GET THE APP

..

Journal of Computer Science & Systems Biology

ISSN: 0974-7230

Open Access

OMICS Techniques and Identification of Pathogen Virulence Genes Application to the Analysis of Respiratory Pathogens

Abstract

Sergio Hernández, Antonio Gómez, Juan Cedano and Enrique Querol

The advent of genomics should have facilitated the identification of microbial virulence factors, a key objective for vaccine design, especially for live attenuated vaccines. It is generally assumed than when the bacterial pathogen infects the host it expresses a set of genes, a number of them being virulence factors. However, up to now, although several Omics methods have been applied to identify virulence genes, i.e., DNA microarrays, In Vivo Expression Technology (IVET), Signature-Tagged Mutagenesis (STM), Differential Fluorescence Induction (DFI), etc., the results are quite meager. Among the genes identified by these techniques there are many related to cellular stress, basal metabolism, etc., which cannot be directly involved in virulence, or at least cannot be considered useful candidates to be deleted for designing a vaccine. Among the genes disclosed by these methodologies there are a number annotated as being hypothetical or unknown proteins. As these ORFs can hide some true virulence factors, we have selected all of these hypothetical proteins from several respiratory diseases and predicted their biological functions by a careful and in-depth analysis of each one. Although some of the re-annotations match with functions that can be related to microbial virulence, it can be concluded that identification of virulence factors remains elusive.

PDF

Share this article

Google Scholar citation report
Citations: 2279

Journal of Computer Science & Systems Biology received 2279 citations as per Google Scholar report

Journal of Computer Science & Systems Biology peer review process verified at publons

Indexed In

 
arrow_upward arrow_upward