Genomic Plasticity of the Human Fungal Pathogen Candida albicans

The genomic plasticity of Candida albicans, a commensal and common opportunistic fungal pathogen, continues to reveal unexpected surprises. Once thought to be asexual, we now know that the organism can generate genetic diversity through several mechanisms, including mating between cells of the opposite or of the same mating type and by a parasexual reduction in chromosome number that can be accompanied by recombination events (2, 12, 14, 53, 77, 115). In addition, dramatic genome changes can appear quite rapidly in mitotic cells propagated in vitro as well as in vivo. The detection of aneuploidy in other fungal pathogens isolated directly from patients (145) and from environmental samples (71) suggests that variations in chromosome organization and copy number are a common mechanism used by pathogenic fungi to rapidly generate diversity in response to stressful growth conditions, including, but not limited to, antifungal drug exposure. Since cancer cells often become polyploid and/or aneuploid, some of the lessons learned from studies of genome plasticity in C. albicans may provide important insights into how these processes occur in higher-eukaryotic cells exposed to stresses such as anticancer drugs.The purpose of this review is to describe the tools used to detect genome changes, to highlight recent advances in our understanding of large-scale chromosome changes that arise in Candida albicans, and to discuss the role of specific stresses in eliciting these genome changes. The types of genomic diversity that have been characterized suggest that C. albicans can undergo extreme genomic changes in order to survive stresses in the human host. We propose that C. albicans and other pathogens may have evolved mechanisms not only to tolerate but also to generate large-scale genetic variation as a means of adaptation.C. albicans is a polymorphic yeast with a 16-Mb (haploid) genome organized in 8 diploid chromosomes (140, 154, 203). The C. albicans genome displays a very high degree of plasticity. This plasticity includes the types of genomic changes frequently observed with cancer cells, including gross chromosomal rearrangements, aneuploidy, and loss of heterozygosity (reviewed in references 100, 117, and 157). Similar to somatic cancer cells, C. albicans reproduces primarily through asexual clonal division (65, 84). Nonetheless, it has retained much of the machinery needed for mating and meiosis (189), yet meiosis has never been observed (13, 120).C. albicans has two mating-type-like (MTL) alleles, MTLa and MTLα (76). The MTL locus is on the left arm of chromosome 5 (Chr5), approximately 80 kbp from the centromere. Most C. albicans isolates are heterozygous for the MTL locus, but approximately 3 to 10% of clinical isolates are naturally homozygous at MTL (104, 108). Mating can occur between strains carrying the opposite MTL locus, and most strains that were found to be naturally MTL homozygous are mating competent (104, 108). MTL-homozygous strains were also constructed from MTL-heterozygous strains by deletion of either the MTLa or MTLα locus (77) or by selection for Chr5 loss on sorbose (87, 115).Mating between these diploid strains of opposite mating type can occur both in vitro (115) and in vivo (77, 97). The products are tetraploid and do not undergo a conventional meiotic reduction in ploidy (12, 120). Rather, they undergo random loss of multiple chromosomes, a process termed “concerted chromosome loss,” until they reach a near-diploid genome content (2, 12, 53, 85). A subset of these cells also undergoes multiple gene conversion events reminiscent of meiotic recombination, and most remain trisomic for one to several chromosomes (53). While mating and concerted chromosome loss have been induced in the laboratory, the role of the parasexual cycle during the host-pathogen interaction and in the response to stresses, such as exposure to antifungal drugs, remains unclear. The prevailing model is that adaptive mutations (such as those that occur with the acquisition of drug resistance) evolve through somatic events, including point mutations, recombination, gene conversion, loss of heterozygosity, and/or aneuploidy (13).     

Splitting the BLOSUM Score into Numbers of Biological Significance

Mathematical tools developed in the context of Shannon information theory were used to analyze the meaning of the BLOSUM score, which was split into three components termed as the BLOSUM spectrum (or BLOSpectrum). These relate respectively to the sequence convergence (the stochastic similarity of the two protein sequences), to the background frequency divergence (typicality of the amino acid probability distribution in each sequence), and to the target frequency divergence (compliance of the amino acid variations between the two sequences to the protein model implicit in the BLOCKS database). This treatment sharpens the protein sequence comparison, providing a rationale for the biological significance of the obtained score, and helps to identify weakly related sequences. Moreover, the BLOSpectrum can guide the choice of the most appropriate scoring matrix, tailoring it to the evolutionary divergence associated with the two sequences, or indicate if a compositionally adjusted matrix could perform better.[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29]     

Analysis of Free Energy Signals Arising from Nucleotide Hybridization Between rRNA and mRNA Sequences during Translation in Eubacteria

A decoding algorithm is tested that mechanistically models the progressive alignments that arise as the mRNA moves past the rRNA tail during translation elongation. Each of these alignments provides an opportunity for hybridization between the single-stranded, -terminal nucleotides of the 16S rRNA and the spatially accessible window of mRNA sequence, from which a free energy value can be calculated. Using this algorithm we show that a periodic, energetic pattern of frequency 1/3 is revealed. This periodic signal exists in the majority of coding regions of eubacterial genes, but not in the non-coding regions encoding the 16S and 23S rRNAs. Signal analysis reveals that the population of coding regions of each bacterial species has a mean phase that is correlated in a statistically significant way with species () content. These results suggest that the periodic signal could function as a synchronization signal for the maintenance of reading frame and that codon usage provides a mechanism for manipulation of signal phase.[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32]     

Algorithms for Finding Small Attractors in Boolean Networks

A Boolean network is a model used to study the interactions between different genes in genetic regulatory networks. In this paper, we present several algorithms using gene ordering and feedback vertex sets to identify singleton attractors and small attractors in Boolean networks. We analyze the average case time complexities of some of the proposed algorithms. For instance, it is shown that the outdegree-based ordering algorithm for finding singleton attractors works in time for , which is much faster than the naive time algorithm, where is the number of genes and is the maximum indegree. We performed extensive computational experiments on these algorithms, which resulted in good agreement with theoretical results. In contrast, we give a simple and complete proof for showing that finding an attractor with the shortest period is NP-hard.[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32]