Evolutionary Perspectives on Human Fungal Pathogens.

Developing Galleria mellonella as a model host for human pathogens

Fungi represent a central yet often overlooked domain of clinically relevant pathogens that have become increasingly important in human disease. With unique adaptive lifestyles that vary widely across species, human fungal pathogens show remarkable diversity in their virulence strategies. The majority of these fungal pathogens are opportunistic, primarily existing in the environment or as commensals that take advantage of immunocompromised hosts to cause disease. In addition, many fungal pathogens have evolved from non-pathogenic lifestyles. The extent of genetic diversity and heritability of virulence traits remains poorly explored in human fungal pathogens. Genetic variation caused by mutations, genomic rearrangements, gene gain or loss, changes in ploidy, and sexual reproduction have profound effects on genetic diversity. These mechanisms contribute to the remarkable diversity of fungal genomes and have large impacts on their prevalence in human disease, virulence, and resistance to antifungal therapies. Here, we focus on the genomic structure of the most common human fungal pathogens and the aspects of genetic variability that contribute to their dominance in human disease.

Antifungal and antibacterial activities of crude extracts of carpophore compared with those of sclerotium of Pleurotus tuber-regium were investigated on 11 species of bacterial and 3 fungal human pathogens. The minimal inhibitory concentration (MIC) of carpophore extract was recorded to be 12.5 mg/mL on Bacillus subtilis, Enterococcus faecalis, Staphylococcus epidermidis, Escherichia cloacae, Proteus mirabilis, P. vulgaris, Klebsiella oxytoca, and K. aerogenes and 6.25 mg/mL on Staphylococcus aureus, Escherichia coli, and Mycobacterium smegmatis as well as on all three species of fungal pathogens including Candida albicans, Aspergillus fumigatus, and A. ochraceus. In comparison, the MIC of sclerotium was recorded to be 12.5 mg/mL on Bacillus subtilis and Klebsiella aerogenes; 6.25 mg/mL on Enterococcus faecalis, Staphylococcus aureus, S. epidermidis, Enterobacter cloacae, E. coli, Mycobacterium smegmatis, Proteus mirabilis, P. vulgaris, and Klebsiella oxytoca; and 3.13 mg/mL on the three fungal pathogens. Based on the abovementioned figures, it appears that strains of pathogenic fungi tested are much more sensitive to crude extracts than the abovementioned bacteria. In fact, antimicrobial activities of crude extracts of P. tuber-regium, no matter whether it is that of the carpophore or its sclerotium, are in general stronger on human pathogenic fungi than bacteria. These figures also demonstrate that crude extracts of sclerotium show a higher antimicrobial activity than that of carpophore. Carpophores and sclerotia of P. tuber-regium could therefore constitute a source of new molecules potentially more efficient than synthetic products against some human pathogenic fungi and bacteria.

Introduction In the previous chapters, we had discussed methods for studying the genetic content of bacteria on a genomic scale. In the process, we highlighted characteristics of certain bacterial genomes, besides discussing properties common to many bacterial genomes. We also documented intra-specific variation in gene content between bacteria. Different strains of the same bacterial species might show considerable variation in gene content, as a result of mutations getting fixed in a particular context, or the dynamics of gene acquisition and loss. Many of these variations might arise from selection resulting from their niches and/or lifestyles. However, this does not reflect the fact that the same bacterium might be phenotypically distinct under different environmental or cellular contexts. Much of these differences might be attributed to gene expression changes, i.e., under a given condition, a bacterium expresses only a subset of its genes, with the remaining genes being silent. Or, the expression level of the same gene might be quantitatively different between two conditions, in contrast to the dramatic on–off distinction made by the previous statement. Thus, the genetic content of a bacterium can be interpreted by a ‘gene expression machinery’ in different ways at different times. The expression of genes, and the manner in which it is regulated, have been studied in recent years using genome-scale techniques. Many of these approaches use DNA microarrays or next-generation sequencing, the basics of which have been covered in the previous two chapters. In the present, core chapter of this book, we will discuss the application of these technologies to the study of gene expression and its control in bacteria. The discussion of techniques and data analysis will focus on gene expression measurements and investigation of genomic regions that bind to a protein of interest. We will also present particular exemplary research as case studies in the process.

Rtf1 is generally considered to be a subunit of the Paf1 complex (Paf1C), which is a multifunctional protein complex involved in histone modification and RNA biosynthesis at multiple stages. Rtf1 is stably associated with the Paf1C in Saccharomyces cerevisiae, but not in other species including humans. Little is known about its function in human fungal pathogens. Here, we show that Rtf1 is required for facilitating H2B monoubiquitination (H2Bub1), and regulates fungal morphogenesis and pathogenicity in the meningitis-causing fungal pathogen Cryptococcus neoformans. Rtf1 is not tightly associated with the Paf1C, and its histone modification domain (HMD) is sufficient to promote H2Bub1 and the expression of genes related to fungal mating and filamentation. Moreover, Rtf1 HMD fully restores fungal morphogenesis and pathogenicity; however, it fails to restore defects of thermal tolerance and melanin production in the rtf1Δ strain background. The present study establishes a role for cryptococcal Rtf1 as a Paf1C-independent regulator in regulating fungal morphogenesis and pathogenicity, and highlights the function of HMD in facilitating global H2Bub1 in C. neoformans.

Variation in protein gene and intron content among land plant mitogenomes

Knowing the full set of essential genes for a given organism provides important information about ways to promote, and to limit, its growth and survival. For many non-model organisms, the lack of a stable haploid state and low transformation efficiencies impede the use of conventional approaches to generate a genome-wide comprehensive set of mutant strains and the identification of the genes essential for growth. Here we report on the isolation and utilization of a highly stable haploid derivative of the human pathogenic fungus Candida albicans, together with a modified heterologous transposon and machine learning (ML) analysis method, to predict the degree to which all of the open reading frames are required for growth under standard laboratory conditions. We identified 1,610 C. albicans essential genes, including 1,195 with high “essentiality confidence” scores, thereby increasing the number of essential genes (currently 66 in the Candida Genome Database) by >20-fold and providing an unbiased approach to determine the degree of confidence in the determination of essentiality. Among the genes essential in C. albicans were 602 genes also essential in the model budding and fission yeasts analyzed by both deletion and transposon mutagenesis. We also identified essential genes conserved among the four major human pathogens C. albicans, Aspergillus fumigatus, Cryptococcus neoformans, and Histoplasma capsulatum and highlight those that lack homologs in humans and that thus could serve as potential targets for the design of antifungal therapies. IMPORTANCE Comprehensive understanding of an organism requires that we understand the contributions of most, if not all, of its genes. Classical genetic approaches to this issue have involved systematic deletion of each gene in the genome, with comprehensive sets of mutants available only for very-well-studied model organisms. We took a different approach, harnessing the power of in vivo transposition coupled with deep sequencing to identify >500,000 different mutations, one per cell, in the prevalent human fungal pathogen Candida albicans and to map their positions across the genome. The transposition approach is efficient and less labor-intensive than classic approaches. Here, we describe the production and analysis (aided by machine learning) of a large collection of mutants and the comprehensive identification of 1,610 C. albicans genes that are essential for growth under standard laboratory conditions. Among these C. albicans essential genes, we identify those that are also essential in two distantly related model yeasts as well as those that are conserved in all four major human fungal pathogens and that are not conserved in the human genome. This list of genes with functions important for the survival of the pathogen provides a good starting point for the development of new antifungal drugs, which are greatly needed because of the emergence of fungal pathogens with elevated resistance and/or tolerance of the currently limited set of available antifungal drugs.

Since ancient times, man has been observing not only diversities but also similarities that existed in the plant world. Similarities among certain species have long been predominantly used in the botanical systematisation. Thus, for instance, while studying the evolution of various plant and animal species, Darwin realised that there was a parallelism in the variation both within one species and between/among related species. According to many scientists and systematists, the similarity among plant species is inversely proportional to their evolutionary distance, and a greater distance means greater differences in traits of individual species. At the beginning of the 20th century, this regularity, even at the morphological level, was recognised and described by the Russian scientist Vavilov, calling it the law of homologous series. Studying collections of cultivated plants and their relatives from different parts of the world, Vavilov noticed that individual series of expressions of certain traits were regularly repeated in related species. Based on this regularity, this scientist could have predicted the existence of a trait in species in which it was as yet unknown. The observed differences and similarities at the morphological level have long been assumed to have their basis at the molecular level, in the genetic background/hereditary basis. At the end of the 20th century, the development of molecular biology led to the elucidation of the genetic code of the hereditary basis and provided establishing of a new scientific discipline, called comparative genomics. Comparative genetics is a science in which differences and similarities of related species are observed at the level of individual traits and genes that tends to explain traits from the evolutionary perspective and to determin to what extent the variation of individual traits is a result of orthologous genes, i.e. genes of the same origin. Comparative genomics is a scientific discipline in which similarities and differences in related species are studied not only at the level of individual genes, but at the level of the whole genome. It is considered that almost entire experimental biology will be, in the near future, based on hypotheses derived from comparisons of genes and genomes of related organisms, indicating the importance of comparative genetics and genomics. In practical sense, knowledge of homologous series in variation of traits within a species, between species and genera, that is knowledge of the laws of comparative genetics and genomics, is of great importance in breeding of plants with new traits. Cereal comparative genomics has been evolving for the past 25 years along side with the development of molecular genetics, providing better understanding of the evolution of cultivated species of the grass family, better comprehension of many important biological processes and invention of tools to be used in selection and breeding. Darwin's theoretical assumptions, especially of Vavilov's law of homologous series of variation, have come to full confirmation. Technological improvements in sequencing techniques have enabled decoding of genomes of many organisms, but also a complete application of laws of comparative genetics and genomics. On the other hand, the traditional approach to genetic and molecular studies has led to mapping and isolation of many different genes controlling regulating instead of controlling resistance to viruses and diseases, but also to important breeding traits in barley and wheat. Wholegenome sequencing of barley and wheat will in the near future provide efficient breeding for many traits at the allele level/for many allele-level traits, thus contributing to a broader genetic basis of all breeding-relevant traits in cereals. Comparative genomics will be extremely important, and it will play a special role in the isolation of important genes in cereals with large genomes in the vicinity of centromeres.

Lifting the veil on fungal toxins.

The wealth of genomic data in bacteria is helping microbiologists understand the factors involved in gene innovation. Among these, the expansion and reduction of gene families appears to have a fundamental role in this, but the factors influencing gene family size are unclear. The relative content of paralogous genes in bacterial genomes increases with genome size, largely due to the expansion of gene family size in large genomes. Bacteria undergoing genome reduction display a parallel process of redundancy elimination, by which gene families are reduced to one or a few members. Gene family size is also influenced by sequence divergence and physiological function. Large gene families show wider sequence divergence, suggesting they are probably older, and certain functions (such as metabolite transport mechanisms) are overrepresented in large families. The size of a given gene family is remarkably similar in strains of the same species and in closely related species, suggesting that homologous gene families are vertically transmitted and depend little on horizontal gene transfer (HGT). The remarkable preservation of copy numbers in widely different ecotypes indicates a functional role for the different copies rather than simply a back-up role. When different genera are compared, the increase in phylogenetic distance and/or ecological specialization disrupts this preservation, albeit in a gradual manner and maintaining an overall similarity, which also supports this view. HGT can have an important role, however, in nonhomologous gene families, as exemplified by a comparison between saprophytic and enterohemorrhagic strains of Escherichia coli.

This chapter examines how cell identity influences mating-type determination, particularly in fungal pathogens. It explores cases where cell identity plays roles outside of mating type, affects cell morphology, and influences pathogenesis. The chapter begins with a description of cell type determination in the budding yeast Saccharomyces cerevisiae and uses this as a platform for exploring mechanisms in the human fungal pathogens Candida albicans and Cryptococcus neoformans as well as the plant fungal pathogen Ustilago maydis. It concludes with a short description of the influence of cell identity on the behaviors of several other plant and human fungal pathogens and how cell identity in fungi is evolving to encompass a more diverse array of fungal behaviors. A fungal pathogen in which cell identity determination has come to the fore is in the basidiomycete fungus C. neoformans. There are two obvious possibilities for specifying haploid cell identity: either the pheromone and pheromone receptor alleles in each mating type have diverged from one another sufficiently to confer pheromone-receptor binding specificity, or there are other factors or mechanisms at play in determining haploid cell types. The authors will continue to discover new strategies undertaken by the pathogenic fungi to develop and integrate multiple cell identities in the effort to survive.

Having the ability to predict the protein-encoding gene content of an incomplete genome or metagenome-assembled genome is important for a variety of bioinformatic tasks. In this study, as a proof of concept, we built machine learning classifiers for predicting variable gene content in Escherichia coli genomes using only the nucleotide k-mers from a set of 100 conserved genes as features. Protein families were used to define orthologs, and a single classifier was built for predicting the presence or absence of each protein family occurring in 10%-90% of all E. coli genomes. The resulting set of 3,259 extreme gradient boosting classifiers had a per-genome average macro F1 score of 0.944 [0.943-0.945, 95% CI]. We show that the F1 scores are stable across multi-locus sequence types and that the trend can be recapitulated by sampling a smaller number of core genes or diverse input genomes. Surprisingly, the presence or absence of poorly annotated proteins, including "hypothetical proteins" was accurately predicted (F1 = 0.902 [0.898-0.906, 95% CI]). Models for proteins with horizontal gene transfer-related functions had slightly lower F1 scores but were still accurate (F1s = 0.895, 0.872, 0.824, and 0.841 for transposon, phage, plasmid, and antimicrobial resistance-related functions, respectively). Finally, using a holdout set of 419 diverse E. coli genomes that were isolated from freshwater environmental sources, we observed an average per-genome F1 score of 0.880 [0.876-0.883, 95% CI], demonstrating the extensibility of the models. Overall, this study provides a framework for predicting variable gene content using a limited amount of input sequence data. IMPORTANCE Having the ability to predict the protein-encoding gene content of a genome is important for assessing genome quality, binning genomes from shotgun metagenomic assemblies, and assessing risk due to the presence of antimicrobial resistance and other virulence genes. In this study, we built a set of binary classifiers for predicting the presence or absence of variable genes occurring in 10%-90% of all publicly available E. coli genomes. Overall, the results show that a large portion of the E. coli variable gene content can be predicted with high accuracy, including genes with functions relating to horizontal gene transfer. This study offers a strategy for predicting gene content using limited input sequence data.

During the course of evolution, genomes can undergo large-scale mutation events such as rearrangement and lateral transfer. Such mutations can result in significant variations in gene order and gene content among otherwise closely related organisms. The Mauve genome alignment system can successfully identify such rearrangement and lateral transfer events in comparisons of multiple microbial genomes even under high levels of recombination. This chapter outlines the main features of Mauve and provides examples that describe how to use Mauve to conduct a rigorous multiple genome comparison and study evolutionary patterns.

Fungi are major causes of human, animal and plant disease. Human fungal infections can be fatal, but there are limited options for therapy, and resistance to commonly used anti-fungal drugs is widespread. The genomes of many fungi have recently been sequenced, allowing identification of proteins that may become targets for novel therapies. We examined the genomes of human fungal pathogens for genes encoding homologues of cation channels, which are prominent drug targets. Many of the fungal genomes examined contain genes encoding homologues of potassium (K+), calcium (Ca2+) and transient receptor potential (Trp) channels, but not sodium (Na+) channels or ligand-gated channels. Some fungal genomes contain multiple genes encoding homologues of K+ and Trp channel subunits, and genes encoding novel homologues of voltage-gated Kv channel subunits are found in Cryptococcus spp. Only a single gene encoding a homologue of a plasma membrane Ca2+ channel was identified in the genome of each pathogenic fungus examined. These homologues are similar to the Cch1 Ca2+ channel of Saccharomyces cerevisiae. The genomes of Aspergillus spp. and Cryptococcus spp., but not those of S. cerevisiae or the other pathogenic fungi examined, also encode homologues of the mitochondrial Ca2+ uniporter (MCU). In contrast to humans, which express many K+, Ca2+ and Trp channels, the genomes of pathogenic fungi encode only very small numbers of K+, Ca2+ and Trp channel homologues. Furthermore, the sequences of fungal K+, Ca2+, Trp and MCU channels differ from those of human channels in regions that suggest differences in regulation and susceptibility to drugs.

It has been repeatedly reported that transposable elements (TE) become active and/or mobile in the genomes of replicatively and stress-induced senescent mammalian cells. However, the biological role of senescence-associated transposon activation and its occurrence and relevance in other eukaryotic cells remain to be elucidated. In the present study, Candida albicans, a prevalent opportunistic fungal pathogen in humans, was used to analyze changes in gene copy number of selected TE, namely Cirt2, Moa and Cmut1 during long-term culture (up to 90 days). The effects of stress stimuli (fluconazole, hydrogen peroxide, hypochlorite) and ploidy state (haploid, diploid, tetraploid cells) were also considered. An increase in copy number of Cirt2 and Moa was the most accented in tetraploid cells after 90 days of culture that was accompanied by changes in karyotype patterns and slightly more limited growth rate compared to haploid and diploid cells. Stress stimuli did not potentiate TE activity. Elevation in chromosomal DNA breaks was also observed during long-term culture of cells of different ploidy, however this was not correlated with increased TE activity. Our results suggest that increased TE activity may promote genomic diversity and plasticity, and cellular heterogeneity during long-term culture of C. albicans cells.