Mathematical modeling of pathogenicity of Cryptococcus neoformans

• Published in: Molecular systems biology Vol. 4; no. 1; pp. 183 - n/a
• Main Authors: Garcia, Jacqueline, Shea, John, Alvarez‐Vasquez, Fernando, Qureshi, Asfia, Luberto, Chiara, Voit, Eberhard O, Del Poeta, Maurizio
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 2008; John Wiley & Sons, Ltd; EMBO Press; Nature Publishing Group; Springer Nature
• Subjects: Adaptation; Biochemical Systems Theory; Cell cycle; ceramide; Ceramides - metabolism; Computational Biology - methods; Computer applications; Computer simulation; Cryptococcus neoformans; Cryptococcus neoformans - metabolism; Cryptococcus neoformans - pathogenicity; Cytoplasm - metabolism; EMBO21; EMBO23; Endoplasmic Reticulum - metabolism; Enzymes; Fluxes; Fungal infections; Fungi; Gene expression; Golgi Apparatus - metabolism; Hydrogen-Ion Concentration; Investigations; Macrophages; Mathematical models; Membranes; Meningitis; Metabolism; Metabolites; Mitochondria - metabolism; Models, Biological; Models, Theoretical; Pathogenesis; Pathogenicity; Pathogens; Phagocytes; Proteins; sphingolipid; Sphingolipids - metabolism; System theory; Systems Biology; S‐system; Virulence; ceramide; S‐system; sphingolipid; Biochemical Systems Theory
• ISSN: 1744-4292; 1744-4292
• DOI: 10.1038/msb.2008.17

Cryptococcus neoformans ( Cn ) is the most common cause of fungal meningitis worldwide. In infected patients, growth of the fungus can occur within the phagolysosome of phagocytic cells, especially in non‐activated macrophages of immunocompromised subjects. Since this environment is characteristically acidic, Cn must adapt to low pH to survive and efficiently cause disease. In the present work, we designed, tested, and experimentally validated a theoretical model of the sphingolipid biochemical pathway in Cn under acidic conditions. Simulations of metabolic fluxes and enzyme deletions or downregulation led to predictions that show good agreement with experimental results generated post hoc and reconcile intuitively puzzling results. This study demonstrates how biochemical modeling can yield testable predictions and aid our understanding of fungal pathogenesis through the design and computational simulation of hypothetical experiments. Synopsis Extended Synopsis Cryptococcus neoformans ( Cn ) is a fungal microbial pathogen that lives in the environment and in the gastrointestinal tract of several birds, pigeons in particular (Casadevall and Perfect, 1998 ). Upon inhalation of Cn spores or desiccated yeast cells, the fungus can grow in the extracellular space of the alveoli and in the intracellular environment of phagocytic cells, particularly alveolar macrophages (Levitz et al , 1999). Hence, Cn is considered a facultative intracellular pathogen. Thus, once in the lung, the fungus must adapt to two different environments: the extracellular space characterized by neutral/alkaline pH and the intracellular milieu of the phagolysosome characterized by acidic pH. In recent years, we have found that a class of lipids, sphingolipids, represents a reservoir of molecules implicated in the regulation of fungal growth either in neutral/alkaline (Rittershaus et al , 2006 ; Kechichian et al , 2007) or acidic environments (Shea et al , 2006 ), in the modulation of Cn virulence factors, such as melanin production (Heung et al , 2004 , 2005 ), and in the regulation of phagocytosis (Luberto et al , 2003; Mare et al , 2005 ; Tommasino et al , 2008). Interestingly, the shift of Cn cells from the extracellular to the intracellular compartment is particularly important because it changes the outcome of the infection in a severely immunocompromised host (Kechichian et al , 2007). Interestingly, the contribution of each Cn population (extracellular versus intracellular) to the outcome of infection is determined by the host immune status (Luberto et al , 2003). Therefore, the understanding of the mechanism(s) that regulate survival of Cn in both compartments (extracellular versus intracellular) may lead to novel therapeutic interventions based on the fine tune up of important Cn switches determined by the host immune status. In this paper, a mathematical model representing the sphingolipid metabolic pathway of Cn was developed. It was tested to simulate sphingolipid adaptation to a shift from an alkaline to an acidic pH, to mimic the phagocytosis of Cn by macrophages (Figure 1 ). The model was designed and analyzed within the framework of the biochemical system theory, which uses power‐law representations for all enzymatic and transport processes (Savageau, 1969a, b, 59 , 60 , 61 ; Torres and Voit, 2002 ). By coupling mathematical simulations using the model with experimental determinations, multiple factors were found to be required for adaptation of Cn to the acidic environment. In particular, experimental determinations showed that sphingolipid phytoceramide C 26 significantly increases when cells are shifted from alkaline to acidic pH (Table I ), and this result was predicted by the model. Interestingly, production of phytoceramide C 26 is under the control of inositol phosphosphingolipid phospholipase C (Isc1) enzyme, because a Δ isc1 mutant strain dramatically reduces the level of this sphingolipid. As expected, Δ isc1 mutant has a growth defect at acidic pH ( Supplementary Figure 1 ). Moreover, the use of a different mutant of the sphingolipid pathway showed that phytoceramide C 26 is necessary but not sufficient for the adaptation process. In particular, downregulation of inositol phosphorylceramide synthase (Ipc1), which uses phytoceramide as a substrate, shows also a growth defect at low pH even though the levels of phytoceramide C 26 are not altered. Therefore, it is proposed that other lipids regulated by Ipc1, such as complex sphingolipids and/or diacylglycerol, may also be involved in this adaptation process. Based on our simulations, the model suggests that the growth defect at low pH observed when Isc1 is deleted or Ipc1 downregulated is due to a decreased activity of the plasma membrane H + ATPase (Pma1), and the experimental findings (Table V) indeed support this prediction (Figure 1 ). We hypothesize that Isc1 regulates Pma1 through phytoceramide C 26 , whereas Ipc1 regulates Pma1 through DAG and/or complex sphingolipids. In conclusion, the mathematical model of sphingolipid metabolism helps to predict the adaptation of Cn in the host environments and contributes to a better understanding of its pathogenic traits. This article presents a mathematical model of the sphingolipid metabolic pathway of the pathogenic fungus Cryptococcus neoformans. The model predicts that the sphingolipids regulated by two sphingolipid enzymes, inositol phosphorylceramide synthase (Ipc1) and inositol phosphosphingolipidphospholipase C (Isc1), are critical to promote fungal growth at acidic pH. Based on our simulations, the model suggests that in conditions in which Isc1 is deleted or Ipc1 is down regulated the activity of the plasma membrane H+ ATPase (Pma1) decreases, and our experimental findings indeed demonstrates this prediction. Isc1 and Ipc1 regulate Pma1 through different mechanisms: Isc1 through phytoceramide C26 and Ipc1 through complex sphingolipids or/and diacylglycerol.