The use of PCR-based techniques for directed gene alterations has become a standard tool in Saccharomyces cerevisiae. In our efforts to increase the speed of functional analysis of Candida albicans genes, we constructed a modular system of plasmid vectors and successfully applied PCR-amplified functional analysis (FA)-cassettes in the transformation of C. albicans. These cassettes facilitate: (a) gene disruptions; (b) tagging of 3 -ends of genes with green fluorescent protein (GFP); and (c) replacements of endogenous promoters to achieve regulated expression. The modules consists of a core of three selectable marker genes, CaURA3, CaHIS1 and CaARG4. Modules for C-terminal GFP-tagging were generated by adding GFPsequences flanked at the 5 -end by a (Gly-Ala) 3 -linker and at the 3 -end by the S. cerevisiae URA3-terminator to these selection markers. Promoter exchange modules consist of the respective marker genes followed by the regulatable CaMAL2 or CaMET3 promoters at their 3 -ends. In order to ensure a reliably high rate of homologous gene targeting, the flanking homology regions required a size of 100 bp of gene-specific sequences, which were provided with the oligonucleotide primers. The use of shorter flanking homology regions produced unsatisfactory results with C. albicans strain BWP17. With these new modules only a minimal set of primers is required to achieve the functional analysis of C. albicans genes and, therefore, provides a basic tool to increase the number of functionally characterized C. albicans genes of this human pathogen in the near future.

Several modules for efficient PCR-based gene disruption have recently been introduced in Candida albicans. These are based on auxotrophic marker genes for deficient strains derived from SC5314/CAI4. Commonly used protocols for the transformation C. albicans are based either on the lithium acetate procedure or on electroporation also used for Saccharomyces cerevisiae. Here we present our updated arsenal of pFA-modules that now include the heterologous marker genes HIS1 from C. dubliniensis and LEU2 from C. maltosa (Noble and Johnson 2005) and the dominant selection marker ca SAT1 (Reuss et al. 2004). We also introduce the Ashbya gossypii TEF1 -promoter as a strong constitutive promoter. With these new elements an enlarged collection of pFA-marker and pFA-marker-promoter modules were generated containing 17 new modules. In addition, N-terminal tagging with GFP-(GA) 6 and epitope-tagging modules using the 6 x-HIS-tag were constructed. This adds to the previous modules that only enabled C-terminal GFP-tagging of genes (Gola et al. 2003). In total 29 pFA-modules are currently freely available from our lab which - together with an update on the diagnostic verification procedure - further enlarge the C. albicans molecular toolbox and enhance our capabilities to use PCR-based gene alteration methods in C. albicans.

IntroductionInactivation of proteins that participate in more than one cellular process leads to a variety of apparently unconnected phenotypes. Understanding the molecular cause for each phenotype might reveal how seemingly independent cellular processes are regulated and coordinated in the cell. Genome-wide gene interaction data based on the simultaneous inactivation of more than one gene greatly facilitate this inherently complex analysis because genes with pleiotropic phenotypes often occupy central positions in the corresponding interaction networks (Costanzo et al., 2010;Tong et al., 2004). By assigning physical connections, protein-protein interaction maps provide the necessary complementary information. Interpretation of these maps is usually not straightforward. Genetic interactions can result from complex functional relationships between the investigated pairs of genes and protein interaction maps are generally projections of contacts that occur at different times and places in the cell. To transform protein interaction data into mechanistically meaningful models, it is necessary to resolve these projections into their different interaction planes. We define an interaction plane or state as the sum of all simultaneously occurring contacts. Ideally, these states should be defined by time-and space-resolved in vivo studies. However, these studies are technically demanding and usually not suited for measuring multiple contacts (Maeder et al., 2007). Using the protein pair Ptc1p-Nbp2p of the yeast Saccharomyces cerevisiae as an example and the split-ubiquitin method (SplitUb) as the experimental tool, we present an alternative approach for defining interaction states. The derived constraint interaction network reduces the number of possible states and thus provides a useful framework for model building and the initiation of more detailed studies.