Effects of operational taxonomic unit inference methods on soil microeukaryote community analysis using long-read metabarcoding

Phylogenetic classification of arbuscular mycorrhizal fungi: new species and higher-ranking taxa in Glomeromycota and Mucoromycota (class Endogonomycetes)

Arbuscular mycorrhizal (AM) fungi - Glomeromycota and Endogonomycetes - comprise multiple species and higher-level taxa that have remained undescribed. We propose a mixed morphology- and DNA-based classification framework to promote taxonomic communication and shed light into the phylogenetic structure of these ecologically essential fungi. Based on eDNA samples and long reads as type materials, we describe 15 new species and corresponding genera (Pseudoentrophosporakesseensis, Hoforsarebekkae, Kahvenarebeccae, Kelottijaerviashannonae, Kungsaengenashadiae, Langduoadianae, Lehetuaindrekii, Lokrumastenii, Moosteastephanieae, Nikkaluoktamahdiehiae, Parniguacraigii, Riederbergasylviae, Ruuacoralieae, Tammsaareavivikae and Unemaeeanathalieae), the genus Parvocarpum as well as 19 families (Pseudoentrophosporaceae, Hoforsaceae, Kahvenaceae, Kelottijaerviaceae, Kungsaengenaceae, Langduoaceae, Lehetuaceae, Lokrumaceae, Moosteaceae, Nikkaluoktaceae, Parniguaceae, Riederbergaceae, Ruuaceae, Tammsaareaceae, Unemaeeaceae, Bifigurataceae, Planticonsortiaceae, Jimgerdemanniaceae and Vinositunicaceae) and 17 orders (Hoforsales, Kahvenales, Kelottijaerviales, Kungsaengenales, Langduoales, Lehetuales, Lokrumales, Moosteales, Nikkaluoktales, Parniguales, Riederbergales, Ruuales, Tammsaareales, Unemaeeales, Bifiguratales and Densosporales), and propose six combinations (Diversisporabareae, Diversisporanevadensis, Fuscutatacerradensis, Fuscutatareticulata, Viscosporadeserticola and Parvocarpumbadium) based on phylogenetic evidence. We highlight further knowledge gaps in the phylogenetic structure of AM fungi and propose an alphanumeric coding system for preliminary communication and reference-based eDNA quality-filtering of the remaining undescribed genus- and family-level groups. Using AM fungi as examples, we hope to offer a sound, mixed framework for classification to boost research in the alpha taxonomy of fungi, especially the "dark matter fungi".

Considerations for the inclusion of metabarcoding data in the plant protection product risk assessment of the soil microbiome

There is increasing interest in further developing the plant protection product (PPP) environmental risk assessment, particularly within the European Union, to include the assessment of soil microbial community composition, as measured by metabarcoding approaches. However, to date, there has been little discussion as to how this could be implemented in a standardized, reliable, and robust manner suitable for regulatory decision-making. Introduction of metabarcoding-based assessments of the soil microbiome into the PPP risk assessment would represent a significant increase in the degree of complexity of the data that needs to be processed and analyzed in comparison to the existing risk assessment on in-soil organisms. The bioinformatics procedures to process DNA sequences into community compositional data sets currently lack standardization, while little information exists on how these data should be used to generate regulatory endpoints and the ways in which these endpoints should be interpreted. Through a thorough and critical review, we explore these challenges. We conclude that currently, we do not have a sufficient degree of standardization or understanding of the required bioinformatics and data analysis procedures to consider their use in an environmental risk assessment context. However, we highlight critical knowledge gaps and the further research required to understand whether metabarcoding-based assessments of the soil microbiome can be utilized in a statistically and ecologically relevant manner within a PPP risk assessment. Only once these challenges are addressed can we consider if and how we should use metabarcoding as a tool for regulatory decision-making to assess and monitor ecotoxicological effects on soil microorganisms within an environmental risk assessment of PPPs. Integr Environ Assess Manag 2024;20:337-358. © 2023 SETAC.

Intragenomic diversity of the V9 hypervariable domain in eukaryotes has little effect on metabarcoding

Metabarcoding revolutionized our understanding of diversity and ecology of microorganisms in different habitats. However, it is also associated with several inherent biases, one of which is associated with intragenomic diversity of a molecular barcode. Here, we compare intragenomic variability of the V9 region of the 18S rRNA gene in 19 eukaryotic phyla abundant in marine plankton. The level of intragenomic variability is comparable across all the phyla, and in most genomes and transcriptomes one V9 sequence and one OTU is predominant. However, most of the variability observed at the barcode level is probably caused by sequencing errors and is mitigated by using a denoising tool, DADA2. The SWARM algorithm commonly used in metabarcoding studies is not optimal for collapsing genuine and erroneous sequences into a single OTU, leading to an overestimation of diversity in metabarcoding data. For an unknown reason, SWARM inflates diversity of eupelagonemids more than that of other eukaryotes.

MinION Sequencing of Yeast Mock Communities To Assess the Effect of Databases and ITS-LSU Markers on the Reliability of Metabarcoding Analysis

Microbial communities play key roles both for humans and the environment. They are involved in ecosystem functions, maintaining their stability, and provide important services, such as carbon cycle and nitrogen cycle. Acting both as symbionts and as pathogens, description of the structure and composition of these communities is important. Metabarcoding uses ribosomal DNA (rDNA) (eukaryotic) or rRNA gene (prokaryotic) sequences for identification of species present in a site and measuring their abundance. This procedure requires several technical steps that could be source of bias producing a distorted view of the real community composition. In this work, we took advantage of an innovative "long-read" next-generation sequencing (NGS) technology (MinION) amplifying the DNA spanning from the internal transcribed spacer (ITS) to large subunit (LSU) that can be read simultaneously in this platform, providing more information than "short-read" systems. The experimental system consisted of six fungal mock communities composed of species present at various relative amounts to mimic natural situations characterized by predominant and low-frequency species. The influence of the sequencing platform (MinION and Illumina MiSeq) and the effect of different reference databases and marker sequences on metagenomic identification of species were evaluated. The results showed that the ITS-based database provided more accurate species identification than LSU. Furthermore, a procedure based on a preliminary identification with standard reference databases followed by the production of custom databases, including only the best outputs of the first step, is proposed. This additional step improved the estimate of species proportion of the mock communities and reduced the number of ghost species not really present in the simulated communities. IMPORTANCE Metagenomic analyses are fundamental in many research areas; therefore, improvement of methods and protocols for the description of microbial communities becomes more and more necessary. Long-read sequencing could be used for reducing biases due to the multicopy nature of rDNA sequences and short-read limitations. However, these novel technologies need to be assessed and standardized with controlled experiments, such as mock communities. The interest behind this work was to evaluate how long reads performed identification and quantification of species mixed in precise proportions and how the choice of database affects such analyses. Development of a pipeline that mitigates the effect of the barcoding sequences and the impact of the reference database on metagenomic analyses can help microbiome studies go one step further.