. BMC Genomics 18:165
Zhang, Kai; Bian, Jiang; Deng, Yijie et al. (2016) Lyme disease spirochaete Borrelia burgdorferi does not require thiamin. Nat Microbiol 2:16213
Martin, Che L; Martin, Che I; Sukarna, Tika Y et al. (2015) Phylogenomic identification of regulatory sequences in bacteria: an analysis of statistical power and an application to Borrelia burgdorferi sensu lato. MBio 6:
Heavner, Mary Ellen; Qiu, Wei-Gang; Cheng, Hai-Ping (2015) Phylogenetic Co-Occurrence of ExoR, ExoS, and ChvI, Components of the RSI Bacterial Invasion Switch, Suggests a Key Adaptive Mechanism Regulating the Transition between Free-Living and Host-Invading Phases in Rhizobiales. PLoS One 10:e0135655
Gorson, Juliette; Ramrattan, Girish; Verdes, Aida et al. (2015) Molecular Diversity and Gene Evolution of the Venom Arsenal of Terebridae Predatory Marine Snails. Genome Biol Evol 7:1761-78
Qiu, Wei-Gang; Martin, Che L (2014) Evolutionary genomics of Borrelia burgdorferi sensu lato: findings, hypotheses, and the rise of hybrids. Infect Genet Evol 27:576-93

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