UFCG: database of universal fungal core genes and pipeline for genome-wide phylogenetic analysis of fungi

A conserved terpene cyclase gene in Sanghuangporus for abscisic acid-related sesquiterpenoid biosynthesis

BACKGROUND

The medicinal mushroom Sanghuangporus is renowned in East Asia for its potent therapeutic properties, attributed in part to its bioactive sesquiterpenoids. However, despite their recognized medicinal potential, the biosynthetic pathways and specific enzymes responsible for sesquiterpenoid production in Sanghuangporus remain unexplored, limiting opportunities to optimize their medicinal applications.

RESULTS

Sesquiterpenoids from four Sanghuangporus species were extracted through targeted isolation using mass spectrometry (MS)-based metabolomics, resulting in the discovery of six known abscisic acid-related compounds and one new compound, whose structure was determined through spectroscopic and computational analysis. We employed a natural product genome mining approach to identify a putative biosynthetic gene cluster (BGC) containing a sesquiterpene synthase gene, ancA, associated with the detected compounds. Biosynthetic pathways for these compounds were proposed based on an integrative approach combining BGC analysis and MS2 fragment-based dereplication. Further analyses revealed that the gene content and synteny of the ancA BGC are relatively well-conserved across Sanghuangporus species but less so outside the genus.

CONCLUSIONS

A sesquiterpene synthase gene, its associated BGC, and the biosynthetic pathway for a group of detected abscisic acid-related sesquiterpenoids in Sanghuangporus were predicted through genomic and metabolic data analyses. This study addresses a critical gap in understanding the genetic basis of sesquiterpenoid production in Sanghuangporus and offers insights for future research on engineering metabolic pathways to enhance sesquiterpenoid production for medicinal use.

Challenges in capturing the mycobiome from shotgun metagenome data: lack of software and databases

BACKGROUND

The mycobiome, representing the fungal component of microbial communities, is increasingly acknowledged as an integral part of the gut microbiome. However, research in this area remains relatively limited. The characterization of mycobiome taxa from metagenomic data is heavily reliant on the quality of the software and databases. In this study, we evaluated the feasibility of mycobiome profiling using existing bioinformatics tools on simulated fungal metagenomic data.

RESULTS

We identified seven tools claiming to perform taxonomic assignment of fungal shotgun metagenomic sequences. One of these was outdated and required substantial modifications of the code to be functional and was thus excluded. To evaluate the accuracy of identification and relative abundance of the remaining tools (Kraken2, MetaPhlAn4, EukDetect, FunOMIC, MiCoP, and HumanMycobiomeScan), we constructed 18 mock communities of varying species richness and abundance levels. The mock communities comprised up to 165 fungal species belonging to the phyla Ascomycota and Basidiomycota, commonly found in gut microbiomes. Of the tools, FunOMIC and HumanMycobiomeScan needed source code modifications to run. Notably, only one species, Candida orthopsilosis, was consistently identified by all tools across all communities where it was included. Increasing community richness improved precision of Kraken2 and the relative abundance accuracy of all tools on species, genus, and family levels. MetaPhlAn4 accurately identified all genera present in the communities and FunOMIC identified most species. The top three tools for overall accuracy in both identification and relative abundance estimation were EukDetect, MiCoP, and FunOMIC, respectively. Adding 90% and 99% bacterial background did not significantly impact these tools' performance. Among the whole genome reference tools (Kraken2, HMS, and MiCoP), MiCoP exhibited the highest accuracy when the same reference database was used.

CONCLUSION

Our survey of mycobiome-specific software revealed a very limited selection of such tools and their poor robustness due to error-prone software, along with a significant lack of comprehensive databases enabling characterization of the mycobiome. None of the implemented tools fully agreed on the mock community profiles. FunOMIC recognized most of the species, but EukDetect and MiCoP provided predictions that were closest to the correct compositions. The bacterial background did not impact these tools' performance. Video Abstract.

A New Method for Constructing High-Resolution Phylogenomic Topologies Using Core Gene-Associated MNP Markers: A Case Study From Agaricus bisporus

Accurate strain identification is essential for economically significant fungi, as it aids in understanding their diverse agronomic traits, pathogenicity, and other important characteristics. However, traditional methods often face challenges related to limited accuracy, high workloads, and reproducibility issues. Recently, multiple nucleotide polymorphism (MNP) markers have been employed in mushroom strain identification, demonstrating significantly improved accuracy and reproducibility. Nevertheless, the identification of strains across different species still heavily depends on specific and often overly complex MNP markers. In this study, we address these challenges by developing a novel method for constructing high-resolution phylogenomic topologies using core gene-associated multiple nucleotide polymorphism (cgMNP) markers, focusing on Agaricus bisporus (button mushroom). Utilising resequencing data from 213 cultivated and wild strains of A. bisporus, we identified 84 cgMNP markers within 83 core genes from 1011 MNP markers. Phylogenetic analysis based on cgMNP sequences and the genetic distance between strain pairs allowed for precise identification of all strains. Moreover, the successful transferability of these cgMNP markers to an additional 385 A. bisporus strains and other fungal species, including Flammulina filiformis (enoki mushroom) and Saccharomyces cerevisiae (yeast), highlights their cross-species applicability. The high resolution and strong congruence of cgMNP markers with whole-genome data provide a robust and reliable method for strain-level discrimination in fungi. The success of this approach in A. bisporus sets a promising precedent for its application to a broader range of fungal taxa.

Metagenomic analysis of pristine oil sheds new light on the global distribution of microbial genetic repertoire in hydrocarbon-associated ecosystems

Oil reservoirs are society's primary source of hydrocarbons. While microbial communities in industrially exploited oil reservoirs have been investigated in the past, pristine microbial communities in untapped oil reservoirs are little explored, as are distribution patterns of respective genetic signatures. Here, we show that a pristine oil sample contains a complex community consisting of bacteria and fungi for the degradation of hydrocarbons. We identified microorganisms and their pathways for the degradation of methane, n-alkanes, mono-aromatic, and polycyclic aromatic compounds in a metagenome retrieved from biodegraded petroleum encountered in a subsurface reservoir in the Barents Sea. Capitalizing on marker genes from metagenomes and public data mining, we compared the prokaryotes, putative viruses, and putative plasmids of the sampled site to those from 10 other hydrocarbon-associated sites, revealing a shared network of species and genetic elements across the globe. To test for the potential dispersal of the microbes and predicted elements via seawater, we compared our findings to the Tara Ocean dataset, resulting in a broad distribution of prokaryotic and viral signatures. Although frequently shared between hydrocarbon-associated sites, putative plasmids, however, showed little coverage in the Tara Oceans dataset, suggesting an undiscovered mode of transfer between hydrocarbon-affected ecosystems. Based on our analyses, genetic information is globally shared between oil reservoirs and hydrocarbon-associated sites, and we propose that currents and other physical occurrences within the ocean along with deep aquifers are major distributors of prokaryotes and viruses into these subsurface ecosystems.

Biodegradation of imidacloprid and diuron by Simplicillium sp. QHSH-33

Imidacloprid (IMI) and diuron (DIU) are widely used pesticides in agricultural production. However, their excessive use and high residues have caused harm to the ecological environment and human health. Microbial remediation as an efficient and low-toxic method has become a research hotspot for controlling environmental pollutants. A fungus QHSH-33, identified as Simplicillium sp., has the ability to degrade neonicotinoids IMI and phenylurea DIU. When QHSH-33 and pesticide were co-cultured in liquid medium for 7 days, the degradation rates of IMI and DIU by QHSH-33 in simulated field soil microenvironment were 50.19 % and 70.57 %, respectively. Through HPLC-MS analysis, it was found that the degradation of IMI mainly involved nitro reduction, hydroxylation and other reactions. Three degradation pathways and eight degradation products were identified, among which two metabolites were obtained by microbial transformation of IMI for the first time. The degradation of DIU mainly involved demethylation and dehalogenation reactions, and two degradation pathways and four degradation products were identified, one of which was a new degradation product of DIU. Toxicity assessment demonstrated that most of the degradation products might be considerably less harmful than IMI and DIU. Whole genome sequencing of QHSH-33 revealed a genome size of 33.2 Mbp with 11,707 genes. The genome of QHSH-33 was annotated by KEGG to reveal 128 genes related to exogenous degradation and metabolism. After local blast with reported IMI and DIU degrading enzymes, seven IMI-degrading related genes and seven DIU-degrading related genes were identified in the QHSH-33 genome. The results of this study will help to expand our knowledge on the microbial decomposition metabolism of IMI and DIU, and provide new insights into the degradation mechanism of IMI and DIU in soil and pure culture system, laying a foundation for QHSH-33 strain applied to the removal, biotransformation or detoxification of IMI and DIU.

Genome sequence of a European Diplocarpon coronariae strain and in silico structure of the mating-type locus

Diplocarpon coronariae is a fungal pathogen that is prevalent in low-input apple production. Over the past 15 years, it has become increasingly distributed in Europe. However, comprehensive insights into its biology and pathogenicity remain limited. One particular aspect is the rarity of the sexual morph of this pathogen, a phenomenon hitherto unobserved in Europe. Diplocarpon coronariae reproduces through a heterothallic mating system requiring at least two different mating types for sexual reproduction. Genes determining the mating types are located on the mating-type locus. In this study, D. coronariae strain DC1_JKI from Dresden, Germany, was sequenced and used to unravel the structure of the mating type locus. Using short-read and long-read sequencing methods, the first gapless and near-complete telomere-to-telomere genome assembly of D. coronariae was achieved. The assembled genome spans 51.2 Mbp and comprises 21 chromosome-scale contigs of high completeness. The generated genome sequence was used to in silico elucidate the structure of the mating-type locus, identified as MAT1-2. Furthermore, an examination of MAT1-1 and MAT1-2 frequency across a diverse set of samples sourced from Europe and Asia revealed the exclusive presence of MAT1-2 in European samples, whereas both MAT loci were present in Asian counterparts. Our findings suggest an explanation for the absence of the sexual morph, potentially linked to the absence of the second mating idiomorph of D. coronariae in European apple orchards.

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.

Meta-transcriptomic analysis of companion animal infectomes reveals their diversity and potential roles in animal and human disease

Companion animals such as cats and dogs harbor diverse microbial communities that can potentially impact human health due to close and frequent contact. To better characterize their total infectomes and assess zoonotic risks, we characterized the overall infectomes of companion animals (cats and dogs) and evaluated their potential zoonotic risks. Meta-transcriptomic analyses were performed on 239 samples from cats and dogs collected across China, identifying 24 viral species, 270 bacterial genera, and two fungal genera. Differences in the overall microbiome and infectome composition were compared across different animal species (cats or dogs), sampling sites (rectal or oropharyngeal), and health status (healthy or diseased). Diversity analyses revealed that viral abundance was generally higher in diseased animals compared to healthy ones, while differences in microbial composition were mainly driven by sampling site, followed by animal species and health status. Disease association analyses validated the pathogenicity of known pathogens and suggested potential pathogenic roles of previously undescribed bacteria and newly discovered viruses. Cross-species transmission analyses identified seven pathogens shared between cats and dogs, such as alphacoronavirus 1, which was detected in both oropharyngeal and rectal swabs albeit with differential pathogenicity. Further analyses showed that some viruses, like alphacoronavirus 1, harbored multiple lineages exhibiting distinct pathogenicity, tissue, or host preferences. Ultimately, a systematic evolutionary screening identified 27 potential zoonotic pathogens in this sample set, with far more bacterial than viral species, implying potential health threats to humans. Overall, our meta-transcriptomic analysis reveals a landscape of actively transcribing microorganisms in major companion animals, highlighting key pathogens, those with the potential for cross-species transmission, and possible zoonotic threats.

IMPORTANCE

This study provides a comprehensive characterization of the entire community of infectious microbes (viruses, bacteria, and fungi) in companion animals like cats and dogs, termed the "infectome." By analyzing hundreds of samples from across China, the researchers identified numerous known and novel pathogens, including 27 potential zoonotic agents that could pose health risks to both animals and humans. Notably, some of these zoonotic pathogens were detected even in apparently healthy pets, highlighting the importance of surveillance. The study also revealed key microbial factors associated with respiratory and gastrointestinal diseases in pets, as well as potential cross-species transmission events between cats and dogs. Overall, this work sheds light on the complex microbial landscapes of companion animals and their potential impacts on animal and human health, underscoring the need for monitoring and management of these infectious agents.

Lightweight taxonomic profiling of long-read metagenomic datasets with Lemur and Magnet

The advent of long-read sequencing of microbiomes necessitates the development of new taxonomic profilers tailored to long-read shotgun metagenomic datasets. Here, we introduce Lemur and Magnet, a pair of tools optimized for lightweight and accurate taxonomic profiling for long-read shotgun metagenomic datasets. Lemur is a marker-gene-based method that leverages an EM algorithm to reduce false positive calls while preserving true positives; Magnet is a whole-genome read-mapping-based method that provides detailed presence and absence calls for bacterial genomes. We demonstrate that Lemur and Magnet can run in minutes to hours on a laptop with 32 GB of RAM, even for large inputs, a crucial feature given the portability of long-read sequencing machines. Furthermore, the marker gene database used by Lemur is only 4 GB and contains information from over 300,000 RefSeq genomes. Lemur and Magnet are open-source and available at https://github.com/treangenlab/lemur and https://github.com/treangenlab/magnet.

Analysis of Whole-Genome for Identification of Seven Penicillium Species with Significant Economic Value

The Penicillium genus exhibits a broad global distribution and holds substantial economic value in sectors including agriculture, industry, and medicine. Particularly in agriculture, Penicillium species significantly impact plants, causing diseases and contamination that adversely affect crop yields and quality. Timely detection of Penicillium species is crucial for controlling disease and preventing mycotoxins from entering the food chain. To tackle this issue, we implement a novel species identification approach called Analysis of whole GEnome (AGE). Here, we initially applied bioinformatics analysis to construct specific target sequence libraries from the whole genomes of seven Penicillium species with significant economic impact: P. canescens, P. citrinum, P. oxalicum, P. polonicum, P. paneum, P. rubens, and P. roqueforti. We successfully identified seven Penicillium species using the target we screened combined with Sanger sequencing and CRISPR-Cas12a technologies. Notably, based on CRISPR-Cas12a technology, AGE can achieve rapid and accurate identification of genomic DNA samples at a concentration as low as 0.01 ng/µL within 30 min. This method features high sensitivity and portability, making it suitable for on-site detection. This robust molecular approach provides precise fungal species identification with broad implications for agricultural control, industrial production, clinical diagnostics, and food safety.

Aspergillus brasiliensis E_15.1: A Novel Thermophilic Endophyte from a Volcanic Crater Unveiled through Comprehensive Genome-Wide, Phenotypic Analysis, and Plant Growth-Promoting Trails

Thermophilic fungi have been seldom studied despite the fact that they can contribute to understanding ecological mechanisms of adaptation in diverse environments and have attractive toolboxes with a wide range of biotechnological applications. This work describes for the first time an endophytic and thermophilic strain of Aspergillus brasiliensis that was isolated in the crater of the active volcano "El Chichonal" in Mexico. This strain was capable of surviving in soil with a temperature of 60 °C and a pH of neutral acidity, which preluded a high thermostability and a potential in industrial application. The complete genome of A. brasiliensis E_15.1 was sequenced and assembled in 37 Mb of genomic DNA. We performed a comprehensive phylogenomic analysis for the precise taxonomic identification of this species as a novel strain of Aspergillus brasiliensis. Likewise, the predicted coding sequences were classified according to various functions including Carbohydrate-Active Enzymes (CAZymes), biosynthetic gene clusters of secondary metabolites (BGCs), and metabolic pathways associated with plant growth promotion. A. brasiliensis E_15.1 was found to degrade chitin, chitooligosaccharides, xylan, and cellulose. The genes to biosynthesize clavaric acid (a triterpene with antitumor activity) were found, thus probably having antitumor activity. In addition to the genomic analysis, a set of enzymatic assays confirmed the thermostability of extracellular xylanases and cellulases of A. brasiliensis E_15.1. The enzymatic repertoire of A. brasiliensis E_15.1 suggests that A. brasiliensis E_15.1 has a high potential for industrial application due to its thermostability and can promote plant growth at high temperatures. Finally, this strain constitutes an interesting source of terpenoids with pharmacological activity.

Metagenome-assembled genome of Zalaria obscura strain JY119

Here, we report a 22.1-Mbp genome sequence of microcolonial fungi, Zalaria obscura, isolated from a pine tree bark. The microbiome of the new fungi is predicted to be largely associated with Acidobacteriota. The genome sequence of Zalaria obscura will help us in understanding the unusual relationship with Acidobacteriota member(s).

Analysis of Whole-Genome facilitates rapid and precise identification of fungal species

Fungal identification is a cornerstone of fungal research, yet traditional molecular methods struggle with rapid and accurate onsite identification, especially for closely related species. To tackle this challenge, we introduce a universal identification method called Analysis of whole GEnome (AGE). AGE includes two key steps: bioinformatics analysis and experimental practice. Bioinformatics analysis screens candidate target sequences named Targets within the genome of the fungal species and determines specific Targets by comparing them with the genomes of other species. Then, experimental practice using sequencing or non-sequencing technologies would confirm the results of bioinformatics analysis. Accordingly, AGE obtained more than 1,000,000 qualified Targets for each of the 13 fungal species within the phyla Ascomycota and Basidiomycota. Next, the sequencing and genome editing system validated the ultra-specific performance of the specific Targets; especially noteworthy is the first-time demonstration of the identification potential of sequences from unannotated genomic regions. Furthermore, by combining rapid isothermal amplification and phosphorothioate-modified primers with the option of an instrument-free visual fluorescence method, AGE can achieve qualitative species identification within 30 min using a single-tube test. More importantly, AGE holds significant potential for identifying closely related species and differentiating traditional Chinese medicines from their adulterants, especially in the precise detection of contaminants. In summary, AGE opens the door for the development of whole-genome-based fungal species identification while also providing guidance for its application in plant and animal kingdoms.

Update on the proposed minimal standards for the use of genome data for the taxonomy of prokaryotes

The field of microbial taxonomy is dynamic, aiming to provide a stable and contemporary classification system for prokaryotes. Traditionally, reliance on phenotypic characteristics limited the comprehensive understanding of microbial diversity and evolution. The introduction of molecular techniques, particularly DNA sequencing and genomics, has transformed our perception of prokaryotic diversity. In the past two decades, advancements in genome sequencing have transitioned from traditional methods to a genome-based taxonomic framework, not only to define species, but also higher taxonomic ranks. As technology and databases rapidly expand, maintaining updated standards is crucial. This work seeks to revise the 2018 guidelines for applying genome sequencing data in microbial taxonomy, adapting minimal standards and recommendations to reflect technological progress during this period.

Exophiala chapopotensis sp. nov., an extremotolerant black yeast from an oil-polluted soil in Mexico; phylophenetic approach to species hypothesis in the Herpotrichiellaceae family

Exophiala is a black fungi of the family Herpotrichiellaceae that can be found in a wide range of environments like soil, water and the human body as potential opportunistic pathogen. Some species are known to be extremophiles, thriving in harsh conditions such as deserts, glaciers, and polluted habitats. The identification of novel Exophiala species across diverse environments underlines the remarkable biodiversity within the genus. However, its classification using traditional phenotypic and phylogenetic analyses has posed a challenges. Here we describe a novel taxon, Exophiala chapopotensis sp. nov., strain LBMH1013, isolated from oil-polluted soil in Mexico, delimited according to combined morphological, molecular, evolutionary and statistics criteria. This species possesses the characteristic dark mycelia growing on PDA and tends to be darker in the presence of hydrocarbons. Its growth is dual with both yeast-like and hyphal forms. LBMH1013 differs from closely related species such as E. nidicola due to its larger aseptate conidia and could be distinguished from E. dermatitidis and E. heteromorpha by its inability to thrive above 37°C or 10% of NaCl. A comprehensive genomic analyses using up-to-date overall genome relatedness indices, several multigene phylogenies and molecular evolutionary analyzes using Bayesian speciation models, further validate its species-specific transition from all current Exophiala/Capronia species. Additionally, we applied the phylophenetic conceptual framework to delineate the species-specific hypothesis in order to incorporate this proposal within an integrative taxonomic framework. We believe that this approach to delimit fungal species will also be useful to our peers.

UACG: Up-to-Date Archaeal Core Genes and Software for Phylogenomic Tree Reconstruction

In the post-genomic era, phylogenomics is a powerful and routinely-used tool to discover evolutionary relationships between microorganisms. Inferring phylogenomic trees by concatenating core gene sequences into a supermatrix is the standard method. The previously released up-to-date bacterial core gene (UBCG) tool provides a pipeline to infer phylogenomic trees using single-copy core genes for the Bacteria domain. In this study, we established up-to-date archaeal core gene (UACG), comprising 128 genes suitable for inferring archaeal phylogenomic trees. To test the gene set, we selected the Haloarcula genus and scrutinized its phylogeny. The phylogeny inferred using the UACG tool was consistent with the orthoANIu dendrogram, whereas the 16S rRNA gene phylogeny showed high intragenomic heterogeneity resulting in phylogenetic discrepancies. The software tool using the UACG set is available at https://www.ezbiocloud.net/tools/uacg .