A systems biology approach to studying Enterobacteria

1. A systems biology approach to studying Enterobacteria Joshua Adkins Center for Systems Biology of EnteroPathogens SBWG Web-Conference January 26, 2010

2. Family of the Enterobacteriaceae *Pang et al. Trends Micro. 3 253-255 (1995) • Gram-negative, rod-shaped, facultative anaerobes • Important members of the gut microbiome • A number of important human pathogens including • Salmonella • Yersinia • Shigella • Escherichia • Diseases caused include, systemic bacteremia, gastroenteritis, urinary infections, respiratory infections, nosocomial infections, broadly opportunistic, etc. • >1 billion cases of human disease per year by some estimates for Salmonella alone*

3. Center of Systems Biology for EnteroPathogens Dick Smith LC-MS Omics Fred Heffron Salmonella Scott Peterson Genomics Vladimir Motin Yersinia Bernhard Palsson Modeling and E. coli http://www.SysBEP.org/

4. Team Interactions-Dependant on Regular Teleconferences http://www.SysBEP.org/

5. Biology Focus • Adaptation to the host environment • Regulation and order of interactions within the host • Omics Approaches • Sample matched measurements • High-throughput global analysis for transcripts, proteins, soluble/insoluble metabolites • Targeted measurements as necessary • Modeling Approaches • Genome-Scale Reconstruction of metabolic and regulatory networks • Inference-based analysis when reconstruction is unavailable Conceptually Simply Projects In Practice Challenging

6. Adaptation-factors versus virulence-effectors • Adaptation factors: proteins required by the bacterium to survive on the nutrients available to it (metabolic, transport, structural, etc) • Virulence-effectors: proteins (or other biomolecules) that are part of the “active” response to the host • Causes changes in the host’s function • Subverts or destroys the host’s response(s) to infection • Make the host more conducive to pathogen growth

7. Yersinia and Salmonella Compared • Diseases caused by members of each genus can be systemic, gastrointestinal, and sometimes auto-immune • Successful infections require both adaptation to and modification of the host environment • In vitro models • Growth on defined media, media that induce “infectious”-like responses • Ex vivo models • Intracellular growth in host-derived cell lines that are relevant to in vivo infections • In vivo models • Animal models relevant to human disease

8. Yersinia Salmonella Yersinia and Salmonella Contrasted • Signals for infectious like conditions • Low [Ca2+] and 37 °C • Gastroenteritis food borne and systemic is vector borne • Extracellular lifecycle • Intracellular at early stage of infection in phagosome • Signals for infectious like conditions • Low pH, iron, [Mg2+] • Gastroenteritis and systemic are both food and water borne • Intracellular lifecycle is propagated in early phagosome-like structures

9. Recent Successes • Data acquisition nearly complete for first major cross-site efforts for both Salmonella and Yersinia projects. (transcriptomics, proteomics, and metabolic reconstructions) • Multiple rounds of metabolomics and lipidomics methods refinement, finalizing the global protocols • Completed community consensus Genome-Scale Reconstruction of the Salmonella metabolic network, Thiele et al. submitted to J. Bac. • Integrating community available “omics” results for initial model testing. • Publication of early project efforts. • Shi et al. 2009, Infection and Immunity (macrophage infection) • Shi et al. 2009, J. Proteomics and Bioinformatics (growth condition refinement) • Auberry et al. 2010, J. Proteomics and Bioinformatics (proteomics, metabolomics, and lipidomics dissemination site)

10. Changes since the first annual meeting • Limited technical changes, but emphasis areas have adapted (increase planning for pathogen-host interactions) • Stronger interconnections and better sense of team • Sub-projects refined and made more efficient, in some cases moving to application rather than refinements • Increased emphasis on multi-site collaborations • PI strategy session discussing opportunities for truly impactful work • On-line data analysis jamborees (balance individual and team needs) • Improving what is meant by “data integration” • Adding a sense of urgency (“18 months”)

11. The SysBEP Team NIH/DHHS NIAID IAA Y1-AI-8401-01 PNNL – Adkins Joshua Adkins Meagan Burnet Jason McDermott Richard Smith, Co-PI Saiful Chowdhury Matthew Monroe Gordon Anderson Michelle Costa Karin Rodland Charles Ansong, PM Young-Mo Kim Alexandra Schrimpe-Rutledge Heather Brewer Tom Metz Liang Shi Roslyn Brown Jessica Martin Mudita Singhal WSU-McAteer Kate McAteer JCVI-Peterson Scott Peterson Marcus Jones OHSU-Heffron Fred Heffron Afshan Kidwai Jie Li George Niemann Hyunjin Yoon UCSD-Palsson Bernhard Palsson Pep Charusanti Daniel Hyduke UTMB-Motin Vladimir Motin Sadhana Chauhan SysBEP.org

12. Genome Scale-Metabolic Reconstruction of Salmonella: Community Driven Consensus Thiele et al., submitted to J Bac Thiele, Hyduke, & Palsson

13. Discovery of Novel Type III Secreted Effectors Niemann, Brown, Li, Brewer, & Heffron

14. Secretion of SrfN viaOuter Membrane Vesicles Yoon et al., in revision NMR structure of STM0082 aka SrfN, pdb: 2JNA NESGC Yoon, Ansong, McDermott, Gritsenko, & Heffron