Computational approaches for discovery of common immunomodulators in fungal infections: towards broad-spectrum immunotherapeutic interventions

BMC Microbiology

Research Article

T M Murali¹  Yared H Kidane²  Christopher Lawrence³ 

[1] Department of Computer Science, Virginia Tech, 24061, Blacksburg, VA, USA;ICTAS Center for Systems Biology of Engineered Tissues, Virginia Tech, 24061, Blacksburg, VA, USA;Genetics, Bioinformatics, and Computational Biology PhD Program, Virginia Tech, 24061, Blacksburg, VA, USA;Universities Space Research Association, 77058, Houston, TX, USA;Virginia Bioinformatics Institute, Virginia Tech, 24061, Blacksburg, VA, USA;Department of Biology, Virginia Tech, 24061, Blacksburg, VA, USA;

关键词: Host-oriented therapy;    Broad-spectrum target;    Immunomodulation;    Drug-resistance;    Drug-target discovery;    Immunotherapy;   

DOI  :  10.1186/1471-2180-13-224

 received in 2013-02-27, accepted in 2013-09-17,  发布年份 2013

来源: Springer

【 摘 要 】

BackgroundFungi are the second most abundant type of human pathogens. Invasive fungal pathogens are leading causes of life-threatening infections in clinical settings. Toxicity to the host and drug-resistance are two major deleterious issues associated with existing antifungal agents. Increasing a host’s tolerance and/or immunity to fungal pathogens has potential to alleviate these problems. A host’s tolerance may be improved by modulating the immune system such that it responds more rapidly and robustly in all facets, ranging from the recognition of pathogens to their clearance from the host. An understanding of biological processes and genes that are perturbed during attempted fungal exposure, colonization, and/or invasion will help guide the identification of endogenous immunomodulators and/or small molecules that activate host-immune responses such as specialized adjuvants.ResultsIn this study, we present computational techniques and approaches using publicly available transcriptional data sets, to predict immunomodulators that may act against multiple fungal pathogens. Our study analyzed data sets derived from host cells exposed to five fungal pathogens, namely, Alternaria alternata, Aspergillus fumigatus, Candida albicans, Pneumocystis jirovecii, and Stachybotrys chartarum. We observed statistically significant associations between host responses to A. fumigatus and C. albicans. Our analysis identified biological processes that were consistently perturbed by these two pathogens. These processes contained both immune response-inducing genes such as MALT1, SERPINE1, ICAM1, and IL8, and immune response-repressing genes such as DUSP8, DUSP6, and SPRED2. We hypothesize that these genes belong to a pool of common immunomodulators that can potentially be activated or suppressed (agonized or antagonized) in order to render the host more tolerant to infections caused by A. fumigatus and C. albicans.ConclusionsOur computational approaches and methodologies described here can now be applied to newly generated or expanded data sets for further elucidation of additional drug targets. Moreover, identified immunomodulators may be used to generate experimentally testable hypotheses that could help in the discovery of broad-spectrum immunotherapeutic interventions. All of our results are available at the following supplementary website: http://bioinformatics.cs.vt.edu/~murali/supplements/2013-kidane-bmc

【 授权许可】

Unknown   
© Kidane et al.; licensee BioMed Central Ltd. 2013. This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.