Perspective Computational Resources in Infectious Disease: Limitations and Challenges

Infectious diseases continue to be a major cause of death in the human population, with tuberculosis and malaria affecting 500 million people and causing 1–2 million deaths annually [1]. The situation is aggravated by the increasing prevalence of antibiotic-resistant bacteria and the risk that terrorists might use infectious organisms to aggress target populations. During the past decade, we have also witnessed the emergence of many new pathogens not previously de-tected in humans, such as the avian influenza virus, severe acute respiratory syndrome (SARS), and Ebola. The ap-pearance of these novel agents and the reemergence of previously eradicated pathogens may be associated with the growing human population, flooding, and other environmental perturbations; global travel and migration; and animal trade and domestic animal husbandry practices. Simultaneously, we have seen an explosion of genome sequence data. Sequencing is now the method of choice for character-ization of new disease agents, as exempli-fied by the rapid sequencing of the genome of the SARS virus, which was made available within a month of identi-fication of the virus [2,3]. Like SARS, most newly emerging disease agents orig-inate in animals and have been transmit-ted to humans recently at food markets, by insect bites, or through hunting [1]. The new sequencing technologies enable small academic research groups to create huge genome datasets at low cost. As a result, scientists with expertise in other fields of research, such as clinical microbi-ology and ecology, are just beginning to face the challenge of handling, comparing, and extracting useful information from millions of sequences. Here, we discuss the limitations of publicly available resourc-es in the field of genomics of emerging bacterial pathogens, emphasizing areas where increased efforts in computational biology are urgently needed