Whole-genome sequencing of Ganoderma boninense, the causal agent of basal stem rot disease in oil palm, via combined short- and long-read sequencing.

The hemibiotrophic Basidiomycete pathogen Ganoderma boninense (Gb) is the dominant causal agent of oil palm basal stem rot disease. Here, we report a complete chromosomal genome map of Gb using a combination of short-read Illumina and long-read Pacific Biosciences (PacBio) sequencing platforms combined with chromatin conformation capture data from the Chicago and Hi-C platforms. The genome was 55.87 Mb in length and assembled to a high contiguity (N50: 304.34 kb) of 12 chromosomes built from 112 scaffolds, with a total of only 4.34 Mb (~ 7.77%) remaining unplaced. The final assemblies were evaluated for completeness of the genome by using Benchmarking Universal Single Copy Orthologs (BUSCO) v4.1.4, and based on 4464 total BUSCO polyporales group searches, the assemblies yielded 4264 (95.52%) of the conserved orthologs as complete and only a few fragmented BUSCO of 42 (0.94%) as well as a missing BUSCO of 158 (3.53%). Genome annotation predicted a total of 21,074 coding genes, with a GC content ratio of 59.2%. The genome features were analyzed with different databases, which revealed 2471 Gene Ontology/GO (11.72%), 5418 KEGG (Kyoto Encyclopedia of Genes and Genomes) Orthologous/KO (25.71%), 13,913 Cluster of Orthologous Groups of proteins/COG (66.02%), 60 ABC transporter (0.28%), 1049 Carbohydrate-Active Enzymes/CAZy (4.98%), 4005 pathogen-host interactions/PHI (19%), and 515 fungal transcription factor/FTFD (2.44%) genes. The results obtained in this study provide deep insight for further studies in the future.

Aspergillus flavus pangenome (AflaPan) uncovers novel aflatoxin and secondary metabolite associated gene clusters.

BACKGROUND: Aspergillus flavus is an important agricultural and food safety threat due to its production of carcinogenic aflatoxins. It has high level of genetic diversity that is adapted to various environments. Recently, we reported two reference genomes of A. flavus isolates, AF13 (MAT1-2 and highly aflatoxigenic isolate) and NRRL3357 (MAT1-1 and moderate aflatoxin producer). Where, an insertion of 310 kb in AF13 included an aflatoxin producing gene bZIP transcription factor, named atfC. Observations of significant genomic variants between these isolates of contrasting phenotypes prompted an investigation into variation among other agricultural isolates of A. flavus with the goal of discovering novel genes potentially associated with aflatoxin production regulation. Present study was designed with three main objectives: (1) collection of large number of A. flavus isolates from diverse sources including maize plants and field soils; (2) whole genome sequencing of collected isolates and development of a pangenome; and (3) pangenome-wide association study (Pan-GWAS) to identify novel secondary metabolite cluster genes. RESULTS: Pangenome analysis of 346 A. flavus isolates identified a total of 17,855 unique orthologous gene clusters, with mere 41% (7,315) core genes and 59% (10,540) accessory genes indicating accumulation of high genomic diversity during domestication. 5,994 orthologous gene clusters in accessory genome not annotated in either the A. flavus AF13 or NRRL3357 reference genomes. Pan-genome wide association analysis of the genomic variations identified 391 significant associated pan-genes associated with aflatoxin production. Interestingly, most of the significantly associated pan-genes (94%; 369 associations) belonged to accessory genome indicating that genome expansion has resulted in the incorporation of new genes associated with aflatoxin and other secondary metabolites. CONCLUSION: In summary, this study provides complete pangenome framework for the species of Aspergillus flavus along with associated genes for pathogen survival and aflatoxin production. The large accessory genome indicated large genome diversity in the species A. flavus, however AflaPan is a closed pangenome represents optimum diversity of species A. flavus. Most importantly, the newly identified aflatoxin producing gene clusters will be a new source for seeking aflatoxin mitigation strategies and needs new attention in research.

Dissecting the genome sequence of a clinical isolated Cunninghamella bertholletiae Z2 strain with rich cytochrome P450 enzymes (Article).

Mucormycosis is receiving much more attention because of its high morbidity and extremely high mortality rate in immunosuppressed populations. In this study, we isolated a Cunnignhamella bertholletiae Z2 strain from a skin lesion of a 14 year, 9 months old girl with acute lymphoblastic leukemia who die of infection from the Z2 strain. Genome sequencing was performed after isolation and amplification of the Z2 strain to reveal potential virulence factors and pathogenic mechanisms. The results showed that the genome size of the Z2 strain is 30.9 Mb with 9213 genes. Mucoral specific virulence factor genes found are ARF, CalN, and CoTH, while no gliotoxin biosynthesis gene cluster was found, which is a known virulence factor in Aspergillus fumigatus adapted to the environment. The Z2 strain was found to have 69 cytochrome P450 enzymes, which are potential drug resistant targets. Sensitivity testing of Z2 showed it was only inhibited by amphotericin B and posaconazole. Detailed genomic information of the C. bertholletiae Z2 strain may provide useful data for treatment.

Predicting fungal secondary metabolite activity from biosynthetic gene cluster data using machine learning.

Fungal secondary metabolites (SMs) contribute to the diversity of fungal ecological communities, niches, and lifestyles. Many fungal SMs have one or more medically and industrially important activities (e.g., antifungal, antibacterial, and antitumor). The genes necessary for fungal SM biosynthesis are typically located right next to each other in the genome and are known as biosynthetic gene clusters (BGCs). However, whether fungal SM bioactivity can be predicted from specific attributes of genes in BGCs remains an open question. We adapted machine learning models that predicted SM bioactivity from bacterial BGC data with accuracies as high as 80% to fungal BGC data. We trained our models to predict the antibacterial, antifungal, and cytotoxic/antitumor bioactivity of fungal SMs on two data sets: (i) fungal BGCs (data set comprised of 314 BGCs) and (ii) fungal (314 BGCs) and bacterial BGCs (1,003 BGCs). We found that models trained on fungal BGCs had balanced accuracies between 51% and 68%, whereas training on bacterial and fungal BGCs had balanced accuracies between 56% and 68%. The low prediction accuracy of fungal SM bioactivities likely stems from the small size of the data set; this lack of data, coupled with our finding that including bacterial BGC data in the training data did not substantially change accuracies currently limits the application of machine learning approaches to fungal SM studies. With >15,000 characterized fungal SMs, millions of putative BGCs in fungal genomes, and increased demand for novel drugs, efforts that systematically link fungal SM bioactivity to BGCs are urgently needed.IMPORTANCEFungi are key sources of natural products and iconic drugs, including penicillin and statins. DNA sequencing has revealed that there are likely millions of biosynthetic pathways in fungal genomes, but the chemical structures and bioactivities of >99% of natural products produced by these pathways remain unknown. We used artificial intelligence to predict the bioactivities of diverse fungal biosynthetic pathways. We found that the accuracies of our predictions were generally low, between 51% and 68%, likely because the natural products and bioactivities of only very few fungal pathways are known. With >15,000 characterized fungal natural products, millions of putative biosynthetic pathways present in fungal genomes, and increased demand for novel drugs, our study suggests that there is an urgent need for efforts that systematically identify fungal biosynthetic pathways, their natural products, and their bioactivities.

Polyploidy is widespread in Microsporidia.

Microsporidia are obligate intracellular eukaryotic parasites with an extremely broad host range. They have both economic and public health importance. Ploidy in microsporidia is variable, with a few species formally identified as diploid and one as polyploid. Given the increase in the number of studies sequencing microsporidian genomes, it is now possible to assess ploidy levels across all currently explored microsporidian diversity. We estimate ploidy for all microsporidian data sets available on the Sequence Read Archive using k-mer-based analyses, indicating that polyploidy is widespread in Microsporidia and that ploidy change is dynamic in the group. Using genome-wide heterozygosity estimates, we also show that polyploid microsporidian genomes are relatively homozygous, and we discuss the implications of these findings on the timing of polyploidization events and their origin.IMPORTANCEMicrosporidia are single-celled intracellular parasites, distantly related to fungi, that can infect a broad range of hosts, from humans all the way to protozoans. Exploiting the wealth of microsporidian genomic data available, we use k-mer-based analyses to assess ploidy status across the group. Understanding a genome's ploidy is crucial in order to assemble it effectively and may also be relevant for better understanding a parasite's behavior and life cycle. We show that tetraploidy is present in at least six species in Microsporidia and that these polyploidization events are likely to have occurred independently. We discuss why these findings may be paradoxical, given that Microsporidia, like other intracellular parasites, have extremely small, reduced genomes.

Single-cell genomics reveals new rozellid lineages and supports their sister relationship to Microsporidia.

The phylum Rozellomycota has been proposed for a group of early-branching holomycotan lineages representing obligate parasites and hyperparasites of zoosporic fungi, oomycotes or phytoplankton. Given their predominantly intracellular lifestyle, rozellids are typically known from environmental ribosomal DNA data, except for the well-studied Rozella species. To date, the phylogenetic relationship between rozellids and microsporidians (Microsporidia) is not fully understood and most reliable hypotheses are based on phylogenomic analyses that incorporate the only publicly available rozellid genome of Rozella allomycis. Here, we provide genomic data of three new rozellid lineages obtained by single-cell sequencing from environmental samples and show with a phylogenomic approach that rozellids form a monophyletic group that is sister to microsporidians, corroborating the previously proposed phylum Rozellomycota. Whereas no mitochondrial genes coding for the respiratory Complex I could be found, we discovered a gene coding for a nucleotide phosphate transporter in one of the three draft genomes. The scattered absence of Complex I genes and scattered presence of nucleotide transporter genes across diverse microsporidian and rozellid lineages suggest that these adaptations to a parasitic lifestyle, which reduce the parasite's capability to synthesize ATP but enables it to steal ATP from its host, evolved independently in microsporidians and rozellids.

Computer-aided, resistance gene-guided genome mining for proteasome and HMG-CoA reductase inhibitors.

Secondary metabolites (SMs) are biologically active small molecules, many of which are medically valuable. Fungal genomes contain vast numbers of SM biosynthetic gene clusters (BGCs) with unknown products, suggesting that huge numbers of valuable SMs remain to be discovered. It is challenging, however, to identify SM BGCs, among the millions present in fungi, that produce useful compounds. One solution is resistance gene-guided genome mining, which takes advantage of the fact that some BGCs contain a gene encoding a resistant version of the protein targeted by the compound produced by the BGC. The bioinformatic signature of such BGCs is that they contain an allele of an essential gene with no SM biosynthetic function, and there is a second allele elsewhere in the genome. We have developed a computer-assisted approach to resistance gene-guided genome mining that allows users to query large databases for BGCs that putatively make compounds that have targets of therapeutic interest. Working with the MycoCosm genome database, we have applied this approach to look for SM BGCs that target the proteasome ß6 subunit, the target of the proteasome inhibitor fellutamide B, or HMG-CoA reductase, the target of cholesterol reducing therapeutics such as lovastatin. Our approach proved effective, finding known fellutamide and lovastatin BGCs as well as fellutamide- and lovastatin-related BGCs with variations in the SM genes that suggest they may produce structural variants of fellutamides and lovastatin. Gratifyingly, we also found BGCs that are not closely related to lovastatin BGCs but putatively produce novel HMG-CoA reductase inhibitors. ONE-SENTENCE SUMMARY: A new computer-assisted approach to resistance gene-directed genome mining is reported along with its use to identify fungal biosynthetic gene clusters that putatively produce proteasome and HMG-CoA reductase inhibitors.

Decoding the chromosome-scale genome of the nutrient-rich Agaricus subrufescens: a resource for fungal biology and biotechnology.

Agaricus subrufescens, also known as the "sun mushroom," has significant nutritional and medicinal value. However, its short shelf life due to the browning process results in post-harvest losses unless it's quickly dehydrated. This restricts its availability to consumers in the form of capsules. A genome sequence of A. subrufescens may lead to new cultivation alternatives or the application of gene editing strategies to delay the browning process. We assembled a chromosome-scale genome using a hybrid approach combining Illumina and Nanopore sequencing. The genome was assembled into 13 chromosomes and 31 unplaced scaffolds, totaling 44.5 Mb with 96.5% completeness and 47.24% GC content. 14,332 protein-coding genes were identified, with 64.6% of the genome covered by genes and 23.41% transposable elements. The mitogenome was circularized and encoded fourteen typical mitochondrial genes. Four polyphenol oxidase (PPO) genes and the Mating-type locus were identified. Phylogenomic analysis supports the placement of A. subrufescens in the Agaricomycetes clade. This is the first available genome sequence of a strain of the "sun mushroom." Results are available through a Genome Browser (https://plantgenomics.ncc.unesp.br/gen.php?id=Asub) and can support further fungal biological and genomic studies.

The Dynamic Fungal Genome: Polyploidy, Aneuploidy and Copy Number Variation in Response to Stress.

Fungal species have dynamic genomes and often exhibit genomic plasticity in response to stress. This genome plasticity often comes with phenotypic consequences that affect fitness and resistance to stress. Fungal pathogens exhibit genome plasticity in both clinical and agricultural settings and often during adaptation to antifungal drugs, posing significant challenges to human health. Therefore, it is important to understand the rates, mechanisms, and impact of large genomic changes. This review addresses the prevalence of polyploidy, aneuploidy, and copy number variation across diverse fungal species, with special attention to prominent fungal pathogens and model species. We also explore the relationship between environmental stress and rates of genomic changes and highlight the mechanisms underlying genotypic and phenotypic changes. A comprehensive understanding of these dynamic fungal genomes is needed to identify novel solutions for the increase in antifungal drug resistance.

Conserved unique peptide patterns (CUPP) online platform 2.0: implementation of +1000 JGI fungal genomes.

Carbohydrate-processing enzymes, CAZymes, are classified into families based on sequence and three-dimensional fold. Because many CAZyme families contain members of diverse molecular function (different EC-numbers), sophisticated tools are required to further delineate these enzymes. Such delineation is provided by the peptide-based clustering method CUPP, Conserved Unique Peptide Patterns. CUPP operates synergistically with the CAZy family/subfamily categorizations to allow systematic exploration of CAZymes by defining small protein groups with shared sequence motifs. The updated CUPP library contains 21,930 of such motif groups including 3,842,628 proteins. The new implementation of the CUPP-webserver, https://cupp.info/, now includes all published fungal and algal genomes from the Joint Genome Institute (JGI), genome resources MycoCosm and PhycoCosm, dynamically subdivided into motif groups of CAZymes. This allows users to browse the JGI portals for specific predicted functions or specific protein families from genome sequences. Thus, a genome can be searched for proteins having specific characteristics. All JGI proteins have a hyperlink to a summary page which links to the predicted gene splicing including which regions have RNA support. The new CUPP implementation also includes an update of the annotation algorithm that uses only a fourth of the RAM while enabling multi-threading, providing an annotation speed below 1 ms/protein.

Genomic and Secretomic Analyses of the Newly Isolated Fungus Perenniporia fraxinea SS3 Identified CAZymes Potentially Related to a Serious Pathogenesis of Hardwood Trees.

Perenniporia fraxinea can colonize living trees and cause severe damage to standing hardwoods by secreting a number of carbohydrate-activate enzymes (CAZymes), unlike other well-studied Polyporales. However, significant knowledge gaps exist in understanding the detailed mechanisms for this hardwood-pathogenic fungus. To address this issue, five monokaryotic P. fraxinea strains, SS1 to SS5, were isolated from the tree species Robinia pseudoacacia, and high polysaccharide-degrading activities and the fastest growth were found for P. fraxinea SS3 among the isolates. The whole genome of P. fraxinea SS3 was sequenced, and its unique CAZyme potential for tree pathogenicity was determined in comparison to the genomes of other nonpathogenic Polyporales. These CAZyme features are well conserved in a distantly related tree pathogen, Heterobasidion annosum. Furthermore, the carbon source-dependent CAZyme secretions of P. fraxinea SS3 and a nonpathogenic and strong white-rot Polyporales member, Phanerochaete chrysosporium RP78, were compared by activity measurements and proteomic analyses. As seen in the genome comparisons, P. fraxinea SS3 exhibited higher pectin-degrading activities and higher laccase activities than P. chrysosporium RP78, which were attributed to the secretion of abundant glycoside hydrolase family 28 (GH28) pectinases and auxiliary activity family 1_1 (AA1_1) laccases, respectively. These enzymes are possibly related to fungal invasion into the tree lumens and the detoxification of tree defense substances. Additionally, P. fraxinea SS3 showed secondary cell wall degradation capabilities at the same level as that of P. chrysosporium RP78. Overall, this study suggested mechanisms for how this fungus can attack the cell walls of living trees as a serious pathogen and differs from other nonpathogenic white-rot fungi. IMPORTANCE Many studies have been done to understand the mechanisms underlying the degradation of plant cell walls of dead trees by wood decay fungi. However, little is known about how some of these fungi weaken living trees as pathogens. P. fraxinea belongs to the Polyporales, a group of strong wood decayers, and is known to aggressively attack and fell standing hardwood trees all over the world. Here, we report CAZymes potentially related to plant cell wall degradation and pathogenesis factors in a newly isolated fungus, P. fraxinea SS3, by genome sequencing in conjunction with comparative genomic and secretomic analyses. The present study provides insights into the mechanisms of the degradation of standing hardwood trees by the tree pathogen, which will contribute to the prevention of this serious tree disease.

Gapless genome assembly of Fusarium verticillioides, a filamentous fungus threatening plant and human health.

Fusarium verticillioides is a filamentous fungus that causes plant diseases and harms human health through cancer-inducing mycotoxin and life-threatening Fusariosis. Given its threat to agriculture and public health, genome assembly of this fungus is critical to our understanding of its pathobiology and developing antifungal drugs. Here, we report a gap-free genome assembly of F. verticillioides using PacBio HiFi data and high-throughput chromosome capture (Hi-C) sequencing data. The assembled 42.0 Mb sequence contains eleven gapless chromosomes capturing all centromeres and 19 of all 22 telomeres. This assembly represents a significant improvement over previous version on contiguity (contig N50: 4.3 Mb), completeness (BUSCO score: 99.0%) and correctness (QV: 88.8). A total of 15,230 protein-coding genes were predicted, 6.2% of which are newly annotated genes. In addition, we identified three-dimension chromatin structures such as TADs-like structures and chromatin loops based on Hi-C data of ultra-high coverage. This gap-free genome of F. verticillioides is an excellent resource for further panoramic understanding mechanisms of fungal genome evolution, mycotoxin production and pathogenesis on plant and human host.

Structural and Functional Analysis of Peptides Derived from KEX2-Processed Repeat Proteins in Agaricomycetes Using Reverse Genetics and Peptidomics.

Bioactivities of fungal peptides are of interest for basic research and therapeutic drug development. Some of these peptides are derived from "KEX2-processed repeat proteins" (KEPs), a recently defined class of precursor proteins that contain multiple peptide cores flanked by KEX2 protease cleavage sites. Genome mining has revealed that KEPs are widespread in the fungal kingdom. Their functions are largely unknown. Here, we present the first in-depth structural and functional analysis of KEPs in a basidiomycete. We bioinformatically identified KEP-encoding genes in the genome of the model agaricomycete Coprinopsis cinerea and established a detection protocol for the derived peptides by overexpressing the C. cinerea KEPs in the yeast Pichia pastoris. Using this protocol, which includes peptide extraction and mass spectrometry with data analysis using the search engine Mascot, we confirmed the presence of several KEP-derived peptides in C. cinerea, as well as in the edible mushrooms Lentinula edodes, Pleurotus ostreatus, and Pleurotus eryngii. While CRISPR-mediated knockout of C. cinerea kep genes did not result in any detectable phenotype, knockout of kex genes caused defects in mycelial growth and fruiting body formation. These results suggest that KEP-derived peptides may play a role in the interaction of C. cinerea with the biotic environment and that the KEP-processing KEX proteases target a variety of substrates in agaricomycetes, including some important for mycelial growth and differentiation. IMPORTANCE Two recent bioinformatics studies have demonstrated that KEX2-processed repeat proteins are widespread in the fungal kingdom. However, despite the prevalence of KEPs in fungal genomes, only few KEP-derived peptides have been detected and studied so far. Here, we present a protocol for the extraction and structural characterization of KEP-derived peptides from fungal culture supernatants and tissues. The protocol was successfully used to detect several linear and minimally modified KEP-derived peptides in the agaricomycetes C. cinerea, L. edodes, P. ostreatus, and P. eryngii. Our study establishes a new protocol for the targeted search of KEP-derived peptides in fungi, which will hopefully lead to the discovery of more of these interesting fungal peptides and allow a further characterization of KEPs.

Enhanced flavour profiles through radicicol induced genomic variation in the lager yeasts, Saccharomyces pastorianus.

The yeasts, Saccharomyces pastorianus, are hybrids of Saccharomyces cerevisiae and Saccharomyces eubayanus and have acquired traits from the combined parental genomes such as ability to ferment a range of sugars at low temperatures and to produce aromatic flavour compounds, allowing for the production of lager beers with crisp, clean flavours. The polyploid strains are sterile and have reached an evolutionary bottleneck for genetic variation. Here we describe an accelerated evolution approach to obtain lager yeasts with enhanced flavour profiles. As the relative expression of orthologous alleles is a significant contributor to the transcriptome during fermentation, we aimed to induce genetic variation by altering the S. cerevisiae to S. eubayanus chromosome ratio. Aneuploidy was induced through the temporary inhibition of the cell's stress response and strains with increased production of aromatic amino acids via the Shikimate pathway were selected by resistance to amino acid analogues. Genomic changes such as gross chromosomal rearrangements, chromosome loss and chromosome gain were detected in the characterised mutants, as were single-nucleotide polymorphisms in ARO4, encoding for DAHP synthase, the catalytic enzyme in the first step of the Shikimate pathway. Transcriptome analysis confirmed the upregulation of genes encoding enzymes in the Ehrlich pathway and the concomitant increase in the production of higher alcohols and esters such as 2-phenylethanol, 2-phenylethyl acetate, tryptophol, and tyrosol. We propose that the polyploid nature of S. pastorianus genomes is an advantageous trait supporting opportunities for genetic alteration in otherwise sterile strains.

Halogenation in Fungi: What Do We Know and What Remains to Be Discovered?

In nature, living organisms produce a wide variety of specialized metabolites to perform many biological functions. Among these specialized metabolites, some carry halogen atoms on their structure, which can modify their chemical characteristics. Research into this type of molecule has focused on how organisms incorporate these atoms into specialized metabolites. Several families of enzymes have been described gathering metalloenzymes, flavoproteins, or S-adenosyl-L-methionine (SAM) enzymes that can incorporate these atoms into different types of chemical structures. However, even though the first halogenation enzyme was discovered in a fungus, this clade is still lagging behind other clades such as bacteria, where many enzymes have been discovered. This review will therefore focus on all halogenation enzymes that have been described in fungi and their associated metabolites by searching for proteins available in databases, but also by using all the available fungal genomes. In the second part of the review, the chemical diversity of halogenated molecules found in fungi will be discussed. This will allow the highlighting of halogenation mechanisms that are still unknown today, therefore, highlighting potentially new unknown halogenation enzymes.

Diploid genome assembly of Kluyveromyces marxianus NRRL Y-50883 (SLP1).

The yeast Kluyveromyces marxianus SLP1 has the potential for application in biotechnological processes because it can metabolize several sugars and produce high-value metabolites. K. marxianus SLP1 is a thermotolerant yeast isolated from the mezcal process, and it is tolerant to several cell growth inhibitors such as saponins, furan aldehydes, weak acids, and phenolics compounds. The genomic differences between dairy and nondairy strains related to K. marxianus variability are a focus of research attention, particularly the pathways leading this species toward polyploidy. We report the diploid genome assembly of K. marxianus SLP1 nonlactide strain into 32 contigs to reach a size of ∼12 Mb (N50 = 1.3 Mb) and a ∼39% GC content. Genome size is consistent with the k-mer frequency results. Genome annotation by Funannotate estimated 5000 genes in haplotype A and 4910 in haplotype B. The enriched annotated genes by ontology show differences between alleles in biological processes and cellular component. The analysis of variants related to DMKU3 and between haplotypes shows changes in LAC12 and INU1, which we hypothesize can impact carbon source performance. This report presents the first polyploid K. marxianus strain recovered from nonlactic fermenting medium.

Draft Genome Sequence of Alternaria longipes Causing Tobacco Brown Spot.

Alternaria is a cosmopolitan fungal genus associated with diverse hosts. Tobacco brown spot caused by Alternaria longipes is one of the most destructive diseases of tobacco. A. longipes can also infect many other plants, some animals and even humans. Here, we report a genome assembly of A. longipes CBS 540.94 using Oxford Nanopore Technologies. A total of 15 contigs were assembled, and the genome size was 37.5 Mb with contig N50 of 4.33 Mb. This genome resource will provide information for further research on comparative genomics of the genus Alternaria and be a valuable resource in investigations of the molecular interactions of pathogen and hosts.

The TOR kinase pathway is relevant for nitrogen signaling and antagonism of the mycoparasite Trichoderma atroviride.

Trichoderma atroviride (Ascomycota, Sordariomycetes) is a well-known mycoparasite applied for protecting plants against fungal pathogens. Its mycoparasitic activity involves processes shared with plant and human pathogenic fungi such as the production of cell wall degrading enzymes and secondary metabolites and is tightly regulated by environmental cues. In eukaryotes, the conserved Target of Rapamycin (TOR) kinase serves as a central regulator of cellular growth in response to nutrient availability. Here we describe how alteration of the activity of TOR1, the single and essential TOR kinase of T. atroviride, by treatment with chemical TOR inhibitors or by genetic manipulation of selected TOR pathway components affected various cellular functions. Loss of TSC1 and TSC2, that are negative regulators of TOR complex 1 (TORC1) in mammalian cells, resulted in altered nitrogen source-dependent growth of T. atroviride, reduced mycoparasitic overgrowth and, in the case of Δtsc1, a diminished production of numerous secondary metabolites. Deletion of the gene encoding the GTPase RHE2, whose mammalian orthologue activates mTORC1, led to rapamycin hypersensitivity and altered secondary metabolism, but had an only minor effect on vegetative growth and mycoparasitic overgrowth. The latter also applied to mutants missing the npr1-1 gene that encodes a fungus-specific kinase known as TOR target in yeast. Genome-wide transcriptome analysis confirmed TOR1 as a regulatory hub that governs T. atroviride metabolism and processes associated to ribosome biogenesis, gene expression and translation. In addition, mycoparasitism-relevant genes encoding terpenoid and polyketide synthases, peptidases, glycoside hydrolases, small secreted cysteine-rich proteins, and G protein coupled receptors emerged as TOR1 targets. Our results provide the first in-depth insights into TOR signaling in a fungal mycoparasite and emphasize its importance in the regulation of processes that critically contribute to the antagonistic activity of T. atroviride.

The long non-coding RNA landscape of Candida yeast pathogens.

Long non-coding RNAs (lncRNAs) constitute a poorly studied class of transcripts with emerging roles in key cellular processes. Despite efforts to characterize lncRNAs across a wide range of species, these molecules remain largely unexplored in most eukaryotic microbes, including yeast pathogens of the Candida clade. Here, we analyze thousands of publicly available sequencing datasets to infer and characterize the lncRNA repertoires of five major Candida pathogens: Candida albicans, Candida tropicalis, Candida parapsilosis, Candida auris and Candida glabrata. Our results indicate that genomes of these species encode hundreds of lncRNAs that show levels of evolutionary constraint intermediate between those of intergenic genomic regions and protein-coding genes. Despite their low sequence conservation across the studied species, some lncRNAs are syntenic and are enriched in shared sequence motifs. We find co-expression of lncRNAs with certain protein-coding transcripts, hinting at potential functional associations. Finally, we identify lncRNAs that are differentially expressed during infection of human epithelial cells for four of the studied species. Our comprehensive bioinformatic analyses of Candida lncRNAs pave the way for future functional characterization of these transcripts.