Metabarcoding reveals ecologically distinct fungal assemblages in river and groundwater along an Austrian alpine to lowland gradient

Biodiversity, the source of origin, and ecological roles of fungi in groundwater are to this day a largely neglected field in fungal and freshwater ecology. We used DNA-based Illumina high-throughput sequence analysis of both fungal gene markers 5.8S and internal transcribed spacers region 2 (ITS2), improving taxonomic classification. This study focused on the groundwater and river mycobiome along an altitudinal and longitudinal transect of a pre-alpine valley in Austria in two seasons. Using Bayesian network modeling approaches, we identified patterns in fungal community assemblages that were mostly shaped by differences in landscape (climatic, topological, and geological) and environmental conditions. While river fungi were comparatively more diverse, unique fungal assemblages could be recovered from groundwater, including typical aquatic lineages such as Rozellomycota and Olpidiomycota. The most specious assemblages in groundwater were not linked to the input of organic material from the surface, and as such, seem to be sustained by characteristic groundwater conditions. Based on what is known from closely related fungi, our results suggest that the present fungal communities potentially contribute to mineral weathering, carbon cycling, and denitrification in groundwater. Furthermore, we were able to observe the effects of varying land cover due to agricultural practices on fungal biodiversity in groundwater ecosystems. This study contributes to improving our understanding of fungi in the subsurface aquatic biogeosphere.

Microbial DNA sample preservation and possible artifacts for field-based research in remote tropical peatlands

Surveying bacterial and archaeal microbial communities in host and environmental studies requires the collection and storage of samples. Many studies are conducted in distant locations challenging these prerequisites. The use of preserving buffers is an important alternative when lacking access to cryopreservation, however, its effectivity for samples with challenging chemistry or samples that provide opportunities for fast bacterial or archaeal growth upon exposure to an aerobic environment, like peat samples, requires methodological assessment. Here, in combination with an identified optimal DNA extraction kit for peat soil samples, we test the application of several commercial and a homemade preservation buffer and make recommendations on the method that can most effectively preserve a microbiome reflective of the original state. In treatments with a non-optimal buffer or in the absence, we observed notable community shifts beginning as early as three days post-preservation lowering diversity and community evenness, with growth-driven artifacts from a few specific phyla. However other buffers retain a very close composition relative to the original state, and we described several metrics to understand some variation across them. Due to the chemical effects of preservation buffers, it is critical to test their compatibility and reliability to preserve the original bacterial and archaeal community in different environments.

The development of terrestrial ecosystems emerging after glacier retreat

The global retreat of glaciers is dramatically altering mountain and high-latitude landscapes, with new ecosystems developing from apparently barren substrates1-4. The study of these emerging ecosystems is critical to understanding how climate change interacts with microhabitat and biotic communities and determines the future of ice-free terrains1,5. Here, using a comprehensive characterization of ecosystems (soil properties, microclimate, productivity and biodiversity by environmental DNA metabarcoding6) across 46 proglacial landscapes worldwide, we found that all the environmental properties change with time since glaciers retreated, and that temperature modulates the accumulation of soil nutrients. The richness of bacteria, fungi, plants and animals increases with time since deglaciation, but their temporal patterns differ. Microorganisms colonized most rapidly in the first decades after glacier retreat, whereas most macroorganisms took longer. Increased habitat suitability, growing complexity of biotic interactions and temporal colonization all contribute to the increase in biodiversity over time. These processes also modify community composition for all the groups of organisms. Plant communities show positive links with all other biodiversity components and have a key role in ecosystem development. These unifying patterns provide new insights into the early dynamics of deglaciated terrains and highlight the need for integrated surveillance of their multiple environmental properties5.

Metabarcoding read abundances of orchid mycorrhizal fungi are correlated to copy numbers estimated using ddPCR

Quantifying the abundances of fungi is key to understanding natural variation in mycorrhizal communities in relation to plant ecophysiology and environmental heterogeneity. High-throughput metabarcoding approaches have transformed our ability to characterize and compare complex mycorrhizal communities. However, it remains unclear how well metabarcoding read counts correlate with actual read abundances in the sample, potentially limiting their use as a proxy for species abundances. Here, we use droplet digital PCR (ddPCR) to evaluate the reliability of ITS2 metabarcoding data for quantitative assessments of mycorrhizal communities in the orchid species Neottia ovata sampled at multiple sites. We performed specific ddPCR assays for eight families of orchid mycorrhizal fungi and compared the results with read counts obtained from metabarcoding. Our results demonstrate a significant correlation between DNA copy numbers measured by ddPCR assays and metabarcoding read counts of major mycorrhizal partners of N. ovata, highlighting the usefulness of metabarcoding for quantifying the abundance of orchid mycorrhizal fungi. Yet, the levels of correlation between the two methods and the numbers of false zero values varied across fungal families, which warrants cautious evaluation of the reliability of low-abundance families. This study underscores the potential of metabarcoding data for more quantitative analyses of mycorrhizal communities and presents practical workflows for metabarcoding and ddPCR to achieve a more comprehensive understanding of orchid mycorrhizal communities.

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.

On-Site Bioaerosol Sampling and Airborne Microorganism Detection Technologies

Bioaerosols are small airborne particles composed of microbiological fragments, including bacteria, viruses, fungi, pollens, and/or by-products of cells, which may be viable or non-viable wherever applicable. Exposure to these agents can cause a variety of health issues, such as allergic and infectious diseases, neurological disorders, and cancer. Therefore, detecting and identifying bioaerosols is crucial, and bioaerosol sampling is a key step in any bioaerosol investigation. This review provides an overview of the current bioaerosol sampling methods, both passive and active, as well as their applications and limitations for rapid on-site monitoring. The challenges and trends for detecting airborne microorganisms using molecular and immunological methods are also discussed, along with a summary and outlook for the development of prompt monitoring technologies.

The importance of species addition 'versus' replacement varies over succession in plant communities after glacier retreat

The mechanisms underlying plant succession remain highly debated. Due to the local scope of most studies, we lack a global quantification of the relative importance of species addition 'versus' replacement. We assessed the role of these processes in the variation (β-diversity) of plant communities colonizing the forelands of 46 retreating glaciers worldwide, using both environmental DNA and traditional surveys. Our findings indicate that addition and replacement concur in determining community changes in deglaciated sites, but their relative importance varied over time. Taxa addition dominated immediately after glacier retreat, as expected in harsh environments, while replacement became more important for late-successional communities. These changes were aligned with total β-diversity changes, which were more pronounced between early-successional communities than between late-successional communities (>50 yr since glacier retreat). Despite the complexity of community assembly during plant succession, the observed global pattern suggests a generalized shift from the dominance of facilitation and/or stochastic processes in early-successional communities to a predominance of competition later on.

The MetaInvert soil invertebrate genome resource provides insights into below-ground biodiversity and evolution

Soil invertebrates are among the least understood metazoans on Earth. Thus far, the lack of taxonomically broad and dense genomic resources has made it hard to thoroughly investigate their evolution and ecology. With MetaInvert we provide draft genome assemblies for 232 soil invertebrate species, representing 14 common groups and 94 families. We show that this data substantially extends the taxonomic scope of DNA- or RNA-based taxonomic identification. Moreover, we confirm that theories of genome evolution cannot be generalised across evolutionarily distinct invertebrate groups. The soil invertebrate genomes presented here will support the management of soil biodiversity through molecular monitoring of community composition and function, and the discovery of evolutionary adaptations to the challenges of soil conditions.

Metatranscriptomics reveals contrasting effects of elevation on the activity of bacteria and bacterial viruses in soil

Soil microbial diversity affects ecosystem functioning and global biogeochemical cycles. Soil bacterial communities catalyse a diversity of biogeochemical reactions and have thus sparked considerable scientific interest. One driver of bacterial community dynamics in natural ecosystems has so far been largely neglected: the predator-prey interactions between bacterial viruses (bacteriophages) and bacteria. To generate ground level knowledge on environmental drivers of these particular predator-prey dynamics, we propose an activity-based ecological framework to simultaneous capture community dynamics of bacteria and bacteriophages in soils. An ecological framework and specifically the analyses of community dynamics across latitudinal and elevational gradients have been widely used in ecology to understand community-wide responses of innumerable taxa to environmental change, in particular to climate. Here, we tested the hypothesis that the activity of bacteria and bacteriophages codeclines across an elevational gradient. We used metatranscriptomics to investigate bacterial and bacteriophage activity patterns at five sites across 400 elevational metres in the Swiss Alps in 2015 and 2017. We found that metabolic activity (transcription levels) of bacteria declined significantly with increasing elevation, but activity of bacteriophages did not. We showed that bacteriophages are consistently active in soil along the entire gradient, making bacteriophage activity patterns divergent from that of their putative bacterial prey. Future efforts will be necessary to link the environment-activity relationship to predator-prey dynamics, and to understand the magnitude of viral contributions to carbon, nitrogen and phosphorus cycling when infection causes bacterial cell death, a process that may represent an overlooked component of soil biogeochemical cycles.

Metabarcoding data reveal vertical multitaxa variation in topsoil communities during the colonization of deglaciated forelands

Ice-free areas are expanding worldwide due to dramatic glacier shrinkage and are undergoing rapid colonization by multiple lifeforms, thus representing key environments to study ecosystem development. It has been proposed that the colonization dynamics of deglaciated terrains is different between surface and deep soils but that the heterogeneity between communities inhabiting surface and deep soils decreases through time. Nevertheless, tests of this hypothesis remain scarce, and it is unclear whether patterns are consistent among different taxonomic groups. Here, we used environmental DNA metabarcoding to test whether community diversity and composition of six groups (Eukaryota, Bacteria, Mycota, Collembola, Insecta, and Oligochaeta) differ between the surface (0-5 cm) and deeper (7.5-20 cm) soil at different stages of development and across five Alpine glaciers. Taxonomic diversity increased with time since glacier retreat and with soil evolution. The pattern was consistent across groups and soil depths. For Eukaryota and Mycota, alpha-diversity was highest at the surface. Time since glacier retreat explained more variation of community composition than depth. Beta-diversity between surface and deep layers decreased with time since glacier retreat, supporting the hypothesis that the first 20 cm of soil tends to homogenize through time. Several molecular operational taxonomic units of bacteria and fungi were significant indicators of specific depths and/or soil development stages, confirming the strong functional variation of microbial communities through time and depth. The complexity of community patterns highlights the importance of integrating information from multiple taxonomic groups to unravel community variation in response to ongoing global changes.

Short-term responses of the soil microbiome and its environment indicate an uncertain future of restored peatland forests

Restoring peatland ecosystems involves significant uncertainty due to complex ecological and socio-economic feedbacks as well as alternative stable ecological states. The primary aim of this study was to investigate to what extent the natural functioning of drainage-affected peat soils can be restored, and to examine role of soil microbiota in this recovery process. To address these questions, a large-scale before-after-control-impact (BACI) experiment was conducted in drained peatland forests in Estonia. The restoration treatments included ditch closure and partial tree cutting to raise the water table and restore stand structure. Soil samples and environmental data were collected before and 3-4 years after the treatments; the samples were subjected to metabarcoding to assess fungal and bacterial communities and analysed for their chemical properties. The study revealed some indicators of a shift toward the reference state (natural mixotrophic bog-forests): the spatial heterogeneity in soil fungi and bacteria increased, as well as the relative abundance of saprotrophic fungi; while nitrogen content in the soil decreased significantly. However, a general stability of other physico-chemical properties (including pH remaining elevated by ca. one unit) and annual fluctuations in the microbiome suggested that soil recovery will remain incomplete and patchy for decades. The main implication is the necessity to manage hydrologically restored peatland forests while explicitly considering an uncertain future and diverse outcomes. This includes their continuous monitoring and the adoption of a precautionary approach to prevent further damage both to these ecosystems and to surrounding intact peatlands.

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.

Comparison of Oxford Nanopore Technologies and Illumina MiSeq sequencing with mock communities and agricultural soil

Illumina MiSeq is the current standard for characterizing microbial communities in soil. The newer alternative, Oxford Nanopore Technologies MinION sequencer, is quickly gaining popularity because of the low initial cost and longer sequence reads. However, the accuracy of MinION, per base, is much lower than MiSeq (95% versus 99.9%). The effects of this difference in base-calling accuracy on taxonomic and diversity estimates remains unclear. We compared the effects of platform, primers, and bioinformatics on mock community and agricultural soil samples using short MiSeq, and short and full-length MinION 16S rRNA amplicon sequencing. For all three methods, we found that taxonomic assignments of the mock community at both the genus and species level matched expectations with minimal deviation (genus: 80.9-90.5%; species: 70.9-85.2% Bray-Curtis similarity); however, the short MiSeq with error correction (DADA2) resulted in the correct estimate of mock community species richness and much lower alpha diversity for soils. Several filtering strategies were tested to improve these estimates with varying results. The sequencing platform also had a significant influence on the relative abundances of taxa with MiSeq resulting in significantly higher abundances Actinobacteria, Chloroflexi, and Gemmatimonadetes and lower abundances of Acidobacteria, Bacteroides, Firmicutes, Proteobacteria, and Verrucomicrobia compared to the MinION platform. When comparing agricultural soils from two different sites (Fort Collins, CO and Pendleton, OR), methods varied in the taxa identified as significantly different between sites. At all taxonomic levels, the full-length MinION method had the highest similarity to the short MiSeq method with DADA2 correction with 73.2%, 69.3%, 74.1%, 79.3%, 79.4%, and 82.28% of the taxa at the phyla, class, order, family, genus, and species levels, respectively, showing similar patterns in differences between the sites. In summary, although both platforms appear suitable for 16S rRNA microbial community composition, biases for different taxa may make the comparison between studies problematic; and even with a single study (i.e., comparing sites or treatments), the sequencing platform can influence the differentially abundant taxa identified.

Network analysis of 16S rRNA sequences suggests microbial keystone taxa contribute to marine N2O cycling

The mechanisms by which large-scale microbial community function emerges from complex ecological interactions between individual taxa and functional groups remain obscure. We leveraged network analyses of 16S rRNA amplicon sequences obtained over a seven-month timeseries in seasonally anoxic Saanich Inlet (Vancouver Island, Canada) to investigate relationships between microbial community structure and water column N2O cycling. Taxa separately broadly into three discrete subnetworks with contrasting environmental distributions. Oxycline subnetworks were structured around keystone aerobic heterotrophs that correlated with nitrification rates and N2O supersaturations, linking N2O production and accumulation to taxa involved in organic matter remineralization. Keystone taxa implicated in anaerobic carbon, nitrogen, and sulfur cycling in anoxic environments clustered together in a low-oxygen subnetwork that correlated positively with nitrification N2O yields and N2O production from denitrification. Close coupling between N2O producers and consumers in the anoxic basin is indicated by strong correlations between the low-oxygen subnetwork, PICRUSt2-predicted nitrous oxide reductase (nosZ) gene abundances, and N2O undersaturation. This study implicates keystone taxa affiliated with common ODZ groups as a potential control on water column N2O cycling and provides a theoretical basis for further investigations into marine microbial interaction networks.

Optimal sequence similarity thresholds for clustering of molecular operational taxonomic units in DNA metabarcoding studies

Clustering approaches are pivotal to handle the many sequence variants obtained in DNA metabarcoding data sets, and therefore they have become a key step of metabarcoding analysis pipelines. Clustering often relies on a sequence similarity threshold to gather sequences into molecular operational taxonomic units (MOTUs), each of which ideally represents a homogeneous taxonomic entity (e.g., a species or a genus). However, the choice of the clustering threshold is rarely justified, and its impact on MOTU over-splitting or over-merging even less tested. Here, we evaluated clustering threshold values for several metabarcoding markers under different criteria: limitation of MOTU over-merging, limitation of MOTU over-splitting, and trade-off between over-merging and over-splitting. We extracted sequences from a public database for nine markers, ranging from generalist markers targeting Bacteria or Eukaryota, to more specific markers targeting a class or a subclass (e.g., Insecta, Oligochaeta). Based on the distributions of pairwise sequence similarities within species and within genera, and on the rates of over-splitting and over-merging across different clustering thresholds, we were able to propose threshold values minimizing the risk of over-splitting, that of over-merging, or offering a trade-off between the two risks. For generalist markers, high similarity thresholds (0.96-0.99) are generally appropriate, while more specific markers require lower values (0.85-0.96). These results do not support the use of a fixed clustering threshold. Instead, we advocate careful examination of the most appropriate threshold based on the research objectives, the potential costs of over-splitting and over-merging, and the features of the studied markers.

Global trends in research of high-throughput sequencing technology associated with chronic wounds from 2002 to 2022: A bibliometric and visualized study

Background

Chronic wounds are a complex medical problem. With the difficulty of skin healing, the microbial ecology of chronic wounds is an essential factor affecting wound healing. High-throughput sequencing (HTS) technology is a vital method to reveal the microbiome diversity and population structure of chronic wounds.

Objective

The aim of this paper was to delineate the scientific output characteristics, research trends, hotspots and frontiers of HTS technologies related to chronic wounds globally over the past 20 years.

Methods

We searched the Web of Science Core Collection (WoSCC) database for articles published between 2002 and 2022 and their full record information. The Bibliometrix software package was used to analyze bibliometric indicators and VOSviewer visualization analysis results.

Results

Ultimately, a total of 449 original articles were reviewed, and the results showed that the number of annual publications (Nps) about HTS associated with chronic wounds has steadily increased over the last 20 years. The United States and China produce the most articles and have the highest H-index, while the United States and England have the largest number of citations (Nc) in this field. The University of California, Wound Repair and Regeneration and National Institutes of Health Nih United States were the most published institutions, journals and fund resources, respectively. The global research could be divided into 3 clusters as follows: microbial infection of chronic wounds, the healing process of wounds and microscopic processes, skin repair mechanism stimulated by antimicrobial peptides and oxidative stress. In recent years, "wound healing", "infections", "expression", "inflammation", "chronic wounds", "identification" and "bacteria" "angiogenesis", "biofilms" and "diabetes" were the most frequently used keywords. In addition, research on "prevalence", "gene expression", "inflammation" and "infection" has recently become a hotspot.

Conclusions

This paper compares the research hotspots and directions in this field globally from the perspectives of countries, institutions and authors, analyzes the trend of international cooperation, and reveals the future development direction of the field and research hotspots of great scientific research value. Through this paper, we can further explore the value of HTS technology in chronic wounds to better solve the problem of chronic wounds.

Ecological stoichiometry and fungal community turnover reveal variation among mycorrhizal partners in their responses to warming and drought

Symbiotic fungi mediate important energy and nutrient transfers in terrestrial ecosystems. Environmental change can lead to shifts in communities of symbiotic fungi, but the consequences of these shifts for nutrient dynamics among symbiotic partners are poorly understood. Here, we assessed variation in carbon (C), nitrogen (N) and phosphorus (P) in tissues of arbuscular mycorrhizal (AM) fungi and a host plant (Medicago sativa) in response to experimental warming and drought. We linked compositional shifts in AM fungal communities in roots and soil to variation in hyphal chemistry by using high-throughput DNA sequencing and joint species distribution modelling. Compared to plants, AM hyphae was 43% lower in (C) and 24% lower in (N) but more than nine times higher in (P), with significantly lower C:N, C:P and N:P ratios. Warming and drought resulted in increases in (P) and reduced C:P and N:P ratios in all tissues, indicating fungal P accumulation was exacerbated by climate-associated stress. Warming and drought modified the composition of AM fungal communities, and many of the AM fungal genera that were linked to shifts in mycelial chemistry were also negatively impacted by climate variation. Our study offers a unified framework to link climate change, fungal community composition, and community-level functional traits. Thus, our study provides insight into how environmental change can alter ecosystem functions via the promotion or reduction of fungal taxa with different stoichiometric characteristics and responses.

Metabarcoding of the Three Domains of Life in Aquatic Saline Ecosystems

High-throughput amplicon sequencing, known as metabarcoding, is a powerful technique to decipher exhaustive microbial diversity considering specific gene markers. While most of the studies investigating ecosystem functioning through microbial diversity targeted only one domain of life, either bacteria, or archaea or microeukaryotes, the remaining challenge in microbial ecology is to uncover the integrated view of microbial diversity occurring in ecosystems. Indeed, interactions occurring between the different microbial counterparts are now recognized having a great impact on stability and resilience of ecosystems. Here, we summarize protocols describing sampling, molecular, and simultaneous metabarcoding of bacteria, archaea, and microeukaryotes, as well as a bioinformatic pipeline allowing the study of exhaustive microbial diversity in natural aquatic saline samples.

Ciliate Morpho-Taxonomy and Practical Considerations before Deploying Metabarcoding to Ciliate Community Diversity Surveys in Urban Receiving Waters

Disentangling biodiversity and community assembly effects on ecosystem function has always been an important topic in ecological research. The development and application of a DNA metabarcoding method has fundamentally changed the way we describe prokaryotic communities and estimate biodiversity. Compared to prokaryotes (bacteria and archaea), the eukaryotic microbes (unicellular eukaryotes) also fulfill extremely important ecological functions in different ecosystems regarding their intermediate trophic positions. For instance, ciliated microbes (accounting for a substantial portion of the diversity of unicellular eukaryotes) perform pivotal roles in microbial loops and are essential components in different ecosystems, especially in water purification processes. Therefore, the community composition of ciliated species has been widely utilized as a proxy for water quality and biological assessment in urban river ecosystems and WWTPs (wastewater treatment plants). Unfortunately, investigating the dynamic changes and compositions in ciliate communities relies heavily on existing morpho-taxonomical descriptions, which is limited by traditional microscopic approaches. To deal with this dilemma, we discuss the DNA-based taxonomy of ciliates, the relative merits and challenges of deploying its application using DNA metabarcoding for surveys of ciliate community diversity in urban waterbodies, and provide suggestions for minimizing relevant sources of biases in its implementation. We expect that DNA metabarcoding could untangle relationships between community assembly and environmental changes affecting ciliate communities. These analyses and discussions could offer a replicable method in support of the application of evaluating communities of ciliated protozoa as indicators of urban freshwater ecosystems.

The community ecology perspective of omics data

The measurement of uncharacterized pools of biological molecules through techniques such as metabarcoding, metagenomics, metatranscriptomics, metabolomics, and metaproteomics produces large, multivariate datasets. Analyses of these datasets have successfully been borrowed from community ecology to characterize the molecular diversity of samples (ɑ-diversity) and to assess how these profiles change in response to experimental treatments or across gradients (β-diversity). However, sample preparation and data collection methods generate biases and noise which confound molecular diversity estimates and require special attention. Here, we examine how technical biases and noise that are introduced into multivariate molecular data affect the estimation of the components of diversity (i.e., total number of different molecular species, or entities; total number of molecules; and the abundance distribution of molecular entities). We then explore under which conditions these biases affect the measurement of ɑ- and β-diversity and highlight how novel methods commonly used in community ecology can be adopted to improve the interpretation and integration of multivariate molecular data. Video Abstract.

Root associated fungal lineages of a tropical montane forest show contrasting sensitivities to the long-term addition of nitrogen and phosphorus

Root associated fungal (RAF) communities can exert strong effects on plant communities and are potentially sensitive to shifts in soil fertility. As increased atmospheric nitrogen (N) and phosphorus (P) deposition can alter the nutrient balance in natural ecosystems, we assessed the response of RAF communities to a fertilization experiment deployed on a highly diverse Andean forest. The stand level fine root fraction was sampled after 7 years of systematic N and P additions and RAF communities were characterized by a deep sequencing approach. We expected that fertilization will enhance competition of fungal taxa for limiting nutrients, thus eliciting diversity reductions and alterations in the structure of RAF communities. Fertilization treatments did not reduce RAF richness but affected community composition. At the phylum level fertilization reduced richness exclusively among Glomeromycota. In contrast, N and P additions (alone or in combination) altered the composition of several fungal phyla. The lack of a generalized response to long-term fertilization among RAF lineages suggests that most of these lineages will not be directly and immediately affected by the increasing rates of atmospheric N and P deposition expected for this region by 2050.

Strategies for sample labelling and library preparation in DNA metabarcoding studies

Metabarcoding of DNA extracted from environmental or bulk specimen samples is increasingly used to profile biota in basic and applied biodiversity research because of its targeted nature that allows sequencing of genetic markers from many samples in parallel. To achieve this, PCR amplification is carried out with primers designed to target a taxonomically informative marker within a taxonomic group, and sample-specific nucleotide identifiers are added to the amplicons prior to sequencing. The latter enables assignment of the sequences back to the samples they originated from. Nucleotide identifiers can be added during the metabarcoding PCR and during "library preparation", that is, when amplicons are prepared for sequencing. Different strategies to achieve this labelling exist. All have advantages, challenges and limitations, some of which can lead to misleading results, and in the worst case compromise the fidelity of the metabarcoding data. Given the range of questions addressed using metabarcoding, ensuring that data generation is robust and fit for the chosen purpose is critically important for practitioners seeking to employ metabarcoding for biodiversity assessments. Here, we present an overview of the three main workflows for sample-specific labelling and library preparation in metabarcoding studies on Illumina sequencing platforms; one-step PCR, two-step PCR, and tagged PCR. Further, we distill the key considerations for researchers seeking to select an appropriate metabarcoding strategy for their specific study. Ultimately, by gaining insights into the consequences of different metabarcoding workflows, we hope to further consolidate the power of metabarcoding as a tool to assess biodiversity across a range of applications.

Best practices in metabarcoding of fungi: From experimental design to results

The development of high-throughput sequencing (HTS) technologies has greatly improved our capacity to identify fungi and unveil their ecological roles across a variety of ecosystems. Here we provide an overview of current best practices in metabarcoding analysis of fungal communities, from experimental design through molecular and computational analyses. By reanalysing published data sets, we demonstrate that operational taxonomic units (OTUs) outperform amplified sequence variants (ASVs) in recovering fungal diversity, a finding that is particularly evident for long markers. Additionally, analysis of the full-length ITS region allows more accurate taxonomic placement of fungi and other eukaryotes compared to the ITS2 subregion. Finally, we show that specific methods for compositional data analyses provide more reliable estimates of shifts in community structure. We conclude that metabarcoding analyses of fungi are especially promising for integrating fungi into the full microbiome and broader ecosystem functioning context, recovery of novel fungal lineages and ancient organisms as well as barcoding of old specimens including type material.

The biodiversity effect of reduced tillage on soil microbiota

The conversion of natural habitats into farmland has been a leading cause of species loss worldwide. Here, we investigated to what extent less intensive soil disturbance can mitigate this loss. Specifically, we examined whether reduced soil disturbance by tillage in agricultural fields could contribute to soil microbial biodiversity by providing a habitat for species that are limited by conventional tillage. To do so, we studied the diversity of soil biotas from three agricultural practices representing conventional tillage, reduced tillage and no tillage. Study fields were sampled by taking a bulk soil sample at the centre and edge of each field. The soil communities were recorded with environmental DNA metabarcoding using three molecular markers targeting bacteria, fungi and eukaryotes. While these three markers represent the vast majority of biotic variation in the soil, they will inevitably be dominated by the megadiverse microbiota of bacteria, microfungi and protists. We found a significant differentiation in community composition related to the intensity of tillage. Richness was weakly correlated to tillage, and more influenced by whether the sample was taken in the center or the edge of the field. Despite the significant effect of tillage on composition, comparisons with natural ecosystems revealed that all 30 study fields were much more similar in composition to other rotational fields than to more natural habitats, oldfields and leys. Despite a slightly higher similarity to oldfields and semi-natural grasslands, the contribution of no-till soil communities to biodiversity conservation is negligible, and our results indicate that restoration on set aside land may contribute more to conservation.

Metabarcoding of insect-associated fungal communities: a comparison of internal transcribed spacer (ITS) and large-subunit (LSU) rRNA markers

Full taxonomic characterisation of fungal communities is necessary for establishing ecological associations and early detection of pathogens and invasive species. Complex communities of fungi are regularly characterised by metabarcoding using the Internal Transcribed Spacer (ITS) and the Large-Subunit (LSU) gene of the rRNA locus, but reliance on a single short sequence fragment limits the confidence of identification. Here we link metabarcoding from the ITS2 and LSU D1-D2 regions to characterise fungal communities associated with bark beetles (Scolytinae), the likely vectors of several tree pathogens. Both markers revealed similar patterns of overall species richness and response to key variables (beetle species, forest type), but identification against the respective reference databases using various taxonomic classifiers revealed poor resolution towards lower taxonomic levels, especially the species level. Thus, Operational Taxonomic Units (OTUs) could not be linked via taxonomic classifiers across ITS and LSU fragments. However, using phylogenetic trees (focused on the epidemiologically important Sordariomycetes) we placed OTUs obtained with either marker relative to reference sequences of the entire rRNA cistron that includes both loci and demonstrated the largely similar phylogenetic distribution of ITS and LSU-derived OTUs. Sensitivity analysis of congruence in both markers suggested the biologically most defensible threshold values for OTU delimitation in Sordariomycetes to be 98% for ITS2 and 99% for LSU D1-D2. Studies of fungal communities using the canonical ITS barcode require corroboration across additional loci. Phylogenetic analysis of OTU sequences aligned to the full rRNA cistron shows higher success rate and greater accuracy of species identification compared to probabilistic taxonomic classifiers.

Current Insight into Traditional and Modern Methods in Fungal Diversity Estimates

Fungi are an important and diverse component in various ecosystems. The methods to identify different fungi are an important step in any mycological study. Classical methods of fungal identification, which rely mainly on morphological characteristics and modern use of DNA based molecular techniques, have proven to be very helpful to explore their taxonomic identity. In the present compilation, we provide detailed information on estimates of fungi provided by different mycologistsover time. Along with this, a comprehensive analysis of the importance of classical and molecular methods is also presented. In orderto understand the utility of genus and species specific markers in fungal identification, a polyphasic approach to investigate various fungi is also presented in this paper. An account of the study of various fungi based on culture-based and cultureindependent methods is also provided here to understand the development and significance of both approaches. The available information on classical and modern methods compiled in this study revealed that the DNA based molecular studies are still scant, and more studies are required to achieve the accurate estimation of fungi present on earth.

Extending Association Rule Mining to Microbiome Pattern Analysis: Tools and Guidelines to Support Real Applications

Boosted by the exponential growth of microbiome-based studies, analyzing microbiome patterns is now a hot-topic, finding different fields of application. In particular, the use of machine learning techniques is increasing in microbiome studies, providing deep insights into microbial community composition. In this context, in order to investigate microbial patterns from 16S rRNA metabarcoding data, we explored the effectiveness of Association Rule Mining (ARM) technique, a supervised-machine learning procedure, to extract patterns (in this work, intended as groups of species or taxa) from microbiome data. ARM can generate huge amounts of data, making spurious information removal and visualizing results challenging. Our work sheds light on the strengths and weaknesses of pattern mining strategy into the study of microbial patterns, in particular from 16S rRNA microbiome datasets, applying ARM on real case studies and providing guidelines for future usage. Our results highlighted issues related to the type of input and the use of metadata in microbial pattern extraction, identifying the key steps that must be considered to apply ARM consciously on 16S rRNA microbiome data. To promote the use of ARM and the visualization of microbiome patterns, specifically, we developed microFIM (microbial Frequent Itemset Mining), a versatile Python tool that facilitates the use of ARM integrating common microbiome outputs, such as taxa tables. microFIM implements interest measures to remove spurious information and merges the results of ARM analysis with the common microbiome outputs, providing similar microbiome strategies that help scientists to integrate ARM in microbiome applications. With this work, we aimed at creating a bridge between microbial ecology researchers and ARM technique, making researchers aware about the strength and weaknesses of association rule mining approach.

Cable bacteria at oxygen-releasing roots of aquatic plants: a widespread and diverse plant-microbe association

Cable bacteria are sulfide-oxidising, filamentous bacteria that reduce toxic sulfide levels, suppress methane emissions and drive nutrient and carbon cycling in sediments. Recently, cable bacteria have been found associated with roots of aquatic plants and rice (Oryza sativa). However, the extent to which cable bacteria are associated with aquatic plants in nature remains unexplored. Using newly generated and public 16S rRNA gene sequence datasets combined with fluorescence in situ hybridisation, we investigated the distribution of cable bacteria around the roots of aquatic plants, encompassing seagrass (including seagrass seedlings), rice, freshwater and saltmarsh plants. Diverse cable bacteria were found associated with roots of 16 out of 28 plant species and at 36 out of 55 investigated sites, across four continents. Plant-associated cable bacteria were confirmed across a variety of ecosystems, including marine coastal environments, estuaries, freshwater streams, isolated pristine lakes and intensive agricultural systems. This pattern indicates that this plant-microbe relationship is globally widespread and neither obligate nor species specific. The occurrence of cable bacteria in plant rhizospheres may be of general importance to vegetation vitality, primary productivity, coastal restoration practices and greenhouse gas balance of rice fields and wetlands.

Disturbance alters the forest soil microbiome

Billions of microorganisms perform critical below-ground functions in all terrestrial ecosystems. While largely invisible to the naked eye, they support all higher lifeforms, form symbiotic relationships with ~90% of terrestrial plant species, stabilize soils, and facilitate biogeochemical cycles. Global increases in the frequency of disturbances are driving major changes in the structure and function of forests. However, despite their functional significance, the disturbance responses of forest microbial communities are poorly understood. Here, we explore the influence of disturbance on the soil microbiome (archaea, fungi and bacteria) of some of the world's tallest and most carbon-dense forests, the Mountain Ash forests of south-eastern Australia. From 80 sites, we identified 23,277 and 19,056 microbial operational taxonomic units from the 0-10 cm and 20-30 cm depths of soil respectively. From this extensive data set, we found the diversity and composition of these often cryptic communities has been altered by human and natural disturbance events. For instance, the diversity of ectomycorrhizal fungi declined with clearcut logging, the diversity of archaea declined with salvage logging, and bacterial diversity and overall microbial diversity declined with the number of fires. Moreover, we identified key associations between edaphic (soil properties), environmental (slope, elevation) and spatial variables and the composition of all microbial communities. Specifically, we found that soil pH, manganese, magnesium, phosphorus, iron and nitrate were associated with the composition of all microbial communities. In a period of widespread degradation of global forest ecosystems, our findings provide an important and timely insight into the disturbance responses of soil microbial communities, which may influence key ecological functions.

DNA metabarcoding and morphological methods show complementary patterns in the metacommunity organization of lentic epiphytic diatoms

Diatoms are important organisms in freshwater ecosystems due to their position as primary producers and therefore, analyzing their assemblages provides relevant information on ecosystem functioning. Diatoms have historically been identified based on morphological traits, which is time-consuming and requires well-trained specialists. Nevertheless, DNA barcoding offers an alternative approach to overcome some limitations of the morphological method. Here, we assess if both approaches are comparable methods to study patterns and mechanisms (including environmental filtering and dispersal limitation) of epiphytic diatom metacommunities using a comprehensive dataset from 22 Mediterranean ponds at different taxonomic resolutions. We used a fragment of rbcL barcode gene combined with High-Throughput Sequencing to infer diatom community composition. The overall degree of correspondence between both approaches was assessed by Procrustean rotation analysis and Procrustean randomization tests, whereas the role of local environmental variables and geographical distances was studied using a comprehensive combination of BIOENV, Mantel tests and distance-based redundancy analysis. Our results showed a relatively poor correspondence in the compositional variation of diatom metacommunity between both approaches. We speculate that the incompleteness of the reference database and the bioinformatics processing are the biases most likely affecting the molecular approach, whereas the limited counting effort and the presence of cryptic species are presumably the major biases related with the morphological method. On the other hand, variation in diatom community composition detected with both approaches was strongly related to the environmental template, which may be related with the narrow community-environment relationships in diatoms. Nevertheless, we found no significant relationship between compositional variation and geographical distances. Overall, our work shows the complementary nature of both approaches and highlights the importance of DNA metabarcoding to address empirical research questions of community ecology in freshwaters, especially once the reference databases include most genotypes of occurring taxa and bioinformatics biases are overcome.

Dissolved organic matter (DOM) quality drives biogeographic patterns of soil bacterial communities and their association networks in semi-arid regions

It is of great interest to elucidate the biogeographic patterns of soil microorganisms and their driving forces, which is fundamental to predicting alterations in microbial-mediated functions arising from environment changes. Although dissolved organic matter (DOM) represents an important resource for soil microorganisms, knowledge of how its quality affects microbial biogeography is limited. Here, we characterized soil bacterial communities and DOM quality in 45 soil samples collected from a 1500-km sampling transect through semi-arid regions in northern China which are currently suffering great pressure from climate change, using Illumina Miseq sequencing and fluorescence spectroscopy, respectively. We found that DOM quality (i.e. the source of DOM and the humification degree of DOM) had profound shaping influence on the biogeographic patterns exhibited by bacterial diversity, community composition and association networks. Specifically, the composition of bacteria community closely associated with DOM quality. Plant-derived DOM sustained higher bacterial diversity relative to microbial-derived DOM. Meanwhile, bacterial diversity linearly increased with increasing humification degree of DOM. Additionally, plant-derived DOM was observed to foster more complex bacterial association networks with less competition. Together, our work contributes to the factors underlying biogeographic patterns not only of bacterial diversity, community composition but also of their association networks and reports previously undocumented important role of DOM quality in shaping these patterns.

Spatial Patterns of Soil Fungal Communities Are Driven by Dissolved Organic Matter (DOM) Quality in Semi-Arid Regions

Soil fungi are ecologically important as decomposers, pathogens, and symbionts in nature. Understanding their biogeographic patterns and driving forces is pivotal to predict alterations arising from environmental changes in ecosystem. Dissolved organic matter (DOM) is an essential resource for soil fungi; however, the role of its quality in structuring fungal community patterns remains elusive. Here using Illumina MiSeq sequencing, we characterized total fungi and their functional groups in 45 soil samples collected from a 1500-km sampling transect through semi-arid regions in northern China, which are currently suffering great pressure from climate change. Total fungi and their functional groups were all observed to exhibit significant biogeographic patterns which were primarily driven by environmental variables. DOM quality was the best and consistent predictor of diversity of both total fungi and functional groups. Specifically, plant-derived DOM was associated with greater diversity relative to microbe-dominated origins. In addition, fungal diversity linearly increased with increases in degree of humification in DOM. Similarly, among all measured environmental variables, DOM quality had the strongest effects on the community composition of total fungi and functional groups. Together, our work contributes to the factors underlying fungal biogeographic patterns and adds detail to the importance of DOM quality in structuring fungal communities.

Hidden Fungi: Combining Culture-Dependent and -Independent DNA Barcoding Reveals Inter-Plant Variation in Species Richness of Endophytic Root Fungi in Elymus repens

The root endophyte community of the grass species Elymus repens was investigated using both a culture-dependent approach and a direct amplicon sequencing method across five sites and from individual plants. There was much heterogeneity across the five sites and among individual plants. Focusing on one site, 349 OTUs were identified by direct amplicon sequencing but only 66 OTUs were cultured. The two approaches shared ten OTUs and the majority of cultured endophytes do not overlap with the amplicon dataset. Media influenced the cultured species richness and without the inclusion of 2% MEA and full-strength MEA, approximately half of the unique OTUs would not have been isolated using only PDA. Combining both culture-dependent and -independent methods for the most accurate determination of root fungal species richness is therefore recommended. High inter-plant variation in fungal species richness was demonstrated, which highlights the need to rethink the scale at which we describe endophyte communities.

Sampling cores and sequencing depths affected the measurement of microbial diversity in soil quadrats

Due to the massive quantity and broad phylogeny, an accurate measurement of microbial diversity is highly challenging in soil ecosystems. Initially, the deviation caused by sampling should be adequately considered. Here, we attempted to uncover the effect of different sampling strategies on α diversity measurement of soil prokaryotes. Four 1 m² sampling quadrats in a typical grassland were thoroughly surveyed through deep 16S rRNA gene sequencing (over 11 million reads per quadrat) with numerous replicates (33 soil sampling cores with total 141 replicates per quadrat). We found the difference in diversity was relatively small when pooling soil cores before and after DNA extraction and sequencing, but they were both superior to a non-pooling strategy. Pooling a small number of soil cores (i.e., 5 or 9) combined with several technical replicates is sufficient to estimate diversities for soil prokaryotes, and there is great flexibility in pooling original samples or data at different experimental steps. Additionally, the distribution of local α diversity varies with sampling core number, sequencing depth, and abundance distribution of the community, especially for high orders of Hill diversity index (i.e., Shannon entropy and inverse Simpson index). For each grassland soil quadrat (1 m²), retaining 100,000 reads after taxonomic clustering might be a realistic option, as these number of reads can efficiently cover the majority of common species in this area. Our findings provide important guidance for soil sampling strategy, and the general results can serve as a basis for further studies.

Parasites, niche modification and the host microbiome: A field survey of multiple parasites

Parasites can affect and be affected by the host's microbiome, with consequences for host susceptibility, parasite transmission, and host and parasite fitness. Yet, two aspects of the relationship between parasite infection and host microbiota remain little understood: the nature of the relationship under field conditions, and how the relationship varies among parasites. To overcome these limitations, we performed a field survey of the within-leaf fungal community in a tall fescue population. We investigated how diversity and composition of the fungal microbiome associate with natural infection by fungal parasites with different feeding strategies. A parasite's feeding strategy affects both parasite requirements of the host environment and parasite impacts on the host environment. We hypothesized that parasites that more strongly modify niches available within a host will be associated with greater changes in microbiome diversity and composition. Parasites with a feeding strategy that creates necrotic tissue to extract resources (necrotrophs) may not only have different niche requirements, but also act as particularly strong niche modifiers. Barcoded amplicon sequencing of the fungal ITS region revealed that leaf segments symptomatic of necrotrophs had lower fungal diversity and distinct composition compared to segments that were asymptomatic or symptomatic of other parasites. There were no clear differences in fungal diversity or composition between leaf segments that were asymptomatic and segments symptomatic of other parasite feeding strategies. Our results motivate future experimental work to test how the relationship between the microbiome and parasite infection is impacted by parasite feeding strategy and highlight the potential importance of parasite traits.

Integrating eDNA metabarcoding and simultaneous underwater visual surveys to describe complex fish communities in a marine biodiversity hotspot

Marine biodiversity can be surveyed using underwater visual censuses and recently with eDNA metabarcoding. Although a promising tool, eDNA studies have shown contrasting results related to its detection scale and the number of species identified compared to other survey methods. Also, its accuracy relies on complete reference databases used for taxonomic assignment and, as other survey methods, species detection may show false-negative and false-positive errors. Here, we compared results from underwater visual censuses and simultaneous eDNA metabarcoding fish surveys in terms of observed species and community composition. We also assess the effect of a custom reference database in the taxonomic assignment, and evaluate occupancy, capture and detection probabilities, as well as error rates of eDNA survey data. We amplified a 12S rRNA fish barcode from 24 sampling sites in the gulf of California. More species were detected with eDNA metabarcoding than with UVC. Because each survey method largely detected different sets of species, the combined approach doubled the number of species registered. Both survey methods recovered a known biodiversity gradient and a biogeographic break, but eDNA captured diversity over a broader geographic and bathymetric scale. Furthermore, the use of a modest-sized custom reference database significantly increased taxonomic assignment. In a subset of species, occupancy models revealed eDNA surveys provided similar or higher detection probabilities compared to UVC. The occupancy value of each species had a large influence on eDNA detectability, and in the false positive and negative error. Overall, these results highlight the potential of eDNA metabarcoding in complementing other established ecological methods for studies of marine fishes.

Comparative Fungal Community Analyses Using Metatranscriptomics and Internal Transcribed Spacer Amplicon Sequencing from Norway Spruce

The health, growth, and fitness of boreal forest trees are impacted and improved by their associated microbiomes. Microbial gene expression and functional activity can be assayed with RNA sequencing (RNA-Seq) data from host samples. In contrast, phylogenetic marker gene amplicon sequencing data are used to assess taxonomic composition and community structure of the microbiome. Few studies have considered how much of this structural and taxonomic information is included in transcriptomic data from matched samples. Here, we described fungal communities using both host-derived RNA-Seq and fungal ITS1 DNA amplicon sequencing to compare the outcomes between the methods. We used a panel of root and needle samples from the coniferous tree species Picea abies (Norway spruce) growing in untreated (nutrient-deficient) and nutrient-enriched plots at the Flakaliden forest research site in boreal northern Sweden. We show that the relationship between samples and alpha and beta diversity indicated by the fungal transcriptome is in agreement with that generated by the ITS data, while also identifying a lack of taxonomic overlap due to limitations imposed by current database coverage. Furthermore, we demonstrate how metatranscriptomics data additionally provide biologically informative functional insights. At the community level, there were changes in starch and sucrose metabolism, biosynthesis of amino acids, and pentose and glucuronate interconversions, while processing of organic macromolecules, including aromatic and heterocyclic compounds, was enriched in transcripts assigned to the genus Cortinarius.

IMPORTANCE A deeper understanding of microbial communities associated with plants is revealing their importance for plant health and productivity. RNA extracted from plant field samples represents the host and other organisms present. Typically, gene expression studies focus on the plant component or, in a limited number of studies, expression in one or more associated organisms. However, metatranscriptomic data are rarely used for taxonomic profiling, which is currently performed using amplicon approaches. We created an assembly-based, reproducible, and hardware-agnostic workflow to taxonomically and functionally annotate fungal RNA-Seq data obtained from Norway spruce roots, which we compared to matching ITS amplicon sequencing data. While we identified some limitations and caveats, we show that functional, taxonomic, and compositional insights can all be obtained from RNA-Seq data. These findings highlight the potential of metatranscriptomics to advance our understanding of interaction, response, and effect between host plants and their associated microbial communities.

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.

Applications of endophytic microbes in agriculture, biotechnology, medicine, and beyond

Endophytes are emerging as integral components of plant microbiomes. Some of them play pivotal roles in plant development and plant responses to pathogens and abiotic stresses, whereas others produce useful and/or interesting secondary metabolites. The appreciation of their abilities to affect plant phenotypes and produce useful compounds via genetic and molecular interactions has paved the way for these abilities to be exploited for health and welfare of plants, humans and ecosystems. Here we comprehensively review current and potential applications of endophytes in the agricultural, pharmaceutical, and industrial sectors. In addition, we briefly discuss the research objectives that should be focused upon in the coming years in order for endophytes and their metabolites to be fully harnessed for potential use in diverse areas.

Identification of Penicillium verrucosum, Penicillium commune, and Penicillium crustosum Isolated from Chicken Eggs

Penicillium species belong to main causative agents of food spoilage leading to significant economic losses and potential health risk for consumers. These fungi have been isolated from various food matrices, including table eggs. In this study, both conventional Polymerase Chain Reaction (PCR) and Polymerase Chain Reaction-Internal Transcribed Spacer-Restriction Fragment Length Polymorphism (PCR-ITS-RFLP) methods were used for species identification of Penicillium (P.) spp. isolated from the eggshells of moldy chicken eggs. Seven restriction endonucleases (Bsp1286I, XmaI, HaeIII, HinfI, MseI, SfcI, Hpy188I) were applied to create ribosomal restriction patterns of amplified ITS regions. To identify P. verrucosum, P. commune, and P. crustosum with the help of conventional PCR assay, species-specific primer pairs VERF/VERR, COMF/COMR, and CRUF/CRUR were designed on the base of 5.8 subunit-Internal Transcribed Spacer (5.8S-ITS) region. Altogether, 121 strains of microscopic filamentous fungi were isolated by traditional culture mycological examination. After morphological evaluation of both macroscopic and microscopic features, 96 strains were classified in Penicillium spp. Two molecular methods used have confirmed eight isolates as P. verrucosum, 42 isolates as P. commune, and 19 isolates as P. crustosum. Both PCR-ITS-RFLP and conventional PCR assays appear to be suitable alternatives for rapid identification of the above mentioned Penicillium species.

Aquatic food webs in deep temperate lakes: Key species establish through their autecological versatility

Microbial planktonic communities are the basis of food webs in aquatic ecosystems since they contribute substantially to primary production and nutrient recycling. Network analyses of DNA metabarcoding data sets emerged as a powerful tool to untangle the complex ecological relationships among the key players in food webs. In this study, we evaluated co-occurrence networks constructed from time-series metabarcoding data sets (12 months, biweekly sampling) of protistan plankton communities in surface layers (epilimnion) and bottom waters (hypolimnion) of two temperate deep lakes, Lake Mondsee (Austria) and Lake Zurich (Switzerland). Lake Zurich plankton communities were less tightly connected, more fragmented and had a higher susceptibility to a species extinction scenario compared to Lake Mondsee communities. We interpret these results as a lower robustness of Lake Zurich protistan plankton to environmental stressors, especially stressors resulting from climate change. In all networks, the phylum Ciliophora contributed the highest number of nodes, among them several in key positions of the networks. Associations in ciliate-specific subnetworks resembled autecological species-specific traits that indicate adaptions to specific environmental conditions. We demonstrate the strength of co-occurrence network analyses to deepen our understanding of plankton community dynamics in lakes and indicate biotic relationships, which resulted in new hypotheses that may guide future research in climate-stressed ecosystems.

Microbial networks inferred from environmental DNA data for biomonitoring ecosystem change: Strengths and pitfalls

Environmental DNA contains information on the species interaction networks that support ecosystem functions and services. Next-generation biomonitoring proposes the use of this data to reconstruct ecological networks in real time and then compute network-level properties to assess ecosystem change. We investigated the relevance of this proposal by assessing: (i) the replicability of DNA-based networks in the absence of ecosystem change, and (ii) the benefits and shortcomings of community- and network-level properties for monitoring change. We selected crop-associated microbial networks as a case study because they support disease regulation services in agroecosystems and analysed their response to change in agricultural practice between organic and conventional systems. Using two statistical methods of network inference, we showed that network-level properties, especially β-properties, could detect change. Moreover, consensus networks revealed robust signals of interactions between the most abundant species, which differed between agricultural systems. These findings complemented those obtained with community-level data that showed, in particular, a greater microbial diversity in the organic system. The limitations of network-level data included (i) the very high variability of network replicates within each system; (ii) the low number of network replicates per system, due to the large number of samples needed to build each network; and (iii) the difficulty in interpreting links of inferred networks. Tools and frameworks developed over the last decade to infer and compare microbial networks are therefore relevant to biomonitoring, provided that the DNA metabarcoding data sets are large enough to build many network replicates and progress is made to increase network replicability and interpretation.

Diatom DNA metabarcoding for ecological assessment: Comparison among bioinformatics pipelines used in six European countries reveals the need for standardization

Ecological assessment of lakes and rivers using benthic diatom assemblages currently requires considerable taxonomic expertise to identify species using light microscopy. This traditional approach is also time-consuming. Diatom metabarcoding is a promising alternative and there is increasing interest in using this approach for routine assessment. However, until now, analysis protocols for diatom metabarcoding have been developed and optimised by research groups working in isolation. The diversity of existing bioinformatics methods highlights the need for an assessment of the performance and comparability of results of different methods. The aim of this study was to test the correspondence of outputs from six bioinformatics pipelines currently in use for diatom metabarcoding in different European countries. Raw sequence data from 29 biofilm samples were treated by each of the bioinformatics pipelines, five of them using the same curated reference database. The outputs of the pipelines were compared in terms of sequence unit assemblages, taxonomic assignment, biotic index score and ecological assessment outcomes. The three last components were also compared to outputs from traditional light microscopy, which is currently accepted for ecological assessment of phytobenthos, as required by the Water Framework Directive. We also tested the performance of the pipelines on the two DNA markers (rbcL and 18S-V4) that are currently used by the working groups participating in this study. The sequence unit assemblages produced by different pipelines showed significant differences in terms of assigned and unassigned read numbers and sequence unit numbers. When comparing the taxonomic assignments at genus and species level, correspondence of the taxonomic assemblages between pipelines was weak. Most discrepancies were linked to differential detection or quantification of taxa, despite the use of the same reference database. Subsequent calculation of biotic index scores also showed significant differences between approaches, which were reflected in the final ecological assessment. Use of the rbcL marker always resulted in better correlation among molecular datasets and also in results closer to these generated using traditional microscopy. This study shows that decisions made in pipeline design have implications for the dataset's structure and the taxonomic assemblage, which in turn may affect biotic index calculation and ecological assessment. There is a need to define best-practice bioinformatics parameters in order to ensure the best representation of diatom assemblages. Only the use of similar parameters will ensure the compatibility of data from different working groups. The future of diatom metabarcoding for ecological assessment may also lie in the development of new metrics using, for example, presence/absence instead of relative abundance data.

Benthic monitoring of oil and gas offshore platforms in the North Sea using environmental DNA metabarcoding

Since 2010, considerable efforts have been undertaken to monitor the environmental status of European marine waters and ensuring the development of methodological standards for the evaluation of this status. However, the current routine biomonitoring implicates time-consuming and costly manual sorting and morphological identification of benthic macrofauna. Environmental DNA (eDNA) metabarcoding represents an alternative to the traditional monitoring method with very promising results. Here, we tested it further by performing eDNA metabarcoding of benthic eukaryotic communities in the vicinity of two offshore oil and gas platforms in the North Sea. Three different genetic markers (18S V1V2, 18S V9 and COI) were used to assess the environmental pressures induced by the platforms. All markers showed patterns of alpha and beta diversity consistent with morphology-based macrofauna analyses. In particular, the communities' structure inferred from metabarcoding and morphological data significantly changed along distance gradients from the platforms. The impact of the operational discharges was also detected by the variation of biotic index values, AMBI index showing the best correlation between morphological and eDNA data sets. Finally, the sediment physicochemical parameters were used to build a local de novo pressure index that served as benchmark to test the potential of a taxonomy-free approach. Our study demonstrates that metabarcoding approach outperforms morphology-based approach and can be used as a cost and time-saving alternative solution to the traditional morphology-based monitoring in order to monitor more efficiently the impact of industrial activities on marine biodiversity.

Bacterial Communities in the Rhizosphere and Phyllosphere of Halophytes and Drought-Tolerant Plants in Mediterranean Ecosystems

The aim of the study was to investigate the bacterial community diversity and structure by means of 16S rRNA gene high-throughput amplicon sequencing, in the rhizosphere and phyllosphere of halophytes and drought-tolerant plants in Mediterranean ecosystems with different soil properties. The locations of the sampled plants included alkaline, saline-sodic soils, acidic soils, and the volcanic soils of Santorini Island, differing in soil fertility. Our results showed high bacterial richness overall with Proteobacteria and Actinobacteria dominating in terms of OTUs number and indicated that variable bacterial communities differed depending on the plant's compartment (rhizosphere and phyllosphere), the soil properties and location of sampling. Furthermore, a shared pool of generalist bacterial taxa was detected independently of sampling location, plant species, or plant compartment. We conclude that the rhizosphere and phyllosphere of native plants in stressed Mediterranean ecosystems consist of common bacterial assemblages contributing to the survival of the plant, while at the same time the discrete soil properties and environmental pressures of each habitat drive the development of a complementary bacterial community with a distinct structure for each plant and location. We suggest that this trade-off between generalist and specialist bacterial community is tailored to benefit the symbiosis with the plant.