Cryptococcus neoformans is pathogenic yeast, responsible for highly lethal infections in compromised patients around the globe. C. neoformans typically initiates infections in mammalian lung tissue and subsequently disseminates to the central nervous system where it causes significant pathologies. Virulence genes of C. neoformans are being characterized at an increasing rate, however, we are far from a comprehensive understanding of their roles and genetic interactions. Some of these reported virulence genes are scattered throughout different databases, while others are not yet included. This study gathered and analyzed 150 reported virulence associated factors (VAFs) of C. neoformans. Using the web resource STRING database, our study identified different interactions between the total VAFs and those involved specifically in lung and brain infections and identified a new strain specific virulence gene, SHO1, involved in the mitogen-activated protein kinase signaling pathway. As predicted by our analysis, SHO1 expression enhanced C. neoformans virulence in a mouse model of pulmonary infection, contributing to enhanced non-protective immune Th2 bias and progressively enhancing fungal growth in the infected lungs. Sequence analysis indicated 77.4% (116) of total studied VAFs are soluble proteins, and 22.7% (34) are transmembrane proteins. Motifs involved in regulation and signaling such as protein kinases and transcription factors are highly enriched in Cryptococcus VAFs. Altogether, this study represents a pioneering effort in analysis of the virulence composite network of C. neoformans using a systems biology approach.
|Journal||Frontiers in Microbiology|
|Publication status||Published - 2016 Oct 27|
Bibliographical noteFunding Information:
These studies were supported by BLR&D Merit Review grants from the Department of Veterans' Affairs BXI01BX000656-05A1 (MO) and 1I01CX000911-01A2 (YH). These studies were partly supported by National Research Foundation of Korea grants (2015R1A2A1A15055687) from MEST, the Strategic Initiative for Microbiomes in Agriculture and Food funded by Ministry of Agriculture, Food and Rural Affairs (916006-2). MY was supported by USAID Egypt grant for international scholars. The authors wish to acknowledge help of Drs. Jintao Xu, Zhenzong Fa, and Xueli Gao in experimental efforts and analysis of data from the infection model.
© 2016 Malachowski, Yosri, Park, Bahn, He and Olszewski.
All Science Journal Classification (ASJC) codes
- Microbiology (medical)