Washington, May 19 : A scientist from the Department of Biomedical Engineering at the University of Virginia Health System has unravelled the metabolic properties of two deadly pathogens, Leishmania major and Pseudomonas aeruginosa.
Using network analysis methods for investigation, Jason Papin, Ph.D., principle investigator in the Computational Systems Laboratory at UVA, discovered how the two pathogens survive and also found out the genes, which when knocked out, cause them to weaken.
Leishmania major causes Leishmaniasis, a disease caused by the bite of sand flies and currently affects US soldiers fighting in Iraq. On the other hand, Pseudomonas aeruginosa is an opportunistic pathogen that mainly affects immunocompromised patients and facilitates 10 percent of hospital acquired infections. Pseudomonas is matter of concern due to its resistance to nearly all available antibiotics.
"By discovering the metabolic properties of these pathogens we can figure out how they grow and live. Once broken down, a variety of gene sequences can be deleted in silico to see if it will halt the progress of the pathogen. This could lead to new drugs or vaccines for the treatment and prevention of their effects," said Papin.
Recently, he used some computer-based methods to predict the essentiality of metabolic genes in Pseudomonas, a study that would have taken years in a traditional laboratory.
And now, Papin can run all possible gene combinations from the metabolism of a pathogen using a computer in matter of a few minutes. Amongst thousands of possibilities, the computer finds the most probable combinations necessary to sustain the life of the pathogen. These discoveries can lead to new and better therapies that target the life-sustaining forces of these two pathogens.
"Systems analysis has become a requirement for making sense of high-throughput data and for characterizing properties of biological networks. In order to extend these recent developments to medical applications, there is a pressing need for reconstructing and analyzing the networks that direct cellular processes," said Papin.
He also found that the metabolic network of Leishmania major contains many genes across multiple metabolic processes critical to the general function of the pathogen.
And in case of Pseudomonas aeruginosa pathogen, Papin is currently comparing network-generated data about the metabolic network using existing genome data in order to have a better understanding of the genetic and environmental relationships in this versatile pathogen.
"Scientists who work in drug development need to know what to target in order to make better drugs. Through network analysis, we can get them this information faster than we could just ten years ago," said Papin.