106 research outputs found
Identification of metabolic pathways influenced by the G-protein coupled receptors GprB and GprD in Aspergillus nidulans
Heterotrimeric G-protein-mediated signaling pathways play a pivotal role in transmembrane signaling in eukaryotes. Our main aim was to identify signaling pathways regulated by A. nidulans GprB and GprD G-protein coupled receptors (GPCRs). When these two null mutant strains were compared to the wild-type strain, the DeltagprB mutant showed an increased protein kinase A (PKA) activity while growing in glucose 1% and during starvation. In contrast, the DeltagprD has a much lower PKA activity upon starvation. Transcriptomics and (1)H NMR-based metabolomics were performed on two single null mutants grown on glucose. We noted modulation in the expression of 11 secondary metabolism gene clusters when the DeltagprB and DeltagprD mutant strains were grown in 1% glucose. Several members of the sterigmatocystin-aflatoxin gene cluster presented down-regulation in both mutant strains. The genes of the NR-PKS monodictyphenone biosynthesis cluster had overall increased mRNA accumulation in DeltagprB, while in the DeltagprD mutant strain the genes had decreased mRNA accumulation. Principal component analysis of the metabolomic data demonstrated that there was a significant metabolite shift in the DeltagprD strain. The (1)H NMR analysis revealed significant expression of essential amino acids with elevated levels in the DeltagprD strain, compared to the wild-type and DeltagprB strains. With the results, we demonstrated the differential expression of a variety of genes related mainly to secondary metabolism, sexual development, stress signaling, and amino acid metabolism. We propose that the absence of GPCRs triggered stress responses at the genetic level. The data suggested an intimate relationship among different G-protein coupled receptors, fine-tune regulation of secondary and amino acid metabolisms, and fungal development
An efficient gene deletion procedure for the mushroom-forming basidiomycete Schizophyllum commune
Chromosomal Rearrangements between Serotype A and D Strains in Cryptococcus neoformans
Cryptococcus neoformans is a major human pathogenic fungus that can cause meningoencephalitis in immunocompromised hosts. It contains two divergent varieties, var. grubii (serotype A) and var. neoformans (serotype D), as well as hybrids (serotype AD) between these two varieties. In this study, we investigated the extent of chromosomal rearrangements between the two varieties, estimated the effects of chromosomal rearrangements on recombination frequencies, and surveyed the potential polymorphisms of the rearrangements among natural strains of the three serotypes. Through the analyses of two sequenced genomes from strains H99 (representing var. grubii) and JEC21 (representing var. neoformans), we revealed a total of 32 unambiguous chromosome rearrangements, including five translocations, nine simple inversions, and 18 complex rearrangements. Our analyses identified that overall, rearranged regions had recombination frequencies about half of those around syntenic regions. Using a direct PCR screening strategy, we examined the potential polymorphisms of 11 rearrangements among 64 natural C. neoformans strains from five countries. We found no polymorphism within var. neoformans and very limited polymorphism within var. grubii. However, strains of serotype AD showed significant polymorphism, consistent with their hybrid origins coupled with differential loss of heterozygosity. We discuss the implications of these results on the genome structure, ecology, and evolution of C. neoformans
ISOLATION OF Cryptococcus neoformans FROM ENVIRONMENTAL SAMPLES COLLECTED IN SOUTHEASTERN NIGERIA
SUMMARY Cryptococcosis caused by Cryptococcus neoformans is the second most common fungal opportunistic pathogen and a lifethreatening infection with serious clinical manifestations especially in HIV/AIDS and other immunocompromised patients. In Nigeria, HIV/AIDS infection has reached an alarming level. Despite this, information on the presence of this fungus in clinical and environmental samples is very scanty in Nigeria and many other parts of Africa. We set out to evaluate the presence of Cryptococcus neoformans or C. gattii in pigeon droppings obtained from Southeastern Nigeria. One hundred and seventy-seven samples of pigeon droppings from six sample types were collected. The area covered comprised of ten cities and other locations spanning across five States in Nigeria. Using established techniques, Cryptococcus neoformans was isolated from 39 of the 177 (22.0%) samples overall. No C. gattiiwas isolated. Most of the isolates (32.4%) were recovered from dovecotes (11 of 34) followed closely by samples taken from markets (31.8%; seven of 22) and least from the church (4.0%; one of 25). The highest isolation rate (38.9%) was found in samples from Enugu-Ezike(seven of 23) while the least came from Afikpoand the other locations each with 9.1% isolation rate. This is the first large-scale screening of Cryptococcus neoformans from pigeon droppings in Nigeria. The ecological and epidemiological significance of these findings are discussed
Maximal Extraction of Biological Information from Genetic Interaction Data
Targeted genetic perturbation is a powerful tool for inferring gene function in model organisms. Functional relationships between genes can be inferred by observing the effects of multiple genetic perturbations in a single strain. The study of these relationships, generally referred to as genetic interactions, is a classic technique for ordering genes in pathways, thereby revealing genetic organization and gene-to-gene information flow. Genetic interaction screens are now being carried out in high-throughput experiments involving tens or hundreds of genes. These data sets have the potential to reveal genetic organization on a large scale, and require computational techniques that best reveal this organization. In this paper, we use a complexity metric based in information theory to determine the maximally informative network given a set of genetic interaction data. We find that networks with high complexity scores yield the most biological information in terms of (i) specific associations between genes and biological functions, and (ii) mapping modules of co-functional genes. This information-based approach is an automated, unsupervised classification of the biological rules underlying observed genetic interactions. It might have particular potential in genetic studies in which interactions are complex and prior gene annotation data are sparse
Allelic Exchange of Pheromones and Their Receptors Reprograms Sexual Identity in Cryptococcus neoformans
Cell type specification is a fundamental process that all cells must carry out to ensure appropriate behaviors in response to environmental stimuli. In fungi, cell identity is critical for defining “sexes” known as mating types and is controlled by components of mating type (MAT) loci. MAT–encoded genes function to define sexes via two distinct paradigms: 1) by controlling transcription of components common to both sexes, or 2) by expressing specially encoded factors (pheromones and their receptors) that differ between mating types. The human fungal pathogen Cryptococcus neoformans has two mating types (a and α) that are specified by an extremely unusual MAT locus. The complex architecture of this locus makes it impossible to predict which paradigm governs mating type. To identify the mechanism by which the C. neoformans sexes are determined, we created strains in which the pheromone and pheromone receptor from one mating type (a) replaced the pheromone and pheromone receptor of the other (α). We discovered that these “αa” cells effectively adopt a new mating type (that of a cells); they sense and respond to α factor, they elicit a mating response from α cells, and they fuse with α cells. In addition, αa cells lose the α cell type-specific response to pheromone and do not form germ tubes, instead remaining spherical like a cells. Finally, we discovered that exogenous expression of the diploid/dikaryon-specific transcription factor Sxi2a could then promote complete sexual development in crosses between α and αa strains. These data reveal that cell identity in C. neoformans is controlled fully by three kinds of MAT–encoded proteins: pheromones, pheromone receptors, and homeodomain proteins. Our findings establish the mechanisms for maintenance of distinct cell types and subsequent developmental behaviors in this unusual human fungal pathogen
The Mating-Type Chromosome in the Filamentous Ascomycete Neurospora tetrasperma Represents a Model for Early Evolution of Sex Chromosomes
We combined gene divergence data, classical genetics, and phylogenetics to study the evolution of the mating-type chromosome in the filamentous ascomycete Neurospora tetrasperma. In this species, a large non-recombining region of the mating-type chromosome is associated with a unique fungal life cycle where self-fertility is enforced by maintenance of a constant state of heterokaryosis. Sequence divergence between alleles of 35 genes from the two single mating-type component strains (i.e. the homokaryotic mat A or mat a-strains), derived from one N. tetrasperma heterokaryon (mat A+mat a), was analyzed. By this approach we were able to identify the boundaries and size of the non-recombining region, and reveal insight into the history of recombination cessation. The non-recombining region covers almost 7 Mbp, over 75% of the chromosome, and we hypothesize that the evolution of the mating-type chromosome in this lineage involved two successive events. The first event was contemporaneous with the split of N. tetrasperma from a common ancestor with its outcrossing relative N. crassa and suppressed recombination over at least 6.6 Mbp, and the second was confined to a smaller region in which recombination ceased more recently. In spite of the early origin of the first “evolutionary stratum”, genealogies of five genes from strains belonging to an additional N. tetrasperma lineage indicate independent initiations of suppressed recombination in different phylogenetic lineages. This study highlights the shared features between the sex chromosomes found in the animal and plant kingdoms and the fungal mating-type chromosome, despite fungi having no separate sexes. As is often found in sex chromosomes of plants and animals, recombination suppression of the mating-type chromosome of N. tetrasperma involved more than one evolutionary event, covers the majority of the mating-type chromosome and is flanked by distal regions with obligate crossovers
The Mating Type Locus (MAT) and Sexual Reproduction of Cryptococcus heveanensis: Insights into the Evolution of Sex and Sex-Determining Chromosomal Regions in Fungi
Mating in basidiomycetous fungi is often controlled by two unlinked, multiallelic loci encoding homeodomain transcription factors or pheromones/pheromone receptors. In contrast to this tetrapolar organization, Cryptococcus neoformans/Cryptococcus gattii have a bipolar mating system, and a single biallelic locus governs sexual reproduction. The C. neoformans MAT locus is unusually large (>100 kb), contains >20 genes, and enhances virulence. Previous comparative genomic studies provided insights into how this unusual MAT locus might have evolved involving gene acquisitions into two unlinked loci and fusion into one contiguous locus, converting an ancestral tetrapolar system to a bipolar one. Here we tested this model by studying Cryptococcus heveanensis, a sister species to the pathogenic Cryptococcus species complex. An extant sexual cycle was discovered; co-incubating fertile isolates results in the teleomorph (Kwoniella heveanensis) with dikaryotic hyphae, clamp connections, septate basidia, and basidiospores. To characterize the C. heveanensis MAT locus, a fosmid library was screened with C. neoformans/C. gattii MAT genes. Positive fosmids were sequenced and assembled to generate two large probably unlinked MAT gene clusters: one corresponding to the homeodomain locus and the other to the pheromone/receptor locus. Strikingly, two divergent homeodomain genes (SXI1, SXI2) are present, similar to the bE/bW Ustilago maydis paradigm, suggesting one or the other homeodomain gene was recently lost in C. neoformans/C. gattii. Sequencing MAT genes from other C. heveanensis isolates revealed a multiallelic homeodomain locus and at least a biallelic pheromone/receptor locus, similar to known tetrapolar species. Taken together, these studies reveal an extant C. heveanensis sexual cycle, define the structure of its MAT locus consistent with tetrapolar mating, and support the proposed evolutionary model for the bipolar Cryptococcus MAT locus revealing transitions in sexuality concomitant with emergence of a pathogenic clade. These studies provide insight into convergent processes that independently punctuated evolution of sex-determining loci and sex chromosomes in fungi, plants, and animals
Predicting Protein Phenotypes Based on Protein-Protein Interaction Network
BACKGROUND: Identifying associated phenotypes of proteins is a challenge of the modern genetics since the multifactorial trait often results from contributions of many proteins. Besides the high-through phenotype assays, the computational methods are alternative ways to identify the phenotypes of proteins. METHODOLOGY/PRINCIPAL FINDINGS: Here, we proposed a new method for predicting protein phenotypes in yeast based on protein-protein interaction network. Instead of only the most likely phenotype, a series of possible phenotypes for the query protein were generated and ranked according to the tethering potential score. As a result, the first order prediction accuracy of our method achieved 65.4% evaluated by Jackknife test of 1,267 proteins in budding yeast, much higher than the success rate (15.4%) of a random guess. And the likelihood of the first 3 predicted phenotypes including all the real phenotypes of the proteins was 70.6%. CONCLUSIONS/SIGNIFICANCE: The candidate phenotypes predicted by our method provided useful clues for the further validation. In addition, the method can be easily applied to the prediction of protein associated phenotypes in other organisms
Multiple TORC1-Associated Proteins Regulate Nitrogen Starvation-Dependent Cellular Differentiation in Saccharomyces cerevisiae
The budding yeast Saccharomyces cerevisiae undergoes differentiation into filamentous-like forms and invades the growth medium as a foraging response to nutrient and environmental stresses. These developmental responses are under the downstream control of effectors regulated by the cAMP/PKA and MAPK pathways. However, the upstream sensors and signals that induce filamentous growth through these signaling pathways are not fully understood. Herein, through a biochemical purification of the yeast TORC1 (Target of Rapamycin Complex 1), we identify several proteins implicated in yeast filamentous growth that directly associate with the TORC1 and investigate their roles in nitrogen starvation-dependent or independent differentiation in yeast.We isolated the endogenous TORC1 by purifying tagged, endogenous Kog1p, and identified associated proteins by mass spectrometry. We established invasive and pseudohyphal growth conditions in two S. cerevisiae genetic backgrounds (Σ1278b and CEN.PK). Using wild type and mutant strains from these genetic backgrounds, we investigated the roles of TORC1 and associated proteins in nitrogen starvation-dependent diploid pseudohyphal growth as well as nitrogen starvation-independent haploid invasive growth.We show that several proteins identified as associated with the TORC1 are important for nitrogen starvation-dependent diploid pseudohyphal growth. In contrast, invasive growth due to other nutritional stresses was generally not affected in mutant strains of these TORC1-associated proteins. Our studies suggest a role for TORC1 in yeast differentiation upon nitrogen starvation. Our studies also suggest the CEN.PK strain background of S. cerevisiae may be particularly useful for investigations of nitrogen starvation-induced diploid pseudohyphal growth
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