A fungal mock community control for amplicon sequencing experiments

New insights into biologic interpretation of bioinformatic pipelines for fish eDNA metabarcoding: A case study in Pearl River estuary

Environmental DNA (eDNA) metabarcoding is an emerging tool for monitoring biological communities in aquatic ecosystems. The selection of bioinformatic pipelines significantly impacts the results of biodiversity assessments. However, there is currently no consensus on the appropriate bioinformatic pipelines for fish community analysis in eDNA metabarcoding. In this study, we compared three bioinformatic pipelines (Uparse, DADA2, and UNOISE3) using real and mock (constructed with 15/30 known fish) communities to investigate the differences in biological interpretation during the data analysis process in eDNA metabarcoding. Performance evaluation and diversity analyses revealed that the choice of bioinformatic pipeline could impact the biological results of metabarcoding experiments. Among the three pipelines, the operational taxonomic units (OTU)-based pipeline (Uparse) showed the best performance (sensitivity: 0.6250 ± 0.0166; compositional similarity: 0.4000 ± 0.0571), the highest richness (25-102) and minimal inter-group differences in alpha diversity. It suggested the OTU-based pipeline possessed superior capability in fish diversity monitoring compared to ASV/ZOTU-based pipeline. Additionally, the Bray-Curtis distance matrix achieved the highest discriminative effect in the PCoA (43.3%-53.89%) and inter-group analysis (P < 0.01), indicating it was better at distinguishing compositional differences or specific genera of fish community at different sampling sites than other distance matrices. These findings provide new insights into fish community monitoring through eDNA metabarcoding in estuarine environments.

Unveiling errors in soil microbial community sequencing: a case for reference soils and improved diagnostics for nanopore sequencing

The sequencing platform and workflow strongly influence microbial community analyses through potential errors at each step. Effective diagnostics and experimental controls are needed to validate data and improve reproducibility. This cross-laboratory study evaluates sources of variability and error at three main steps of a standardized amplicon sequencing workflow (DNA extraction, polymerase chain reaction [PCR], and sequencing) using Oxford Nanopore MinION to analyze agricultural soils and a simple mock community. Variability in sequence results occurs at each step in the workflow with PCR errors and differences in library size greatly influencing diversity estimates. Common bioinformatic diagnostics and the mock community are ineffective at detecting PCR abnormalities. This work outlines several diagnostic checks and techniques to account for sequencing depth and ensure accuracy and reproducibility in soil community analyses. These diagnostics and the inclusion of a reference soil can help ensure data validity and facilitate the comparison of multiple sequencing runs within and between laboratories.

High intensity perturbations induce an abrupt shift in soil microbial state

Soil microbial communities play a pivotal role in regulating ecosystem functioning. But they are increasingly being shaped by human-induced environmental change, including intense "pulse" perturbations, such as droughts, which are predicted to increase in frequency and intensity with climate change. While it is known that soil microbial communities are sensitive to such perturbations and that effects can be long-lasting, it remains untested whether there is a threshold in the intensity and frequency of perturbations that can trigger abrupt and persistent transitions in the taxonomic and functional characteristics of soil microbial communities. Here we demonstrate experimentally that intense pulses of drought equivalent to a 30-year drought event (<15% WHC) induce a major shift in the soil microbial community characterised by significantly altered bacterial and fungal community structures of reduced complexity and functionality. Moreover, the characteristics of this transformed microbial community persisted after returning soil to its previous moisture status. As a result, we found that drought had a strong legacy effect on bacterial community function, inducing an enhanced growth rate following subsequent drought. Abrupt transitions are widely documented in aquatic and terrestrial plant communities in response to human-induced perturbations. Our findings demonstrate that such transitions also occur in soil microbial communities in response to high intensity pulse perturbations, with potentially deleterious consequences for soil health.

Manipulating atmospheric CO2 concentration induces shifts in wheat leaf and spike microbiomes and in Fusarium pathogen communities

Changing atmospheric composition represents a source of uncertainty in our assessment of future disease risks, particularly in the context of mycotoxin producing fungal pathogens which are predicted to be more problematic with climate change. To address this uncertainty, we profiled microbiomes associated with wheat plants grown under ambient vs. elevated atmospheric carbon dioxide concentration [CO2] in a field setting over 2 years. We also compared the dynamics of naturally infecting versus artificially introduced Fusarium spp. We found that the well-known temporal dynamics of plant-associated microbiomes were affected by [CO2]. The abundances of many amplicon sequence variants significantly differed in response to [CO2], often in an interactive manner with date of sample collection or with tissue type. In addition, we found evidence that two strains within Fusarium - an important group of mycotoxin producing fungal pathogens of plants - responded to changes in [CO2]. The two sequence variants mapped to different phylogenetic subgroups within the genus Fusarium, and had differential [CO2] responses. This work informs our understanding of how plant-associated microbiomes and pathogens may respond to changing atmospheric compositions.

THAPBI PICT-a fast, cautious, and accurate metabarcoding analysis pipeline

THAPBI PICT is an open source software pipeline for metabarcoding analysis of Illumina paired-end reads, including cases of multiplexing where more than one amplicon is amplified per DNA sample. Initially a Phytophthora ITS1 Classification Tool (PICT), we demonstrate using worked examples with our own and public data sets how, with appropriate primer settings and a custom database, it can be applied to other amplicons and organisms, and used for reanalysis of existing datasets. The core dataflow of the implementation is (i) data reduction to unique marker sequences, often called amplicon sequence variants (ASVs), (ii) dynamic thresholds for discarding low abundance sequences to remove noise and artifacts (rather than error correction by default), before (iii) classification using a curated reference database. The default classifier assigns a label to each query sequence based on a database match that is either perfect, or a single base pair edit away (substitution, deletion or insertion). Abundance thresholds for inclusion can be set by the user or automatically using per-batch negative or synthetic control samples. Output is designed for practical interpretation by non-specialists and includes a read report (ASVs with classification and counts per sample), sample report (samples with counts per species classification), and a topological graph of ASVs as nodes with short edit distances as edges. Source code available from https://github.com/peterjc/thapbi-pict/ with documentation including installation instructions.

Profiling Walnut Fungal Pathobiome Associated with Walnut Dieback Using Community-Targeted DNA Metabarcoding

Walnut dieback can be caused by several fungal pathogenic species, which are associated with symptoms ranging from branch dieback to fruit necrosis and blight, challenging the one pathogen-one disease concept. Therefore, an accurate and extensive description of the walnut fungal pathobiome is crucial. To this end, DNA metabarcoding represents a powerful approach provided that bioinformatic pipelines are evaluated to avoid misinterpretation. In this context, this study aimed to determine (i) the performance of five primer pairs targeting the ITS region in amplifying genera of interest and estimating their relative abundance based on mock communities and (ii) the degree of taxonomic resolution using phylogenetic trees. Furthermore, our pipelines were also applied to DNA sequences from symptomatic walnut husks and twigs. Overall, our results showed that the ITS2 region was a better barcode than ITS1 and ITS, resulting in significantly higher sensitivity and/or similarity of composition values. The ITS3/ITS4_KYO1 primer set allowed to cover a wider range of fungal diversity, compared to the other primer sets also targeting the ITS2 region, namely, GTAA and GTAAm. Adding an extraction step to the ITS2 sequence influenced both positively and negatively the taxonomic resolution at the genus and species level, depending on the primer pair considered. Taken together, these results suggested that Kyo set without ITS2 extraction was the best pipeline to assess the broadest fungal diversity, with a more accurate taxonomic assignment, in walnut organs with dieback symptoms.

Microbiome Analysis of Sugarcane Juices and Biofilms from Louisiana Raw Sugar Factories

During postharvest processing of sugarcane for raw sugar, microbial activity results in sucrose loss and undesirable exopolysaccharide (EPS) production. Historically, culture-based approaches have focused on the bacterium Leuconostoc mesenteroides as the main contributor to both processes. However, recent studies have shown that diverse microbes are present in sugarcane factories and may also contribute to sugarcane juice deterioration. In the present study, high-throughput amplicon-based sequence profiling was applied to gain a more comprehensive view of the microbial community in Louisiana raw sugar factories. Microbial profiling of the bacterial and fungal microbiomes by 16S V4 and ITS1 sequences, respectively, identified 417 bacterial amplicon sequence variants (ASVs) and 793 fungal ASVs. While Leuconostoc was indeed the most abundant bacterial genus overall (40.9% of 16S sequences), multiple samples were dominated by other taxa such as Weissella and Lactobacillus, underscoring the microbial diversity present in sugarcane factories. Furthermore, flask cultures inoculated with the same samples demonstrated differences in the rate of sucrose consumption, as well as the production of exopolysaccharides and other organic acids, which may result from the observed differences in microbial composition. IMPORTANCE Amplicon-based sequencing was utilized to address long-ignored gaps in microbiological knowledge about the diversity of microbes present in processing streams at Louisiana sugarcane raw sugar factories. These results support an emerging model where diverse organisms contribute to sugarcane juice degradation, help to contextualize microbial contamination problems faced by raw sugar factories, and will guide future studies on biocontrol measures to mitigate sucrose losses and operational challenges due to exopolysaccharide production.

Old-growth Acer macrophyllum trees host a unique suite of arbuscular mycorrhizal fungi and other root-associated fungal taxa in their canopy soil environment

Canopy soils occur on tree branches throughout the temperate rainforests of the Pacific Northwest Coast and are recognized as a defining characteristic of these ecosystems. Certain tree species extend adventitious roots into these canopy soil environments. Yet, research on adventitious root-associated fungi remains limited. Our study used microscopy to compare fungal colonization intensity between canopy and forest floor roots of old-growth bigleaf maple (Acer macrophyllum) trees. Subsequently, two high-throughput sequencing platforms were used to explore the spatial and seasonal variation of root-associated fungi between the two soil environments over one year. We found that canopy and forest floor roots had similar colonization intensity and were associating with a diversity of arbuscular mycorrhizal fungi and other potential symbionts, many of which were resolved to species level. Soil environment and seasonality affected root-associated fungal community composition, and several fungal species were indicative of the canopy soil environment. In Washington State's (USA) temperate old-growth rainforests, these canopy soil environments host a unique suite of root-associated fungi. The presence of arbuscular mycorrhizae provides further evidence that adventitious roots form fungal associations to exploit canopy soils for resources, and there may be novel relationships forming with other fungi. These soils may be providing a redundancy compartment (i.e., "nutrient reserve"), imparting a resiliency to disturbances for certain old-growth trees.

Porcine fungal mock community analyses: Implications for mycobiome investigations

Introduction

The gut microbiome is an integral partner in host health and plays a role in immune development, altered nutrition, and pathogen prevention. The mycobiome (fungal microbiome) is considered part of the rare biosphere but is still a critical component in health. Next generation sequencing has improved our understanding of fungi in the gut, but methodological challenges remain. Biases are introduced during DNA isolation, primer design and choice, polymerase selection, sequencing platform selection, and data analyses, as fungal reference databases are often incomplete or contain erroneous sequences.

Methods

Here, we compared the accuracy of taxonomic identifications and abundances from mycobiome analyses which vary among three commonly selected target gene regions (18S, ITS1, or ITS2) and the reference database (UNITE - ITS1, ITS2 and SILVA - 18S). We analyze multiple communities including individual fungal isolates, a mixed mock community created from five common fungal isolates found in weanling piglet feces, a purchased commercial fungal mock community, and piglet fecal samples. In addition, we calculated gene copy numbers for the 18S, ITS1, and ITS2 regions of each of the five isolates from the piglet fecal mock community to determine whether copy number affects abundance estimates. Finally, we determined the abundance of taxa from several iterations of our in-house fecal community to assess the effects of community composition on taxon abundance.

Results

Overall, no marker-database combination consistently outperformed the others. Internal transcribed space markers were slightly superior to 18S in the identification of species in tested communities, but Lichtheimia corymbifera, a common member of piglet gut communities, was not amplified by ITS1 and ITS2 primers. Thus, ITS based abundance estimates of taxa in piglet mock communities were skewed while 18S marker profiles were more accurate. Kazachstania slooffiae displayed the most stable copy numbers (83-85) while L. corymbifera displayed significant variability (90-144) across gene regions.

Discussion

This study underscores the importance of preliminary studies to assess primer combinations and database choice for the mycobiome sample of interest and raises questions regarding the validity of fungal abundance estimates.

Soil Chemistry and Soil History Significantly Structure Oomycete Communities in Brassicaceae Crop Rotations

Oomycetes are critically important in soil microbial communities, especially for agriculture, where they are responsible for major declines in yields. Unfortunately, oomycetes are vastly understudied compared to bacteria and fungi. As such, our understanding of how oomycete biodiversity and community structure vary through time in the soil remains poor. Soil history established by previous crops is one factor known to structure other soil microbes, but this has not been investigated for its influence on oomycetes. In this study, we established three different soil histories in field trials; the following year, these plots were planted with five different Brassicaceae crops. We hypothesized that the previously established soil histories would structure different oomycete communities, regardless of their current Brassicaceae crop host, in both the roots and rhizosphere. We used a nested internal transcribed spacer amplicon strategy incorporated with MiSeq metabarcoding, where the sequencing data was used to infer amplicon sequence variants of the oomycetes present in each sample. This allowed us to determine the impact of different soil histories on the structure and biodiversity of the oomycete root and rhizosphere communities from the five different Brassicaceae crops. We found that each soil history structured distinct oomycete rhizosphere communities, regardless of different Brassicaceae crop hosts, while soil chemistry structured the oomycete communities more during a dry year. Interestingly, soil history appeared specific to oomycetes but was less influential for bacterial communities previously identified from the same samples. These results advance our understanding of how different agricultural practices and inputs can alter edaphic factors to impact future oomycete communities. Examining how different soil histories endure and impact oomycete biodiversity will help clarify how these important communities may be assembled in agricultural soils. IMPORTANCE Oomycetes cause global plant diseases that result in substantial losses, yet they are highly understudied compared to other microbes, like fungi and bacteria. We wanted to investigate how past soil events, like changing crops in rotation, would impact subsequent oomycete communities. We planted different oilseed crops in three different soil histories and found that each soil history structured a distinct oomycete community regardless of which new oilseed crop was planted, e.g., oomycete communities from last year's lentil plots were still detected the following year regardless of which new oilseed crops we planted. This study demonstrated how different agricultural practices can impact future microbial communities differently. Our results also highlight the need for continued monitoring of oomycete biodiversity and quantification.

VTAM: A robust pipeline for validating metabarcoding data using controls

To obtain accurate estimates for biodiversity and ecological studies, metabarcoding studies should be carefully designed to minimize both false positive (FP) and false negative (FN) occurrences. Internal controls (mock samples and negative controls), replicates, and overlapping markers allow controlling metabarcoding errors but current metabarcoding software packages do not explicitly integrate these additional experimental data to optimize filtering. We have developed the metabarcoding analysis software VTAM, which uses explicitly these elements of the experimental design to find optimal parameter settings that minimize FP and FN occurrences. VTAM showed similar sensitivity, but a higher precision compared to two other pipelines using three datasets and two different markers (COI, 16S). The stringent filtering procedure implemented in VTAM aims to produce robust metabarcoding data to obtain accurate ecological estimates and represents an important step towards a non-arbitrary and standardized validation of metabarcoding data for conducting ecological studies. VTAM is implemented in Python and available from: https://github.com/aitgon/vtam. The VTAM benchmark code is available from: https://github.com/aitgon/vtam_benchmark.

Minimal impacts on the wheat microbiome when Trichoderma gamsii T6085 is applied as a biocontrol agent to manage fusarium head blight disease

Fusarium head blight (FHB) is a major fungal disease that causes severe yield and quality loss in wheat. Biological control can be integrated with other management strategies to control FHB. For this purpose, Trichoderma gamsii strain T6085 is a potential biocontrol agent to limit the infection of F. graminearum and F. culmorum in wheat. However, the possible impacts of T. gamsii T6085 on the broader microbiome associated with the wheat plant are not currently understood. Therefore, we identified bacteria and fungi associated with different wheat tissues, including assessment of their relative abundances and dynamics in response to the application of T6085 and over time, using amplicon sequencing. Residues of the prior year’s wheat crop and the current year’s wheat spikes were collected at multiple time points, and kernel samples were collected at harvest. DNA was extracted from the collected wheat tissues, and amplicon sequencing was performed to profile microbiomes using 16S v4 rRNA amplicons for bacteria and ITS2 amplicons for fungi. Quantitative PCR was performed to evaluate the absolute abundances of F. graminearum and T. gamsii in different wheat tissues. Disease progression was tracked visually during the growing season, revealing that FHB severity and incidence were significantly reduced when T6085 was applied to wheat spikes at anthesis. However, treatment with T6085 did not lessen the F. graminearum abundance in wheat spikes or kernels. There were substantial changes in F. graminearum abundance over time; in crop residue, pathogen abundance was highest at the initial time point and declined over time, while in wheat spikes, pathogen abundance increased significantly over time. The predominant bacterial taxa in wheat spikes and kernels were Pseudomonas, Enterobacter, and Pantoea, while Alternaria and Fusarium were the dominant fungal groups. Although the microbiome structure changed substantially over time, there were no community-scale rearrangements due to the T6085 treatment. The work suggests several other taxa that could be explored as potential biocontrol agents to integrate with T6085 treatment. However, the timing and the type of T6085 application need to be improved to give more advantages for T6085 to colonize and reduce the F. graminearum inoculum in the field.

Limited effect of thermal pruning on wild blueberry crop and its root-associated microbiota

Thermal pruning was a common pruning method in the past but has progressively been replaced by mechanical pruning for economic reasons. Both practices are known to enhance and maintain high yields; however, thermal pruning was documented to have an additional sanitation effect by reducing weeds and fungal diseases outbreaks. Nevertheless, there is no clear consensus on the optimal fire intensity required to observe these outcomes. Furthermore, fire is known to alter the soil microbiome as it impacts the soil organic layer and chemistry. Thus far, no study has investigated into the effect of thermal pruning intensity on the wild blueberry microbiome in agricultural settings. This project aimed to document the effects of four gradual thermal pruning intensities on the wild blueberry performance, weeds, diseases, as well as the rhizosphere fungal and bacterial communities. A field trial was conducted using a block design where agronomic variables were documented throughout the 2-year growing period. MiSeq amplicon sequencing was used to determine the diversity as well as the structure of the bacterial and fungal communities. Overall, yield, fruit ripeness, and several other agronomical variables were not significantly impacted by the burning treatments. Soil phosphorus was the only parameter with a significant albeit temporary change (1 month after thermal pruning) for soil chemistry. Our results also showed that bacterial and fungal communities did not significantly change between burning treatments. The fungal community was dominated by ericoid mycorrhizal fungi, while the bacterial community was mainly composed of Acidobacteriales, Isosphaerales, Frankiales, and Rhizobiales. However, burning at high intensities temporarily reduced Septoria leaf spot disease in the season following thermal pruning. According to our study, thermal pruning has a limited short-term influence on the wild blueberry ecosystem but may have a potential impact on pests (notably Septoria infection), which should be explored in future studies to determine the burning frequency necessary to control this disease.

Seedborne Cercospora beticola Can Initiate Cercospora Leaf Spot from Sugar Beet (Beta vulgaris) Fruit Tissue

Cercospora leaf spot (CLS) is a globally important disease of sugar beet (Beta vulgaris) caused by the fungus Cercospora beticola. Long-distance movement of C. beticola has been indirectly evidenced in recent population genetic studies, suggesting potential dispersal via seed. Commercial sugar beet "seed" consists of the reproductive fruit (true seed surrounded by maternal pericarp tissue) coated in artificial pellet material. In this study, we confirmed the presence of viable C. beticola in sugar beet fruit for 10 of 37 tested seed lots. All isolates harbored the G143A mutation associated with quinone outside inhibitor resistance, and 32 of 38 isolates had reduced demethylation inhibitor sensitivity (EC₅₀ > 1 µg/ml). Planting of commercial sugar beet seed demonstrated the ability of seedborne inoculum to initiate CLS in sugar beet. C. beticola DNA was detected in DNA isolated from xylem sap, suggesting the vascular system is used to systemically colonize the host. We established nuclear ribosomal internal transcribed spacer region amplicon sequencing using the MinION platform to detect fungi in sugar beet fruit. Fungal sequences from 19 different genera were identified from 11 different sugar beet seed lots, but Fusarium, Alternaria, and Cercospora were consistently the three most dominant taxa, comprising an average of 93% relative read abundance over 11 seed lots. We also present evidence that C. beticola resides in the pericarp of sugar beet fruit rather than the true seed. The presence of seedborne inoculum should be considered when implementing integrated disease management strategies for CLS of sugar beet in the future.

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.

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.

Analysis of Salivary Mycobiome in a Cohort of Oral Squamous Cell Carcinoma Patients From Sudan Identifies Higher Salivary Carriage of Malassezia as an Independent and Favorable Predictor of Overall Survival

Background

Microbial dysbiosis and microbiome-induced inflammation have emerged as important factors in oral squamous cell carcinoma (OSCC) tumorigenesis during the last two decades. However, the “rare biosphere” of the oral microbiome, including fungi, has been sparsely investigated. This study aimed to characterize the salivary mycobiome in a prospective Sudanese cohort of OSCC patients and to explore patterns of diversities associated with overall survival (OS).

Materials and Methods

Unstimulated saliva samples (n = 72) were collected from patients diagnosed with OSCC (n = 59) and from non-OSCC control volunteers (n = 13). DNA was extracted using a combined enzymatic–mechanical extraction protocol. The salivary mycobiome was assessed using a next-generation sequencing (NGS)-based methodology by amplifying the ITS2 region. The impact of the abundance of different fungal genera on the survival of OSCC patients was analyzed using Kaplan–Meier and Cox regression survival analyses (SPPS).

Results

Sixteen genera were identified exclusively in the saliva of OSCC patients. Candida, Malassezia, Saccharomyces, Aspergillus, and Cyberlindnera were the most relatively abundant fungal genera in both groups and showed higher abundance in OSCC patients. Kaplan–Meier survival analysis showed higher salivary carriage of the Candida genus significantly associated with poor OS of OSCC patients (Breslow test: p = 0.043). In contrast, the higher salivary carriage of Malassezia showed a significant association with favorable OS in OSCC patients (Breslow test: p = 0.039). The Cox proportional hazards multiple regression model was applied to adjust the salivary carriage of both Candida and Malassezia according to age (p = 0.029) and identified the genus Malassezia as an independent predictor of OS (hazard ratio = 0.383, 95% CI = 0.16–0.93, p = 0.03).

Conclusion

The fungal compositional patterns in saliva from OSCC patients were different from those of individuals without OSCC. The fungal genus Malassezia was identified as a putative prognostic biomarker and therapeutic target for OSCC.

Agricultural Management Affects the Active Rhizosphere Bacterial Community Composition and Nitrification

Cropping system diversity provides yield benefits that may result from shifts in the composition of root-associated bacterial and fungal communities, which either enhance nutrient availability or limit nutrient loss. We investigated whether temporal diversity of annual cropping systems (four versus two crops in rotation) influences the composition and metabolic activities of root-associated microbial communities in maize at a developmental stage when the peak rate of nitrogen uptake occurs. We monitored total (DNA-based) and potentially active (RNA-based) bacterial communities and total (DNA-based) fungal communities in the soil, rhizosphere, and endosphere. Cropping system diversity strongly influenced the composition of the soil microbial communities, which influenced the recruitment of the resident microbial communities and, in particular, the potentially active rhizosphere and endosphere bacterial communities. The diversified cropping system rhizosphere recruited a more diverse bacterial community (species richness), even though there was little difference in soil species richness between the two cropping systems. In contrast, fungal species richness was greater in the conventional rhizosphere, which was enriched in fungal pathogens; the diversified rhizosphere, however, was enriched in Glomeromycetes. While cropping system influenced endosphere community composition, greater correspondence between DNA- and RNA-based profiles suggests a higher representation of active bacterial populations. Cropping system diversity influenced the composition of ammonia oxidizers, which coincided with diminished potential nitrification activity and gross nitrate production rates, particularly in the rhizosphere. The results of our study suggest that diversified cropping systems shift the composition of the rhizosphere’s active bacterial and total fungal communities, resulting in tighter coupling between plants and microbial processes that influence nitrogen acquisition and retention.

IMPORTANCE Crops in simplified, low-diversity agroecosystems assimilate only a fraction of the inorganic nitrogen (N) fertilizer inputs. Much of this N fertilizer is lost to the environment as N oxides, which degrade water quality and contribute to climate change and loss of biodiversity. Ecologically inspired management may facilitate mutualistic interactions between plant roots and microbes to liberate nutrients when plants need them, while also decreasing nutrient loss and pathogen pressure. In this study, we investigate the effects of a conventional (2-year rotation, inorganic fertilization) and a diversified (4-year rotation, manure amendments) cropping system on the assembly of bacterial and fungal root-associated communities, at a maize developmental stage when nitrogen demand is beginning to increase. Our results indicate that agricultural management influences the recruitment of root-associated microbial communities and that diversified cropping systems have lower rates of nitrification (particularly in the rhizosphere), thereby reducing the potential for loss of nitrate from these systems.

Equine grass sickness (a multiple systems neuropathy) is associated with alterations in the gastrointestinal mycobiome

BACKGROUND

Equine grass sickness (EGS) is a multiple systems neuropathy of grazing horses of unknown aetiology. An apparently identical disease occurs in cats, dogs, rabbits, hares, sheep, alpacas and llamas. Many of the risk factors for EGS are consistent with it being a pasture mycotoxicosis. To identify potential causal fungi, the gastrointestinal mycobiota of EGS horses were evaluated using targeted amplicon sequencing, and compared with those of two control groups. Samples were collected post mortem from up to 5 sites in the gastrointestinal tracts of EGS horses (EGS group; 150 samples from 54 horses) and from control horses that were not grazing EGS pastures and that had been euthanased for reasons other than neurologic and gastrointestinal diseases (CTRL group; 67 samples from 31 horses). Faecal samples were also collected from healthy control horses that were co-grazing pastures with EGS horses at disease onset (CoG group; 48 samples from 48 horses).

RESULTS

Mycobiota at all 5 gastrointestinal sites comprised large numbers of fungi exhibiting diverse taxonomy, growth morphology, trophic mode and ecological guild. FUNGuild analysis parsed most phylotypes as ingested environmental microfungi, agaricoids and yeasts, with only 1% as gastrointestinal adapted animal endosymbionts. Mycobiota richness varied throughout the gastrointestinal tract and was greater in EGS horses. There were significant inter-group and inter-site differences in mycobiota structure. A large number of phylotypes were differentially abundant among groups. Key phylotypes (n = 56) associated with EGS were identified that had high abundance and high prevalence in EGS samples, significantly increased abundance in EGS samples, and were important determinants of the inter-group differences in mycobiota structure. Many key phylotypes were extremophiles and/or were predicted to produce cytotoxic and/or neurotoxic extrolites.

CONCLUSIONS

This is the first reported molecular characterisation of the gastrointestinal mycobiota of grazing horses. Key phylotypes associated with EGS were identified. Further work is required to determine whether neurotoxic extrolites from key phylotypes contribute to EGS aetiology or whether the association of key phylotypes and EGS is a consequence of disease or is non-causal.

Fecal sample collection methods and time of day impact microbiome composition and short chain fatty acid concentrations

Associations between the human gut microbiome and health outcomes continues to be of great interest, although fecal sample collection methods which impact microbiome studies are sometimes neglected. Here, we expand on previous work in sample optimization, to promote high quality microbiome data. To compare fecal sample collection methods, amplicons from the bacterial 16S rRNA gene (V4) and fungal (ITS2) region, as well as short chain fatty acid (SCFA) concentrations were determined in fecal material over three timepoints. We demonstrated that spot sampling of stool results in variable detection of some microbial members, and inconsistent levels of SCFA; therefore, sample homogenization prior to subsequent analysis or subsampling is recommended. We also identify a trend in microbial and metabolite composition that shifts over two consecutive stool collections less than 25 h apart. Lastly, we show significant differences in bacterial composition that result from collecting stool samples in OMNIgene·Gut tube (DNA Genotec) or Stool Nucleic Acid Collection and Preservation Tube (NORGEN) compared to immediate freezing. To assist with planning fecal sample collection and storage procedures for microbiome investigations with multiple analyses, we recommend participants to collect the first full bowel movement of the day and freeze the sample immediately after collection.

Root traits explain rhizosphere fungal community composition among temperate grassland plant species

While it is known that interactions between plants and soil fungi drive many essential ecosystem functions, considerable uncertainty exists over the drivers of fungal community composition in the rhizosphere. Here, we examined the roles of plant species identity, phylogeny and functional traits in shaping rhizosphere fungal communities and tested the robustness of these relationships to environmental change. We conducted a glasshouse experiment consisting of 21 temperate grassland species grown under three different environmental treatments and characterised the fungal communities within the rhizosphere of these plants. We found that plant species identity, plant phylogenetic relatedness and plant traits all affected rhizosphere fungal community composition. Trait relationships with fungal communities were primarily driven by interactions with arbuscular mycorrhizal fungi, and root traits were stronger predictors of fungal communities than leaf traits. These patterns were independent of the environmental treatments the plants were grown under. Our results showcase the key role of plant root traits, especially root diameter, root nitrogen and specific root length, in driving rhizosphere fungal community composition, demonstrating the potential for root traits to be used within predictive frameworks of plant-fungal relationships. Furthermore, we highlight how key limitations in our understanding of fungal function may obscure previously unmeasured plant-fungal interactions.

Metagenomics Approaches for the Detection and Surveillance of Emerging and Recurrent Plant Pathogens

Globalization has a dramatic effect on the trade and movement of seeds, fruits and vegetables, with a corresponding increase in economic losses caused by the introduction of transboundary plant pathogens. Current diagnostic techniques provide a useful and precise tool to enact surveillance protocols regarding specific organisms, but this approach is strictly targeted, while metabarcoding and shotgun metagenomics could be used to simultaneously detect all known pathogens and potentially new ones. This review aims to present the current status of high-throughput sequencing (HTS) diagnostics of fungal and bacterial plant pathogens, discuss the challenges that need to be addressed, and provide direction for the development of methods for the detection of a restricted number of related taxa (specific surveillance) or all of the microorganisms present in a sample (general surveillance). HTS techniques, particularly metabarcoding, could be useful for the surveillance of soilborne, seedborne and airborne pathogens, as well as for identifying new pathogens and determining the origin of outbreaks. Metabarcoding and shotgun metagenomics still suffer from low precision, but this issue can be limited by carefully choosing primers and bioinformatic algorithms. Advances in bioinformatics will greatly accelerate the use of metagenomics to address critical aspects related to the detection and surveillance of plant pathogens in plant material and foodstuffs.

Prokaryotic and Fungal Characterization of the Facilities Used to Assemble, Test, and Launch the OSIRIS-REx Spacecraft

To characterize the ATLO (Assembly, Test, and Launch Operations) environment of the OSIRIS-REx spacecraft, we analyzed 17 aluminum witness foils and two blanks for bacterial, archaeal, fungal, and arthropod DNA. Under NASA’s Planetary Protection guidelines, OSIRIS-REx is a Category II outbound, Category V unrestricted sample return mission. As a result, it has no bioburden restrictions. However, the mission does have strict organic contamination requirements to achieve its primary objective of returning pristine carbonaceous asteroid regolith to Earth. Its target, near-Earth asteroid (101955) Bennu, is likely to contain organic compounds that are biologically available. Therefore, it is useful to understand what organisms were present during ATLO as part of the larger contamination knowledge effort—even though it is unlikely that any of the organisms will survive the multi-year deep space journey. Even though these samples of opportunity were not collected or preserved for DNA analysis, we successfully amplified bacterial and archaeal DNA (16S rRNA gene) from 16 of the 17 witness foils containing as few as 7 ± 3 cells per sample. Fungal DNA (ITS1) was detected in 12 of the 17 witness foils. Despite observing arthropods in some of the ATLO facilities, arthropod DNA (COI gene) was not detected. We observed 1,009 bacterial and archaeal sOTUs (sub-operational taxonomic units, 100% unique) and 167 fungal sOTUs across all of our samples (25–84 sOTUs per sample). The most abundant bacterial sOTU belonged to the genus Bacillus. This sOTU was present in blanks and may represent contamination during sample handling or storage. The sample collected from inside the fairing just prior to launch contained several unique bacterial and fungal sOTUs that describe previously uncharacterized potential for contamination during the final phase of ATLO. Additionally, fungal richness (number of sOTUs) negatively correlates with the number of carbon-bearing particles detected on samples. The total number of fungal sequences positively correlates with total amino acid concentration. These results demonstrate that it is possible to use samples of opportunity to characterize the microbiology of low-biomass environments while also revealing the limitations imposed by sample collection and preservation methods not specifically designed with biology in mind.

Dadasnake, a Snakemake implementation of DADA2 to process amplicon sequencing data for microbial ecology

BACKGROUND

Amplicon sequencing of phylogenetic marker genes, e.g., 16S, 18S, or ITS ribosomal RNA sequences, is still the most commonly used method to determine the composition of microbial communities. Microbial ecologists often have expert knowledge on their biological question and data analysis in general, and most research institutes have computational infrastructures to use the bioinformatics command line tools and workflows for amplicon sequencing analysis, but requirements of bioinformatics skills often limit the efficient and up-to-date use of computational resources.

RESULTS

We present dadasnake, a user-friendly, 1-command Snakemake pipeline that wraps the preprocessing of sequencing reads and the delineation of exact sequence variants by using the favorably benchmarked and widely used DADA2 algorithm with a taxonomic classification and the post-processing of the resultant tables, including hand-off in standard formats. The suitability of the provided default configurations is demonstrated using mock community data from bacteria and archaea, as well as fungi.

CONCLUSIONS

By use of Snakemake, dadasnake makes efficient use of high-performance computing infrastructures. Easy user configuration guarantees flexibility of all steps, including the processing of data from multiple sequencing platforms. It is easy to install dadasnake via conda environments. dadasnake is available at https://github.com/a-h-b/dadasnake.

Cascabel: A Scalable and Versatile Amplicon Sequence Data Analysis Pipeline Delivering Reproducible and Documented Results

Marker gene sequencing of the rRNA operon (16S, 18S, ITS) or cytochrome c oxidase I (CO1) is a popular means to assess microbial communities of the environment, microbiomes associated with plants and animals, as well as communities of multicellular organisms via environmental DNA sequencing. Since this technique is based on sequencing a single gene, or even only parts of a single gene rather than the entire genome, the number of reads needed per sample to assess the microbial community structure is lower than that required for metagenome sequencing. This makes marker gene sequencing affordable to nearly any laboratory. Despite the relative ease and cost-efficiency of data generation, analyzing the resulting sequence data requires computational skills that may go beyond the standard repertoire of a current molecular biologist/ecologist. We have developed Cascabel, a scalable, flexible, and easy-to-use amplicon sequence data analysis pipeline, which uses Snakemake and a combination of existing and newly developed solutions for its computational steps. Cascabel takes the raw data as input and delivers a table of operational taxonomic units (OTUs) or Amplicon Sequence Variants (ASVs) in BIOM and text format and representative sequences. Cascabel is a highly versatile software that allows users to customize several steps of the pipeline, such as selecting from a set of OTU clustering methods or performing ASV analysis. In addition, we designed Cascabel to run in any linux/unix computing environment from desktop computers to computing servers making use of parallel processing if possible. The analyses and results are fully reproducible and documented in an HTML and optional pdf report. Cascabel is freely available at Github: https://github.com/AlejandroAb/CASCABEL.

Optimized metabarcoding with Pacific biosciences enables semi-quantitative analysis of fungal communities

Recent studies have questioned the use of high-throughput sequencing of the nuclear ribosomal internal transcribed spacer (ITS) region to derive a semi-quantitative representation of fungal community composition. However, comprehensive studies that quantify biases occurring during PCR and sequencing of ITS amplicons are still lacking. We used artificially assembled communities consisting of 10 ITS-like fragments of varying lengths and guanine-cytosine (GC) contents to evaluate and quantify biases during PCR and sequencing with Illumina MiSeq, PacBio RS II and PacBio Sequel I technologies. Fragment length variation was the main source of bias in observed community composition relative to the template, with longer fragments generally being under-represented for all sequencing platforms. This bias was three times higher for Illumina MiSeq than for PacBio RS II and Sequel I. All 10 fragments in the artificial community were recovered when sequenced with PacBio technologies, whereas the three longest fragments (> 447 bases) were lost when sequenced with Illumina MiSeq. Fragment length bias also increased linearly with increasing number of PCR cycles but could be mitigated by optimization of the PCR setup. No significant biases related to GC content were observed. Despite lower sequencing output, PacBio sequencing was better able to reflect the community composition of the template than Illumina MiSeq sequencing.

Environmental DNA assessment of airborne plant and fungal seasonal diversity

Environmental DNA (eDNA) metabarcoding and metagenomics analyses can improve taxonomic resolution in biodiversity studies. Only recently, these techniques have been applied in aerobiology, to target bacteria, fungi and plants in airborne samples. Here, we present a nine-month aerobiological study applying eDNA metabarcoding in which we analyzed simultaneously airborne diversity and variation of fungi and plants across five locations in North and Central Italy. We correlated species composition with the ecological characteristics of the sites and the seasons. The most abundant taxa among all sites and seasons were the fungal genera Cladosporium, Alternaria, and Epicoccum and the plant genera Brassica, Corylus, Cupressus and Linum, the latter being much more variable among sites. PERMANOVA and indicator species analyses showed that the plant diversity from air samples is significantly correlated with seasons, while that of fungi varied according to the interaction between seasons and sites. The results consolidate the performance of a new eDNA metabarcoding pipeline for the simultaneous amplification and analysis of airborne plant and fungal particles. They also highlight the promising complementarity of this approach with more traditional biomonitoring frameworks and routine reports of air quality provided by environmental agencies.

Accurate estimation of microbial sequence diversity with Distanced

MOTIVATION

Microbes are the most diverse organisms on the planet. Deep sequencing of ribosomal DNA (rDNA) suggests thousands of different microbes may be present in a single sample. However, errors in sequencing have made any estimate of within-sample (alpha) diversity uncertain.

RESULTS

We developed a tool to estimate alpha diversity of rDNA sequences from microbes (and other sequences). Our tool, Distanced, calculates how different (distant) sequences would be without sequencing errors. It does this using a Bayesian approach. Using this approach, Distanced accurately estimated alpha diversity of rDNA sequences from bacteria and fungi. It had lower root mean square prediction error (RMSPE) than when using no tool (leaving sequencing errors uncorrected). It was also accurate with non-microbial sequences (antibody mRNA). State-of-the-art tools (DADA2 and Deblur) were far less accurate. They often had higher RMSPE than when using no tool. Distanced thus represents an improvement over existing tools. Distanced will be useful to several disciplines, given microbial diversity affects everything from human health to ecosystem function.

AVAILABILITY AND IMPLEMENTATION

Distanced is freely available at https://github.com/thackmann/Distanced.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

An Overview of Bioinformatics Tools for DNA Meta-Barcoding Analysis of Microbial Communities of Bioaerosols: Digest for Microbiologists

High-throughput DNA sequencing (HTS) has changed our understanding of the microbial composition present in a wide range of environments. Applying HTS methods to air samples from different environments allows the identification and quantification (relative abundance) of the microorganisms present and gives a better understanding of human exposure to indoor and outdoor bioaerosols. To make full use of the avalanche of information made available by these sequences, repeated measurements must be taken, community composition described, error estimates made, correlations of microbiota with covariates (variables) must be examined, and increasingly sophisticated statistical tests must be conducted, all by using bioinformatics tools. Knowing which analysis to conduct and which tools to apply remains confusing for bioaerosol scientists, as a litany of tools and data resources are now available for characterizing microbial communities. The goal of this review paper is to offer a guided tour through the bioinformatics tools that are useful in studying the microbial ecology of bioaerosols. This work explains microbial ecology features like alpha and beta diversity, multivariate analyses, differential abundances, taxonomic analyses, visualization tools and statistical tests using bioinformatics tools for bioaerosol scientists new to the field. It illustrates and promotes the use of selected bioinformatic tools in the study of bioaerosols and serves as a good source for learning the “dos and don’ts” involved in conducting a precise microbial ecology study.

Enhanced Resistance to Fusarium graminearum in Transgenic Arabidopsis Plants Expressing a Modified Plant Thionin

The fungal pathogen Fusarium graminearum causes Fusarium head blight (FHB) on wheat, barley, and other grains. FHB results in yield reductions and contaminates grain with trichothecene mycotoxins, which threaten food safety and food security. Innovative mechanisms for controlling FHB are urgently needed. We have previously shown that transgenic tobacco and citrus plants expressing a modified thionin (Mthionin) exhibited enhanced resistance toward several bacterial pathogens. The aim of this study was to investigate whether overexpression of Mthionin could be similarly efficacious against F. graminearum, and whether transgenic expression of Mthionin impacts the plant microbiome. Transgenic Arabidopsis plants expressing Mthionin were generated and confirmed. When challenged with F. graminearum, Mthionin-expressing plants showed less disease and fungal biomass in both leaves and inflorescences compared with control plants. When infiltrated into leaves, macroconidia of F. graminearum germinated at lower rates and produced less hyphal growth in Arabidopsis leaves expressing Mthionin. Moreover, marker genes related to defense signaling pathways were expressed at significantly higher levels after F. graminearum infection in Mthionin transgenic Arabidopsis plants. However, Mthionin expression did not appreciably alter the overall microbiome associated with transgenic plants grown under controlled conditions; across leaves and roots of Mthionin-expressing and control transgenic plants, only a few bacterial and fungal taxa differed, and differences between Mthionin transformants were of similar magnitude compared with control plants. In sum, our data indicate that Mthionin is a promising candidate to produce transgenic crops for reducing FHB severity and ultimately mycotoxin contamination.

PEMA: a flexible Pipeline for Environmental DNA Metabarcoding Analysis of the 16S/18S ribosomal RNA, ITS, and COI marker genes

BACKGROUND

Environmental DNA and metabarcoding allow the identification of a mixture of species and launch a new era in bio- and eco-assessment. Many steps are required to obtain taxonomically assigned matrices from raw data. For most of these, a plethora of tools are available; each tool's execution parameters need to be tailored to reflect each experiment's idiosyncrasy. Adding to this complexity, the computation capacity of high-performance computing systems is frequently required for such analyses. To address the difficulties, bioinformatic pipelines need to combine state-of-the art technologies and algorithms with an easy to get-set-use framework, allowing researchers to tune each study. Software containerization technologies ease the sharing and running of software packages across operating systems; thus, they strongly facilitate pipeline development and usage. Likewise programming languages specialized for big data pipelines incorporate features like roll-back checkpoints and on-demand partial pipeline execution.

FINDINGS

PEMA is a containerized assembly of key metabarcoding analysis tools that requires low effort in setting up, running, and customizing to researchers' needs. Based on third-party tools, PEMA performs read pre-processing, (molecular) operational taxonomic unit clustering, amplicon sequence variant inference, and taxonomy assignment for 16S and 18S ribosomal RNA, as well as ITS and COI marker gene data. Owing to its simplified parameterization and checkpoint support, PEMA allows users to explore alternative algorithms for specific steps of the pipeline without the need of a complete re-execution. PEMA was evaluated against both mock communities and previously published datasets and achieved results of comparable quality.

CONCLUSIONS

A high-performance computing-based approach was used to develop PEMA; however, it can be used in personal computers as well. PEMA's time-efficient performance and good results will allow it to be used for accurate environmental DNA metabarcoding analysis, thus enhancing the applicability of next-generation biodiversity assessment studies.

Mycobiome diversity: high-throughput sequencing and identification of fungi

Fungi are major ecological players in both terrestrial and aquatic environments by cycling organic matter and channelling nutrients across trophic levels. High-throughput sequencing (HTS) studies of fungal communities are redrawing the map of the fungal kingdom by hinting at its enormous - and largely uncharted - taxonomic and functional diversity. However, HTS approaches come with a range of pitfalls and potential biases, cautioning against unwary application and interpretation of HTS technologies and results. In this Review, we provide an overview and practical recommendations for aspects of HTS studies ranging from sampling and laboratory practices to data processing and analysis. We also discuss upcoming trends and techniques in the field and summarize recent and noteworthy results from HTS studies targeting fungal communities and guilds. Our Review highlights the need for reproducibility and public data availability in the study of fungal communities. If the associated challenges and conceptual barriers are overcome, HTS offers immense possibilities in mycology and elsewhere.

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

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

Characterizing fungal communities in medicinal and edible Cassiae Semen using high-throughput sequencing

Cassiae Semen (CS) has been widely used as roasted tea and traditional Chinese medicine for decades. However, CS is easily contaminated by fungi and mycotoxins during pre-harvest and post-harvest process, thus posing a potential threat to consumer health. In this study, we used the Illumina MiSeq PE300 platform and targeted the internal transcribed spacer 2 sequences to survey the occurrence of fungi in raw and roasted CS samples. Results showed the fungal contamination in all 12 test samples. Ascomycota was the prevailing fungus at the phylum level, with the relative abundance of 66.50%-99.42%. At the genus level, Aspergillus, Cladosporium, and Penicillium were the most dominant genera, accounting for 0.66%-85.51%, 0.20%-29.11%, and 0.11%-32.92% of the fungal reads, respectively. A total of 68 species were identified, among which six potential toxigenic fungi belonging to Aspergillus, Penicillium, Candida, and Schizophyllum genera were detected. Moreover, differences in fungal communities were observed in raw and roasted CS samples. In conclusion, amplicon sequencing is feasible for analyzing fungal communities in CS samples, which provides a new approach to investigate the fungal contamination in edible-medicinal herb, thereby ensuring food safety and drug efficacy.

A rapid approach to profiling diverse fungal communities using the MinION™ nanopore sequencer

The Oxford Nanopore Technologies MinION™ sequencer holds the capability to generate long amplicon reads; however, only a small amount of information is available regarding methodological approaches and the ability to identify a broad diversity of fungal taxa. To assess capabilities, three fungal mock communities were sequenced, each of which had varying ratios of 16 taxa. The data were processed through our selected pipeline. The MinION recovered all mock community members, when mixed at equal ratios. When a taxon was represented at a lower ratio, it was not recovered or decreased in relative abundance. Despite high error rates, highly accurate consensus sequences can be derived. This methodological approach identified all mock community taxa, demonstrating the MinION can be used as a practical alternative to profile fungal communities.

Towards PacBio-based pan-eukaryote metabarcoding using full-length ITS sequences

Development of high-throughput sequencing techniques has greatly benefited our understanding about microbial ecology, yet the methods producing short reads suffer from species-level resolution and uncertainty of identification. Here, we optimize Pacific Biosciences-based metabarcoding protocols covering the internal transcribed spacer (ITS region) and partial small subunit of the rRNA gene for species-level identification of all eukaryotes, with a specific focus on Fungi (including Glomeromycota) and Stramenopila (particularly Oomycota). Based on tests on composite soil samples and mock communities, we propose best suitable degenerate primers, ITS9munngs + ITS4ngsUni for eukaryotes and selected groups therein and discuss the pros and cons of long read-based identification of eukaryotes.

Microbial Correlates of Fusarium Load and Deoxynivalenol Content in Individual Wheat Kernels

Characteristics or constituents of plant-associated microbiomes may assist in constraining disease development. To investigate this possibility for the wheat-Fusarium head blight pathosystem, we assessed seed weight, pathogen load, deoxynivalenol content, and microbiome profiles for individual wheat kernels collected over 2 years from a disease-conducive environment. We found that the microbiomes of individual, hulled wheat kernels consist of dozens to greater than a hundred bacterial taxa and up to several dozen fungal taxa, and that year-to-year variation in microbiome structure was large. Measures of microbial community diversity were negatively correlated with measures of disease severity, and had significant power to explain variation in pathogen load among seeds. Several operational taxonomic units belonging to the genus Sphingomonas demonstrated particularly strong negative relationships with pathogen load. This study illuminates the composition of microbiomes associated with wheat kernels under disease-conducive field conditions, and suggests relationships between microbiome characteristics and Fusarium head blight that warrant further study.

Issues and current standards of controls in microbiome research

Good scientific practice is important in all areas of science. In recent years this has gained more and more attention, especially considering the 'scientific reproducibility crisis'. While most researchers are aware of the issues with good scientific practice, not all of these issues are necessarily clear, and the details can be very complicated. For many years it has been accepted to perform and publish sequencing based microbiome studies without including proper controls. Although in recent years more scientists realize the necessity of implementing controls, this poses a problem due to the complexity of the field. Another concern is the inability to properly interpret the information gained from controls in microbiome studies. Here, we will discuss these issues and provide a comprehensive overview of problematic points regarding controls in microbiome research, and of the current standards in this area.

Analysis of the Fungal Community in Ziziphi Spinosae Semen through High-Throughput Sequencing

Ziziphi Spinosae Semen (ZSS) has been widely used in traditional Chinese medicine system for decades. Under proper humidity and temperature, ZSS is easily contaminated by fungi and mycotoxins during harvest, storage, and transport, thereby posing a considerable threat to consumer health. In this study, we first used the Illumina MiSeq PE250 platform and targeted the internal transcribed spacer 2 sequences to investigate the presence of fungi in moldy and normal ZSS samples collected from five producing areas in China. Results showed that all 14 samples tested were contaminated by fungi. Ascomycota was the dominant fungus at the phylum level, accounting for 64.36⁻99.74% of the fungal reads. At the genus level, Aspergillus, Candida, and Wallemia were the most predominant genera, with the relative abundances of 13.52⁻87.87%, 0.42⁻64.56%, and 0.06⁻34.31%, respectively. Meanwhile, 70 fungal taxa were identified at the species level. Among these taxa, three potential mycotoxin-producing fungi, namely, Aspergillusflavus, A. fumigatus, and Penicillium citrinum that account for 0.30⁻36.29%, 0.04⁻7.37%, and 0.01⁻0.80% of the fungal reads, respectively, were detected in all ZSS samples. Moreover, significant differences in fungal communities were observed in the moldy and normal ZSS samples. In conclusion, our results indicated that amplicon sequencing is feasible for the detection and analysis of the fungal community in the ZSS samples. This study used a new approach to survey the fungal contamination in herbal materials. This new approach can provide early warning for mycotoxin contamination in herbal materials, thereby ensuring drug efficacy and safety.

Protax-fungi: a web-based tool for probabilistic taxonomic placement of fungal internal transcribed spacer sequences

Incompleteness of reference sequence databases and unresolved taxonomic relationships complicates taxonomic placement of fungal sequences. We developed Protax-fungi, a general tool for taxonomic placement of fungal internal transcribed spacer (ITS) sequences, and implemented it into the PlutoF platform of the UNITE database for molecular identification of fungi. With empirical data on root- and wood-associated fungi, Protax-fungi reliably identified (with at least 90% identification probability) the majority of sequences to the order level but only around one-fifth of them to the species level, reflecting the current limited coverage of the databases. Protax-fungi outperformed the Sintax and Rdb classifiers in terms of increased accuracy and decreased calibration error when applied to data on mock communities representing species groups with poor sequence database coverage. We applied Protax-fungi to examine the internal consistencies of the Index Fungorum and UNITE databases. This revealed inconsistencies in the taxonomy database as well as mislabelling and sequence quality problems in the reference database. The according improvements were implemented in both databases. Protax-fungi provides a robust tool for performing statistically reliable identifications of fungi in spite of the incompleteness of extant reference sequence databases and unresolved taxonomic relationships.