A Flucytosine-Responsive Mbp1/Swi4-Like Protein, Mbs1, Plays Pleiotropic Roles in Antifungal Drug Resistance, Stress Response, and Virulence of Cryptococcus neoformans

Song, Min; Lee, Jang-Won; Kim, Min Su; Yoon, Ja Kyung; White, Theodore C.; Floyd, Anna; Heitman, Joseph; Strain, Anna K.; Nielsen, Judith N.; Nielsen, Kirsten; Bahn, Yong-Sun

doi:10.1128/ec.05236-11

Cited by 41 publications

(42 citation statements)

References 59 publications

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“…The Mbs1 transcription factor is repressed by Hog1, and mbs1⌬ mutants have a minor defect in encapsulation (188). These data imply that Hog1 represses capsule under normal conditions by repressing the Mbs1 activator of encapsulation.…”

Section: Stressmentioning

confidence: 77%

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The Cryptococcus neoformans Capsule: a Sword and a Shield

2012

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SUMMARY The human fungal pathogen Cryptococcus neoformans is characterized by its ability to induce a distinct polysaccharide capsule in response to a number of host-specific environmental stimuli. The induction of capsule is a complex biological process encompassing regulation at multiple steps, including the biosynthesis, transport, and maintenance of the polysaccharide at the cell surface. By precisely regulating the composition of its cell surface and secreted polysaccharides, C. neoformans has developed intricate ways to establish chronic infection and dormancy in the human host. The plasticity of the capsule structure in response to various host conditions also underscores the complex relationship between host and parasite. Much of this precise regulation of capsule is achieved through the transcriptional responses of multiple conserved signaling pathways that have been coopted to regulate this C. neoformans -specific virulence-associated phenotype. This review focuses on specific host stimuli that trigger the activation of the signal transduction cascades and on the downstream transcriptional responses that are required for robust encapsulation around the cell.

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Section: Stressmentioning

confidence: 77%

“…Mbs1 is required for titan cell formation, but the impact of the upstream regulators of Mbs1 on titan cell formation has not been investigated (188). cdc420⌬ and gap1⌬ mutants have defects in titan cell formation, and the Cnc1560, Pcl103, and Rho104 proteins act to repress titan cell formation (153,226).…”

Section: Titan Cells-a Special Casementioning

confidence: 99%

The Cryptococcus neoformans Capsule: a Sword and a Shield

2012

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“…Only 11 of the 27 had been previously reported to influence capsule thickness. (The phenotype of cells lacking MBS1, which we studied because of its PhenoProphet score, was reported while our analysis was in progress [Song et al 2012]. ) Figure 3A shows the altered capsule thicknesses of 17 mutants lacking TF-encoding genes that we selected based only on expression data, analyzed by either capsule size correlation or PhenoProphet.…”

Section: Expression-based Network Mapping Predicts Tfs Involved In Camentioning

confidence: 99%

Model-driven mapping of transcriptional networks reveals the circuitry and dynamics of virulence regulation

et al. 2015

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Key steps in understanding a biological process include identifying genes that are involved and determining how they are regulated. We developed a novel method for identifying transcription factors (TFs) involved in a specific process and used it to map regulation of the key virulence factor of a deadly fungus-its capsule. The map, built from expression profiles of 41 TF mutants, includes 20 TFs not previously known to regulate virulence attributes. It also reveals a hierarchy comprising executive, midlevel, and "foreman" TFs. When grouped by temporal expression pattern, these TFs explain much of the transcriptional dynamics of capsule induction. Phenotypic analysis of TF deletion mutants revealed complex relationships among virulence factors and virulence in mice. These resources and analyses provide the first integrated, systems-level view of capsule regulation and biosynthesis. Our methods dramatically improve the efficiency with which transcriptional networks can be analyzed, making genomic approaches accessible to laboratories focused on specific physiological processes.[Supplemental material is available for this article.]In this paper we present an efficient means of comprehensively mapping the network of transcription factors (TFs) that regulate a particular physiological process. Our approach cycles through deletion of TFs, expression profiling of TF mutants, model construction, and model-directed selection of TFs for the next round of deletion. This predictive genetics approach identifies TFs that affect the process of interest, providing a valuable complement to undirected mutagenesis and screening. Simultaneously, it builds a network model that explains how the TFs affect the process, yielding novel insights into the biological system under study.Mapping the network that regulates a specific process requires knowing which TFs affect that process. One way to identify such TFs is to screen comprehensive mutant libraries, but generating such libraries is not always feasible. Furthermore, genome-scale screening assays must be fast and scalable; such assays may not exist for the process of interest or may be less sensitive than other, more laborious assays. An alternative approach is to map the targets of all TFs encoded in a genome by using methods such as chromatin-immunoprecipitation (ChIP) or large-scale TF deletion and expression analysis. However, undirected, genome-wide approaches are costly and inefficient for probing a specific biological process in detail. We report a model-guided approach that addresses all of these problems by focusing experimental effort on the TFs most likely to be involved in the process of interest. Furthermore, our approach generates a network that provides mechanistic explanations for the phenotypes of TF deletion mutants.Our approach alternates network building by using an algorithm we call NetProphet with identifying relevant TFs by using an algorithm we call PhenoProphet. NetProphet is a validated method for mapping direct, functional regulation that significantly out...

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“…The HOG pathway modulates susceptibility to multiple classes of antifungal agents: (i) the HOG pathway promotes susceptibility to a member of the phenylpyrrole class of fungicide, fludioxonil, by triggering intracellular glycerol synthesis and cell swelling in C. neoformans (34); (ii) the HOG pathway affects azole and polyene drug susceptibility by repressing the expression of ERG11 (15); and (iii) the HOG pathway is involved in flucytosine susceptibility (36). Therefore, we next investigated the effects of changes in the negative regulation of the HOG pathway by PTP2 on antifungal drug susceptibility.…”

Section: Fig 4 the Balanced Regulation Of The Hog Pathway Is Criticalmentioning

confidence: 99%

Distinct and Redundant Roles of Protein Tyrosine Phosphatases Ptp1 and Ptp2 in Governing the Differentiation and Pathogenicity of Cryptococcus neoformans

et al. 2014

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bProtein tyrosine phosphatases (PTPs) serve as key negative-feedback regulators of mitogen-activated protein kinase (MAPK) signaling cascades. However, their roles and regulatory mechanisms in human fungal pathogens remain elusive. In this study, we characterized the functions of two PTPs, Ptp1 and Ptp2, in Cryptococcus neoformans, which causes fatal meningoencephalitis. PTP1 and PTP2 were found to be stress-inducible genes, which were controlled by the MAPK Hog1 and the transcription factor Atf1. Ptp2 suppressed the hyperphosphorylation of Hog1 and was involved in mediating vegetative growth, sexual differentiation, stress responses, antifungal drug resistance, and virulence factor regulation through the negative-feedback loop of the HOG pathway. In contrast, Ptp1 was not essential for Hog1 regulation, despite its Hog1-dependent induction. However, in the absence of Ptp2, Ptp1 served as a complementary PTP to control some stress responses. In differentiation, Ptp1 acted as a negative regulator, but in a Hog1-and Cpk1-independent manner. Additionally, Ptp1 and Ptp2 localized to the cytosol but were enriched in the nucleus during the stress response, affecting the transient nuclear localization of Hog1. Finally, Ptp1 and Ptp2 played minor and major roles, respectively, in the virulence of C. neoformans. Taken together, our data suggested that PTPs could be exploited as novel antifungal targets.

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A Flucytosine-Responsive Mbp1/Swi4-Like Protein, Mbs1, Plays Pleiotropic Roles in Antifungal Drug Resistance, Stress Response, and Virulence of Cryptococcus neoformans

Cited by 41 publications

References 59 publications

The Cryptococcus neoformans Capsule: a Sword and a Shield

The Cryptococcus neoformans Capsule: a Sword and a Shield

Model-driven mapping of transcriptional networks reveals the circuitry and dynamics of virulence regulation

Distinct and Redundant Roles of Protein Tyrosine Phosphatases Ptp1 and Ptp2 in Governing the Differentiation and Pathogenicity of Cryptococcus neoformans

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