%0 Journal Article
%T Secretome: clues into pathogen infection and clinical applications
%A Shoba Ranganathan
%A Gagan Garg
%J Genome Medicine
%D 2009
%I BioMed Central
%R 10.1186/gm113
%X The secretome constitutes the entire set of secreted proteins, representing up to 30% of the proteome of an organism [1], and includes functionally diverse classes of molecules such as cytokines, chemokines, hormones, digestive enzymes, antibodies, extracellular proteinases, morphogens, toxins and antimicrobial peptides. Some of these proteins are involved in a host of diverse and vital biological processes, including cell adhesion, cell migration, cell-cell communication, differentiation, proliferation, morphogenesis, survival and defense, virulence factors in bacteria and immune responses [2]. Excretory/secretory proteins (ESPs) circulating throughout the body of an organism (for example, in the extracellular space) are localized to or released from the cell surface, making them readily accessible to drugs and/or the immune system. These characteristics make these molecules extremely attractive targets for novel vaccines and therapeutics, which are currently the focus of major drug discovery research programs [2-4]. In particular, proteins secreted by pathogens (bacterial, protozoan, fungal, viral or helminth) mediate interactions with the host, because these are present or active at the interface between the pathogen and the host cells, and can regulate or mediate the host responses and/or cause disease [5,6].A brief overview of the currently available methods for generating and analyzing pathogen secretome data is presented, followed by a critical analysis of their contribution to our understanding of pathogen infection and host responses, especially in comparison to other genome analysis approaches. Some early successes in the applications of secretome data in the areas of therapeutic target identification, diagnostic tools and pathogen control are also presented.Genome sequence analysis is based on transcript profiling and computational analysis. The computational prediction of secreted proteins seeks to identify the presence of signal peptides, which are cons
%U http://genomemedicine.com/content/1/11/113