Bioinformatics Seminar: Computational Methods for the Design of Ultraspecific Signatures for Pathogen Identification

Speaker

Catherine Putonti
Associate Director of Bioinformatics Laboratory
Department of Computer Science
University of Houston

Abstract

Reliable detection and identification of pathogens in complex biological samples is a challenging diagnostic problem. Difficulties also arise due to the complications in finding a single, unique genomic sequence that is present simultaneously in all genomes of a pathogen species and absent in the genomes of the host and/or sample background. Although numerous nucleic acid-based tests have been developed for pathogen identification, especially PCR, the probability of false positives due to mispriming with the host and/or contaminating DNA remains a problem. A set of novel algorithms were recently developed that make it possible to rigorously compute all subsequences (n-mers) present in the genomic sequence of a target organism and absent from the host genome as well as absent from the host genome given any one, two, three, etc. base change mutations. Such subsequences are referred to as being "host-blind"(human-blind, mosquito-blind, mouse-blind, rat-blind, etc.) sequences. The greater the number of changes necessary to "convert" such a host-blind sequence to a sequence found in the host genome, the less likely the host-blind sequence, when used as a PCR primer and/or microarray probe, is to mispair with the host's genomic sequence. This new computational approach has lead to the creation of a new, more robust technology for pathogen identification.