Identification of fungi in shotgun metagenomics datasets

The first ITS1 profiling of honey samples from the Southeast Asian region Lombok, Bali and Banggi Island

Southern Asian flowers offer honeybees a diversity of nectar. Based on its geographical origin, honey quality varies. Traditional methods are less authentic than DNA-based identification. The origin of honey is determined by pollen, polyphenolic, and macro-microorganisms. In this study, amplicon sequencing targets macro-microorganisms in eDNA using the ITS1 region to explore honey's geographical location and authentication. The variety of honey samples was investigated using ITS1 with Illumina sequencing. For all four honey samples, raw sequence reads showed 979,380 raw ITS1 amplicon reads and 375 ASVs up to the phylum level. The highest total number of 202 ASVs up to phylum level identified Bali honey with 211,189 reads, followed by Banggi honey with 309,207 a total number of 111 ASVs, and Lombok represents only 63 ASVs up to phylum level with several read 458,984. Based on Shannon and Chao1, honey samples from Bali (B2) and (B3) exhibited higher diversity than honey from Lombok (B1) and green honey from Sabah (B4), while the Simpson index showed that Banggi honey (B4) had higher diversity. Honey samples had significant variance in mycobiome taxonomic composition and abundance. Zygosaccharomyces and Aspergillus were the main genera found in Lombok honey, with percentages of 68.81% and 29.76% respectively. Bali honey samples (B2 and B3) were identified as having a significant amount of the genus Aureobasidium, accounting for 40.81% and 25% of the readings, respectively. The microbiome composition of Banggi honey (B4) showed a high presence of Zygosaccharomyces 45.17% and Aureobasidium 35.24%. The ITS1 analysis effectively distinguishes between honey samples of different origins and its potential as a discriminatory tool for honey origin and authentication purposes.

Proteomic characterization of Pseudogymnoascus spp. isolates from polar and temperate regions

Proteomics has been used extensively in the field of mycology, mainly in trying to understand the complex network of protein-protein interactions that has been implicated in the molecular functions of fungi. It is also a useful tool to compare metabolic differences within a genus. Species of Pseudogymnoascus, a genus under the phyla Ascomycota, have been shown to play an important role in the soil environment. They have been found in both polar and temperate regions and are a known producer of many extracellular hydrolases that contribute to soil decomposition. Despite the apparent importance of Pseudogymnoascus spp. in the soil ecosystem, investigations into their molecular functions are still very limited. In the present study, proteomic characterization of six Pseudogymnoascus spp. isolated from three biogeographic regions (the Arctic, Antarctic, and temperate regions) was carried out using tandem mass spectrometry. Prior to proteomic analysis, the optimization for protein extraction was carried out. Trichloroacetic acid‑acetone‑phenol was found to be the best extraction method to be used for proteomic profiling of Pseudogymnoascus spp. The proteomic analysis identified 2003 proteins that were successfully mapped to the UniProtKB database. The identified proteins were clustered according to their biological processes and molecular functions. The shared proteins found in all Pseudogymnoascus spp. (1201 proteins) showed a significantly close relationship in their basic cellular functions, despite differences in morphological structures. Analysis of Pseudogymnoascus spp. proteome also identified proteins that were unique to each region. However, a high number of these proteins belonged to protein families of similar molecular functions, namely, transferases and hydrolases. Our proteomic data can be used as a reference for Pseudogymnoascus spp. across different global regions and a foundation for future soil ecosystem function research.

Combining compositional data sets introduces error in covariance network reconstruction

Microbial communities are diverse biological systems that include taxa from across multiple kingdoms of life. Notably, interactions between bacteria and fungi play a significant role in determining community structure. However, these statistical associations across kingdoms are more difficult to infer than intra-kingdom associations due to the nature of the data involved using standard network inference techniques. We quantify the challenges of cross-kingdom network inference from both theoretical and practical points of view using synthetic and real-world microbiome data. We detail the theoretical issue presented by combining compositional data sets drawn from the same environment, e.g. 16S and ITS sequencing of a single set of samples, and we survey common network inference techniques for their ability to handle this error. We then test these techniques for the accuracy and usefulness of their intra- and inter-kingdom associations by inferring networks from a set of simulated samples for which a ground-truth set of associations is known. We show that while the two methods mitigate the error of cross-kingdom inference, there is little difference between techniques for key practical applications including identification of strong correlations and identification of possible keystone taxa (i.e. hub nodes in the network). Furthermore, we identify a signature of the error caused by transkingdom network inference and demonstrate that it appears in networks constructed using real-world environmental microbiome data.

Characterization of the Cassava Mycobiome in Symptomatic Leaf Tissues Displaying Cassava Superelongation Disease

Superelongation disease (SED) is a fungal disease that affects cassava in the Caribbean. The symptoms include the appearance of dry necrotic spots and lesions on the leaves, which may severely affect the plant yield. However, the primary causal pathogen is difficult to culture and isolate in the lab because of its slow growth and potential contamination from faster-growing organisms. In addition, the leaf symptoms can be confused with those caused by other pathogens that produce similar necrotic spots and scab-like lesions. There is also little or no information on the contribution of endophytes, if any, to disease symptoms in cassava, a plant where the disease is prevalent. Therefore, this study aimed to characterize the fungal communities in cassava associated with SED symptoms by analyzing gross fungal morphology and performing metagenomics profiling. First, several individual pathogenic fungi were isolated and cultured from diseased cassava leaf tissues from seven locations in Barbados (BB). Both culture isolation and molecular community analyses showed the presence of several other fungi in the disease microenvironment of symptomatic cassava leaves. These included Fusarium, Colletotrichum, and Alternaria species and the suspected species Elsinoë brasiliensis synonym Sphaceloma manihoticola. Additionally, a community analysis using ITS2 amplicon sequencing of 21 symptomatic leaf tissues from BB, St. Vincent and the Grenadines (SVG), Trinidad and Tobago (TT), and Jamaica (JA) revealed that the disease symptoms of superelongation may also result from the interactions of fungal communities in the mycobiome, including Elsinoë species and other fungi such as Colletotrichum, Cercospora, Alternaria, and Fusarium. Therefore, we suggest that examining the pathobiome concept in SED in the future is necessary.

Fecal Fungal Microbiota (Mycobiome) Study as a Potential Tool for Precision Medicine in Inflammatory Bowel Disease

There is growing evidence of the role of fungal microbiota in the pathogenesis of inflammatory bowel disease (IBD). Fungi can exert direct pro-inflammatory effects or modify the bacterial composition via interkingdom interactions. Although several studies have demonstrated alterations in the fecal fungal microbiota composition in IBD, there is a wide variation in the mycobiome in different populations, with no definite pattern that can define the mycobiome in IBD having yet been identified. Recent work has suggested that characterizing the fecal fungal composition may influence therapeutic decisions and help to predict outcomes in a subset of IBD patients. In this study, we review the current literature on the emerging role of the fecal mycobiome as a potential tool for precision medicine in IBD.

Skin microbiome differentiates into distinct cutotypes with unique metabolic functions upon exposure to polycyclic aromatic hydrocarbons

BACKGROUND

The effects of air pollutants, particularly polycyclic aromatic hydrocarbons (PAHs), on the skin microbiome remain poorly understood. Thus, to better understand the interplay between air pollutants, microbiomes, and skin conditions, we applied metagenomics and metabolomics to analyze the effects of PAHs in air pollution on the skin microbiomes of over 120 subjects residing in two cities in China with different levels of air pollution.

RESULTS

The skin microbiomes differentiated into two cutotypes (termed 1 and 2) with distinct taxonomic, functional, resistome, and metabolite compositions as well as skin phenotypes that transcended geography and host factors. High PAH exposure was linked to dry skin and cutotype 2, which was enriched with species with potential biodegradation functions and had reduced correlation network structure integrity. The positive correlations identified between dominant taxa, key functional genes, and metabolites in the arginine biosynthesis pathway in cutotype 1 suggest that arginine from bacteria contributes to the synthesis of filaggrin-derived natural moisturizing factors (NMFs), which provide hydration for the skin, and could explain the normal skin phenotype observed. In contrast, no correlation with the arginine biosynthesis pathway was observed in cutotype 2, which indicates the limited hydration functions of NMFs and explains the observed dry skin phenotype. In addition to dryness, skin associated with cutotype 2 appeared prone to other adverse conditions such as inflammation.

CONCLUSIONS

This study revealed the roles of PAHs in driving skin microbiome differentiation into cutotypes that vary extensively in taxonomy and metabolic functions and may subsequently lead to variations in skin-microbe interactions that affect host skin health. An improved understanding of the roles of microbiomes on skin exposed to air pollutants can aid the development of strategies that harness microbes to prevent undesirable skin conditions. Video Abstract.

Fungal Integrated Histomolecular Diagnosis Using Targeted Next-Generation Sequencing on Formalin-Fixed Paraffin-Embedded Tissues

Histopathology is the gold standard for fungal infection (FI) diagnosis, but it does not provide a genus and/or species identification. The objective of the present study was to develop targeted next-generation sequencing (NGS) on formalin-fixed tissue samples (FTs) to achieve a fungal integrated histomolecular diagnosis. Nucleic acid extraction was optimized on a first group of 30 FTs with Aspergillus fumigatus or Mucorales infection by macrodissecting the microscopically identified fungal-rich area and comparing Qiagen and Promega extraction methods through DNA amplification by A. fumigatus and Mucorales primers. Targeted NGS was developed on a second group of 74 FTs using three primer pairs (ITS-3/ITS-4, MITS-2A/MITS-2B, and 28S-12-F/28S-13-R) and two databases (UNITE and RefSeq). A prior fungal identification of this group was established on fresh tissues. Targeted NGS and Sanger sequencing results on FTs were compared. To be valid, the molecular identifications had to be compatible with the histopathological analysis. In the first group, the Qiagen method yielded a better extraction efficiency than the Promega method (100% and 86.7% of positive PCRs, respectively). In the second group, targeted NGS allowed fungal identification in 82.4% (61/74) of FTs using all primer pairs, in 73% (54/74) using ITS-3/ITS-4, in 68.9% (51/74) using MITS-2A/MITS-2B, and in 23% (17/74) using 28S-12-F/28S-13-R. The sensitivity varied according to the database used (81% [60/74] using UNITE compared to 50% [37/74] using RefSeq [P = 0.000002]). The sensitivity of targeted NGS (82.4%) was higher than that of Sanger sequencing (45.9%; P < 0.00001). To conclude, fungal integrated histomolecular diagnosis using targeted NGS is suitable on FTs and improves fungal detection and identification.

Comprehensive evaluation of shotgun metagenomics, amplicon sequencing, and harmonization of these platforms for epidemiological studies

In a large cohort of 1,772 participants from the Hispanic Community Health Study/Study of Latinos with overlapping 16SV4 rRNA gene (bacterial amplicon), ITS1 (fungal amplicon), and shotgun sequencing data, we demonstrate that 16SV4 amplicon sequencing and shotgun metagenomics offer the same level of taxonomic accuracy for bacteria at the genus level even at shallow sequencing depths. In contrast, for fungal taxa, we did not observe meaningful agreements between shotgun and ITS1 amplicon results. Finally, we show that amplicon and shotgun data can be harmonized and pooled to yield larger microbiome datasets with excellent agreement (<1% effect size variance across three independent outcomes) using pooled amplicon/shotgun data compared to pure shotgun metagenomic analysis. Thus, there are multiple approaches to study the microbiome in epidemiological studies, and we provide a demonstration of a powerful pooling approach that will allow researchers to leverage the massive amount of amplicon sequencing data generated over the last two decades.

Mycobiota and diet-derived fungal xenosiderophores promote Salmonella gastrointestinal colonization

The fungal gut microbiota (mycobiota) has been implicated in diseases that disturb gut homeostasis, such as inflammatory bowel disease. However, little is known about functional relationships between bacteria and fungi in the gut during infectious colitis. Here we investigated the role of fungal metabolites during infection with the intestinal pathogen Salmonella enterica serovar Typhimurium, a major cause of gastroenteritis worldwide. We found that, in the gut lumen, both the mycobiota and fungi present in the diet can be a source of siderophores, small molecules that scavenge iron from the host. The ability to use fungal siderophores, such as ferrichrome and coprogen, conferred a competitive growth advantage to Salmonella strains expressing the fungal siderophore receptors FhuA or FhuE in vitro and in a mouse model. Our study highlights the role of inter-kingdom cross-feeding between fungi and Salmonella and elucidates an additional function of the gut mycobiota, revealing the importance of these understudied members of the gut ecosystem during bacterial infection.

Wochenende — modular and flexible alignment-based shotgun metagenome analysis

Background

Shotgun metagenome analysis provides a robust and verifiable method for comprehensive microbiome analysis of fungal, viral, archaeal and bacterial taxonomy, particularly with regard to visualization of read mapping location, normalization options, growth dynamics and functional gene repertoires. Current read classification tools use non-standard output formats, or do not fully show information on mapping location. As reference datasets are not perfect, portrayal of mapping information is critical for judging results effectively.

Results

Our alignment-based pipeline, Wochenende, incorporates flexible quality control, trimming, mapping, various filters and normalization. Results are completely transparent and filters can be adjusted by the user. We observe stringent filtering of mismatches and use of mapping quality sharply reduces the number of false positives. Further modules allow genomic visualization and the calculation of growth rates, as well as integration and subsequent plotting of pipeline results as heatmaps or heat trees. Our novel normalization approach additionally allows calculation of absolute abundance profiles by comparison with reads assigned to the human host genome.

Conclusion

Wochenende has the ability to find and filter alignments to all kingdoms of life using both short and long reads, and requires only good quality reference genomes. Wochenende automatically combines multiple available modules ranging from quality control and normalization to taxonomic visualization. Wochenende is available at https://github.com/MHH-RCUG/nf_wochenende.

Drastic reduction of false positive species in samples of insects by intersecting the default output of two popular metagenomic classifiers

The use of high-throughput sequencing to recover short DNA reads of many species has been widely applied on biodiversity studies, either as amplicon metabarcoding or shotgun metagenomics. These reads are assigned to taxa using classifiers. However, for different reasons, the results often contain many false positives. Here we focus on the reduction of false positive species attributable to the classifiers. We benchmarked two popular classifiers, BLASTn followed by MEGAN6 (BM) and Kraken2 (K2), to analyse shotgun sequenced artificial single-species samples of insects. To reduce the number of misclassified reads, we combined the output of the two classifiers in two different ways: (1) by keeping only the reads that were attributed to the same species by both classifiers (intersection approach); and (2) by keeping the reads assigned to some species by any classifier (union approach). In addition, we applied an analytical detection limit to further reduce the number of false positives species. As expected, both metagenomic classifiers used with default parameters generated an unacceptably high number of misidentified species (tens with BM, hundreds with K2). The false positive species were not necessarily phylogenetically close, as some of them belonged to different orders of insects. The union approach failed to reduce the number of false positives, but the intersection approach got rid of most of them. The addition of an analytic detection limit of 0.001 further reduced the number to ca. 0.5 false positive species per sample. The misidentification of species by most classifiers hampers the confidence of the DNA-based methods for assessing the biodiversity of biological samples. Our approach to alleviate the problem is straightforward and significantly reduced the number of reported false positive species.

Methods used for the study of endophytic fungi: a review on methodologies and challenges, and associated tips

Endophytic fungi are microorganisms that colonize the interior of plant tissues (e.g. leaves, seeds, stem, trunk, roots, fruits, flowers) in intracellular and/or extracellular spaces without causing symptoms of disease in host plants. These microorganisms have been isolated from plant species in a wide variety of habitats worldwide, and it is estimated that all terrestrial plants are colonized by one or more species of endophytic fungus. In addition, these microorganisms have been drawing the attention of researchers because of their ability to synthesize a wide range of bioactive molecules with potential for applications in agriculture, medicine and biotechnology. However, several obstacles come up when studying the diversity and chemical potential of endophytic fungi. For example, the usage of an inappropriate surface disinfection method for plant tissue may not eliminate the epiphytic microbiota or may end up interfering with the endophytic mycobiota, which consequently generates erroneous results. Moreover, the composition of the culture medium and the culture conditions can favor the growth of certain species and inhibit others, which generates underestimated results. Other inconsistencies can arise from the fungus misidentification and consequent exploration of its chemical potential. Based on the methodological biases that may occur at all stages of studies dealing with endophytic fungi, the objective of this review is to discuss the main methods employed in these studies as well as highlight the challenges derived from the different approaches. We also report associated tips to help future studies on endophytic fungi as a contribution.

Novel technologies to characterize and engineer the microbiome in inflammatory bowel disease

We present an overview of recent experimental and computational advances in technology used to characterize the microbiome, with a focus on how these developments improve our understanding of inflammatory bowel disease (IBD). Specifically, we present studies that make use of flow cytometry and metabolomics assays to provide a functional characterization of microbial communities. We also describe computational methods for strain-level resolution, temporal series, mycobiome and virome data, co-occurrence networks, and compositional data analysis. In addition, we review novel techniques to therapeutically manipulate the microbiome in IBD. We discuss the benefits and drawbacks of these technologies to increase awareness of specific biases, and to facilitate a more rigorous interpretation of results and their potential clinical application. Finally, we present future lines of research to better characterize the relation between microbial communities and IBD pathogenesis and progression.

MLR-OOD: A Markov Chain Based Likelihood Ratio Method for Out-Of-Distribution Detection of Genomic Sequences

Machine learning or deep learning models have been widely used for taxonomic classification of metagenomic sequences and many studies reported high classification accuracy. Such models are usually trained based on sequences in several training classes in hope of accurately classifying unknown sequences into these classes. However, when deploying the classification models on real testing data sets, sequences that do not belong to any of the training classes may be present and are falsely assigned to one of the training classes with high confidence. Such sequences are referred to as out-of-distribution (OOD) sequences and are ubiquitous in metagenomic studies. To address this problem, we develop a deep generative model-based method, MLR-OOD, that measures the probability of a testing sequencing belonging to OOD by the likelihood ratio of the maximum of the in-distribution (ID) class conditional likelihoods and the Markov chain likelihood of the testing sequence measuring the sequence complexity. We compose three different microbial data sets consisting of bacterial, viral, and plasmid sequences for comprehensively benchmarking OOD detection methods. We show that MLR-OOD achieves the state-of-the-art performance demonstrating the generality of MLR-OOD to various types of microbial data sets. It is also shown that MLR-OOD is robust to the GC content, which is a major confounding effect for OOD detection of genomic sequences. In conclusion, MLR-OOD will greatly reduce false positives caused by OOD sequences in metagenomic sequence classification.

FunOMIC: Pipeline with built-in fungal taxonomic and functional databases for human mycobiome profiling

While analysis of the bacterial microbiome has become routine, that of the fungal microbiome is still hampered by the lack of robust databases and bioinformatic pipelines. Here, we present FunOMIC, a pipeline with built-in taxonomic (1.6 million marker genes) and functional (3.4 million non-redundant fungal proteins) databases for the identification of fungi. Applied to more than 2,600 human metagenomic samples, the tool revealed fungal species associated with geography, body sites, and diseases. Correlation network analysis provided new insights into inter-kingdom interactions. With this pipeline and two of the most comprehensive fungal databases, we foresee a fast-growing resource for mycobiome studies.

Current State and Challenges of the Global Outcomes of Dental Caries Research in the Meta-Omics Era

Despite significant healthcare advances in the 21st century, the exact etiology of dental caries remains unsolved. The past two decades have witnessed a tremendous growth in our understanding of dental caries amid the advent of revolutionary omics technologies. Accordingly, a consensus has been reached that dental caries is a community-scale metabolic disorder, and its etiology is beyond a single causative organism. This conclusion was based on a variety of microbiome studies following the flow of information along the central dogma of biology from genomic data to the end products of metabolism. These studies were facilitated by the unprecedented growth of the next- generation sequencing tools and omics techniques, such as metagenomics and metatranscriptomics, to estimate the community composition of oral microbiome and its functional potential. Furthermore, the rapidly evolving proteomics and metabolomics platforms, including nuclear magnetic resonance spectroscopy and/or mass spectrometry coupled with chromatography, have enabled precise quantification of the translational outcomes. Although the majority supports ‘conserved functional changes’ as indicators of dysbiosis, it remains unclear how caries dynamics impact the microbiota functions and vice versa, over the course of disease onset and progression. What compounds the situation is the host-microbiota crosstalk. Genome-wide association studies have been undertaken to elucidate the interaction of host genetic variation with the microbiome. However, these studies are challenged by the complex interaction of host genetics and environmental factors. All these complementary approaches need to be orchestrated to capture the key players in this multifactorial disease. Herein, we critically review the milestones in caries research focusing on the state-of-art singular and integrative omics studies, supplemented with a bibliographic network analysis to address the oral microbiome, the host factors, and their interactions. Additionally, we highlight gaps in the dental literature and shed light on critical future research questions and study designs that could unravel the complexities of dental caries, the most globally widespread disease.

Clinical Aspergillus Signatures in COPD and Bronchiectasis

Pulmonary mycoses remain a global threat, causing significant morbidity and mortality. Patients with airways disease, including COPD and bronchiectasis, are at increased risks of pulmonary mycoses and its associated complications. Frequent use of antibiotics and corticosteroids coupled with impaired host defenses predispose patients to fungal colonization and airway persistence, which are associated with negative clinical consequences. Notably, Aspergillus species remain the best-studied fungal pathogen and induce a broad spectrum of clinical manifestations in COPD and bronchiectasis ranging from colonization and sensitization to more invasive disease. Next-generation sequencing (NGS) has gained prominence in the field of respiratory infection, and in some cases is beginning to act as a viable alternative to traditional culture. NGS has revolutionized our understanding of airway microbiota and in particular fungi. In this context, it permits the identification of the previously unculturable, fungal composition, and dynamic change within microbial communities of the airway, including potential roles in chronic respiratory disease. Furthermore, inter-kingdom microbial interactions, including fungi, in conjunction with host immunity have recently been shown to have important clinical roles in COPD and bronchiectasis. In this review, we provide an overview of clinical Aspergillus signatures in COPD and bronchiectasis and cover the current advances in the understanding of the mycobiome in these disease states. The challenges and limitations of NGS will be addressed.

de la Pedrosa E, López-Campos JL, Máiz L, del Campo R, Martínez-García MÁ. The Human Mycobiome in Chronic Respiratory Diseases: Current Situation and Future Perspectives

Microbes play an important role in the pathogenesis of chronic lung diseases, such as chronic obstructive pulmonary disease, cystic fibrosis, non-cystic fibrosis bronchiectasis, and asthma. While the role of bacterial pathogens has been extensively studied, the contribution of fungal species to the pathogenesis of chronic lung diseases is much less understood. The recent introduction of next-generation sequencing techniques has revealed the existence of complex microbial lung communities in healthy individuals and patients with chronic respiratory disorders, with fungi being an important part of these communities’ structure (mycobiome). There is growing evidence that the components of the lung mycobiome influence the clinical course of chronic respiratory diseases, not only by direct pathogenesis but also by interacting with bacterial species and with the host’s physiology. In this article, we review the current knowledge on the role of fungi in chronic respiratory diseases, which was obtained by conventional culture and next-generation sequencing, highlighting the limitations of both techniques and exploring future research areas.

Inferring Species Compositions of Complex Fungal Communities from Long- and Short-Read Sequence Data

Our study is unique in that it provides an in-depth comparative study of a real-life complex fungal community analyzed with multiple long- and short-read sequencing approaches. These technologies and their application are currently of great interest to diverse biologists as they seek to characterize the community compositions of microbiomes.

The Neglected Gut Microbiome: Fungi, Protozoa, and Bacteriophages in Inflammatory Bowel Disease

The gut microbiome has been implicated in the pathogenesis of inflammatory bowel disease (IBD). Studies suggest that the IBD gut microbiome is less diverse than that of the unaffected population, a phenomenon often referred to as dysbiosis. However, these studies have heavily focused on bacteria, while other intestinal microorganisms-fungi, protozoa, and bacteriophages-have been neglected. Of the nonbacterial microbes that have been studied in relation to IBD, most are thought to be pathogens, although there is evidence that some of these species may instead be harmless commensals. In this review, we discuss the nonbacterial gut microbiome of IBD, highlighting the current biases, limitations, and outstanding questions that can be addressed with high-throughput DNA sequencing methods. Further, we highlight the importance of studying nonbacterial microorganisms alongside bacteria for a comprehensive view of the whole IBD biome and to provide a more precise definition of dysbiosis in patients. With the rise in popularity of microbiome-altering therapies for the treatment of IBD, such as fecal microbiota transplantation, it is important that we address these knowledge gaps to ensure safe and effective treatment of patients.

Analyzing the human gut mycobiome – a short guide for beginners

The human body is a dynamic ecosystem consisting of millions of microbes which are often comprised under the term microbiome. Compared to bacteria, which count for the overwhelming majority of the microbiome, the number of human-associated fungi is small and often underestimated. Nonetheless, they can be found in different host niches such as the gut, the oral cavity and the skin. The fungal community has several potential roles in health and disease of the human host. In this review we will focus on intestinal fungi and their interaction with the host as well as bacteria. We also summarize technical challenges and possible biases researchers must be aware of when conducting mycobiome analysis.

Metagenomic characterization of indoor dust fungal associated with allergy and lung inflammation among school children

The exposure of school children to indoor air pollutants has increased allergy and respiratory diseases. The objective of this study were to determine the toxicodynamic interaction of indoor pollutants exposure, biological and chemical with expression of adhesion molecules on eosinophil and neutrophil. A self-administered questionnaire, allergy skin test, and fractional exhaled nitric oxide (FeNO) analyser were used to collect information on health status, sensitization to allergens and respiratory inflammation, respectively among school children at age of 14 years. The sputum induced were analysed to determine the expression of CD11b, CD35, CD63 and CD66b on eosinophil and neutrophil by using flow cytometry technique. The particulate matter (PM_2.5 and PM₁₀), NO₂, CO₂, and formaldehyde, temperature, and relative humidity were measured inside the classrooms. The fungal DNA were extracted from settled dust collected from classrooms and evaluated using metagenomic techniques. We applied chemometric and regression in statistical analysis. A total of 1869 unique of operational taxonomic units (OTUs) of fungi were identified with dominated at genus level by Aspergillus (15.8%), Verrucoconiothyrium (5.5%), and Ganoderma (4.6%). Chemometric and regression results revealed that relative abundance of T. asahii were associated with down regulation of CD66b expressed on eosinophil, and elevation of FeNO levels in predicting asthmatic children with model accuracy of 63.6%. Meanwhile, upregulation of CD11b expressed on eosinophil were associated with relative abundance of A. clavatus and regulated by PM_2.5. There were significant association of P. bandonii with upregulation of CD63 expressed on neutrophil and exposure to NO₂. Our findings indicate that exposure to PM_2.5, NO₂, T. asahii, P.bandonii and A.clavatus are likely interrelated with upregulation of activation and degranulation markers on both eosinophil and neutrophil.

The taxonomy of two uncultivated fungal mammalian pathogens is revealed through phylogeny and population genetic analyses

Ever since the uncultivated South American fungal pathogen Lacazia loboi was first described 90 years ago, its etiology and evolutionary traits have been at the center of endless controversies. This pathogen infects the skin of humans and as long believed, dolphin skin. However, recent DNA analyses of infected dolphins placed its DNA sequences within Paracoccidioides species. This came as a surprise and suggested the human and dolphin pathogens may be different species. In this study, population genetic analyses of DNA from four infected dolphins grouped this pathogen in a monophyletic cluster sister to P. americana and to the other Paracoccidioides species. Based on the results we have emended the taxonomy of the dolphin pathogen as Paracoccidioides cetii and P. loboi the one infecting human. Our data warn that phylogenetic analysis of available taxa without the inclusion of unusual members may provide incomplete information for the accurate classification of anomalous species.

Current Insight into Culture-Dependent and Culture-Independent Methods in Discovering Ascomycetous Taxa

Culture techniques are vital in both traditional and modern fungal taxonomy. Establishing sexual-asexual links and synanamorphs, extracting DNA and secondary metabolites are mainly based on cultures. However, it is widely accepted that a large number of species are not sporulating in nature while others cannot be cultured. Recent ecological studies based on culture-independent methods revealed these unculturable taxa, i.e., dark taxa. Recent fungal diversity estimation studies suggested that environmental sequencing plays a vital role in discovering missing species. However, Sanger sequencing is still the main approach in determining DNA sequences in culturable species. In this paper, we summarize culture-based and culture-independent methods in the study of ascomycetous taxa. High-throughput sequencing of leaf endophytes, leaf litter fungi and fungi in aquatic environments is important to determine dark taxa. Nevertheless, currently, naming dark taxa is not recognized by the ICN, thus provisional naming of them is essential as suggested by several studies.

Mining Public Metagenomes for Environmental Surveillance of Parasites: A Proof of Principle

Parasites often have complex developmental cycles that account for their presence in a variety of difficult-to-analyze matrices, including feces, water, soil, and food. Detection of parasites in these matrices still involves laborious methods. Untargeted sequencing of nucleic acids extracted from those matrices in metagenomic projects may represent an attractive alternative method for unbiased detection of these pathogens. Here, we show how publicly available metagenomic datasets can be mined to detect parasite specific sequences, and generate data useful for environmental surveillance. We use the protozoan parasite Cryptosporidium parvum as a test organism, and show that detection is influenced by the reference sequence chosen. Indeed, the use of the whole genome yields high sensitivity but low specificity, whereas specificity is improved through the use of signature sequences. In conclusion, querying metagenomic datasets for parasites is feasible and relevant, but requires optimization and validation. Nevertheless, this approach provides access to the large, and rapidly increasing, number of datasets from metagenomic and meta-transcriptomic studies, allowing unlocking hitherto idle signals of parasites in our environments.

The National Ecological Observatory Network's soil metagenomes: assembly and basic analysis

The National Ecological Observatory Network (NEON) annually performs shotgun metagenomic sequencing to sample genes within soils at 47 sites across the United States. NEON serves as a valuable educational resource, thanks to its open data policies and programming tutorials, but there is currently no introductory tutorial for performing analyses with the soil shotgun metagenomic dataset. Here, we describe a workflow for processing raw soil metagenome sequencing reads using the Sunbeam bioinformatics pipeline. The workflow includes cleaning and processing raw reads, taxonomic classification, assembly into contigs, annotation of predicted genes using custom protein databases, and exporting assemblies to the KBase platform for downstream analysis. This workflow is designed to be robust to annual data releases from NEON, and the underlying Snakemake framework can manage complex software dependencies. The workflow presented here aims to increase the accessibility of NEON's shotgun metagenome data, which can provide important clues about soil microbial communities and their ecological roles.

Crossing Kingdoms: How the Mycobiota and Fungal-Bacterial Interactions Impact Host Health and Disease

The term “microbiota” invokes images of mucosal surfaces densely populated with bacteria. These surfaces and the luminal compartments they form indeed predominantly harbor bacteria.

The term “microbiota” invokes images of mucosal surfaces densely populated with bacteria. These surfaces and the luminal compartments they form indeed predominantly harbor bacteria. However, research from this past decade has started to complete the picture by focusing on important but largely neglected constituents of the microbiota: fungi, viruses, and archaea. The community of commensal fungi, also called the mycobiota, interacts with commensal bacteria and the host. It is thus not surprising that changes in the mycobiota have significant impact on host health and are associated with pathological conditions such as inflammatory bowel disease (IBD). In this review we will give an overview of why the mycobiota is an important research area and different mycobiota research tools. We will specifically focus on distinguishing transient and actively colonizing fungi of the oral and gut mycobiota and their roles in health and disease. In addition to correlative and observational studies, we will discuss mechanistic studies on specific cross-kingdom interactions of fungi, bacteria, and the host.

Current State and Future Directions of Genetics and Genomics of Endophytic Fungi for Bioprospecting Efforts

The bioprospecting of secondary metabolites from endophytic fungi received great attention in the 1990s and 2000s, when the controversy around taxol production from Taxus spp. endophytes was at its height. Since then, hundreds of reports have described the isolation and characterization of putative secondary metabolites from endophytic fungi. However, only very few studies also report the genetic basis for these phenotypic observations. With low sequencing cost and fast sample turnaround, genetics- and genomics-based approaches have risen to become comprehensive approaches to study natural products from a wide-range of organisms, especially to elucidate underlying biosynthetic pathways. However, in the field of fungal endophyte biology, elucidation of biosynthetic pathways is still a major challenge. As a relatively poorly investigated group of microorganisms, even in the light of recent efforts to sequence more fungal genomes, such as the 1000 Fungal Genomes Project at the Joint Genome Institute (JGI), the basis for bioprospecting of enzymes and pathways from endophytic fungi is still rather slim. In this review we want to discuss the current approaches and tools used to associate phenotype and genotype to elucidate biosynthetic pathways of secondary metabolites in endophytic fungi through the lens of bioprospecting. This review will point out the reported successes and shortcomings, and discuss future directions in sampling, and genetics and genomics of endophytic fungi. Identifying responsible biosynthetic genes for the numerous secondary metabolites isolated from endophytic fungi opens the opportunity to explore the genetic potential of producer strains to discover novel secondary metabolites and enhance secondary metabolite production by metabolic engineering resulting in novel and more affordable medicines and food additives.

An Overview of Genomics, Phylogenomics and Proteomics Approaches in Ascomycota

Fungi are among the most successful eukaryotes on Earth: they have evolved strategies to survive in the most diverse environments and stressful conditions and have been selected and exploited for multiple aims by humans. The characteristic features intrinsic of Fungi have required evolutionary changes and adaptations at deep molecular levels. Omics approaches, nowadays including genomics, metagenomics, phylogenomics, transcriptomics, metabolomics, and proteomics have enormously advanced the way to understand fungal diversity at diverse taxonomic levels, under changeable conditions and in still under-investigated environments. These approaches can be applied both on environmental communities and on individual organisms, either in nature or in axenic culture and have led the traditional morphology-based fungal systematic to increasingly implement molecular-based approaches. The advent of next-generation sequencing technologies was key to boost advances in fungal genomics and proteomics research. Much effort has also been directed towards the development of methodologies for optimal genomic DNA and protein extraction and separation. To date, the amount of proteomics investigations in Ascomycetes exceeds those carried out in any other fungal group. This is primarily due to the preponderance of their involvement in plant and animal diseases and multiple industrial applications, and therefore the need to understand the biological basis of the infectious process to develop mechanisms for biologic control, as well as to detect key proteins with roles in stress survival. Here we chose to present an overview as much comprehensive as possible of the major advances, mainly of the past decade, in the fields of genomics (including phylogenomics) and proteomics of Ascomycota, focusing particularly on those reporting on opportunistic pathogenic, extremophilic, polyextremotolerant and lichenized fungi. We also present a review of the mostly used genome sequencing technologies and methods for DNA sequence and protein analyses applied so far for fungi.

Crop-Zone Weed Mycobiomes of the South-Western Australian Grain Belt

In the absence of a primary crop host, secondary plant hosts may act as a reservoir for fungal plant pathogens of agricultural crops. Secondary hosts may potentially harbor heteroecious biotrophs (e.g., the stripe rust fungus Puccinia striiformis) or other pathogens with broad host ranges. Agricultural grain production tends toward monoculture or a limited number of crop hosts over large regions, and local weeds are a major source of potential secondary hosts. In this study, the fungal phyllospheres of 12 weed species common in the agricultural regions of Western Australia (WA) were compared through high-throughput DNA sequencing. Amplicons of D2 and ITS were sequenced on an Illumina MiSeq system using previously published primers and BLAST outputs analyzed using MEGAN. A heatmap of cumulative presence-absence for fungal taxa was generated, and variance patterns were investigated using principal components analysis (PCA) and canonical correspondence analysis (CCA). We observed the presence of several major international crop pathogens, including basidiomycete rusts of the Puccinia spp., and ascomycete phytopathogens of the Leptosphaeria and Pyrenophora genera. Unrelated to crop production, several endemic pathogen species including those infecting Eucalyptus trees were also observed, which was consistent with local native flora. We also observed that differences in latitude or climate zones appeared to influence the geographic distributions of plant pathogenic species more than the presence of compatible host species, with the exception of Brassicaceae host family. There was an increased proportion of necrotrophic Ascomycete species in warmer and drier regions of central WA, compared to an increased proportion of biotrophic Basidiomycete species in cooler and wetter regions in southern WA.

Metagenome Proteins and Database Contamination

Continued influx of metagenome-derived proteins with misannotated taxonomy into conventional databases, including RefSeq, threatens to eliminate the value of taxonomy identifiers. To prevent this, urgent efforts should be undertaken by submitters of metagenomic data sets as well as by database managers.

Continued influx of metagenome-derived proteins with misannotated taxonomy into conventional databases, including RefSeq, threatens to eliminate the value of taxonomy identifiers. To prevent this, urgent efforts should be undertaken by submitters of metagenomic data sets as well as by database managers.

Comparative Microbiome Study of Mummified Peach Fruits by Metagenomics and Metatranscriptomics

The dried peach fruits clinging to peach trees or lying on the ground nearby are known as mummified peach fruits. Here, we examined the microbiome communities of three different mummified peach fruits from the nectarine cultivar "Hahong" by DNA- and RNA-sequencing. We found the dominance of Monilinia fructigena followed by Sclerotinia borealis, S. sclerotiorum, and Botrytis cinerea in the mummified peach fruits. Moreover, we found a high number of Proteobacteria, including Frateuria aurantia, Neoasaia chiangmaiensis, Robbsia andropogonis, and Ewingella Americana. Furthermore, we identified several viruses and viroids. Bacteriophages were identified by DNA- and RNA-sequencing, while viruses and viroids with RNA genomes were identified by only RNA-sequencing. Moreover, we identified a novel mycovirus referred to as Monilinia umbra-like virus 1 (MULV1) from M. fructigena. Our results revealed the co-inhabitance of fungi and bacteria in the mummified peach fruits, although dominant microorganisms were present. RNA-sequencing revealed that several fungal and bacterial genes were actively transcribed. Comparative analyses suggested that RNA-sequencing provides more detailed information on microbial communities; however, combining DNA- and RNA-sequencing results increased the diversity of microorganisms, suggesting the importance of databases and analysis tools for microbiome studies. Taken together, our study provides a comprehensive overview of microbial communities in mummified peach fruits by DNA shotgun sequencing and RNA-sequencing.

Toward a Fully Resolved Fungal Tree of Life

In this review, we discuss the current status and future challenges for fully elucidating the fungal tree of life. In the last 15 years, advances in genomic technologies have revolutionized fungal systematics, ushering the field into the phylogenomic era. This has made the unthinkable possible, namely access to the entire genetic record of all known extant taxa. We first review the current status of the fungal tree and highlight areas where additional effort will be required. We then review the analytical challenges imposed by the volume of data and discuss methods to recover the most accurate species tree given the sea of gene trees. Highly resolved and deeply sampled trees are being leveraged in novel ways to study fungal radiations, species delimitation, and metabolic evolution. Finally, we discuss the critical issue of incorporating the unnamed and uncultured dark matter taxa that represent the vast majority of fungal diversity.

Changes of the human skin microbiota upon chronic exposure to polycyclic aromatic hydrocarbon pollutants

BACKGROUND

Polycyclic aromatic hydrocarbons (PAHs) are of environmental and public health concerns and contribute to adverse skin attributes such as premature skin aging and pigmentary disorder. However, little information is available on the potential roles of chronic urban PAH pollutant exposure on the cutaneous microbiota. Given the roles of the skin microbiota have on healthy and undesirable skin phenotypes and the relationships between PAHs and skin properties, we hypothesize that exposure of PAHs may be associated with changes in the cutaneous microbiota. In this study, the skin microbiota of over two hundred Chinese individuals from two cities in China with varying exposure levels of PAHs were characterized by bacterial and fungal amplicon and shotgun metagenomics sequencing.

RESULTS

Skin site and city were strong parameters in changing microbial communities and their assembly processes. Reductions of bacterial-fungal microbial network structural integrity and stability were associated with skin conditions (acne and dandruff). Multivariate analysis revealed associations between abundances of Propionibacterium and Malassezia with host properties and pollutant exposure levels. Shannon diversity increase was correlated to exposure levels of PAHs in a dose-dependent manner. Shotgun metagenomics analysis of samples (n = 32) from individuals of the lowest and highest exposure levels of PAHs further highlighted associations between the PAHs quantified and decrease in abundances of skin commensals and increase in oral bacteria. Functional analysis identified associations between levels of PAHs and abundance of microbial genes of metabolic and other pathways with potential importance in host-microbe interactions as well as degradation of aromatic compounds.

CONCLUSIONS

The results in this study demonstrated the changes in composition and functional capacities of the cutaneous microbiota associated with chronic exposure levels of PAHs. Findings from this study will aid the development of strategies to harness the microbiota in protecting the skin against pollutants. Video Abstract.

Shotgun sequencing of honey DNA can describe honey bee derived environmental signatures and the honey bee hologenome complexity

Honey bees are large-scale monitoring tools due to their extensive environmental exploration. In their activities and from the hive ecosystem complex, they get in close contact with many organisms whose traces can be transferred into the honey, which can represent an interesting reservoir of environmental DNA (eDNA) signatures and information useful to analyse the honey bee hologenome complexity. In this study, we tested a deep shotgun sequencing approach of honey DNA coupled with a specifically adapted bioinformatic pipeline. This methodology was applied to a few honey samples pointing out DNA sequences from 191 organisms spanning different kingdoms or phyla (viruses, bacteria, plants, fungi, protozoans, arthropods, mammals). Bacteria included the largest number of species. These multi-kingdom signatures listed common hive and honey bee gut microorganisms, honey bee pathogens, parasites and pests, which resembled a complex interplay that might provide a general picture of the honey bee pathosphere. Based on the Apis mellifera filamentous virus genome diversity (the most abundant detected DNA source) we obtained information that could define the origin of the honey at the apiary level. Mining Apis mellifera sequences made it possible to identify the honey bee subspecies both at the mitochondrial and nuclear genome levels.

Overview of the Potential Role of Malassezia in Gut Health and Disease

Malassezia is the most prevalent fungus identified in the human skin microbiota; originally described at the end of the nineteenth century, this genus is composed of at least 14 species. The role of Malassezia on the skin remains controversial because this genus has been associated with both healthy skin and pathologies (dermatitis, eczema, etc.). However, with the recent development of next-generation sequencing methods, allowing the description of the fungal diversity of various microbiota, Malassezia has also been identified as a resident fungus of diverse niches such as the gut or breast milk. A potential role for Malassezia in gut inflammation and cancer has also been suggested by recent studies. The aim of this review is to describe the findings on Malassezia in these unusual niches, to investigate what is known of the adaptation of Malassezia to the gut environment and to speculate on the role of this yeast in the host physiology specifically related to the gastrointestinal tract.

The use of taxon-specific reference databases compromises metagenomic classification

A recent article in BMC Genomics describes a new bioinformatics tool, HumanMycobiomeScan, to classify fungal taxa in metagenomic samples. This tool was used to characterize the gut mycobiome of hunter-gatherers and Western populations, resulting in the identification of a range of fungal species in the vast majority of samples. In the HumanMycobiomeScan pipeline, sequence reads are mapped against a reference database containing fungal genome sequences only. We argue that using reference databases comprised of a single taxonomic group leads to an unacceptably high number of false-positives due to: (i) mapping to conserved genetic regions in reference genomes, and (ii) sequence contamination in the assembled reference genomes. To demonstrate this, we replaced the HumanMycobiomeScan's fungal reference database with one containing genome sequences of amphibians and reptiles and re-analysed their case study. The classification pipeline recovered all species present in the reference database, revealing turtles (Geoemydidae), bull frogs (Pyxicephalidae) and snakes (Colubridae) as the most abundant herpetological taxa in the human gut. We also re-analysed their case study using a kingdom-agnostic pipeline. This revealed that while the gut of hunter-gatherers and Western subjects may be colonized by a range of microbial eukaryotes, only three fungal families were retrieved. These results highlight the pitfalls of using taxon-specific reference databases for metagenome classification, even when they are comprised of curated whole genome data. We propose that databases containing all domains of life provide the most suitable option for metagenomic species profiling, especially when targeting microbial eukaryotes.

The Human Oral Microbiome in Health and Disease: From Sequences to Ecosystems

Abstract: The human oral cavity is home to an abundant and diverse microbial community (i.e., the oral microbiome), whose composition and roles in health and disease have been the focus of intense research in recent years. Thanks to developments in sequencing-based approaches, such as 16S ribosomal RNA metabarcoding, whole metagenome shotgun sequencing, or meta-transcriptomics, we now can efficiently explore the diversity and roles of oral microbes, even if unculturable. Recent sequencing-based studies have charted oral ecosystems and how they change due to lifestyle or disease conditions. As studies progress, there is increasing evidence of an important role of the oral microbiome in diverse health conditions, which are not limited to diseases of the oral cavity. This, in turn, opens new avenues for microbiome-based diagnostics and therapeutics that benefit from the easy accessibility of the oral cavity for microbiome monitoring and manipulation. Yet, many challenges remain ahead. In this review, we survey the main sequencing-based methodologies that are currently used to explore the oral microbiome and highlight major findings enabled by these approaches. Finally, we discuss future prospects in the field.

Metatranscriptomic dynamics after Verticillium dahliae infection and root damage in Olea europaea

BACKGROUND

The olive tree is of particular economic interest in the Mediterranean basin. Researchers have conducted several studies on one of the most devastating disorders affecting this tree, the Verticillium wilt, which causes substantial economic losses in numerous areas. We analyzed metatranscriptomic samples taken from a previous study conducted on leaves and roots of Olea europaea that were infected with Verticillium dahliae. In addition, we also analyzed mechanically damaged roots. The aim of our approach is to describe the dynamics of the root microbiome after severe perturbations.

RESULTS

Our results not only describe the dynamics of the microbial community associated with the disturbance, but also show the high complexity of these systems and explain how this can lead to a conflicting assignment of the various types of parasitism observed in a specific organism.

CONCLUSIONS

Our findings indicate that this infection, although led by Verticillium, is driven not by a single species, but by a polymicrobial consortium that also includes natural endophytes of the olive tree. This community contains both biotrophic and necrotrophic organisms that alternate and live together during the infection. In addition, opportunistic organisms appear that take profit not from plant tissues, but from new emerging populations of microorganisms. Therefore, this system can be described as a complex biological system composed of different interacting communities. Notably, our work has important considerations when it comes to classifying the type of parasitism of a given species.

Estimation of the relative abundance of species in artificial mixtures of insects using low-coverage shotgun metagenomics

Amplicon metabarcoding is an established technique to analyse the taxonomic composition of communities of organisms using high-throughput DNA sequencing, but there are doubts about its ability to quantify the relative proportions of the species, as opposed to the species list. Here, we bypass the enrichment step and avoid the PCR-bias, by directly sequencing the extracted DNA using shotgun metagenomics. This approach is common practice in prokaryotes, but not in eukaryotes, because of the low number of sequenced genomes of eukaryotic species. We tested the metagenomics approach using insect species whose genome is already sequenced and assembled to an advanced degree. We shotgun-sequenced, at low-coverage, 18 species of insects in 22 single-species and 6 mixed-species libraries and mapped the reads against 110 reference genomes of insects. We used the single-species libraries to calibrate the process of assignation of reads to species and the libraries created from species mixtures to evaluate the ability of the method to quantify the relative species abundance. Our results showed that the shotgun metagenomic method is easily able to set apart closely-related insect species, like four species of Drosophila included in the artificial libraries. However, to avoid the counting of rare misclassified reads in samples, it was necessary to use a rather stringent detection limit of 0.001, so species with a lower relative abundance are ignored. We also identified that approximately half the raw reads were informative for taxonomic purposes. Finally, using the mixed-species libraries, we showed that it was feasible to quantify with confidence the relative abundance of individual species in the mixtures.

Metagenomics methods for the study of plant-associated microbial communities: A review

Plant microbiota have different effects on the plant which can be beneficial or pathogenic. In this study, we concentrated on beneficial microbes associated with plants using endophytic microbes as a case study. Detailed knowledge of the microbial diversity, abundance, composition, functional genes patterns, and metabolic pathways at genome level could assist in understanding the contributions of microbial community towards plant growth and health. Recently, the study of microbial community has improved greatly with the discovery of next-generation sequencing and bioinformatics technologies. Analysis of next generation sequencing data and a proper computational method plays a key role in examining microbial metagenome. This review presents the general metagenomics and computational methods used in processing plant associated metagenomes with concentration on endophytes. This includes 1) introduction of plant-associated microbiota and the factors driving their diversity. 2) plant metagenome focusing on DNA extraction, verification and quality control. 3) metagenomics methods used in community analysis of endophytes focusing on maize plant and, 4) computational methods used in the study of endophytic microbiomes. Limitations and future prospects of metagenomics and computational methods for the analysis of plant-associated metagenome (endophytic metagenome) were also discussed with the aim of fostering its development. We conclude that there is need to adopt advanced genomic features such as k-mers of random size, which do not depend on annotation and can represent other sequence alternatives.

The Mycobiome in Health and Disease: Emerging Concepts, Methodologies and Challenges

Fungal disease is an increasingly recognised global clinical challenge associated with high mortality. Early diagnosis of fungal infection remains problematic due to the poor sensitivity and specificity of current diagnostic modalities. Advances in sequencing technologies hold promise in addressing these shortcomings and for improved fungal detection and identification. To translate such emerging approaches into mainstream clinical care will require refinement of current sequencing and analytical platforms, ensuring standardisation and consistency through robust clinical benchmarking and its validation across a range of patient populations. In this state-of-the-art review, we discuss current diagnostic and therapeutic challenges associated with fungal disease and provide key examples where the application of sequencing technologies has potential diagnostic application in assessing the human ‘mycobiome’. We assess how ready access to fungal sequencing may be exploited in broadening our insight into host–fungal interaction, providing scope for clinical diagnostics and the translation of emerging mycobiome research into clinical practice.

Improved metagenomic analysis with Kraken 2

Although Kraken's k-mer-based approach provides a fast taxonomic classification of metagenomic sequence data, its large memory requirements can be limiting for some applications. Kraken 2 improves upon Kraken 1 by reducing memory usage by 85%, allowing greater amounts of reference genomic data to be used, while maintaining high accuracy and increasing speed fivefold. Kraken 2 also introduces a translated search mode, providing increased sensitivity in viral metagenomics analysis.

Improved metagenomic analysis with Kraken 2

Although Kraken’s k-mer-based approach provides a fast taxonomic classification of metagenomic sequence data, its large memory requirements can be limiting for some applications. Kraken 2 improves upon Kraken 1 by reducing memory usage by 85%, allowing greater amounts of reference genomic data to be used, while maintaining high accuracy and increasing speed fivefold. Kraken 2 also introduces a translated search mode, providing increased sensitivity in viral metagenomics analysis.

Metagenomics of Atacama Lithobiontic Extremophile Life Unveils Highlights on Fungal Communities, Biogeochemical Cycles and Carbohydrate-Active Enzymes

Halites, which are typically found in various Atacama locations, are evaporitic rocks that are considered as micro-scaled salterns. Both structural and functional metagenomic analyses of halite nodules were performed. Structural analyses indicated that the halite microbiota is mainly composed of NaCl-adapted microorganisms. In addition, halites appear to harbor a limited diversity of fungal families together with a biodiverse collection of protozoa. Functional analysis indicated that the halite microbiome possesses the capacity to make an extensive contribution to carbon, nitrogen, and sulfur cycles, but possess a limited capacity to fix nitrogen. The halite metagenome also contains a vast repertory of carbohydrate active enzymes (CAZY) with glycosyl transferases being the most abundant class present, followed by glycosyl hydrolases (GH). Amylases were also present in high abundance, with GH also being identified. Thus, the halite microbiota is a potential useful source of novel enzymes that could have biotechnological applicability. This is the first metagenomic report of fungi and protozoa as endolithobionts of halite nodules, as well as the first attempt to describe the repertoire of CAZY in this community. In addition, we present a comprehensive functional metagenomic analysis of the metabolic capacities of the halite microbiota, providing evidence for the first time on the sulfur cycle in Atacama halites.

MycopathologiaGENOMES: The New 'Home' for the Publication of Fungal Genomes

The wider availability of information on genomes has become essential for future advances in fungal biology, pathogenesis and epidemiology, and for the discovery of new drugs and diagnostics. MycopathologiaGENOMES is designed for the rapid publication of new genomes of human and animal pathogenic fungi using a checklist-based, standardized format.

The gut mycobiota: insights into analysis, environmental interactions and role in gastrointestinal diseases

The gut microbiota is a dense and diverse ecosystem that is involved in many physiological functions as well as in disease pathogenesis. It is dominated by bacteria, which have been extensively studied in the past 15 years; however, other microorganisms, such as fungi, phages, archaea and protists, are also present in the gut microbiota. Exploration of the fungal component, namely, the mycobiota, is at an early stage, and several specific technical challenges are associated with mycobiota analysis. The number of fungi in the lower gastrointestinal tract is far lower than that of bacteria, but fungal cells are much larger and much more complex than bacterial cells. In addition, a role of the mycobiota in disease, notably in IBD, is indicated by both descriptive data in humans and mechanistic data in mice. Interactions between bacteria and fungi within the gut, their functional roles and their interplay with the host and its immune system are fascinating areas that researchers are just beginning to investigate. In this Review, we discuss the newest data on the gut mycobiota and explore both the technical aspects of its study and its role in health and gastrointestinal diseases.