Early days: genomics and human responses to infection

Abstract

DNA microarray-based gene transcript-profiling of the responses of primates to infection has begun to yield new insights into host-pathogen interactions; this approach, however, remains plagued by challenges and complexities that have yet to be adequately addressed. The rapidly changing nature over time of acute infectious diseases in a host, and the genetic diversity of microbial pathogens present unique problems for the design and interpretation of functional-genomic studies in this field. In addition, there are the more common problems related to heterogeneity within clinical samples, the complex, non-standardized confounding variables associated with human subjects and the complexities posed by the analysis and validation of highly parallel data. Whereas various approaches have been developed to address each of these issues, there are significant limitations that remain to be overcome. The resolution of these problems should lead to a better understanding of the dialogue between the host and pathogen.

Figure 1

Number of published articles on gene expression profiling per year, by topic. The following search strategy was used in PubMed (http:/www.pubmed.com) to identify articles focused on host-pathogen interactions: (“Gene Expression Profiling” [MeSH] OR “Oligonucleotide Array Sequence Analysis” [MESH]) AND (“Parasitic Diseases” [MeSH] OR “Bacterial Infections and Mycoses” [MeSH] OR “Virus Diseases” [MeSH]). To identify similar articles discussing cancer-related gene expression patterns, the pathogen MeSH terms were replaced with “Neoplasms” [MeSH]. Abbreviation: MeSH, medical subject heading.

Figure 2

Factors to consider in microarray-based studies of the host response to infection. An overview of variables and points to consider when designing and performing microarray experiments. Abbreviations: ANOVA, analysis of variance; CART, classification and regression tree; MIAME, minimum information about a microarray experiment; PAM, predictive analysis of microarrays; qPCR, quantitative PCR; SAM, significance analysis of microarrays; SOM, self organizing map; SVD, singular value decomposition.