Investigating Common Pathogenic Mechanisms between Homo sapiens and Different Strains of Candida albicans for Drug Design: Systems Biology Approach via Two-Sided NGS Data Identification
2019
Candida albicans (C. albicans) is the most prevalent fungal species. Although it is a healthy microbiota, genetic and epigenetic alterations in host and pathogen, and microenvironment changes would lead to thrush, vaginal yeast infection, and even hematogenously disseminated infection. Despite the fact that cytotoxicity is well-characterized, few studies discuss the genome-wide genetic and epigenetic molecular mechanisms between host and C. albicans. The aim of this study is to identify drug targets and design a multiple-molecule drug to prevent the infection from C. albicans. To investigate the common and specific pathogenic mechanisms in human oral epithelial OKF6/TERT-2 cells during the C. albicans infection in different strains, systems modeling and big databases mining were used to construct candidate host–pathogen genetic and epigenetic interspecies network (GEIN). System identification and system order detection are applied on two-sided next generation sequencing (NGS) data to build real host–pathogen cross-talk GEINs. Core host–pathogen cross-talk networks (HPCNs) are extracted by principal network projection (PNP) method. By comparing with core HPCNs in different strains of C. albicans, common pathogenic mechanisms were investigated and several drug targets were suggested as follows: orf19.5034 (YBP1) with the ability of anti-ROS; orf19.939 (NAM7), orf19.2087 (SAS2), orf19.1093 (FLO8) and orf19.1854 (HHF22) with high correlation to the hyphae growth and pathogen protein interaction; orf19.5585 (SAP5), orf19.5542 (SAP6) and orf19.4519 (SUV3) with the cause of biofilm formation. Eventually, five corresponding compounds—Tunicamycin, Terbinafine, Cerulenin, Tetracycline and Tetrandrine—with three known drugs could be considered as a potential multiple-molecule drug for therapeutic treatment of C. albicans.
Keywords:
- Correction
- Source
- Cite
- Save
- Machine Reading By IdeaReader
80
References
1
Citations
NaN
KQI