Infectomics: Study of Microbial Infections Using Omic Approaches

Abstract

Infectomics is the study of infectomes, which are encoded by both host and microbial genomes, and mirror the interplay between pathogens and their hosts. There are three major types of infectomic approaches for dissecting of microbial infections: ecological infectomics, immunoinfectomics and chemical infectomics. The most challenging issue in infectomics is how to dissect the dynamic duality relationship between symbiosis and pathogenesis in microbial infections, and to predict and to mitigate infectious diseases.

Keywords: infectomics; microbiome; symbiosis; pathogenesis; ecology; dynamic duality relationship (DDR)

Figure 1.

Development cycle of integrated models using immunoinfectomic approaches for vaccine and drug discovery. Integrated models consist of three important components: (1) genotypic and phenotypic selection of antigens using infectomic approaches; (2) mapping of B‐cell and T‐cell epitopes by a combination of prediction algorithms and high throughput technologies and (3) confirmation of the immunogenicity of these epitopes can be carried out in vitro (B‐cell assays and T‐cell assays) and in vivo (transgenic mice). Models are iteratively tested and improved by comparison of predictions with holistic level responses measured experimentally through a combination of traditional assays and high throughput approaches.

Figure 2.

Dynamic changes in adhesion, growth and infectomes of Neisseria meningitidis serogroup B (MenB) during bacteria adhering to epithelial cells: (a) adhering bacteria (squares) were counted after washing and lysis of the host cells (triangles, bacteria freely growing in the medium; circles, growth of cell‐associated bacteria); (b), (c) RNA was isolated at different times from both adhering and freely growing bacteria, and used to probe DNA chips carrying the entire MenB genome: (b) clustered expression profiles of genes whose regulation differs from freely growing bacteria by at least 2‐fold, (c) regulated genes in (b) were further analysed according to activation state (light grey, upregulated; dark grey, downregulated) to give a visual indication of the persistence of gene regulation. Grey scale represents n‐fold difference. cfu: colony‐forming units. (Reproduced by courtesy of G. Grandi from Grifantini R et al. () Previously unrecognized vaccine candidates against group B meningococcus identified by DNA microarrays. Nature Biotechnology20(9): 914–921).

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References

Baldi P and Brunak S (eds) (2001) Bioinformatics: The Machine Learning Approach, 2nd edn, pp. 299–321. Cambridge, MA: MIT Press.

Bianchi ME (2007) DAMPs, PAMPs and alarmins: all we need to know about danger. Journal of Leukocyte Biology 81(1): 1–5.

Björkholm B, Lundin A, Sillen A et al. (2001) Comparison of genetic divergence and fitness between two subclones of Helicobacter pylori. Infection and Immunity 69(12): 7832–7838.

Cummings CA and Relman DA (2000) Using DNA microarrays to study host–microbe interactions. Emerging Infectious Diseases 6(5): 513–525.

Davies MN, Guan PP, Blythe MJ et al. (2007) Using databases and data mining in vaccinology. Expert Opinion on Drug Discovery 2(1): 19–35.

De Groot AS (2006) Immunomics: discovering new targets for vaccines and therapeutics. Drug Discovery Today 11(5–6): 203–209.

Fauci AS (2001) Infectious diseases: considerations for the twenty‐first century. Clinical Infectious Diseases 32(5): 675–685.

Grifantini R, Bartolini E, Muzzi A et al. (2002) Previously unrecognized vaccine candidates against group B meningococcus identified by DNA microarrays. Nature Biotechnology 20(9): 914–921.

Hall SE (2006) Chemoproteomics‐driven drug discovery: addressing high attrition rates. Drug Discovery Today 11: 495–502.

Harris CJ and Stevens AP (2006) Chemogenomics: structuring the drug discovery process to gene families. Drug Discovery Today 11(19/20): 880–888.

Huang SH, Triche T and Jong AY (2002) Infectomics: genomics and proteomics of microbial infections. Functional and Integrative Genomics 1(6): 331–344.

Huang SH, Jong AY and Warburton D (2004) Infectomics in the discovery and development of new antimicrobial agents. Current Medicinal Chemistry‐Anti‐Infective Agents 3(1): 57–67.

Lederberg J (2000) Infectious history. Science 288(5464): 287–293.

Ley RE, Peterson DA and Gordon JI (2006) Ecological and evolutionary forces shaping microbial diversity in the human intestine. Cell 124(4): 837–848.

Ley RE, Knight R and Gordon JI (2007) The human microbiome: eliminating the biomedical/environmental dichotomy in microbial ecology. Environmental Microbiology 9(1): 3–4.

Long CJ, Qi H and Huang SH (2007) A dynamic model for hepatitis B virus infection. Journal of Systemics, Cybernetics and Informatics 5(1): 1–5.

Mason K, Patel NM, Ledel A, Moallemi CC and Wintner EA (2004) Mapping protein pockets through their potential small‐molecule binding volumes: QSCD applied to biological protein structures. Journal of Computer Aided Molecular Design 18(1): 55–70.

Pompe S, Simon J, Wiedemann PM and Tannert C (2005) Future trends and challenges in pathogenomics. A foresight study. EMBO Rep 6(7): 600–605.

Relman DA (2002) New technologies, human‐microbe interactions, and the search for previously unrecognized pathogens. Journal of Infectious Diseases 186 (suppl. 2): S254–S258.

Sette A, Fleri W, Peters B et al. (2005) A roadmap for the immunomics of category A‐C pathogens. Immunity 22(2): 155–161.

Shmulevich I, Dougherty ER, Kim S and Zhang W (2002) Probabilistic Boolean networks: a rule‐based uncertainty model for gene regulatory networks. Bioinformatics 18(2): 261–274.

Sieber SA and Cravatt BF (2006) Analytical platforms for activity‐based protein profiling–exploiting the versatility of chemistry for functional proteomics. Chemical Communications (Camb) 22: 2311–2319.

Van den Driessche M and Veereman‐Wauters G (2002) Functional foods in pediatrics. Acta Gastroenterologica Belgica 65(1): 45–51.

Wang D, Liu S, Trummer BJ, Deng C and Wang A (2002) Carbohydrate microarrays for the recognition of cross‐reactive molecular markers of microbes and host cells. Nature Biotechnology 20(3): 275–281.

Wang D, Carroll GT, Turro NJ et al. (2007) Photogenerated glycan arrays identify immunogenic sugar moieties of Bacillus anthracis exosporium. Proteomics 7(2): 180–184.

Wilks M (2007) Bacteria and early human development. Early Human Development 83(3): 165–170.

Further Reading

Casadevall A and Pirofski LA (2000) Host–pathogen interactions: basic concepts of microbial commensalism, colonization, infection, and disease. Infection and Immunity 68(12): 6511–6518.

Chen T (2006) DNA microarrays – an armory for combating infectious diseases in the new century. Infectious Disorders – Drug Targets 6(3): 263–279.

Hooper LV and Gordon JI (2001) Commensal host–bacterial relationships in the gut. Science 292: 1115–1118.

Joyce EA, Chan K, Salama NR and FalKow S (2002) Redefining bacterial populations: a post‐genomic reformation. Nature Reviews Genetics 3(6): 462–473.

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Huang, Sheng‐He, Li, Bai‐Lian, and Cao, Hong(Sep 2007) Infectomics: Study of Microbial Infections Using Omic Approaches. In: eLS. John Wiley & Sons Ltd, Chichester. http://www.els.net [doi: 10.1002/9780470015902.a0005949.pub2]