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Time-course proteome analysis reveals the dynamic response of Cryptococcus gattii cells to fluconazole.

Chong HS, Campbell L, Padula MP, Hill C, Harry E, Li SS, Wilkins MR, Herbert B, Carter D - PLoS ONE (2012)

Bottom Line: During FLC treatment, an increase in stress response, ATP synthesis and mitochondrial respiratory chain proteins, and a decrease in most ribosomal proteins was observed, suggesting that ATP-dependent efflux pumps had been initiated for survival and that the maintenance of ribosome synthesis was differentially expressed.An integrative network analysis revealed co-ordinated processes involved in drug response, and highlighted hubs in the network representing essential proteins that are required for cell viability.This work demonstrates the dynamic cellular response of a typical susceptible isolate of C. gattii to FLC, and identified a number of proteins and pathways that could be targeted to augment the activity of FLC.

View Article: PubMed Central - PubMed

Affiliation: School of Molecular Bioscience, University of Sydney, Sydney, New South Wales, Australia.

ABSTRACT
Cryptococcus gattii is an encapsulated fungus capable of causing fatal disease in immunocompetent humans and animals. As current antifungal therapies are few and limited in efficacy, and resistance is an emerging issue, the development of new treatment strategies is urgently required. The current study undertook a time-course analysis of the proteome of C. gattii during treatment with fluconazole (FLC), which is used widely in prophylactic and maintenance therapies. The aims were to analyze the overall cellular response to FLC, and to find fungal proteins involved in this response that might be useful targets in therapies that augment the antifungal activity of FLC. During FLC treatment, an increase in stress response, ATP synthesis and mitochondrial respiratory chain proteins, and a decrease in most ribosomal proteins was observed, suggesting that ATP-dependent efflux pumps had been initiated for survival and that the maintenance of ribosome synthesis was differentially expressed. Two proteins involved in fungal specific pathways were responsive to FLC. An integrative network analysis revealed co-ordinated processes involved in drug response, and highlighted hubs in the network representing essential proteins that are required for cell viability. This work demonstrates the dynamic cellular response of a typical susceptible isolate of C. gattii to FLC, and identified a number of proteins and pathways that could be targeted to augment the activity of FLC.

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Drug response network drawn as in Figure 4 and coloured using Gene Ontology data.Network analysis reveals clustering of protein with similar functions and hub proteins with a high degree of connectivity. Potential targets for synergistic therapies are indicated in Figure S2. [GEOMI Force Directed Layout: spring = 50, origin = 80, repulsion = 12, planar = 100].
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pone-0042835-g005: Drug response network drawn as in Figure 4 and coloured using Gene Ontology data.Network analysis reveals clustering of protein with similar functions and hub proteins with a high degree of connectivity. Potential targets for synergistic therapies are indicated in Figure S2. [GEOMI Force Directed Layout: spring = 50, origin = 80, repulsion = 12, planar = 100].

Mentions: As the proteome analysis revealed dynamic changes in protein expression in cells treated with FLC over time, network analysis was used to gain further insight into how the differentially regulated proteins might interact with each other, and how the cells co-ordinate their response to FLC over time. High-quality protein-protein interaction data for the yeast Saccharomyces cerevisiae were used to generate the networks, as protein-protein interactions have not yet been studied on a genome-wide scale in Cryptococcus. Corresponding yeast homologs were identified for each of the differentially expressed proteins listed in Table S2 (Table S3). Seventy-seven of the 82 cryptococcal proteins had a yeast homolog with an E value of less than 10−9. Of these, 47 were present in the yeast protein-protein interaction datasets used, which only include interactions that have been experimentally validated [11], [12]. Using these 47 yeast proteins, two different types of networks were built to investigate the overall cellular drug response in C. gattii. These were seeded with the 47 homologs and extended to show the most direct connections (shortest path) between these homologs using known protein-protein interactions. Figure 4 depicts expression networks for the three time points (3, 4 and 6 h) and shows how the expression of proteins differentially regulated by FLC treatment changes over time (see Figure S1 for larger version of these networks). Figure 5 shows the same network with Gene Ontology (GO) data mapped to the differentially expressed proteins (large spheres), the interacting proteins (small spheres) and the interactions (lines) that join them.


Time-course proteome analysis reveals the dynamic response of Cryptococcus gattii cells to fluconazole.

Chong HS, Campbell L, Padula MP, Hill C, Harry E, Li SS, Wilkins MR, Herbert B, Carter D - PLoS ONE (2012)

Drug response network drawn as in Figure 4 and coloured using Gene Ontology data.Network analysis reveals clustering of protein with similar functions and hub proteins with a high degree of connectivity. Potential targets for synergistic therapies are indicated in Figure S2. [GEOMI Force Directed Layout: spring = 50, origin = 80, repulsion = 12, planar = 100].
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3412811&req=5

pone-0042835-g005: Drug response network drawn as in Figure 4 and coloured using Gene Ontology data.Network analysis reveals clustering of protein with similar functions and hub proteins with a high degree of connectivity. Potential targets for synergistic therapies are indicated in Figure S2. [GEOMI Force Directed Layout: spring = 50, origin = 80, repulsion = 12, planar = 100].
Mentions: As the proteome analysis revealed dynamic changes in protein expression in cells treated with FLC over time, network analysis was used to gain further insight into how the differentially regulated proteins might interact with each other, and how the cells co-ordinate their response to FLC over time. High-quality protein-protein interaction data for the yeast Saccharomyces cerevisiae were used to generate the networks, as protein-protein interactions have not yet been studied on a genome-wide scale in Cryptococcus. Corresponding yeast homologs were identified for each of the differentially expressed proteins listed in Table S2 (Table S3). Seventy-seven of the 82 cryptococcal proteins had a yeast homolog with an E value of less than 10−9. Of these, 47 were present in the yeast protein-protein interaction datasets used, which only include interactions that have been experimentally validated [11], [12]. Using these 47 yeast proteins, two different types of networks were built to investigate the overall cellular drug response in C. gattii. These were seeded with the 47 homologs and extended to show the most direct connections (shortest path) between these homologs using known protein-protein interactions. Figure 4 depicts expression networks for the three time points (3, 4 and 6 h) and shows how the expression of proteins differentially regulated by FLC treatment changes over time (see Figure S1 for larger version of these networks). Figure 5 shows the same network with Gene Ontology (GO) data mapped to the differentially expressed proteins (large spheres), the interacting proteins (small spheres) and the interactions (lines) that join them.

Bottom Line: During FLC treatment, an increase in stress response, ATP synthesis and mitochondrial respiratory chain proteins, and a decrease in most ribosomal proteins was observed, suggesting that ATP-dependent efflux pumps had been initiated for survival and that the maintenance of ribosome synthesis was differentially expressed.An integrative network analysis revealed co-ordinated processes involved in drug response, and highlighted hubs in the network representing essential proteins that are required for cell viability.This work demonstrates the dynamic cellular response of a typical susceptible isolate of C. gattii to FLC, and identified a number of proteins and pathways that could be targeted to augment the activity of FLC.

View Article: PubMed Central - PubMed

Affiliation: School of Molecular Bioscience, University of Sydney, Sydney, New South Wales, Australia.

ABSTRACT
Cryptococcus gattii is an encapsulated fungus capable of causing fatal disease in immunocompetent humans and animals. As current antifungal therapies are few and limited in efficacy, and resistance is an emerging issue, the development of new treatment strategies is urgently required. The current study undertook a time-course analysis of the proteome of C. gattii during treatment with fluconazole (FLC), which is used widely in prophylactic and maintenance therapies. The aims were to analyze the overall cellular response to FLC, and to find fungal proteins involved in this response that might be useful targets in therapies that augment the antifungal activity of FLC. During FLC treatment, an increase in stress response, ATP synthesis and mitochondrial respiratory chain proteins, and a decrease in most ribosomal proteins was observed, suggesting that ATP-dependent efflux pumps had been initiated for survival and that the maintenance of ribosome synthesis was differentially expressed. Two proteins involved in fungal specific pathways were responsive to FLC. An integrative network analysis revealed co-ordinated processes involved in drug response, and highlighted hubs in the network representing essential proteins that are required for cell viability. This work demonstrates the dynamic cellular response of a typical susceptible isolate of C. gattii to FLC, and identified a number of proteins and pathways that could be targeted to augment the activity of FLC.

Show MeSH