Analysis of Similarities and Differences between Disease-Causing Corynebacterium and Mycobacterium Organisms


Meeting Abstract

P2.36  Jan. 5  Analysis of Similarities and Differences between Disease-Causing Corynebacterium and Mycobacterium Organisms FADAEL, R*; SARKAR, N; BOLNET, C; DESALLE, R; Medgar Evers College; American Museum of Natural History; Medgar Evers College; American Museum of Natural History rudfada@yahoo.com

Corynebacterium diphteria, Mycobacterium tuberculosis, M. avium, and M. bovis, are widespread Gram-positive organisms that pose serious threats to human and non-human animal health as well as to the global economy. M. tuberculosis, M. bovis and M. avium infect and cause tuberculosis in human, cattle and other animals respectively. Although C. diphtheriae, M. tuberculosis, M. avium, and M. bovis are all gram-positive bacteria and share a lot of similarities, they also possess an array of differences. However, there is little information to describe the extent of their dissimilarities. Therefore, the goal of this project was investigate the level of similarity and the difference that exist among the 4 bacteria species. In this study, we organized information from a range of resources into a single resource. The aim of creating this resource is to ultimately put the knowledge into a form (i.e., a phylogenetic matrix) so that it can be used for studying the organisms using current tools. In an effort to do this, we used the available scientific literature (research articles, texts, and Medline) to collect information about their shape, size, and rate of growth, incubation period, and diagnosis period as well as the kind of treatments or antibiotics that can be used against them. These characteristics were then categorized into traditional MeSH key terms (used by the National Library of Medicine) and analyzed using the program Mesquite v. 1.05, a phylogenetic program that also performs non-phylogenetic analyses based on character data. In conclusion, we created a phylogenetic matrix that gathers the data in one resource and that can allow us to identify the level of differences and similarities between disease causing Mycobacterium and Corynebacterium organisms.

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