ITSoneDB: a comprehensive collection of eukaryotic ribosomal RNA Internal Transcribed Spacer 1 (ITS1) sequences

A comprehensive overview of microbiome data in the light of machine learning applications: categorization, accessibility, and future directions

Metagenomics, Metabolomics, and Metaproteomics have significantly advanced our knowledge of microbial communities by providing culture-independent insights into their composition and functional potential. However, a critical challenge in this field is the lack of standard and comprehensive metadata associated with raw data, hindering the ability to perform robust data stratifications and consider confounding factors. In this comprehensive review, we categorize publicly available microbiome data into five types: shotgun sequencing, amplicon sequencing, metatranscriptomic, metabolomic, and metaproteomic data. We explore the importance of metadata for data reuse and address the challenges in collecting standardized metadata. We also, assess the limitations in metadata collection of existing public repositories collecting metagenomic data. This review emphasizes the vital role of metadata in interpreting and comparing datasets and highlights the need for standardized metadata protocols to fully leverage metagenomic data's potential. Furthermore, we explore future directions of implementation of Machine Learning (ML) in metadata retrieval, offering promising avenues for a deeper understanding of microbial communities and their ecological roles. Leveraging these tools will enhance our insights into microbial functional capabilities and ecological dynamics in diverse ecosystems. Finally, we emphasize the crucial metadata role in ML models development.

SPLASH: A statistical, reference-free genomic algorithm unifies biological discovery

Today's genomics workflows typically require alignment to a reference sequence, which limits discovery. We introduce a unifying paradigm, SPLASH (Statistically Primary aLignment Agnostic Sequence Homing), which directly analyzes raw sequencing data, using a statistical test to detect a signature of regulation: sample-specific sequence variation. SPLASH detects many types of variation and can be efficiently run at scale. We show that SPLASH identifies complex mutation patterns in SARS-CoV-2, discovers regulated RNA isoforms at the single-cell level, detects the vast sequence diversity of adaptive immune receptors, and uncovers biology in non-model organisms undocumented in their reference genomes: geographic and seasonal variation and diatom association in eelgrass, an oceanic plant impacted by climate change, and tissue-specific transcripts in octopus. SPLASH is a unifying approach to genomic analysis that enables expansive discovery without metadata or references.

DIVE: a reference-free statistical approach to diversity-generating and mobile genetic element discovery

Diversity-generating and mobile genetic elements are key to microbial and viral evolution and can result in evolutionary leaps. State-of-the-art algorithms to detect these elements have limitations. Here, we introduce DIVE, a new reference-free approach to overcome these limitations using information contained in sequencing reads alone. We show that DIVE has improved detection power compared to existing reference-based methods using simulations and real data. We use DIVE to rediscover and characterize the activity of known and novel elements and generate new biological hypotheses about the mobilome. Building on DIVE, we develop a reference-free framework capable of de novo discovery of mobile genetic elements.

[WITHDRAWN] SPLASH: a statistical, reference-free genomic algorithm unifies biological discovery

The authors have withdrawn this manuscript due to a duplicate posting of manuscript number BIORXIV/2022/497555. Therefore, the authors do not wish this work to be cited as reference for the project. If you have any questions, please contact the corresponding author. The correct preprint can be found at doi: https://doi.org/10.1101/2022.06.24.497555.

SPLASH: a statistical, reference-free genomic algorithm unifies biological discovery

Today's genomics workflows typically require alignment to a reference sequence, which limits discovery. We introduce a new unifying paradigm, SPLASH (Statistically Primary aLignment Agnostic Sequence Homing), an approach that directly analyzes raw sequencing data to detect a signature of regulation: sample-specific sequence variation. The approach, which includes a new statistical test, is computationally efficient and can be run at scale. SPLASH unifies detection of myriad forms of sequence variation. We demonstrate that SPLASH identifies complex mutation patterns in SARS-CoV-2 strains, discovers regulated RNA isoforms at the single cell level, documents the vast sequence diversity of adaptive immune receptors, and uncovers biology in non-model organisms undocumented in their reference genomes: geographic and seasonal variation and diatom association in eelgrass, an oceanic plant impacted by climate change, and tissue-specific transcripts in octopus. SPLASH is a new unifying approach to genomic analysis that enables an expansive scope of discovery without metadata or references.

Translational informatics for human microbiota: data resources, models and applications

With the rapid development of human intestinal microbiology and diverse microbiome-related studies and investigations, a large amount of data have been generated and accumulated. Meanwhile, different computational and bioinformatics models have been developed for pattern recognition and knowledge discovery using these data. Given the heterogeneity of these resources and models, we aimed to provide a landscape of the data resources, a comparison of the computational models and a summary of the translational informatics applied to microbiota data. We first review the existing databases, knowledge bases, knowledge graphs and standardizations of microbiome data. Then, the high-throughput sequencing techniques for the microbiome and the informatics tools for their analyses are compared. Finally, translational informatics for the microbiome, including biomarker discovery, personalized treatment and smart healthcare for complex diseases, are discussed.

Interactive Web-Based Services for Metagenomic Data Analysis and Comparisons

Recently, sequencing technologies have become readily available, and scientists are more motivated to conduct metagenomic research to unveil the potential of a myriad of ecosystems and biomes. Metagenomics studies the composition and functions of microbial communities and paves the way to multiple applications in medicine, industry, and ecology. Nonetheless, the immense amount of sequencing data of metagenomics research and the few user-friendly analysis tools and pipelines carry a new challenge to the data analysis.Web-based bioinformatics tools are now being developed to facilitate the analysis of complex metagenomic data without prior knowledge of any programming languages or special installation. Specialized web tools help answer researchers' main questions on the taxonomic classification, functional capabilities, discrepancies between two ecosystems, and the probable functional correlations between the members of a specific microbial community. With an Internet connection and a few clicks, researchers can conveniently and efficiently analyze the metagenomic datasets, summarize results, and visualize key information on the composition and the functional potential of metagenomic samples under study. This chapter provides a simple guide to a few of the fundamental web-based services used for metagenomic data analyses, such as BV-BRC, RDP, MG-RAST, MicrobiomeAnalyst, METAGENassist, and MGnify.

Extension of the shelf-life of fresh pasta using modified atmosphere packaging and bioprotective cultures

Microbial stability of fresh pasta depends on heat treatment, storage temperature, proper preservatives, and atmosphere packaging. This study aimed at improving the microbial quality, safety, and shelf life of fresh pasta using modified atmosphere composition and packaging with or without the addition of bioprotective cultures (Lactobacillus acidophilus, Lactobacillus casei, Bifidobacterium spp., and Bacillus coagulans) into semolina. Three fresh pasta variants were made using (i) the traditional protocol (control), MAP (20:80 CO2:N2), and barrier packaging, (ii) the experimental MAP (40:60 CO2:N2) and barrier packaging, and (iii) the experimental MAP, barrier packaging, and bioprotective cultures. Their effects on physicochemical properties (i.e., content on macro elements, water activity, headspace O2, CO2 concentrations, and mycotoxins), microbiological patterns, protein, and volatile organic compounds (VOC) were investigated at the beginning and the end of the actual or extended shelf-life through traditional and multi-omics approaches. We showed that the gas composition and properties of the packaging material tested in the experimental MAP system, with or without bioprotective cultures, positively affect features of fresh pasta avoiding changes in their main chemical properties, allowing for a storage longer than 120 days under refrigerated conditions. These results support that, although bioprotective cultures were not all able to grow in tested conditions, they can control the spoilage and the associated food-borne microbiota in fresh pasta during storage by their antimicrobials and/or fermentation products synergically. The VOC profiling, based on gas-chromatography mass-spectrometry (GC-MS), highlighted significant differences affected by the different manufacturing and packaging of samples. Therefore, the use of the proposed MAP system and the addition of bioprotective cultures can be considered an industrial helpful strategy to reduce the quality loss during refrigerated storage and to increase the shelf life of fresh pasta for additional 30 days by allowing the economic and environmental benefits spurring innovation in existing production models.

Metagenomics: A Tool for Exploring Key Microbiome With the Potentials for Improving Sustainable Agriculture

Microorganisms are immense in nature and exist in every imaginable ecological niche, performing a wide range of metabolic processes. Unfortunately, using traditional microbiological methods, most microorganisms remain unculturable. The emergence of metagenomics has resolved the challenge of capturing the entire microbial community in an environmental sample by enabling the analysis of whole genomes without requiring culturing. Metagenomics as a non-culture approach encompasses a greater amount of genetic information than traditional approaches. The plant root-associated microbial community is essential for plant growth and development, hence the interactions between microorganisms, soil, and plants is essential to understand and improve crop yields in rural and urban agriculture. Although some of these microorganisms are currently unculturable in the laboratory, metagenomic techniques may nevertheless be used to identify the microorganisms and their functional traits. A detailed understanding of these organisms and their interactions should facilitate an improvement of plant growth and sustainable crop production in soil and soilless agriculture. Therefore, the objective of this review is to provide insights into metagenomic techniques to study plant root-associated microbiota and microbial ecology. In addition, the different DNA-based techniques and their role in elaborating plant microbiomes are discussed. As an understanding of these microorganisms and their biotechnological potentials are unlocked through metagenomics, they can be used to develop new, useful and unique bio-fertilizers and bio-pesticides that are not harmful to the environment.

Comparative Analysis of Metagenomics and Metataxonomics for the Characterization of Vermicompost Microbiomes

The study of microbial communities or microbiotas in animals and environments is important because of their impact in a broad range of industrial applications, diseases and ecological roles. High throughput sequencing (HTS) is the best strategy to characterize microbial composition and function. Microbial profiles can be obtained either by shotgun sequencing of genomes, or through amplicon sequencing of target genes (e.g., 16S rRNA for bacteria and ITS for fungi). Here, we compared both HTS approaches at assessing taxonomic and functional diversity of bacterial and fungal communities during vermicomposting of white grape marc. We applied specific HTS workflows to the same 12 microcosms, with and without earthworms, sampled at two distinct phases of the vermicomposting process occurring at 21 and 63 days. Metataxonomic profiles were inferred in DADA2, with bacterial metabolic pathways predicted via PICRUSt2. Metagenomic taxonomic profiles were inferred in PathoScope, while bacterial functional profiles were inferred in Humann2. Microbial profiles inferred by metagenomics and metataxonomics showed similarities and differences in composition, structure, and metabolic function at different taxonomic levels. Microbial composition and abundance estimated by both HTS approaches agreed reasonably well at the phylum level, but larger discrepancies were observed at lower taxonomic ranks. Shotgun HTS identified ~1.8 times more bacterial genera than 16S rRNA HTS, while ITS HTS identified two times more fungal genera than shotgun HTS. This is mainly a consequence of the difference in resolution and reference richness between amplicon and genome sequencing approaches and databases, respectively. Our study also revealed great differences and even opposite trends in alpha- and beta-diversity between amplicon and shotgun HTS. Interestingly, amplicon PICRUSt2-imputed functional repertoires overlapped ~50% with shotgun Humann2 profiles. Finally, both approaches indicated that although bacteria and fungi are the main drivers of biochemical decomposition, earthworms also play a key role in plant vermicomposting. In summary, our study highlights the strengths and weaknesses of metagenomics and metataxonomics and provides new insights on the vermicomposting of white grape marc. Since both approaches may target different biological aspects of the communities, combining them will provide a better understanding of the microbiotas under study.

Recommendations for connecting molecular sequence and biodiversity research infrastructures through ELIXIR

Threats to global biodiversity are increasingly recognised by scientists and the public as a critical challenge. Molecular sequencing technologies offer means to catalogue, explore, and monitor the richness and biogeography of life on Earth. However, exploiting their full potential requires tools that connect biodiversity infrastructures and resources. As a research infrastructure developing services and technical solutions that help integrate and coordinate life science resources across Europe, ELIXIR is a key player. To identify opportunities, highlight priorities, and aid strategic thinking, here we survey approaches by which molecular technologies help inform understanding of biodiversity. We detail example use cases to highlight how DNA sequencing is: resolving taxonomic issues; Increasing knowledge of marine biodiversity; helping understand how agriculture and biodiversity are critically linked; and playing an essential role in ecological studies. Together with examples of national biodiversity programmes, the use cases show where progress is being made but also highlight common challenges and opportunities for future enhancement of underlying technologies and services that connect molecular and wider biodiversity domains. Based on emerging themes, we propose key recommendations to guide future funding for biodiversity research: biodiversity and bioinformatic infrastructures need to collaborate closely and strategically; taxonomic efforts need to be aligned and harmonised across domains; metadata needs to be standardised and common data management approaches widely adopted; current approaches need to be scaled up dramatically to address the anticipated explosion of molecular data; bioinformatics support for biodiversity research needs to be enabled and sustained; training for end users of biodiversity research infrastructures needs to be prioritised; and community initiatives need to be proactive and focused on enabling solutions. For sequencing data to deliver their full potential they must be connected to knowledge: together, molecular sequence data collection initiatives and biodiversity research infrastructures can advance global efforts to prevent further decline of Earth's biodiversity.

Recommendations for connecting molecular sequence and biodiversity research infrastructures through ELIXIR

Threats to global biodiversity are increasingly recognised by scientists and the public as a critical challenge. Molecular sequencing technologies offer means to catalogue, explore, and monitor the richness and biogeography of life on Earth. However, exploiting their full potential requires tools that connect biodiversity infrastructures and resources. As a research infrastructure developing services and technical solutions that help integrate and coordinate life science resources across Europe, ELIXIR is a key player. To identify opportunities, highlight priorities, and aid strategic thinking, here we survey approaches by which molecular technologies help inform understanding of biodiversity. We detail example use cases to highlight how DNA sequencing is: resolving taxonomic issues; Increasing knowledge of marine biodiversity; helping understand how agriculture and biodiversity are critically linked; and playing an essential role in ecological studies. Together with examples of national biodiversity programmes, the use cases show where progress is being made but also highlight common challenges and opportunities for future enhancement of underlying technologies and services that connect molecular and wider biodiversity domains. Based on emerging themes, we propose key recommendations to guide future funding for biodiversity research: biodiversity and bioinformatic infrastructures need to collaborate closely and strategically; taxonomic efforts need to be aligned and harmonised across domains; metadata needs to be standardised and common data management approaches widely adopted; current approaches need to be scaled up dramatically to address the anticipated explosion of molecular data; bioinformatics support for biodiversity research needs to be enabled and sustained; training for end users of biodiversity research infrastructures needs to be prioritised; and community initiatives need to be proactive and focused on enabling solutions. For sequencing data to deliver their full potential they must be connected to knowledge: together, molecular sequence data collection initiatives and biodiversity research infrastructures can advance global efforts to prevent further decline of Earth's biodiversity.

Skin Metagenomic Sequence Analysis of Early Candida auris Outbreaks in U.S. Nursing Homes

Candida auris is a human fungal pathogen classified as an urgent threat to the delivery of health care due to its extensive antimicrobial resistance and the high mortality rates associated with invasive infections. Global outbreaks have occurred in health care facilities, particularly, long-term care hospitals and nursing homes. Skin is the primary site of colonization for C. auris. To accelerate research studies, we developed microbiome sequencing protocols, including amplicon and metagenomic sequencing, directly from patient samples at health care facilities with ongoing C. auris outbreaks. We characterized the skin mycobiome with a database optimized to classify Candida species and C. auris to the clade level. While Malassezia species were the predominant skin-associated fungi, nursing home residents also harbored Candida species, including C. albicans, and C. parapsilosis. Amplicon sequencing was concordant with culturing studies to identify C. auris-colonized patients and provided further resolution that distinct clades of C. auris are colonizing facilities in New York and Illinois. Shotgun metagenomic sequencing from a clinical sample with a high fungal bioburden generated a skin-associated profile of the C. auris genome. Future larger scale clinical studies are warranted to more systematically investigate the effects of commensal microbes and patient risk factors on the colonization and transmission of C. auris.

IMPORTANCECandida auris is a human pathogen of high concern due to its extensive antifungal drug resistance and high mortality rates associated with invasive infections. Candida auris skin colonization and persistence on environmental surfaces make this pathogen difficult to control once it enters a health care facility. Residents in long-term care hospitals and nursing homes are especially vulnerable. In this study, we developed microbiome sequencing protocols directly from surveillance samples, including amplicon and metagenomic sequencing, demonstrating concordance between sequencing results and culturing.

ITSoneWB: profiling global taxonomic diversity of eukaryotic communities on Galaxy

Summary

ITSoneWB (ITSone WorkBench) is a Galaxy-based bioinformatic environment where comprehensive and high-quality reference data are connected with established pipelines and new tools in an automated and easy-to-use service targeted at global taxonomic analysis of eukaryotic communities based on Internal Transcribed Spacer 1 variants high-throughput sequencing.

Availability and implementation

ITSoneWB has been deployed on the INFN-Bari ReCaS cloud facility and is freely available on the web at http://itsonewb.cloud.ba.infn.it/galaxy.

Supplementary information

Supplementary data are available at Bioinformatics online.

An Introduction to Next Generation Sequencing Bioinformatic Analysis in Gut Microbiome Studies

The gut microbiome is a microbial ecosystem which expresses 100 times more genes than the human host and plays an essential role in human health and disease pathogenesis. Since most intestinal microbial species are difficult to culture, next generation sequencing technologies have been widely applied to study the gut microbiome, including 16S rRNA, 18S rRNA, internal transcribed spacer (ITS) sequencing, shotgun metagenomic sequencing, metatranscriptomic sequencing and viromic sequencing. Various software tools were developed to analyze different sequencing data. In this review, we summarize commonly used computational tools for gut microbiome data analysis, which extended our understanding of the gut microbiome in health and diseases.

User-friendly bioinformatics pipeline gDAT (graphical downstream analysis tool) for analysing rDNA sequences

High-throughput sequencing (HTS) of multiple organisms in parallel (metabarcoding) has become a routine and cost-effective method for the analysis of microbial communities in environmental samples. However, careful data treatment is required to identify potential errors in HTS data, and the large volume of data generated by HTS requires in-house experience with command line tools for downstream analysis. This paper introduces a pipeline that incorporates the most common command line tools into an easy-to-use graphical interface-gDAT. By using the Python scripting language, the pipeline is compatible with the latest Windows, macOS and Linux operating systems. The pipeline supports analysis of Sanger, 454, IonTorrent, Illumina and PacBio sequences, allows custom modification of quality filtering steps, and implements both open and closed-reference operational taxonomic unit-picking for sequence identification. Predefined parameters are optimized for analysis of small subunit (SSU) rRNA gene amplicons from arbuscular mycorrhizal fungi, but the pipeline is widely applicable to metabarcoding studies targeting a broad range of organisms. The pipeline was additionally tested with data using general eukaryotic primers from the SSU gene region and fungal primers from the internal transcribed spacer (ITS) marker region. We describe the pipeline design and evaluate its performance and speed by conducting analysis of example data sets using different marker regions sequenced on Illumina platforms. The graphical interface, with the option to use the command line if needed, provides an accessible tool for rapid data analysis with repeatability and logging capabilities. Keeping the software open-source maximizes code accessibility, allowing scrutiny and bug fixes by the community.

DNA Metabarcoding for the Characterization of Terrestrial Microbiota-Pitfalls and Solutions

Soil-borne microbes are major ecological players in terrestrial environments since they cycle organic matter, channel nutrients across trophic levels and influence plant growth and health. Therefore, the identification, taxonomic characterization and determination of the ecological role of members of soil microbial communities have become major topics of interest. The development and continuous improvement of high-throughput sequencing platforms have further stimulated the study of complex microbiota in soils and plants. The most frequently used approach to study microbiota composition, diversity and dynamics is polymerase chain reaction (PCR), amplifying specific taxonomically informative gene markers with the subsequent sequencing of the amplicons. This methodological approach is called DNA metabarcoding. Over the last decade, DNA metabarcoding has rapidly emerged as a powerful and cost-effective method for the description of microbiota in environmental samples. However, this approach involves several processing steps, each of which might introduce significant biases that can considerably compromise the reliability of the metabarcoding output. The aim of this review is to provide state-of-the-art background knowledge needed to make appropriate decisions at each step of a DNA metabarcoding workflow, highlighting crucial steps that, if considered, ensures an accurate and standardized characterization of microbiota in environmental studies.

A global meta-analysis of ITS rDNA sequences from material belonging to the genus Ganoderma (Basidiomycota, Polyporales) including new data from selected taxa

Ganoderma P. Karst. is a cosmopolitan genus of white-rot fungi which comprises species with highly-prized pharmaceutical properties, valuable biotechnological applications and of significant phytopathological interest. However, the status of the taxonomy within the genus is still highly controversial and ambiguous despite the progress made through molecular approaches. A metadata analysis of 3908 nuclear ribosomal internal transcribed spacer (ITS) rDNA sequences obtained from GenBank/ENA/DDBJ and UNITE was performed by targeting sequences annotated as Ganoderma, but also sequences from environmental samples and from material examined for the first time. Ganoderma taxa segregated into five main lineages (Clades A to E). Clade A corresponds to the core of laccate species and includes G. shanxiense and three major well-supported clusters: Cluster A.1 ('G. lucidum sensu lato') consists of taxa from Eurasia and North America, Cluster A.2 of material with worldwide occurrence including G. resinaceum and Cluster A.3 is composed of species originating from all continents except Europe and comprises G. lingzhi. Clade B includes G. applanatum and allied species with a Holarctic distribution. Clade C comprises taxa from Asia and Africa only. Clade D consists of laccate taxa with tropical/subtropical occurrence, while clade E harbours the highest number of non-laccate species with a cosmopolitan distribution. The 92 Ganoderma-associated names, initially used for sequences labelling, correspond to at least 80 taxa. Amongst them, 21 constitute putatively new phylospecies after our application of criteria relevant to the robustness/support of the terminal clades, intra- and interspecific genetic divergence and available biogeographic data. Moreover, several other groups or individual sequences seem to represent distinct taxonomic entities and merit further investigation. A particularly large number of the public sequences was revealed to be insufficiently and/or incorrectly identified, for example, 87% and 78% of entries labelled as G. australe and G. lucidum, respectively. In general, ITS demonstrated high efficacy in resolving relationships amongst most of the Ganoderma taxa; however, it was not equally useful at elucidating species barriers across the entire genus and such cases are outlined. Furthermore, we draw conclusions on biogeography by evaluating species occurrence on a global scale in conjunction with phylogenetic structure/patterns. The sequence variability assessed in ITS spacers could be further exploited for diagnostic purposes.

PLANiTS: a curated sequence reference dataset for plant ITS DNA metabarcoding

DNA metabarcoding combines DNA barcoding with high-throughput sequencing to identify different taxa within environmental communities. The ITS has already been proposed and widely used as universal barcode marker for plants, but a comprehensive, updated and accurate reference dataset of plant ITS sequences has not been available so far. Here, we constructed reference datasets of Viridiplantae ITS1, ITS2 and entire ITS sequences including both Chlorophyta and Streptophyta. The sequences were retrieved from NCBI, and the ITS region was extracted. The sequences underwent identity check to remove misidentified records and were clustered at 99% identity to reduce redundancy and computational effort. For this step, we developed a script called 'better clustering for QIIME' (bc4q) to ensure that the representative sequences are chosen according to the composition of the cluster at a different taxonomic level. The three datasets obtained with the bc4q script are PLANiTS1 (100 224 sequences), PLANiTS2 (96 771 sequences) and PLANiTS (97 550 sequences), and all are pre-formatted for QIIME, being this the most used bioinformatic pipeline for metabarcoding analysis. Being curated and updated reference databases, PLANiTS1, PLANiTS2 and PLANiTS are proposed as a reliable, pivotal first step for a general standardization of plant DNA metabarcoding studies. The bc4q script is presented as a new tool useful in each research dealing with sequences clustering. Database URL: https://github.com/apallavicini/bc4q; https://github.com/apallavicini/PLANiTS.

Identification of Eukaryotic Microalgal Strains

Proper identification and documentation of microalgae is often lacking in publications of applied phycology, algal physiology and biochemistry. Identification of many eukaryotic microalgae can be very daunting to the non-specialist. We present a systematic process for identifying eukaryotic microalgae using morphological evidence and DNA sequence analysis. Our intent was to provide an identification method that could be used by non-taxonomists, but which is grounded in the current techniques used by algal taxonomists. Central to the identification is database searches with DNA sequences of appropriate loci. We provide usable criteria for identification at the genus or species level, depending on the availability of sequence data in curated databases and repositories. Particular attention is paid to dealing with possible misidentifications in DNA databases and utilizing current taxonomy.

Microbiome Diagnostics

BACKGROUND

During the past decade, breakthroughs in sequencing technology and computational biology have provided the basis for studies of the myriad ways in which microbial communities ("microbiota") in and on the human body influence human health and disease. In almost every medical specialty, there is now a growing interest in accurate and replicable profiling of the microbiota for use in diagnostic and therapeutic application.

CONTENT

This review provides an overview of approaches, challenges, and considerations for diagnostic applications borrowing from other areas of molecular diagnostics, including clinical metagenomics. Methodological considerations and evolving approaches for microbiota profiling from mitochondrially encoded 16S rRNA-based amplicon sequencing to metagenomics and metatranscriptomics are discussed. To improve replicability, at least the most vulnerable steps in testing workflows will need to be standardized and continuous efforts needed to define QC standards. Challenges such as purity of reagents and consumables, improvement of reference databases, and availability of diagnostic-grade data analysis solutions will require joint efforts across disciplines and with manufacturers.

SUMMARY

The body of literature supporting important links between the microbiota at different anatomic sites with human health and disease is expanding rapidly and therapeutic manipulation of the intestinal microbiota is becoming routine. The next decade will likely see implementation of microbiome diagnostics in diagnostic laboratories to fully capitalize on technological and scientific advances and apply them in routine medical practice.

Phylogeny and character evolution in the Dacrymycetes, and systematics of Unilacrymaceae and Dacryonaemataceae fam. nov

We present a multilocus phylogeny of the class Dacrymycetes, based on data from the 18S, ITS, 28S, RPB1, RPB2, TEF-1α, 12S, and ATP6 DNA regions, with c. 90 species including the types of most currently accepted genera. A variety of methodological approaches was used to infer phylogenetic relationships among the Dacrymycetes, from a supermatrix strategy using maximum likelihood and Bayesian inference on a concatenated dataset, to coalescence-based calculations, such as quartet-based summary methods of independent single-locus trees, and Bayesian integration of single-locus trees into a species tree under the multispecies coalescent. We evaluate for the first time the taxonomic usefulness of some cytological phenotypic characters, i.e., vacuolar contents (vacuolar bodies and lipid bodies), number of nuclei of recently discharged basidiospores, and pigments, with especial emphasis on carotenoids. These characters, along with several others traditionally used for the taxonomy of this group (basidium shape, presence and morphology of clamp connections, morphology of the terminal cells of cortical/marginal hyphae, presence and degree of ramification of the hyphidia), are mapped on the resulting phylogenies and their evolution through the class Dacrymycetes discussed. Our analyses reveal five lineages that putatively represent five different families, four of which are accepted and named. Three out of these four lineages correspond to previously circumscribed and published families (Cerinomycetaceae, Dacrymycetaceae, and Unilacrymaceae), and one is proposed as the new family Dacryonaemataceae. Provisionally, only a single order, Dacrymycetales, is accepted within the class. Furthermore, the systematics of the two smallest families, Dacryonaemataceae and Unilacrymaceae, are investigated to the species level, using coalescence-based species delimitation on multilocus DNA data, and a detailed morphological study including morphometric analyses of the basidiospores. Three species are accepted in Dacryonaema, the type, Da. rufum, the newly combined Da. macnabbii (basionym Dacrymyces macnabbii), and a new species named Da. macrosporum. Two species are accepted in Unilacryma, the new U. bispora, and the type, U. unispora, the latter treated in a broad sense pending improved sampling across the Holarctic.

MGnify: the microbiome analysis resource in 2020

MGnify (http://www.ebi.ac.uk/metagenomics) provides a free to use platform for the assembly, analysis and archiving of microbiome data derived from sequencing microbial populations that are present in particular environments. Over the past 2 years, MGnify (formerly EBI Metagenomics) has more than doubled the number of publicly available analysed datasets held within the resource. Recently, an updated approach to data analysis has been unveiled (version 5.0), replacing the previous single pipeline with multiple analysis pipelines that are tailored according to the input data, and that are formally described using the Common Workflow Language, enabling greater provenance, reusability, and reproducibility. MGnify's new analysis pipelines offer additional approaches for taxonomic assertions based on ribosomal internal transcribed spacer regions (ITS1/2) and expanded protein functional annotations. Biochemical pathways and systems predictions have also been added for assembled contigs. MGnify's growing focus on the assembly of metagenomic data has also seen the number of datasets it has assembled and analysed increase six-fold. The non-redundant protein database constructed from the proteins encoded by these assemblies now exceeds 1 billion sequences. Meanwhile, a newly developed contig viewer provides fine-grained visualisation of the assembled contigs and their enriched annotations.

The European Nucleotide Archive in 2019

The European Nucleotide Archive (ENA, https://www.ebi.ac.uk/ena) at the European Molecular Biology Laboratory's European Bioinformatics Institute provides open and freely available data deposition and access services across the spectrum of nucleotide sequence data types. Making the world's public sequencing datasets available to the scientific community, the ENA represents a globally comprehensive nucleotide sequence resource. Here, we outline ENA services and content in 2019 and provide an insight into selected key areas of development in this period.

Putative group I introns in the eukaryote nuclear internal transcribed spacers

Group I introns are mobile genetic elements that interrupt genes encoding proteins and RNAs. In the rRNA operon, introns can insert in the small subunit (SSU) and large subunit (LSU) of a wide variety of protists and various prokaryotes, but they were never found in the ITS region. In this study, unusually long ITS regions of fungi and closely related unicellular organisms (Polychytrium aggregatum, Mitosporidium daphniae, Amoeboaphelidium occidentale and Nuclearia simplex) were analysed. While the insertion of repeats is responsible for long ITS in other eukaryotes, the increased size of the sequences analysed herein seems rather due to the presence of introns in ITS-1 or ITS-2. The identified insertions can be folded in secondary structures according to group I intron models, and they cluster within introns in conserved core-based phylogeny. In addition, for Mitosporidium, Amoeboaphelidium and Nuclearia, more conventional ITS-2 structures can be deduced once spacer introns are removed. Sequences of five shark species were also analysed for their structure and included in phylogeny because of unpublished work reporting introns in their ITS, obtaining congruent results. Overall, the data presented herein indicate that spacer regions may contain introns.

Metagenomic Approaches to Investigate the Contribution of the Vineyard Environment to the Quality of Wine Fermentation: Potentials and Difficulties

The winemaking is a complex process that begins in the vineyard and ends at consumption moment. Recent reports have shown the relevance of microbial populations in the definition of the regional organoleptic and sensory characteristics of a wine. Metagenomic approaches, allowing the exhaustive identification of microorganisms present in complex samples, have recently played a fundamental role in the dissection of the contribution of the vineyard environment to wine fermentation. Systematic approaches have explored the impact of agronomical techniques, vineyard topologies, and climatic changes on bacterial and fungal populations found in the vineyard and in fermentations, also trying to predict or extrapolate the effects on the sensorial characteristics of the resulting wine. This review is aimed at highlighting the major technical and experimental challenges in dissecting the contribution of the vineyard and native environments microbiota to the wine fermentation process, and how metagenomic approaches can help in understanding microbial fluxes and selections across the environments and specimens related to wine fermentation.