Research Interests:

The long-term goals in my laboratory include (1) the development of an integrated and iterative set of experimental and computational tools that can be used to understand and model gene regulatory networks/pathways in microbial systems; (2) the development of an integrated informatics framework for emerging and re-emerging infectious diseases; (3) the development and validation of a complete RNA motif prediction software package. Currently, my laboratory is focusing on the following three directions:

(1) Understanding iron assimilation pathways by integrating computational prediction and experimental validation. Iron is one of the essential nutritional elements for bacteria. Understanding iron uptake pathways may reveal the environmental adaptation for bacteria and even the pathogenesis mechanisms for some microbial pathogens. Previously, we defined the fur modulon in Shewanella oneidensis MR-1, a metal reducing bacterium with bioremediation potential, by integrating genome-wide expression analysis, proteome characterization, and regulatory motif discovery. We generated the hypotheses that fur would act as a positive regulator in S. oneidensis. My laboratory is now trying to further understand the detailed regulation mechanisms of fur as positive regulator in S. oneidensis by integrating computational studies and wet lab experiments, which includes both traditional biochemical techniques and the high throughput techniques such as microarray and proteomics. By comparative genomics and computational modeling, we hope to understand the siderophore-mediated iron assimilation pathway in S. oneidensis. My laboratory is also interested in the iron assimilation pathway in several other pathogenic bacteria.

(2) Understanding avian influenza viruses and their evolutional footprints. Influenza A is a negative strand RNA virus with 8 genomic fragments (HA, NA, PA, PB1, PB2, NP, NS, and M). Genetic shift and genetic drift has led to a rapid emergence of novel genotypes of avian influenza viruses during their evolution. However, there has not been available an efficient and effective approach to characterize genetic reassortments and other evolutional patterns between Influenza A viruses. I am very interested in developing and then applying new quantitative methods to define and identify the genetic reassortment and other evolutional patterns of influenza A viruses. Beyond this, by integrating wet laboratory experiments with computational modeling, my laboratory would begin to explore the connection between genotype, phenotype, and epidemiology, especially, in influenza A viruses. Currently, my laboratory focuses on the avian influenza viruses that cause human infection, such the H5N1 avian influenza virus. Recently, H3N2 avian influenza virus has been isolated in Turkey, thus it is one of my interests as well. My laboratory will be interested in other RNA viruses, such as coronavirus (e.g. SARS-CoV), HIV, and West Nile virus as well.

(3) Identification and functional analyses of RNA motifs. RNA structural motifs may function in various biological processes. For example, the hairpin-loop structure at the end of an mRNA can act as intrinsic terminators, which serves as an economic transcriptional termination machinery in bacteria. Many of conserved local secondary structures are also found in viral RNAs. Thus, predicting RNA structural motifs can shed some light on the biological mechanisms of viruses and may rapidly provide information for virus control and treatment, especially for emerging viral diseases. Previously, I have developed a software package Rnall for RNA local secondary structure prediction as well as the intrinsic terminator prediction. Currently, my laboratory focuses on the distribution and evolutional footprints of intrinsic terminator in prokaryotes. We will iteratively optimize the computational algorithms for intrinsic terminator prediction by experimental validation. My laboratory will also be interested in identifying and functionally characterizing other RNA motifs in genomic scale, such as riboswitch, various RNA motifs in viruses, RNAi, and splicing sites.

Selected Publications in Past Three Years:

• Wan, X.-F., X. Wu, G. Lin, S.B. Holton, R.A. Desmone, C.-R. Shyu, Y. Guan, and M. Emch. Computational Identification of reassortments in avian influenza viruses. Avian Diseases, in press.
• Song, Z., L. Chen, A. Ganapathy, X.-F. Wan, N. Tao, D. Emerich, G. Stacey, and D. Xu. Development and assessment of scoring functions for protein identification using peptide mass fingerprinting data. Electrophoresis, in press.
• Wan, X.-F. and D.K. Thompson. High-throughput technologies and functional genomics. In Systems biology and synthetic biology, Fu ed. John Wiley & Son, Inc., in press.
• Wan, X.-F., G. Lin, and D. Xu. Rnall: An efficient algorithm for predicting RNA local secondary structural landscape in genomes. Journal of Bioinformatics and Computational Biology in press.
• Clark, M.E., Q. He, Z. He, K.H. Huang, E.J. Alm, X.-F. Wan, T.C. Hazen, A.P. Arkin, J.D. Wall, J. Zhou, and M.W. Fields. 2006. Temporal transcriptomic analysis of Desulfovibrio vulgaris Hildenborough transition into stationary phase growth during electron donor depletion. Applied Environmental Microbiology, 72:5578-5588.
• Wu, X., R.G. Goebel, X.-F. Wan and G. Lin. 2006. Weighted Composition Distance for HIV Genotyping. In Proceedings of the 2006 Computational Systems Bioinformatics Conference. Stanford, California, 14-18 August 2006. Pages 179-190.
• Wu, X., X.-F. Wan, G. Wu, D. Xu, and G. Lin. Phylogenetic analysis using complete signature information of whole genomes and clustered neighbor-joining method. International Journal of Bioinformatics Research and Applications, 2:219-248.
• Shababi, M., J. Bourque, P. Karuppaiah, A. Cole, D. Xu, X.-F. Wan, and J. Schoelz. The ribosomal shunt translation strategy of Cauliflower mosaic virus has evolved from ancient long terminal repeats. Journal of Virology, 80:3811-3822.
• Wan, X.-F., J. Zhou, and D. Xu. 2006. CodonO: a new informatics method measuring synonymous codon usage bias. International Journal of General Systems, 35:109-125.
• Leaphart, A.B., D.K. Thompson, K. Huang, E. Alm, X.-F. Wan, A. Arkin, S.D. Brown, L. Wu, and J. Zhou. 2006. Transcriptome analysis of Shewanella oneidensis gene expression in response to acidic and alkaline pH stress. Journal of Bacteriology, 188:1633-1642.
• Wan, X.-F. and D. Xu. 2005. Computational detection of remote homology. Current Protein and Peptide Science, 6:527-546.
• Chung, W. H., S. K. Rhee, X.-F. Wan, J.-W. Bae, Z.-X. Quan, and Y.-H. Park. 2005. Design of long oligonucleotide probe for detection of functional gene in microbial community, Bioinformatics, 21:4092-4100.
• Wan, X.-F., D. Ataman, and D. Xu. 2005. Application of computational biology in understanding emerging infectious diseases: inferring the biological function for S-M complex of SARS-CoV. In Progress in Bioinformatics, pp. 55-80, Nova Publisher, Inc.
• Xu, D., O. Duzlevski, and X.-F. Wan. 2005. In search of remote homolog. In Handbook of Computational Molecular Biology, edited by Aluru, Chapter 33, pp. 1-27, CRC Press.
• Wan, X.-F. and D. Xu. 2005. Intrinsic terminator prediction and its application in Synechococcus sp. WH8102. Journal of Computer Science and Technology, 20:465-482.
• Wan, X.-F., T. Ren, K.-J. Luo, M. Liao, G.-H. Zhang, J.-D. Chen, W.-S. Cao, Y. Li, N.-Y. Jin, D. Xu, and C.A. Xin. 2005. Genetic Characterization of H5N1 avian influenza viruses isolated in Southern China during the 2003-04 avian influenzapandemic. Archives of Virology, 150:1257-1266.
• Wan, X.-F., N.C. VerBerkmoes, L.A. McCue, D. Stanek, H. Connelly, L. Wu, X. Liu, T. Yan, A. Leaphart, R.L. Hettich, J. Zhou, and D.K. Thompson. 2004. Transcriptomic and proteomic characterization of the fur modulon in the metal-reducing bacterium Shewanella oneidensis. Journal of Bacteriology, 186:8385-8400.
• Ganapathy, A., X.-F. Wan, B.D. Gue, J. Wan, J. Thelen, D.W. Emerich, G. Stacey and D. Xu. 2004. Statistical assessment for Mass-spec protein identification using peptide fingerprinting approach. In Proceedings of the 26th Annual International Conference IEEE Engineering in Medicine and Biology Society (EMBS'04). Bioinformatics and Computational Biology, San Francisco, CA, pp. 3051-3054.
• Rhee, S.K., X. Liu, L. Su, S.C. Chong, X. Wan, and J. Zhou. 2004. Detection of Biodegradation and biotransformation genes in microbial communities using 50-mer oligonucleotide microarrays. Applied and Environmental Microbiology, 70:4303-4317.
• Wan, X.-F., S. M. Bridges, and J.A. Boyle. 2004. Revealing different transcription initiation and translation initiation patterns in archaea using an interactive clustering model. Extremophiles, 8:291-299.
• Wan, X.-F., D. Xu, A. Kleinhofs, and J. Zhou. 2004. Quantitative relationship between codon usage bias and GC composition across the unicellular genomes. BMC Evolutionary Biology, 4:19 (http://www.biomedcentral.com/1471-2148/4/19/).
• Wan, X., S.L. Branton, L.A. Hanson, and G.T. Pharr. 2004. Identification and initial characterization of an aminopeptidase gene in M. gallinarum. Current Microbiology, 48:32-38.
• Wan, X., S.L. Branton, M.B. Hughlett, L.A. Hanson, and G.T. Pharr. 2004. Expression and subcellular location of a leucine aminopeptidase of Mycoplasma gallinarum. International Journal of Poultry Science 3(1):70-74.

Faculty: Wan Department of Microbiology/Miami University (Ohio USA) This document was last modified on:      Wednesday, October 04, 2006 at 09:48:47 Mail questions and comments to Henry Wan. [WanX@MUOhio.edu]