Studying salmonellae and yersiniae host-pathogen interactions using integrated 'omics and modeling

Charles Ansong; Brooke L. Deatherage; Daniel Hyduke; Brian Schmidt; Jason E. McDermott; Marcus B. Jones; Sadhana Chauhan; Pep Charusanti; Young Mo Kim; Ernesto S. Nakayasu; Jie Li; Afshan Kidwai; George Niemann; Roslyn N. Brown; Thomas O. Metz; Kathleen McAteer; Fred Heffron; Scott N. Peterson; Vladimir Motin; Bernhard O. Palsson; Richard D. Smith; Joshua N. Adkins

doi:10.1007/82-2012-247

Studying salmonellae and yersiniae host-pathogen interactions using integrated 'omics and modeling

Charles Ansong, Brooke L. Deatherage, Daniel Hyduke, Brian Schmidt, Jason E. McDermott, Marcus B. Jones, Sadhana Chauhan, Pep Charusanti, Young Mo Kim, Ernesto S. Nakayasu, Jie Li, Afshan Kidwai, George Niemann, Roslyn N. Brown, Thomas O. Metz, Kathleen McAteer, Fred Heffron, Scott N. Peterson, Vladimir Motin, Bernhard O. PalssonRichard D. Smith, Joshua N. Adkins

Pathology

Research output: Chapter in Book/Report/Conference proceeding › Chapter

12 Scopus citations

Abstract

Salmonella and Yersinia are two distantly related genera containing species with wide host-range specificity and pathogenic capacity. The metabolic complexity of these organisms facilitates robust lifestyles both outside of and within animal hosts. Using a pathogen-centric systems biology approach, we are combining a multi-omics (transcriptomics, proteomics, metabolomics) strategy to define properties of these pathogens under a variety of conditions including those that mimic the environments encountered during pathogenesis. These high-dimensional omics datasets are being integrated in selected ways to improve genome annotations, discover novel virulence-related factors, and model growth under infectious states. We will review the evolving technological approaches toward understanding complex microbial life through multi-omic measurements and integration, while highlighting some of our most recent successes in this area.

Original language	English (US)
Title of host publication	Systems Biology
Editors	Michael G. Katze
Pages	21-41
Number of pages	21
DOIs	https://doi.org/10.1007/82-2012-247
State	Published - 2012

Publication series

Name	Current Topics in Microbiology and Immunology
Volume	363
ISSN (Print)	0070-217X

ASJC Scopus subject areas

Immunology and Allergy
Microbiology
Immunology
Microbiology (medical)

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10.1007/82-2012-247

Cite this

Ansong, C., Deatherage, B. L., Hyduke, D., Schmidt, B., McDermott, J. E., Jones, M. B., Chauhan, S., Charusanti, P., Kim, Y. M., Nakayasu, E. S., Li, J., Kidwai, A., Niemann, G., Brown, R. N., Metz, T. O., McAteer, K., Heffron, F., Peterson, S. N., Motin, V., ... Adkins, J. N. (2012). Studying salmonellae and yersiniae host-pathogen interactions using integrated 'omics and modeling. In M. G. Katze (Ed.), Systems Biology (pp. 21-41). (Current Topics in Microbiology and Immunology; Vol. 363). https://doi.org/10.1007/82-2012-247

Ansong, C, Deatherage, BL, Hyduke, D, Schmidt, B, McDermott, JE, Jones, MB, Chauhan, S, Charusanti, P, Kim, YM, Nakayasu, ES, Li, J, Kidwai, A, Niemann, G, Brown, RN, Metz, TO, McAteer, K, Heffron, F, Peterson, SN, Motin, V, Palsson, BO, Smith, RD & Adkins, JN 2012, Studying salmonellae and yersiniae host-pathogen interactions using integrated 'omics and modeling. in MG Katze (ed.), Systems Biology. Current Topics in Microbiology and Immunology, vol. 363, pp. 21-41. https://doi.org/10.1007/82-2012-247

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title = "Studying salmonellae and yersiniae host-pathogen interactions using integrated 'omics and modeling",

abstract = "Salmonella and Yersinia are two distantly related genera containing species with wide host-range specificity and pathogenic capacity. The metabolic complexity of these organisms facilitates robust lifestyles both outside of and within animal hosts. Using a pathogen-centric systems biology approach, we are combining a multi-omics (transcriptomics, proteomics, metabolomics) strategy to define properties of these pathogens under a variety of conditions including those that mimic the environments encountered during pathogenesis. These high-dimensional omics datasets are being integrated in selected ways to improve genome annotations, discover novel virulence-related factors, and model growth under infectious states. We will review the evolving technological approaches toward understanding complex microbial life through multi-omic measurements and integration, while highlighting some of our most recent successes in this area.",

author = "Charles Ansong and Deatherage, \{Brooke L.\} and Daniel Hyduke and Brian Schmidt and McDermott, \{Jason E.\} and Jones, \{Marcus B.\} and Sadhana Chauhan and Pep Charusanti and Kim, \{Young Mo\} and Nakayasu, \{Ernesto S.\} and Jie Li and Afshan Kidwai and George Niemann and Brown, \{Roslyn N.\} and Metz, \{Thomas O.\} and Kathleen McAteer and Fred Heffron and Peterson, \{Scott N.\} and Vladimir Motin and Palsson, \{Bernhard O.\} and Smith, \{Richard D.\} and Adkins, \{Joshua N.\}",

year = "2012",

doi = "10.1007/82-2012-247",

language = "English (US)",

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AU - Deatherage, Brooke L.

AU - Hyduke, Daniel

AU - Schmidt, Brian

AU - McDermott, Jason E.

AU - Jones, Marcus B.

AU - Chauhan, Sadhana

AU - Charusanti, Pep

AU - Kim, Young Mo

AU - Nakayasu, Ernesto S.

AU - Li, Jie

AU - Kidwai, Afshan

AU - Niemann, George

AU - Brown, Roslyn N.

AU - Metz, Thomas O.

AU - McAteer, Kathleen

AU - Heffron, Fred

AU - Peterson, Scott N.

AU - Motin, Vladimir

AU - Palsson, Bernhard O.

AU - Smith, Richard D.

AU - Adkins, Joshua N.

PY - 2012

Y1 - 2012

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AB - Salmonella and Yersinia are two distantly related genera containing species with wide host-range specificity and pathogenic capacity. The metabolic complexity of these organisms facilitates robust lifestyles both outside of and within animal hosts. Using a pathogen-centric systems biology approach, we are combining a multi-omics (transcriptomics, proteomics, metabolomics) strategy to define properties of these pathogens under a variety of conditions including those that mimic the environments encountered during pathogenesis. These high-dimensional omics datasets are being integrated in selected ways to improve genome annotations, discover novel virulence-related factors, and model growth under infectious states. We will review the evolving technological approaches toward understanding complex microbial life through multi-omic measurements and integration, while highlighting some of our most recent successes in this area.

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ER -

Studying salmonellae and yersiniae host-pathogen interactions using integrated 'omics and modeling

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