Ecological generalism drives hyperdiversity of secondary metabolite gene clusters in xylarialean endophytes

Cultures as types and the utility of viable specimens for fungal nomenclature

The debates over the requirement of the International Code of Nomenclature for algae, fungi, and plants (ICNafp) for a viable specimen to represent the name-bearing type material for a species or infraspecific taxon have a long history. Taxonomy of fungi commonly studied as living cultures exemplified by yeasts and moulds, strongly depend on viable reference material. The availability of viable cultures is also particularly useful for several groups of filamentous and dimorphic fungi. While the preservation of metabolically inactive cultures is permitted and recommended by the ICNafp, there is room for improvement. Below, we review the history and current status of cultures as the name-bearing type material under the Code. We also present a roadmap with tasks to be achieved in order to establish a stable nomenclatural system that properly manages taxa typified by viable specimens. Furthermore, we propose setting up rules and defining the nomenclatural status of ex-type cultures under Chapter F, the section of the ICNafp that includes provisions specific to names of fungi.

CLOCI: unveiling cryptic fungal gene clusters with generalized detection

Gene clusters are genomic loci that contain multiple genes that are functionally and genetically linked. Gene clusters collectively encode diverse functions, including small molecule biosynthesis, nutrient assimilation, metabolite degradation, and production of proteins essential for growth and development. Identifying gene clusters is a powerful tool for small molecule discovery and provides insight into the ecology and evolution of organisms. Current detection algorithms focus on canonical 'core' biosynthetic functions many gene clusters encode, while overlooking uncommon or unknown cluster classes. These overlooked clusters are a potential source of novel natural products and comprise an untold portion of overall gene cluster repertoires. Unbiased, function-agnostic detection algorithms therefore provide an opportunity to reveal novel classes of gene clusters and more precisely define genome organization. We present CLOCI (Co-occurrence Locus and Orthologous Cluster Identifier), an algorithm that identifies gene clusters using multiple proxies of selection for coordinated gene evolution. Our approach generalizes gene cluster detection and gene cluster family circumscription, improves detection of multiple known functional classes, and unveils non-canonical gene clusters. CLOCI is suitable for genome-enabled small molecule mining, and presents an easily tunable approach for delineating gene cluster families and homologous loci.

Leaf Endophytes Relationship with Host Metabolome Expression in Tropical Gymnosperms

Plant-microbe interactions play a pivotal role in shaping host fitness, especially concerning chemical defense mechanisms. In cycads, establishing direct correlations between specific endophytic microbes and the synthesis of highly toxic defensive phytochemicals has been challenging. Our research delves into the intricate relationship between plant-microbe associations and the variation of secondary metabolite production in two closely related Zamia species that grow in distinct habitats; terrestrial and epiphytic. Employing an integrated approach, we combined microbial metabarcoding, which characterize the leaf endophytic bacterial and fungal communities, with untargeted metabolomics to test if the relative abundances of specific microbial taxa in these two Zamia species were associated with different metabolome profiles. The two species studied shared approximately 90% of the metabolites spanning diverse biosynthetic pathways: alkaloids, amino acids, carbohydrates, fatty acids, polyketides, shikimates, phenylpropanoids, and terpenoids. Co-occurrence networks revealed positive associations among metabolites from different pathways, underscoring the complexity of their interactions. Our integrated analysis demonstrated to some degree that the intraspecific variation in metabolome profiles of the two host species was associated with the abundance of bacterial orders Acidobacteriales and Frankiales, as well as the fungal endophytes belonging to the orders Chaetothyriales, Glomerellales, Heliotiales, Hypocreales, and Sordariales. We further associate individual metabolic similarity with four specific fungal endophyte members of the core microbiota, but no specific bacterial taxa associations were identified. This study represents a pioneering investigation to characterize leaf endophytes and their association with metabolomes in tropical gymnosperms, laying the groundwork for deeper inquiries into this complex domain.

Plant-endophyte communication: Scaling from molecular mechanisms to ecological outcomes

Diverse communities of fungal endophytes reside in plant tissues, where they affect and are affected by plant physiology and ecology. For these intimate interactions to form and persist, endophytes and their host plants engage in intricate systems of communication. The conversation between fungal endophytes and plant hosts ultimately dictates endophyte community composition and function and has cascading effects on plant health and plant interactions. In this review, we synthesize our current knowledge on the mechanisms and strategies of communication used by endophytic fungi and their plant hosts. We discuss the molecular mechanisms of communication that lead to organ specificity of endophytic communities and distinguish endophytes, pathogens, and saprotrophs. We conclude by offering emerging perspectives on the relevance of plant-endophyte communication to microbial community ecology and plant health and function.

Global genome mining-driven discovery of an unusual biosynthetic logic for fungal polyketide-terpenoid hybrids

Genome mining has facilitated the efficient discovery of untapped natural products. We performed global genome mining in fungi and discovered a series of biosynthetic gene clusters (BGCs) that appeared to afford polyketide-terpenoid hybrids via a distinct biosynthetic mechanism from those adopted by known pathways. Characterization of one of the BGCs revealed that it yields the drimane-phthalide hybrid 1. During the biosynthesis of 1, the farnesyl group is unusually introduced by the dimethylallyltryptophan synthase-type prenyltransferase MfmD and is then cyclized by the Pyr4-family terpene cyclase MfmH. The replacement of MfmH with its homologue OcdTC gave another hybrid molecule with a monocyclic terpenoid moiety. Moreover, PsetPT, an MfmD homologue, was found to perform dimethylallylation and was then engineered to install a geranyl group. Our study unraveled an unusual biosynthetic mechanism for fungal phthalide-terpenoid hybrids and provided insights into how their structural diversification could be achieved.

Genome sequencing and molecular networking analysis of the wild fungus Anthostomella pinea reveal its ability to produce a diverse range of secondary metabolites

BACKGROUND

Filamentous fungi are prolific producers of bioactive molecules and enzymes with important applications in industry. Yet, the vast majority of fungal species remain undiscovered or uncharacterized. Here we focus our attention to a wild fungal isolate that we identified as Anthostomella pinea. The fungus belongs to a complex polyphyletic genus in the family of Xylariaceae, which is known to comprise endophytic and pathogenic fungi that produce a plethora of interesting secondary metabolites. Despite that, Anthostomella is largely understudied and only two species have been fully sequenced and characterized at a genomic level.

RESULTS

In this work, we used long-read sequencing to obtain the complete 53.7 Mb genome sequence including the full mitochondrial DNA. We performed extensive structural and functional annotation of coding sequences, including genes encoding enzymes with potential applications in biotechnology. Among others, we found that the genome of A. pinea encodes 91 biosynthetic gene clusters, more than 600 CAZymes, and 164 P450s. Furthermore, untargeted metabolomics and molecular networking analysis of the cultivation extracts revealed a rich secondary metabolism, and in particular an abundance of sesquiterpenoids and sesquiterpene lactones. We also identified the polyketide antibiotic xanthoepocin, to which we attribute the anti-Gram-positive effect of the extracts that we observed in antibacterial plate assays.

CONCLUSIONS

Taken together, our results provide a first glimpse into the potential of Anthstomella pinea to provide new bioactive molecules and biocatalysts and will facilitate future research into these valuable metabolites.

Endophyte genomes support greater metabolic gene cluster diversity compared with non-endophytes in Trichoderma

Trichoderma is a cosmopolitan genus with diverse lifestyles and nutritional modes, including mycotrophy, saprophytism, and endophytism. Previous research has reported greater metabolic gene repertoires in endophytic fungal species compared to closely-related non-endophytes. However, the extent of this ecological trend and its underlying mechanisms are unclear. Some endophytic fungi may also be mycotrophs and have one or more mycoparasitism mechanisms. Mycotrophic endophytes are prominent in certain genera like Trichoderma, therefore, the mechanisms that enable these fungi to colonize both living plants and fungi may be the result of expanded metabolic gene repertoires. Our objective was to determine what, if any, genomic features are overrepresented in endophytic fungi genomes in order to undercover the genomic underpinning of the fungal endophytic lifestyle. Here we compared metabolic gene cluster and mycoparasitism gene diversity across a dataset of thirty-eight Trichoderma genomes representing the full breadth of environmental Trichoderma's diverse lifestyles and nutritional modes. We generated four new Trichoderma endophyticum genomes to improve the sampling of endophytic isolates from this genus. As predicted, endophytic Trichoderma genomes contained, on average, more total biosynthetic and degradative gene clusters than non-endophytic isolates, suggesting that the ability to create/modify a diversity of metabolites potential is beneficial or necessary to the endophytic fungi. Still, once the phylogenetic signal was taken in consideration, no particular class of metabolic gene cluster was independently associated with the Trichoderma endophytic lifestyle. Several mycoparasitism genes, but no chitinase genes, were associated with endophytic Trichoderma genomes. Most genomic differences between Trichoderma lifestyles and nutritional modes are difficult to disentangle from phylogenetic divergences among species, suggesting that Trichoderma genomes maybe particularly well-equipped for lifestyle plasticity. We also consider the role of endophytism in diversifying secondary metabolism after identifying the horizontal transfer of the ergot alkaloid gene cluster to Trichoderma.

Terabase-Scale Coassembly of a Tropical Soil Microbiome

Petabases of environmental metagenomic data are publicly available, presenting an opportunity to characterize complex environments and discover novel lineages of life. Metagenome coassembly, in which many metagenomic samples from an environment are simultaneously analyzed to infer the underlying genomes' sequences, is an essential tool for achieving this goal. We applied MetaHipMer2, a distributed metagenome assembler that runs on supercomputing clusters, to coassemble 3.4 terabases (Tbp) of metagenome data from a tropical soil in the Luquillo Experimental Forest (LEF), Puerto Rico. The resulting coassembly yielded 39 high-quality (>90% complete, <5% contaminated, with predicted 23S, 16S, and 5S rRNA genes and ≥18 tRNAs) metagenome-assembled genomes (MAGs), including two from the candidate phylum Eremiobacterota. Another 268 medium-quality (≥50% complete, <10% contaminated) MAGs were extracted, including the candidate phyla Dependentiae, Dormibacterota, and Methylomirabilota. In total, 307 medium- or higher-quality MAGs were assigned to 23 phyla, compared to 294 MAGs assigned to nine phyla in the same samples individually assembled. The low-quality (<50% complete, <10% contaminated) MAGs from the coassembly revealed a 49% complete rare biosphere microbe from the candidate phylum FCPU426 among other low-abundance microbes, an 81% complete fungal genome from the phylum Ascomycota, and 30 partial eukaryotic MAGs with ≥10% completeness, possibly representing protist lineages. A total of 22,254 viruses, many of them low abundance, were identified. Estimation of metagenome coverage and diversity indicates that we may have characterized ≥87.5% of the sequence diversity in this humid tropical soil and indicates the value of future terabase-scale sequencing and coassembly of complex environments. IMPORTANCE Petabases of reads are being produced by environmental metagenome sequencing. An essential step in analyzing these data is metagenome assembly, the computational reconstruction of genome sequences from microbial communities. "Coassembly" of metagenomic sequence data, in which multiple samples are assembled together, enables more complete detection of microbial genomes in an environment than "multiassembly," in which samples are assembled individually. To demonstrate the potential for coassembling terabases of metagenome data to drive biological discovery, we applied MetaHipMer2, a distributed metagenome assembler that runs on supercomputing clusters, to coassemble 3.4 Tbp of reads from a humid tropical soil environment. The resulting coassembly, its functional annotation, and analysis are presented here. The coassembly yielded more, and phylogenetically more diverse, microbial, eukaryotic, and viral genomes than the multiassembly of the same data. Our resource may facilitate the discovery of novel microbial biology in tropical soils and demonstrates the value of terabase-scale metagenome sequencing.

The Sordariomycetes: an expanding resource with Big Data for mining in evolutionary genomics and transcriptomics

Advances in genomics and transcriptomics accompanying the rapid accumulation of omics data have provided new tools that have transformed and expanded the traditional concepts of model fungi. Evolutionary genomics and transcriptomics have flourished with the use of classical and newer fungal models that facilitate the study of diverse topics encompassing fungal biology and development. Technological advances have also created the opportunity to obtain and mine large datasets. One such continuously growing dataset is that of the Sordariomycetes, which exhibit a richness of species, ecological diversity, economic importance, and a profound research history on amenable models. Currently, 3,574 species of this class have been sequenced, comprising nearly one-third of the available ascomycete genomes. Among these genomes, multiple representatives of the model genera Fusarium, Neurospora, and Trichoderma are present. In this review, we examine recently published studies and data on the Sordariomycetes that have contributed novel insights to the field of fungal evolution via integrative analyses of the genetic, pathogenic, and other biological characteristics of the fungi. Some of these studies applied ancestral state analysis of gene expression among divergent lineages to infer regulatory network models, identify key genetic elements in fungal sexual development, and investigate the regulation of conidial germination and secondary metabolism. Such multispecies investigations address challenges in the study of fungal evolutionary genomics derived from studies that are often based on limited model genomes and that primarily focus on the aspects of biology driven by knowledge drawn from a few model species. Rapidly accumulating information and expanding capabilities for systems biological analysis of Big Data are setting the stage for the expansion of the concept of model systems from unitary taxonomic species/genera to inclusive clusters of well-studied models that can facilitate both the in-depth study of specific lineages and also investigation of trait diversity across lineages. The Sordariomycetes class, in particular, offers abundant omics data and a large and active global research community. As such, the Sordariomycetes can form a core omics clade, providing a blueprint for the expansion of our knowledge of evolution at the genomic scale in the exciting era of Big Data and artificial intelligence, and serving as a reference for the future analysis of different taxonomic levels within the fungal kingdom.

Plants as the Extended Phenotype of Endophytes-The Actual Source of Bioactive Compounds

For thousands of years, plants have been used for their medicinal properties. The industrial production of plant-beneficial compounds is facing many drawbacks, such as seasonal dependence and troublesome extraction and purification processes, which have led to many species being on the edge of extinction. As the demand for compounds applicable to, e.g., cancer treatment, is still growing, there is a need to develop sustainable production processes. The industrial potential of the endophytic microorganisms residing within plant tissues is undeniable, as they are often able to produce, in vitro, similar to or even the same compounds as their hosts. The peculiar conditions of the endophytic lifestyle raise questions about the molecular background of the biosynthesis of these bioactive compounds in planta, and the actual producer, whether it is the plant itself or its residents. Extending this knowledge is crucial to overcoming the current limitations in the implementation of endophytes for larger-scale production. In this review, we focus on the possible routes of the synthesis of host-specific compounds in planta by their endophytes.

Applying molecular and genetic methods to trees and their fungal communities

Forests provide invaluable economic, ecological, and social services. At the same time, they are exposed to several threats, such as fragmentation, changing climatic conditions, or increasingly destructive pests and pathogens. Trees, the inherent species of forests, cannot be viewed as isolated organisms. Manifold (micro)organisms are associated with trees playing a pivotal role in forest ecosystems. Of these organisms, fungi may have the greatest impact on the life of trees. A multitude of molecular and genetic methods are now available to investigate tree species and their associated organisms. Due to their smaller genome sizes compared to tree species, whole genomes of different fungi are routinely compared. Such studies have only recently started in forest tree species. Here, we summarize the application of molecular and genetic methods in forest conservation genetics, tree breeding, and association genetics as well as for the investigation of fungal communities and their interrelated ecological functions. These techniques provide valuable insights into the molecular basis of adaptive traits, the impacts of forest management, and changing environmental conditions on tree species and fungal communities and can enhance tree-breeding cycles due to reduced time for field testing. It becomes clear that there are multifaceted interactions among microbial species as well as between these organisms and trees. We demonstrate the versatility of the different approaches based on case studies on trees and fungi. KEY POINTS: • Current knowledge of genetic methods applied to forest trees and associated fungi. • Genomic methods are essential in conservation, breeding, management, and research. • Important role of phytobiomes for trees and their ecosystems.

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 β6 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.

Tissue Cultivation, Preparation, and Extraction of High Molecular Weight DNA for Single-Molecule Genome Sequencing of Plant-Associated Fungi

Extraction of high-quality, high molecular weight DNA is a critical step for sequencing an organism's genome. For fungi, DNA extraction is often complicated by co-precipitation of secondary metabolites, the most destructive being polysaccharides, polyphenols, and melanin. Different DNA extraction protocols and clean-up methods have been developed to address challenging materials and contaminants; however, the method of fungal cultivation and tissue preparation also plays a critical role to limit the production of inhibitory compounds prior to extraction. Here, we provide protocols and guidelines for (i) fungal tissue cultivation and processing with solid media containing a cellophane overlay or in liquid media, (ii) DNA extraction with customized recommendations for taxonomically and ecologically diverse plant-associated fungi, and (iii) assessing DNA quantity and quality for downstream genome sequencing with single-molecule technology such as PacBio.

Mycology: Metagenomes illuminate evolutionary relationships and reframe symbiotic interactions

An intriguing new study leverages newly generated metagenomes to remap the evolution of the most species-rich clade of fungi, highlighting how some of the most intriguing and visible manifestations of symbioses - lichens - may arise.

Traits along the leaf economics spectrum are associated with communities of foliar endophytic symbionts

Leaf traits of plants worldwide are classified according to the Leaf Economics Spectrum (LES), which links leaf functional traits to evolutionary life history strategies. As a continuum ranging from thicker, tough leaves that are low in nitrogen (N) to thinner, softer, leaves that are high in N, the LES brings together physical, chemical, and ecological traits. Fungal endophytes are common foliar symbionts that occur in healthy, living leaves, especially in tropical forests. Their community composition often differs among co-occurring host species in ways that cannot be explained by environmental conditions or host phylogenetic relationships. Here, we tested the over-arching hypothesis that LES traits act as habitat filters that shape communities of endophytes both in terms of composition, and in terms of selecting for endophytes with particular suites of functional traits. We used culture-based and culture-free surveys to characterize foliar endophytes in mature leaves of 30 phylogenetically diverse plant species with divergent LES traits in lowland Panama, and then measured functional traits of dominant endophyte taxa in vitro. Endophytes were less abundant and less diverse in thick, tough, leaves compared to thin, softer, leaves in the same forest, even in closely related plants. Endophyte communities differed according to leaf traits, including leaf punch strength and carbon and nitrogen content. The most common endophyte taxa in leaves at different ends of the LES differ in their cellulase, protease, chitinase, and antipathogen activity. Our results extend the LES framework for the first time to diverse and ecologically important endophytes, opening new hypotheses regarding the degree to which foliar symbionts respond to, and extend, the functional traits of leaves they inhabit.

Lifestyle Transitions in Fusarioid Fungi are Frequent and Lack Clear Genomic Signatures

The fungal genus Fusarium (Ascomycota) includes well-known plant pathogens that are implicated in diseases worldwide, and many of which have been genome sequenced. The genus also encompasses other diverse lifestyles, including species found ubiquitously as asymptomatic-plant inhabitants (endophytes). Here, we produced structurally annotated genome assemblies for five endophytic Fusarium strains, including the first whole-genome data for Fusarium chuoi. Phylogenomic reconstruction of Fusarium and closely related genera revealed multiple and frequent lifestyle transitions, the major exception being a monophyletic clade of mutualist insect symbionts. Differential codon usage bias and increased codon optimisation separated Fusarium sensu stricto from allied genera. We performed computational prediction of candidate secreted effector proteins (CSEPs) and carbohydrate-active enzymes (CAZymes)—both likely to be involved in the host–fungal interaction—and sought evidence that their frequencies could predict lifestyle. However, phylogenetic distance described gene variance better than lifestyle did. There was no significant difference in CSEP, CAZyme, or gene repertoires between phytopathogenic and endophytic strains, although we did find some evidence that gene copy number variation may be contributing to pathogenicity. Large numbers of accessory CSEPs (i.e., present in more than one taxon but not all) and a comparatively low number of strain-specific CSEPs suggested there is a limited specialisation among plant associated Fusarium species. We also found half of the core genes to be under positive selection and identified specific CSEPs and CAZymes predicted to be positively selected on certain lineages. Our results depict fusarioid fungi as prolific generalists and highlight the difficulty in predicting pathogenic potential in the group.

Structural basis of NLR activation and innate immune signalling in plants

Animals and plants have NLRs (nucleotide-binding leucine-rich repeat receptors) that recognize the presence of pathogens and initiate innate immune responses. In plants, there are three types of NLRs distinguished by their N-terminal domain: the CC (coiled-coil) domain NLRs, the TIR (Toll/interleukin-1 receptor) domain NLRs and the RPW8 (resistance to powdery mildew 8)-like coiled-coil domain NLRs. CC-NLRs (CNLs) and TIR-NLRs (TNLs) generally act as sensors of effectors secreted by pathogens, while RPW8-NLRs (RNLs) signal downstream of many sensor NLRs and are called helper NLRs. Recent studies have revealed three dimensional structures of a CNL (ZAR1) including its inactive, intermediate and active oligomeric state, as well as TNLs (RPP1 and ROQ1) in their active oligomeric states. Furthermore, accumulating evidence suggests that members of the family of lipase-like EDS1 (enhanced disease susceptibility 1) proteins, which are uniquely found in seed plants, play a key role in providing a link between sensor NLRs and helper NLRs during innate immune responses. Here, we summarize the implications of the plant NLR structures that provide insights into distinct mechanisms of action by the different sensor NLRs and discuss plant NLR-mediated innate immune signalling pathways involving the EDS1 family proteins and RNLs.