Exploring rigid-backbone protein docking in biologics discovery: a test using the DARPin scaffold.

Accurate protein-protein docking remains challenging, especially for artificial biologics not coevolved naturally against their protein targets, like antibodies and other engineered scaffolds. We previously developed ProPOSE, an exhaustive docker with full atomistic details, which delivers cutting-edge performance by allowing side-chain rearrangements upon docking. However, extensive protein backbone flexibility limits its practical applicability as indicated by unbound docking tests. To explore the usefulness of ProPOSE on systems with limited backbone flexibility, here we tested the engineered scaffold DARPin, which is characterized by its relatively rigid protein backbone. A prospective screening campaign was undertaken, in which sequence-diversified DARPins were docked and ranked against a directed epitope on the target protein BCL-W. In this proof-of-concept study, only a relatively small set of 2,213 diverse DARPin interfaces were selected for docking from the huge theoretical library from mutating 18 amino-acid positions. A computational selection protocol was then applied for enrichment of binders based on normalized computed binding scores and frequency of binding modes against the predefined epitope. The top-ranked 18 designed DARPin interfaces were selected for experimental validation. Three designs exhibited binding affinities to BCL-W in the nanomolar range comparable to control interfaces adopted from known DARPin binders. This result is encouraging for future screening and engineering campaigns of DARPins and possibly other similarly rigid scaffolds against targeted protein epitopes. Method limitations are discussed and directions for future refinements are proposed.

Comparative Performance of High-Throughput Methods for Protein pKa Predictions.

The medically relevant field of protein-based therapeutics has triggered a demand for protein engineering in different pH environments of biological relevance. In silico engineering workflows typically employ high-throughput screening campaigns that require evaluating large sets of protein residues and point mutations by fast yet accurate computational algorithms. While several high-throughput pKa prediction methods exist, their accuracies are unclear due to the lack of a current comprehensive benchmarking. Here, seven fast, efficient, and accessible approaches including PROPKA3, DeepKa, PKAI, PKAI+, DelPhiPKa, MCCE2, and H++ were systematically tested on a nonredundant subset of 408 measured protein residue pKa shifts from the pKa database (PKAD). While no method outperformed the null hypotheses with confidence, as illustrated by statistical bootstrapping, DeepKa, PKAI+, PROPKA3, and H++ had utility. More specifically, DeepKa consistently performed well in tests across multiple and individual amino acid residue types, as reflected by lower errors, higher correlations, and improved classifications. Arithmetic averaging of the best empirical predictors into simple consensuses improved overall transferability and accuracy up to a root-mean-square error of 0.76 pKa units and a correlation coefficient (R2) of 0.45 to experimental pKa shifts. This analysis should provide a basis for further methodological developments and guide future applications, which require embedding of computationally inexpensive pKa prediction methods, such as the optimization of antibodies for pH-dependent antigen binding.

Redesigning an antibody H3 loop by virtual screening of a small library of human germline-derived sequences.

The design of superior biologic therapeutics, including antibodies and engineered proteins, involves optimizing their specific ability to bind to disease-related molecular targets. Previously, we developed and applied the Assisted Design of Antibody and Protein Therapeutics (ADAPT) platform for virtual affinity maturation of antibodies (Vivcharuk et al. in PLoS One 12(7):e0181490, https://doi.org/10.1371/journal.pone.0181490 , 2017). However, ADAPT is limited to point mutations of hot-spot residues in existing CDR loops. In this study, we explore the possibility of wholesale replacement of the entire H3 loop with no restriction to maintain the parental loop length. This complements other currently published studies that sample replacements for the CDR loops L1, L2, L3, H1 and H2. Given the immense sequence space theoretically available to H3, we focused on the virtual grafting of over 5000 human germline-derived H3 sequences from the IGMT/LIGM database increasing the diversity of the sequence space when compared to using crystalized H3 loop sequences. H3 loop conformations are generated and scored to identify optimized H3 sequences. Experimental testing of high-ranking H3 sequences grafted into the framework of the bH1 antibody against human VEGF-A led to the discovery of multiple hits, some of which had similar or better affinities relative to the parental antibody. In over 75% of the tested designs, the re-designed H3 loop contributed favorably to overall binding affinity. The hits also demonstrated good developability attributes such as high thermal stability and no aggregation. Crystal structures of select re-designed H3 variants were solved and indicated that although some deviations from predicted structures were seen in the more solvent accessible regions of the H3 loop, they did not significantly affect predicted affinity scores.

Binding symmetry and surface flexibility mediate antibody self-association.

Solution stability is an important factor in the optimization of engineered biotherapeutic candidates such as monoclonal antibodies because of its possible effects on manufacturability, pharmacology, efficacy and safety. A detailed atomic understanding of the mechanisms governing self-association of natively folded protein monomers is required to devise predictive tools to guide screening and re-engineering along the drug development pipeline. We investigated pairs of affinity-matured full-size antibodies and observed drastically different propensities to aggregate from variants differing by a single amino-acid. Biophysical testing showed that antigen-binding fragments (Fabs) from the aggregating antibodies also reversibly associated with equilibrium dissociation constants in the low-micromolar range. Crystal structures (PDB accession codes 6MXR, 6MXS, 6MY4, 6MY5) and bottom-up hydrogen-exchange mass spectrometry revealed that Fab self-association occurs in a symmetric mode that involves the antigen complementarity-determining regions. Subtle local conformational changes incurred upon point mutation of monomeric variants foster formation of complementary polar interactions and hydrophobic contacts to generate a dimeric Fab interface. Testing of popular in silico tools generally indicated low reliabilities for predicting the aggregation propensities observed. A structure-aggregation data set is provided here in order to stimulate further improvements of in silico tools for prediction of native aggregation. Incorporation of intermolecular docking, conformational flexibility, and short-range packing interactions may all be necessary features of the ideal algorithm.

ProPOSE: Direct Exhaustive Protein-Protein Docking with Side Chain Flexibility.

Despite decades of development, protein-protein docking remains a largely unsolved problem. The main difficulties are the immense space spanned by the translational and rotational degrees of freedom and the prediction of the conformational changes of proteins upon binding. FFT is generally the preferred method to exhaustively explore the translation-rotation space at a fine grid resolution, albeit with the trade-off of approximating force fields with correlation functions. This work presents a direct search alternative that samples the states in Cartesian space at the same resolution and computational cost as standard FFT methods. Operating in real space allows the use of standard force field functional forms used in typical non-FFT methods as well as the implementation of strategies for focused exploration of conformational flexibility. Currently, a few misplaced side chains can cause docking programs to fail. This work specifically addresses the problem of side chain rearrangements upon complex formation. Based on the observation that most side chains retain their unbound conformation upon binding, each rigidly docked pose is initially scored ignoring up to a limited number of side chain overlaps which are resolved in subsequent repacking and minimization steps. On test systems where side chains are altered and backbones held in their bound state, this implementation provides significantly better native pose recovery and higher quality (lower RMSD) predictions when compared with five of the most popular docking programs. The method is implemented in the software program ProPOSE (Protein Pose Optimization by Systematic Enumeration).

Binding pose and affinity prediction in the 2016 D3R Grand Challenge 2 using the Wilma-SIE method.

The Farnesoid X receptor (FXR) exhibits significant backbone movement in response to the binding of various ligands and can be a challenge for pose prediction algorithms. As part of the D3R Grand Challenge 2, we tested Wilma-SIE, a rigid-protein docking method, on a set of 36 FXR ligands for which the crystal structures had originally been blinded. These ligands covered several classes of compounds. To overcome the rigid protein limitations of the method, we used an ensemble of publicly available structures for FXR from the PDB. The use of the ensemble allowed Wilma-SIE to predict poses with average and median RMSDs of 2.3 and 1.4 Å, respectively. It was quite clear, however, that had we used a single structure for the receptor the success rate would have been much lower. The most successful predictions were obtained on chemical classes for which one or more crystal structures of the receptor bound to a molecule of the same class was available. In the absence of a crystal structure for the class, observing a consensus binding mode for the ligands of the class using one or more receptor structures of other classes seemed to be indicative of a reasonable pose prediction. Affinity prediction proved to be more challenging with generally poor correlation with experimental IC50s (Kendall tau ~ 0.3). Even when the 36 crystal structures were used the accuracy of the predicted affinities was not appreciably improved. A possible cause of difficulty is the internal energy strain arising from conformational differences in the receptor across complexes, which may need to be properly estimated and incorporated into the SIE scoring function.

Evaluation of the Wilma-SIE Virtual Screening Method in Community Structure-Activity Resource 2013 and 2014 Blind Challenges.

Prospective assessments of the Wilma-SIE (solvated interaction energy) platform for ligand docking and ranking were performed during the 2013 and 2014 editions of the Community Structure-Activity Resource (CSAR) blind challenge. Diverse targets like a steroid-binding protein, a serine protease (factor Xa), a tyrosine kinase (Syk), and a nucleotide methyltransferase (TrmD) were included. Pose selection was achieved with high precision; in all 24 tests Wilma-SIE top-ranked the native pose among carefully generated sets of decoy conformations. Good separation for the native pose was also observed indicating robustness in pose scoring. Cross-docking was also accomplished with high accuracy for the various systems, with ligand median-RMSD values around 1 Å from the crystal structures. Larger deviations were occasionally obtained due to the rigid-target approach even if multiple target structures were used. Affinity ranking of congeneric ligands after cross-docking was reasonable for three of the four systems, with Spearman ranking coefficients around 0.6. Poor affinity ranking for FXa is possibly due to missing structural domains, which are present during measurements. Assignment of protonation states is critical for affinity scoring with the SIE function, as shown here for the Syk system. Including the FiSH model improved cross-docking but worsened affinity predictions, pointing to the need for further fine-tuning of this newer solvation model. The consistently strong performance of the Wilma-SIE platform in recent CSAR and SAMPL blind challenges validates its applicability for virtual screening on a broad range of molecular targets.

Small-molecule inhibitors of the pseudaminic acid biosynthetic pathway: targeting motility as a key bacterial virulence factor.

Helicobacter pylori is motile by means of polar flagella, and this motility has been shown to play a critical role in pathogenicity. The major structural flagellin proteins have been shown to be glycosylated with the nonulosonate sugar, pseudaminic acid (Pse). This glycan is unique to microorganisms, and the process of flagellin glycosylation is required for H. pylori flagellar assembly and consequent motility. As such, the Pse biosynthetic pathway offers considerable potential as an antivirulence drug target, especially since motility is required for H. pylori colonization and persistence in the host. This report describes screening the five Pse biosynthetic enzymes for small-molecule inhibitors using both high-throughput screening (HTS) and in silico (virtual screening [VS]) approaches. Using a 100,000-compound library, 1,773 hits that exhibited a 40% threshold inhibition at a 10 µM concentration were identified by HTS. In addition, VS efforts using a 1.6-million compound library directed at two pathway enzymes identified 80 hits, 4 of which exhibited reasonable inhibition at a 10 µM concentration in vitro. Further secondary screening which identified 320 unique molecular structures or validated hits was performed. Following kinetic studies and structure-activity relationship (SAR) analysis of selected inhibitors from our refined list of 320 compounds, we demonstrated that three inhibitors with 50% inhibitory concentrations (IC50s) of approximately 14 µM, which belonged to a distinct chemical cluster, were able to penetrate the Gram-negative cell membrane and prevent formation of flagella.

Exhaustive docking and solvated interaction energy scoring: lessons learned from the SAMPL4 challenge.

We continued prospective assessments of the Wilma-solvated interaction energy (SIE) platform for pose prediction, binding affinity prediction, and virtual screening on the challenging SAMPL4 data sets including the HIV-integrase inhibitor and two host-guest systems. New features of the docking algorithm and scoring function are tested here prospectively for the first time. Wilma-SIE provides good correlations with actual binding affinities over a wide range of binding affinities that includes strong binders as in the case of SAMPL4 host-guest systems. Absolute binding affinities are also reproduced with appropriate training of the scoring function on available data sets or from comparative estimation of the change in target's vibrational entropy. Even when binding modes are known, SIE predictions lack correlation with experimental affinities within dynamic ranges below 2 kcal/mol as in the case of HIV-integrase ligands, but they correctly signaled the narrowness of the dynamic range. Using a common protein structure for all ligands can reduce the noise, while incorporating a more sophisticated solvation treatment improves absolute predictions. The HIV-integrase virtual screening data set consists of promiscuous weak binders with relatively high flexibility and thus it falls outside of the applicability domain of the Wilma-SIE docking platform. Despite these difficulties, unbiased docking around three known binding sites of the enzyme resulted in over a third of ligands being docked within 2 Å from their actual poses and over half of the ligands docked in the correct site, leading to better-than-random virtual screening results.

Protein-ligand binding free energies from exhaustive docking.

We explore the use of exhaustive docking as an alternative to Monte Carlo and molecular dynamics sampling for the direct integration of the partition function for protein-ligand binding. We enumerate feasible poses for the ligand and calculate the Boltzmann factor contribution of each pose to the partition function. From the partition function, the free energy, enthalpy, and entropy can be derived. All our calculations are done with a continuum solvation model that includes solving the Poisson equation. In contrast to Monte Carlo and molecular dynamics simulations, exhaustive docking avoids (within the limitations of a discrete sampling) the question of "Have we run long enough?" due to its deterministic complete enumeration of states. We tested the method on the T4 lysozyme L99A mutant, which has a nonpolar cavity that can accommodate a number of small molecules. We tested two electrostatic models. Model 1 used a solute dielectric of 2.25 for the complex apoprotein and free ligand and 78.5 for the solvent. Model 2 used a solute dielectric of 2.25 for the complex and apoprotein but 1.0 for the free ligand. For our test set of eight molecules, we obtain a reasonable correlation with a Pearson r(2) = 0.66 using model 1. The trend in binding affinity ranking is generally preserved with a Kendall τ = 0.64 and Spearman ρ = 0.83. With model 2, the correlation is improved with a Pearson r(2) = 0.83, Kendall τ = 0.93, and Spearman ρ = 0.98. This suggests that the energy function and sampling method adequately captured most of the thermodynamics of binding of the nonpolar ligands to T4 lysozyme L99A.

Exhaustive search and solvated interaction energy (SIE) for virtual screening and affinity prediction.

We carried out a prospective evaluation of the utility of the SIE (solvation interaction energy) scoring function for virtual screening and binding affinity prediction. Since experimental structures of the complexes were not provided, this was an exercise in virtual docking as well. We used our exhaustive docking program, Wilma, to provide high-quality poses that were rescored using SIE to provide binding affinity predictions. We also tested the combination of SIE with our latest solvation model, first shell of hydration (FiSH), which captures some of the discrete properties of water within a continuum model. We achieved good enrichment in virtual screening of fragments against trypsin, with an area under the curve of about 0.7 for the receiver operating characteristic curve. Moreover, the early enrichment performance was quite good with 50% of true actives recovered with a 15% false positive rate in a prospective calculation and with a 3% false positive rate in a retrospective application of SIE with FiSH. Binding affinity predictions for both trypsin and host-guest complexes were generally within 2 kcal/mol of the experimental values. However, the rank ordering of affinities differing by 2 kcal/mol or less was not well predicted. On the other hand, it was encouraging that the incorporation of a more sophisticated solvation model into SIE resulted in better discrimination of true binders from binders. This suggests that the inclusion of proper Physics in our models is a fruitful strategy for improving the reliability of our binding affinity predictions.

Naphthalene-based RNA editing inhibitor blocks RNA editing activities and editosome assembly in Trypanosoma brucei.

RNA editing, catalyzed by the multiprotein editosome complex, is an essential step for the expression of most mitochondrial genes in trypanosomatid pathogens. It has been shown previously that Trypanosoma brucei RNA editing ligase 1 (TbREL1), a core catalytic component of the editosome, is essential in the mammalian life stage of these parasitic pathogens. Because of the availability of its crystal structure and absence from human, the adenylylation domain of TbREL1 has recently become the focus of several studies for designing inhibitors that target its adenylylation pocket. Here, we have studied new and existing inhibitors of TbREL1 to better understand their mechanism of action. We found that these compounds are moderate to weak inhibitors of adenylylation of TbREL1 and in fact enhance adenylylation at higher concentrations of protein. Nevertheless, they can efficiently block deadenylylation of TbREL1 in the editosome and, consequently, result in inhibition of the ligation step of RNA editing. Further experiments directly showed that the studied compounds inhibit the interaction of the editosome with substrate RNA. This was supported by the observation that not only the ligation activity of TbREL1 but also the activities of other editosome proteins such as endoribonuclease, terminal RNA uridylyltransferase, and uridylate-specific exoribonuclease, all of which require the interaction of the editosome with the substrate RNA, are efficiently inhibited by these compounds. In addition, we found that these compounds can interfere with the integrity and/or assembly of the editosome complex, opening the exciting possibility of using them to study the mechanism of assembly of the editosome components.

The zinc cluster transcription factor Ahr1p directs Mcm1p regulation of Candida albicans adhesion.

Biofilm development by Candida albicans requires cell adhesion for the initial establishment of the biofilm and the continued stability after hyphal development occurs; however, the regulation of the process has not been fully established. Using chromatin immunoprecipitation coupled to microarray analysis (ChIP-chip) we have characterized a regulon containing the Mcm1p factor that is required for the initial surface adhesion during biofilm formation. In the yeast Saccharomyces cerevisiae several Mcm1p regulons have been characterized in which regulatory specificity is achieved through cofactors binding a sequence adjacent to the Mcm1p binding site. This new Mcm1p regulon in C. albicans also requires a cofactor, which we identify as the transcription factor Ahr1p. However, in contrast to the other yeast regulons, Ahr1p alone binds the target promoters, which include several key adhesion genes, and recruits Mcm1p to these sites. Through transcription profiling and qPCR analysis, we demonstrate that this Ahr1p-Mcm1p complex directly activates these adhesion genes. When the regulatory circuit was disrupted by deleting AHR1, the strain displayed reduced adherence to a polystyrene surface. We also demonstrate a role for the regulon in hyphal growth and in virulence. Our work thus establishes a new mechanism of Mcm1p-directed regulation distinct from those observed for other Mcm1p co-regulators.

Experimental annotation of the human pathogen Candida albicans coding and noncoding transcribed regions using high-resolution tiling arrays.

BACKGROUND: Compared to other model organisms and despite the clinical relevance of the pathogenic yeast Candida albicans, no comprehensive analysis has been done to provide experimental support of its in silico-based genome annotation. RESULTS: We have undertaken a genome-wide experimental annotation to accurately uncover the transcriptional landscape of the pathogenic yeast C. albicans using strand-specific high-density tiling arrays. RNAs were purified from cells growing under conditions relevant to C. albicans pathogenicity, including biofilm, lab-grown yeast and serum-induced hyphae, as well as cells isolated from the mouse caecum. This work provides a genome-wide experimental validation for a large number of predicted ORFs for which transcription had not been detected by other approaches. Additionally, we identified more than 2,000 novel transcriptional segments, including new ORFs and exons, non-coding RNAs (ncRNAs) as well as convincing cases of antisense gene transcription. We also characterized the 5' and 3' UTRs of expressed ORFs, and established that genes with long 5' UTRs are significantly enriched in regulatory functions controlling filamentous growth. Furthermore, we found that genomic regions adjacent to telomeres harbor a cluster of expressed ncRNAs. To validate and confirm new ncRNA candidates, we adapted an iterative strategy combining both genome-wide occupancy of the different subunits of RNA polymerases I, II and III and expression data. This comprehensive approach allowed the identification of different families of ncRNAs. CONCLUSIONS: In summary, we provide a comprehensive expression atlas that covers relevant C. albicans pathogenic developmental stages in addition to the discovery of new ORF and non-coding genetic elements.

The functional potential of high Arctic permafrost revealed by metagenomic sequencing, qPCR and microarray analyses.

The fate of the carbon stocked in permafrost following global warming and permafrost thaw is of major concern in view of the potential for increased CH(4) and CO(2) emissions from these soils. Complex carbon compound degradation and greenhouse gas emissions are due to soil microbial communities, but no comprehensive study has yet addressed their composition and functional potential in permafrost. Here, a 2-m deep permafrost sample and its overlying active layer soil were subjected to metagenomic sequencing, quantitative PCR (qPCR) and microarray analyses. The active layer soil and the 2-m permafrost microbial community structures were very similar, with Actinobacteria being the dominant phylum. The two samples also possessed a highly similar spectrum of functional genes, especially when compared with other already published metagenomes. Key genes related to methane generation, methane oxidation and organic matter degradation were highly diverse for both samples in the metagenomic libraries and some (for example, pmoA) showed relatively high abundance in qPCR assays. Genes related to nitrogen fixation and ammonia oxidation, which could have important roles following climatic change in these nitrogen-limited environments, showed low diversity but high abundance. The 2-m permafrost showed lower abundance and diversity for all the assessed genes and taxa. Experimental biases were also evaluated using qPCR and showed that the whole-community genome amplification technique used caused representational biases in the metagenomic libraries by increasing the abundance of Bacteroidetes and decreasing the abundance of Actinobacteria. This study describes for the first time the detailed functional potential of permafrost-affected soils.

Evolutionary tinkering with conserved components of a transcriptional regulatory network.

Gene expression variation between species is a major contributor to phenotypic diversity, yet the underlying flexibility of transcriptional regulatory networks remains largely unexplored. Transcription of the ribosomal regulon is a critical task for all cells; in S. cerevisiae the transcription factors Rap1, Fhl1, Ifh1, and Hmo1 form a multi-subunit complex that controls ribosomal gene expression, while in C. albicans this regulation is under the control of Tbf1 and Cbf1. Here, we analyzed, using full-genome transcription factor mapping, the roles, in both S. cerevisiae and C. albicans, of each orthologous component of this complete set of regulators. We observe dramatic changes in the binding profiles of the generalist regulators Cbf1, Hmo1, Rap1, and Tbf1, while the Fhl1-Ifh1 dimer is the only component involved in ribosomal regulation in both fungi: it activates ribosomal protein genes and rDNA expression in a Tbf1-dependent manner in C. albicans and a Rap1-dependent manner in S. cerevisiae. We show that the transcriptional regulatory network governing the ribosomal expression program of two related yeast species has been massively reshaped in cis and trans. Changes occurred in transcription factor wiring with cellular functions, movements in transcription factor hierarchies, DNA-binding specificity, and regulatory complexes assembly to promote global changes in the architecture of the fungal transcriptional regulatory network.

Transcriptional regulation of carbohydrate metabolism in the human pathogen Candida albicans.

Glycolysis is a metabolic pathway that is central to the assimilation of carbon for either respiration or fermentation and therefore is critical for the growth of all organisms. Consequently, glycolytic transcriptional regulation is important for the metabolic flexibility of pathogens in their attempts to colonize diverse niches. We investigated the transcriptional control of carbohydrate metabolism in the human fungal pathogen Candida albicans and identified two factors, Tye7p and Gal4p, as key regulators of glycolysis. When respiration was inhibited or oxygen was limited, a gal4tye7 C. albicans strain showed a severe growth defect when cultured on glucose, fructose or mannose as carbon sources. The gal4tye7 strain displayed attenuated virulence in both Galleria and mouse models as well, supporting the connection between pathogenicity and metabolism. Chromatin immunoprecipitation coupled with microarray analysis (ChIP-CHIP) and transcription profiling revealed that Tye7p bound the promoter sequences of the glycolytic genes and activated their expression during growth on either fermentable or non-fermentable carbon sources. Gal4p also bound the glycolytic promoter sequences and activated the genes although to a lesser extent than Tye7p. Intriguingly, binding and activation by Gal4p was carbon source-dependent and much stronger during growth on media containing fermentable sugars than on glycerol. Furthermore, Tye7p and Gal4p were responsible for the complete induction of the glycolytic genes under hypoxic growth conditions. Tye7p and Gal4p also regulated unique sets of carbohydrate metabolic genes; Tye7p bound and activated genes involved in trehalose, glycogen, and glycerol metabolism, while Gal4p regulated the pyruvate dehydrogenase complex. This suggests that Tye7p represents the key transcriptional regulator of carbohydrate metabolism in C. albicans and Gal4p provides a carbon source-dependent fine-tuning of gene expression while regulating the metabolic flux between respiration and fermentation pathways.

Rearrangements of the transcriptional regulatory networks of metabolic pathways in fungi.

Growing evidence suggests that transcriptional regulatory networks in many organisms are highly flexible. Here, we discuss the evolution of transcriptional regulatory networks governing the metabolic machinery of sequenced ascomycetes. In particular, recent work has shown that transcriptional rewiring is common in regulons controlling processes such as production of ribosome components and metabolism of carbohydrates and lipids. We note that dramatic rearrangements of the transcriptional regulatory components of metabolic functions have occurred among ascomycetes species.

Widespread occurrence of chromosomal aneuploidy following the routine production of Candida albicans mutants.

It has come to our attention that approximately 35% of >100 published microarray datasets, where transcript levels were compared between two different strains, exhibit some form of chromosome-specific bias. While some of these arose from the use of strains whose aneuploidies were not known at the time, in a worrisome number of cases the recombinant strains have acquired additional aneuploidies that were not initially present in the parental strain. The aneuploidies often affected a different chromosome than the one harboring the insertion site. The affected strains originated from either CAI-4, RM1000, BWP17 or SN95 and were produced through a variety of strategies. These observations suggest that aneuploidies frequently occur during the production of recombinant strains and have an effect on global transcript profiles outside of the afflicted chromosome(s), thus raising the possibility of unintended phenotypic consequences. Thus, we propose that all Candida albicans mutants and strains should be tested for aneuploidy before being used in further studies. To this end, we describe a new rapid testing method, based on a multiplex quantitative PCR assay, that produces eight bands of distinct sizes from either the left or right arms of each C. albicans chromosome.

Transcriptional analysis of the Candida albicans cell cycle.

We have examined the periodic expression of genes through the cell cycle in cultures of the human pathogenic fungus Candida albicans synchronized by mating pheromone treatment. Close to 500 genes show increased expression during the G1, S, G2, or M transitions of the C. albicans cell cycle. Comparisons of these C. albicans periodic genes with those already found in the budding and fission yeasts and in human cells reveal that of 2200 groups of homologous genes, close to 600 show periodicity in at least one organism, but only 11 are periodic in all four species. Overall, the C. albicans regulatory circuit most closely resembles that of Saccharomyces cerevisiae but contains a simplified structure. Although the majority of the C. albicans periodically regulated genes have homologues in the budding yeast, 20% (100 genes), most of which peak during the G1/S or M/G1 transitions, are unique to the pathogenic yeast.