High-throughput Gene Expression Profiling: Its Application in Studying Transfusion-Transmitted Infections

Volume 5 • Issue 1 • 2013 Since the discovery of the ABO blood groups, blood transfusion has been playing an important therapeutic role in clinical medicine. Similar to other therapeutic manipulations, blood transfusion always carries risks, which include transmitted infection threats and noninfectious hazards [1]. Microarray gene-expression profiling, a high throughput method that simultaneously examines gene expression changes at the transcript level has potential applications in screening for prognostic markers and in detecting multiple pathogens from a single sample. Previous studies demonstrated that gene expression profiling has shed light on unrecognized mechanisms of virus resistance that are deemed to be essential for the discovery of new drug targets.


Introduction of Gene Expression Profiling
Since the 1990s, DNA microarrays have been used to study various infections, to diagnose diseases, and to delineate the virus-host interactions. There are three main types of DNA microarrays: 1) in-situ synthesized arrays: microarrays on which the probes are synthesized in situ directly onto the surface of the chip; 2) spotted arrays on glass: independent synthesized probes are printed on special glass slides; 3) self-assembled arrays: synthesizing DNA on small polystyrene beads and depositing those beads on the end of a fiber-optic array [8].

Application of Gene Expression Profiling in Studying Transfusion-Transmitted Infections
Simultaneous detection of multiple transfusion transmitted pathogens DNA microarray allows simultaneous detection of different pathogens possible. Due to the outbreak of large-scale epidemics of arboviral diseases in recent years, there is a pressing need to improve the detection and molecular analysis in urgent clinical situations where the rapid identification and characterization of the pathogen is essential. For example, resequencing DNA microarray (RMA) technology is able to detect single nucleotide polymorphisms (SNPs) within the gene of interest to characterize emerging pathogens. Berthet et al. [9] used high density Pathogen ID v2.0 RMA (PID2-RMA) to successfully detect dengue, West Nile, and Chikungunya viruses in spiked blood samples or sera from individuals infected with dengue virus.

Delineating virus-host interactions to identify new antiviral drug targets and to develop prognostic tools
DNA microarray technology has enabled genome-wide analysis of gene expression changes from clinical tissues and animal models. Previous studies have already shed light on the molecular mechanism of viral resistance. Interferon-α is approved as one of the main therapeutic treatments for chronic hepatitis B virus (HBV) infection, but only a small number of patients achieve Sustained Virological Response (SVR). The molecular basis for interferon (IFN)-α-tolerance to is not clearly defined. Tsuge et al. [10] performed microarray analysis with human hepatocyte chimeric mouse livers to assess the direct impacts of HBV infection and IFN treatments on gene expression profiles. They were able to demonstrate that HBV infection attenuated the expression of IFN-stimulated genes (ISGs) under immune deficient condition, which suggests that HBV proteins are involved in viral escape mechanisms from innate and adaptive immunity.
More than 170 million people worldwide are chronically infected with HCV. Currently there is no vaccine and the most effective treatment is paginated IFN-α-combined with ribavirin and one of the direct acting antiviral (DAAs), which has morbid side effects, variable cure rates, and high costs [11]. Therefore it is necessary to understand molecular mechanisms of virus-host interactions and to predict treatment outcomes before initiating therapy. By comparing the pretreatment hepatic gene expression levels between treatment responders and non-responders of patients chronically infected with HCV, Chen et al. [12,13] identified 18 genes (out of 19,000 host genes or transcripts), whose differential expression levels are associated with treatment outcomes. More interestingly, they demonstrated that the cell-type specific protein expression of ISGs in a novel ubiquity *Corresponding author: Limin Chen, PhD, Toronto General Research Institute, University of Toronto, Canada, Tel: +86-28-61648530; E-mail: limin_chen_99@yahoo.com Page 2 of 2 in-like pathway (ISG 15/USP 18) correlated well with treatment outcomes, with prediction accuracy higher than that predicted by the polymorphism of IL28B [14,15]. Furthermore, they demonstrated that the pre-activation of the endogenous interferon signaling and the celltype differential expression of ISGs are not unique for HCV. Similar findings were identified in patients chronically infected with HBV [15,16]. Put all these together, this is an excellent example on how gene expression profiling can be used to delineate virus-host interactions in order to better understand the molecular mechanisms of viral resistance, leading to the identification of new drug targets [17].

Conclusion
Although gene expression profiling suffers from concentration restriction in virtue of linear signal merely over a limited range of concentrations in solution and its detection only being available for DNA or RNA based on complementary sequence on the array [18] it offers the advantage of being able to detect multiple pathogens in parallel in blood. Moreover, as a useful tool to delineate the virus-host interaction and virus resistance, gene expression profiling is likely to play an increasingly important role in the future development of drug discovery.