Ph.D. 2006, University of Houston
The areas of my current research are computational biology and microbial evolution. Specifically, I have concentrated my scientific interests to the three areas below.
1. Pathogen-Host Coevolution. Sequence similarity, e.g. codon usage, between small viruses and their hosts has been observed for a wide variety of species. Recently we began exploring the correspondence between pathogen-host sequence similarity and pathogen virulence experimentally using the bacteriophage phi X174 and its host Escherichia coli C. By engineering phages such that unfavorable sequence compositions (with respect to the host species) are utilized, we can observe the phage’s changes in virulence.
2. Designing Assays for Pathogen Detection. In recent years, the majority of new pathogen identification and diagnosis assays have used nucleic acid-based technologies. Designing such assays is computationally challenging. A set of novel algorithms and data structures have been developed which make it possible to efficiently calculate the distance or the number of base changes necessary to “convert” the signature to the closest sequence found in the host/background genome where all possible base changes and combinations of base changes are considered. Using this new suite of tools, ultraspecific primers/probes have been designed for the identification of several different viral and bacterial pathogenic organisms.
3. Identifying Genomic Regions of Unusual Compositional Properties. Analysis of the distribution of the frequencies of appearance of short subsequences provides a powerful tool in comparing genomic sequences. While this analysis has traditionally been applied exclusively to bacterial genomes, we have several projects underway that apply this alignment-free approach to the genomes of larger eukaryotic organisms as a means of examining the evolution of species at the chromosomal and whole genomic level.
Further information about our laboratory can be found at our lab’s site: http://sites.google.com/site/putonti/
Feng, C.*, Putonti, C.*, Zhang, M., Eggers, R., Mitra, R., Hogan, M., Jayaraman, K., Fofanov, Y. Ultraspecific probes for high throughput HLA typing. BMC Genomics, 2009, 10:85. (*co-first authors)
Alcaraz, L.D., Olmedo, G., Bonilla, G., Cerritos, R., Hernández, G., Cruz, A., Ramírez, E., Putonti, C., Jiménez, B., Martínez, E., López, V. Arvizu, J.L., Ayala, F., Razo, F., Caballero, J., Siefert, J., Eguiarte, L., Vielle, J.-P., Martínez, O., Souza, V., Herrera-Estrella, A., Herrera-Estrella, L. Adaptation of a bacterial genome to a relic marine environment. Proc. Natl. Acad. Sci. USA, 2008,105(15): 5803-5808.)
Añez, M., Putonti, C., Fox, G.E., Fofanov, Y., Willson, R.C. Exhaustive Computational Identification of Pathogen Sequences Distant from Background Genomes: Identification of Human-blind Dengue PCR Primers. J. Biotechnol. 2007; 133(3): 267-276.)
Putonti, C., Luo, Y., Katili, C., Chumakov, S., Fox, G.E., Graur, D., Fofanov, Y. A computational tool for the genomic identification of regions of unusual compositional properties and its utilization in the detection of horizontally transferred sequences. Mol Biol Evol. 2006; 23(10): 1863-1868.)
Putonti, C., Chumakov, S., Mitra, R., Fox, G.E., Willson, R.C., Fofanov, Y. Human-blind probes and primers for Dengue virus identification: Exhaustive analysis of subsequences present in the human and 83 Dengue genome sequences. FEBS J. 2006; 273(2): 398-408.
Fig. Using computationally identified “ultraspecific” signatures as, for instance PCR primers, it is possible to detect the presence of pathogenic organisms in complex samples. (Photo by: Dr. Jerome Crowder)