A workflow for accurate metabarcoding using nanopore MinION sequencing

An ecological network approach for detecting and validating influential organisms for rice growth

How to achieve sustainable food production while reducing environmental impacts is a major concern in agricultural science, and advanced breeding techniques are promising for achieving such goals. However, rice is usually grown under field conditions and influenced by surrounding ecological community members. How ecological communities influence the rice performance in the field has been underexplored despite the potential of ecological communities to establish an environment-friendly agricultural system. In the present study, we demonstrate an ecological-network-based approach to detect potentially influential, previously overlooked organisms for rice (Oryza sativa). First, we established small experimental rice plots, and measured rice growth and monitored ecological community dynamics intensively and extensively using quantitative environmental DNA metabarcoding in 2017 in Japan. We detected more than 1000 species (including microbes and macrobes such as insects) in the rice plots, and nonlinear time series analysis detected 52 potentially influential organisms with lower-level taxonomic information. The results of the time series analysis were validated under field conditions in 2019 by field manipulation experiments. In 2019, we focused on two species, Globisporangium nunn and Chironomus kiiensis, whose abundance was manipulated in artificial rice plots. The responses of rice, namely, the growth rate and gene expression patterns, were measured before and after the manipulation. We confirmed that, especially in the G. nunn-added treatment, rice growth rate and gene expression pattern were changed. In the present study, we demonstrated that intensive monitoring of an agricultural system and the application of nonlinear time series analysis were helpful to identify influential organisms under field conditions. Although the effects of the manipulations were relatively small, the research framework presented here has future potential to harness the ecological complexity and utilize it in agriculture. Our proof-of-concept study would be an important basis for the further development of field-basis system management.

Nanopore Sequencing with GraphMap for Comprehensive Pathogen Detection in Potato Field Soil

Early detection of causal pathogens is important to prevent crop loss from diseases. However, some diseases, such as soilborne diseases, are difficult to diagnose due to the absence of visible or characteristic symptoms. In the present study, the use of the Oxford Nanopore MinION sequencer as a molecular diagnostic tool was assessed due to its long-read sequencing capabilities and portability. Nucleotide samples (DNA or RNA) from potato field soils were sequenced and analyzed using a locally curated pathogen database, followed by identification via sequence mapping. We performed computational speed tests of three commonly used mapping/annotation tools (BLAST, BWA-BLAST, and BWA-GraphMap) and found BWA-GraphMap to be the fastest tool for local searching against our curated pathogen database. The data collected demonstrate the high potential of Nanopore sequencing as a minimally biased diagnostic tool for comprehensive pathogen detection in soil from potato fields. Our GraphMap-based MinION sequencing method could be useful as a predictive approach for disease management by identifying pathogens present in field soil prior to planting. Although this method still needs further experimentation with a larger sample size for practical use, the data analysis pipeline presented can be applied to other cropping systems and diagnostics for detecting multiple pathogens.

Haplotype-level metabarcoding of freshwater macroinvertebrate species: A prospective tool for population genetic analysis

Metabarcoding is a molecular-based tool capable of large quantity high-throughput species identification from bulk samples that is a faster and more cost-effective alternative to conventional DNA-sequencing approaches. Still, further exploration and assessment of the laboratory and bioinformatics strategies are required to unlock the potential of metabarcoding-based inference of haplotype information. In this study, we assessed the inference of freshwater macroinvertebrate haplotypes from metabarcoding data in a mock sample. We also examined the influence of DNA template concentration and PCR cycle on detecting true and spurious haplotypes. We tested this strategy on a mock sample containing twenty individuals from four species with known haplotypes based on the 658-bp Folmer region of the mitochondrial cytochrome c oxidase gene. We recovered fourteen zero-radius operational taxonomic units (zOTUs) of 421-bp length, with twelve zOTUs having a 100% match with the Sanger haplotype sequences. High-quality reads relatively increased with increasing PCR cycles, and the relative abundance of each zOTU was consistent for each cycle. This suggests that increasing the PCR cycles from 24 to 64 did not affect the relative abundance of each zOTU. As metabarcoding becomes more established and laboratory protocols and bioinformatic pipelines are continuously being developed, our study demonstrated the method's ability to infer intraspecific variability while highlighting the challenges that must be addressed before its eventual application for population genetic studies.

Environmental DNA and visual encounter surveys for amphibian biomonitoring in aquatic environments of the Ecuadorian Amazon

Background

The development of anthropogenic activities has generated a decline in aquatic fauna populations, and amphibians have been the most affected. The decline of batrachofauna is concerning, as 41% of all species worldwide are endangered. For this reason, rapid, efficient, and non-invasive biodiversity monitoring techniques are needed, and environmental DNA (eDNA) is one such tool that has been sparsely applied in Ecuador. This technique has allowed scientists generates information on species diversity and amphibian community composition from a water sample. This study applied eDNA-based biomonitoring analyses and visual encounter surveys (VES) as inventory techniques to identify the diversity of aquatic amphibians in the Tena River micro-basin (TRMB).

Methods

The experimental design was divided into three components: (1) fieldwork: all amphibians were recorded by the VES technique and water samples were collected; (2) laboratory work: DNA isolation from amphibian tissue samples and eDNA-containing filters, amplification, electrophoresis, and sequencing were performed; (3) Data analysis: a local DNA reference database was constructed, and eDNA sequence data were processed for classification, taxonomic assignment, and ecological interpretation.

Results

Using both eDNA and VES, we detected 33 amphibian species (13 with eDNA only, five with VES only, and 15 with both methods). These species belonged to six amphibian families: Hylidae being the richest with 14 species (three eDNA, one VES, and 10 with both methods), followed by Strabomantidae with nine species (six eDNA, one VES, and two with both methods). All families were detected with both methods, except for the Aromobatidae, having one single record (Allobates aff. insperatus) by VES. Individually, eDNA detected 28 species and had a detection probability (DP) of 0.42 CI [0.40-0.45], while VES recorded 20 species with a DP of 0.17 CI [0.14-0.20]. Similarly, using VES, Cochranella resplendens was detected for the first time in TRMB, while with eDNA, four mountain frogs Pristimantis acerus, Pristimantis eriphus, Pristimantis mallii, and Pristimantis sp. (INABIO 15591) previously recorded at 1,518 m.a.s.l. at altitudes below 600 m.a.s.l. were detected.

Conclusions

Results obtained in this study showed that eDNA-based detection had a greater capacity to detect amphibians in aquatic environments compared to VES. The combination of VES and eDNA improves the sensitivity of species detection and provides more reliable, robust, and detailed information. The latter is essential for developing conservation strategies in the Ecuadorian Amazon.

Tracking the Source of Human Q Fever from a Southern French Village: Sentinel Animals and Environmental Reservoir

Coxiella burnetii, also known as the causal agent of Q fever, is a zoonotic pathogen infecting humans and several animal species. Here, we investigated the epidemiological context of C. burnetii from an area in the Hérault department in southern France, using the One Health paradigm. In total, 13 human cases of Q fever were diagnosed over the last three years in an area comprising four villages. Serological and molecular investigations conducted on the representative animal population, as well as wind data, indicated that some of the recent cases are likely to have originated from a sheepfold, which revealed bacterial contamination and a seroprevalence of 47.6%. However, the clear-cut origin of human cases cannot be ruled out in the absence of molecular data from the patients. Multi-spacer typing based on dual barcoding nanopore sequencing highlighted the occurrence of a new genotype of C. burnetii. In addition, the environmental contamination appeared to be widespread across a perimeter of 6 km due to local wind activity, according to the seroprevalence detected in dogs (12.6%) and horses (8.49%) in the surrounding populations. These findings were helpful in describing the extent of the exposed area and thus supporting the use of dogs and horses as valuable sentinel indicators for monitoring Q fever. The present data clearly highlighted that the epidemiological surveillance of Q fever should be reinforced and improved.

A primer on pollen assignment by nanopore-based DNA sequencing

The possibility to identify plants based on the taxonomic information coming from their pollen grains offers many applications within various biological disciplines. In the past and depending on the application or research in question, pollen origin was analyzed by microscopy, usually preceded by chemical treatment methods. This procedure for identification of pollen grains is both time-consuming and requires expert knowledge of morphological features. Additionally, these microscopically recognizable features usually have a low resolution at species-level. Since a few decades, DNA has been used for the identification of pollen taxa, as sequencing technologies evolved both in their handling and affordability. We discuss advantages and challenges of pollen DNA analyses compared to traditional methods. With readers with little experience in this field in mind, we present a hands-on primer for genetic pollen analysis by nanopore sequencing. As our lab mainly works with pollen collected within agroecological research projects, we focus on pollen collected by pollinating insects. We briefly consider sample collection, storage and processing in the laboratory as well as bioinformatic aspects. Currently, pollen metabarcoding is mostly conducted with next-generation sequencing methods that generate short sequence reads (<1 kb). Increasingly, however, pollen DNA analysis is carried out using the long-read generating (several kb), low-budget and mobile MinION nanopore sequencing platform by Oxford Nanopore Technologies. Therefore, we are focusing on aspects for palynology with the MinION DNA sequencing device.

The predator problem and PCR primers in molecular dietary analysis: swamped or silenced; depth or breadth?

Dietary metabarcoding has vastly improved our ability to analyse the diets of animals, but it is hampered by a plethora of technical limitations including potentially reduced data output due to the disproportionate amplification of the DNA of the focal predator, here termed 'the predator problem'. We review the various methods commonly used to overcome this problem, from deeper sequencing to exclusion of predator DNA during PCR, and how they may interfere with increasingly common multi-predator-taxon studies. We suggest that multi-primer approaches with an emphasis on achieving both depth and breadth of prey detections may overcome the issue to some extent, although multi-taxon studies require further consideration, as highlighted by an empirical example. We also review several alternative methods for reducing the prevalence of predator DNA that are conceptually promising but require additional empirical examination. The predator problem is a key constraint on molecular dietary analyses but, through this synthesis, we hope to guide researchers in overcoming this in an effective and pragmatic way.

New-Generation Sequencing Technology in Diagnosis of Fungal Plant Pathogens: A Dream Comes True?

The fast and continued progress of high-throughput sequencing (HTS) and the drastic reduction of its costs have boosted new and unpredictable developments in the field of plant pathology. The cost of whole-genome sequencing, which, until few years ago, was prohibitive for many projects, is now so affordable that a new branch, phylogenomics, is being developed. Fungal taxonomy is being deeply influenced by genome comparison, too. It is now easier to discover new genes as potential targets for an accurate diagnosis of new or emerging pathogens, notably those of quarantine concern. Similarly, with the development of metabarcoding and metagenomics techniques, it is now possible to unravel complex diseases or answer crucial questions, such as "What's in my soil?", to a good approximation, including fungi, bacteria, nematodes, etc. The new technologies allow to redraw the approach for disease control strategies considering the pathogens within their environment and deciphering the complex interactions between microorganisms and the cultivated crops. This kind of analysis usually generates big data that need sophisticated bioinformatic tools (machine learning, artificial intelligence) for their management. Herein, examples of the use of new technologies for research in fungal diversity and diagnosis of some fungal pathogens are reported.

Application of Omics Tools in Designing and Monitoring Marine Protected Areas For a Sustainable Blue Economy

A key component of the global blue economy strategy is the sustainable extraction of marine resources and conservation of marine environments through networks of marine protected areas (MPAs). Connectivity and representativity are essential factors that underlie successful implementation of MPA networks, which can safeguard biological diversity and ecosystem function, and ultimately support the blue economy strategy by balancing ocean use with conservation. New “big data” omics approaches, including genomics and transcriptomics, are becoming essential tools for the development and maintenance of MPA networks. Current molecular omics techniques, including population-scale genome sequencing, have direct applications for assessing population connectivity and for evaluating how genetic variation is represented within and among MPAs. Effective baseline characterization and long-term, scalable, and comprehensive monitoring are essential for successful MPA management, and omics approaches hold great promise to characterize the full range of marine life, spanning the microbiome to megafauna across a range of environmental conditions (shallow sea to the deep ocean). Omics tools, such as eDNA metabarcoding can provide a cost-effective basis for biodiversity monitoring in large and remote conservation areas. Here we provide an overview of current omics applications for conservation planning and monitoring, with a focus on metabarcoding, metagenomics, and population genomics. Emerging approaches, including whole-genome sequencing, characterization of genomic architecture, epigenomics, and genomic vulnerability to climate change are also reviewed. We demonstrate that the operationalization of omics tools can enhance the design, monitoring, and management of MPAs and thus will play an important role in a modern and comprehensive blue economy strategy.

Real-Time On-Site Diagnosis of Quarantine Pathogens in Plant Tissues by Nanopore-Based Sequencing

Rapid and sensitive assays for the identification of plant pathogens are necessary for the effective management of crop diseases. The main limitation of current diagnostic testing is the inability to combine broad and sensitive pathogen detection with the identification of key strains, pathovars, and subspecies. Such discrimination is necessary for quarantine pathogens, whose management is strictly dependent on genotype identification. To address these needs, we have established and evaluated a novel all-in-one diagnostic assay based on nanopore sequencing for the detection and simultaneous characterization of quarantine pathogens, using Xylella fastidiosa as a case study. The assay proved to be at least as sensitive as standard diagnostic tests and the quantitative results agreed closely with qPCR-based analysis. The same sequencing results also allowed discrimination between subspecies when present either individually or in combination. Pathogen detection and typing were achieved within 13 min of sequencing owing to the use of an internal control that allowed to stop sequencing when sufficient data had accumulated. These advantages, combined with the use of portable equipment, will facilitate the development of next-generation diagnostic assays for the efficient monitoring of other plant pathogens.

Current and Future Pathotyping Platforms for Plasmodiophora brassicae in Canada

Clubroot, caused by Plasmodiophora brassicae, is one of the most detrimental threats to crucifers worldwide and has emerged as an important disease of canola (Brassica napus) in Canada. At present, pathotypes are distinguished phenotypically by their virulence patterns on host differential sets, including the systems of Williams, Somé et al., the European Clubroot Differential set, and most recently the Canadian Clubroot Differential set and the Sinitic Clubroot Differential set. Although these are frequently used because of their simplicity of application, they are time-consuming, labor-intensive, and can lack sensitivity. Early, preventative pathotype detection is imperative to maximize productivity and promote sustainable crop production. The decreased turnaround time and increased sensitivity and specificity of genotypic pathotyping will be valuable for the development of integrated clubroot management plans, and interest in molecular techniques to complement phenotypic methods is increasing. This review provides a synopsis of current and future molecular pathotyping platforms for P. brassicae and aims to provide information on techniques that may be most suitable for the development of rapid, reliable, and cost-effective pathotyping assays.