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      Early assessment of fungal and oomycete pathogens in greenhouse irrigation water using Oxford nanopore amplicon sequencing

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          Abstract

          Water-borne plant pathogenic fungi and oomycetes are a major threat in greenhouse production systems. Early detection and quantification of these pathogens would enable us to ascertain both economic and biological thresholds required for a timely treatment, thus improving effective disease management. Here, we used Oxford nanopore MinION amplicon sequencing to analyze microbial communities in irrigation water collected from greenhouses used for growing tomato, cucumber and Aeschynanthus sp. Fungal and oomycete communities were characterized using primers that amplify the full internal transcribed spacer (ITS) region. To assess the sensitivity of the MinION sequencing, we spiked serially diluted mock DNA into the DNA isolated from greenhouse water samples prior to library preparation. Relative abundances of fungal and oomycete reads were distinct in the greenhouse irrigation water samples and in water samples from setups with tomato that was inoculated with Fusarium oxysporum. Sequence reads derived from fungal and oomycete mock communities were proportionate in the respective serial dilution samples, thus confirming the suitability of MinION amplicon sequencing for environmental monitoring. By using spike-ins as standards to test the reliability of quantification using the MinION, we found that the detection of spike-ins was highly affected by the background quantities of fungal or oomycete DNA in the sample. We observed that spike-ins having shorter length (538bp) produced reads across most of our dilutions compared to the longer spikes (>790bp). Moreover, the sequence reads were uneven with respect to dilution series and were least retrievable in the background samples having the highest DNA concentration, suggesting a narrow dynamic range of performance. We suggest continuous benchmarking of the MinION sequencing to improve quantitative metabarcoding efforts for rapid plant disease diagnostic and monitoring in the future.

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          Most cited references52

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          phyloseq: An R Package for Reproducible Interactive Analysis and Graphics of Microbiome Census Data

          Background The analysis of microbial communities through DNA sequencing brings many challenges: the integration of different types of data with methods from ecology, genetics, phylogenetics, multivariate statistics, visualization and testing. With the increased breadth of experimental designs now being pursued, project-specific statistical analyses are often needed, and these analyses are often difficult (or impossible) for peer researchers to independently reproduce. The vast majority of the requisite tools for performing these analyses reproducibly are already implemented in R and its extensions (packages), but with limited support for high throughput microbiome census data. Results Here we describe a software project, phyloseq, dedicated to the object-oriented representation and analysis of microbiome census data in R. It supports importing data from a variety of common formats, as well as many analysis techniques. These include calibration, filtering, subsetting, agglomeration, multi-table comparisons, diversity analysis, parallelized Fast UniFrac, ordination methods, and production of publication-quality graphics; all in a manner that is easy to document, share, and modify. We show how to apply functions from other R packages to phyloseq-represented data, illustrating the availability of a large number of open source analysis techniques. We discuss the use of phyloseq with tools for reproducible research, a practice common in other fields but still rare in the analysis of highly parallel microbiome census data. We have made available all of the materials necessary to completely reproduce the analysis and figures included in this article, an example of best practices for reproducible research. Conclusions The phyloseq project for R is a new open-source software package, freely available on the web from both GitHub and Bioconductor.
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            Minimap2: pairwise alignment for nucleotide sequences

            Heng Li (2018)
            Recent advances in sequencing technologies promise ultra-long reads of ∼100 kb in average, full-length mRNA or cDNA reads in high throughput and genomic contigs over 100 Mb in length. Existing alignment programs are unable or inefficient to process such data at scale, which presses for the development of new alignment algorithms.
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              Development of a dual-index sequencing strategy and curation pipeline for analyzing amplicon sequence data on the MiSeq Illumina sequencing platform.

              Rapid advances in sequencing technology have changed the experimental landscape of microbial ecology. In the last 10 years, the field has moved from sequencing hundreds of 16S rRNA gene fragments per study using clone libraries to the sequencing of millions of fragments per study using next-generation sequencing technologies from 454 and Illumina. As these technologies advance, it is critical to assess the strengths, weaknesses, and overall suitability of these platforms for the interrogation of microbial communities. Here, we present an improved method for sequencing variable regions within the 16S rRNA gene using Illumina's MiSeq platform, which is currently capable of producing paired 250-nucleotide reads. We evaluated three overlapping regions of the 16S rRNA gene that vary in length (i.e., V34, V4, and V45) by resequencing a mock community and natural samples from human feces, mouse feces, and soil. By titrating the concentration of 16S rRNA gene amplicons applied to the flow cell and using a quality score-based approach to correct discrepancies between reads used to construct contigs, we were able to reduce error rates by as much as two orders of magnitude. Finally, we reprocessed samples from a previous study to demonstrate that large numbers of samples could be multiplexed and sequenced in parallel with shotgun metagenomes. These analyses demonstrate that our approach can provide data that are at least as good as that generated by the 454 platform while providing considerably higher sequencing coverage for a fraction of the cost.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: SoftwareRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: ResourcesRole: SoftwareRole: ValidationRole: VisualizationRole: Writing – review & editing
                Role: ConceptualizationRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: Project administrationRole: ResourcesRole: SoftwareRole: Supervision
                Role: ConceptualizationRole: Data curationRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: Project administrationRole: ResourcesRole: SoftwareRole: Supervision
                Role: ConceptualizationRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: Project administrationRole: ResourcesRole: SupervisionRole: ValidationRole: Writing – review & editing
                Role: ConceptualizationRole: Funding acquisitionRole: InvestigationRole: Project administrationRole: SupervisionRole: ValidationRole: VisualizationRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS One
                plos
                PLOS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                15 March 2024
                2024
                : 19
                : 3
                : e0300381
                Affiliations
                [1 ] Department of Agroecology, Faculty of Technical Sciences, Aarhus University, Slagelse, Denmark
                [2 ] Teknologisk Institut Gregersensvej, Taastrup, Denmark
                Franklin & Marshall College, UNITED STATES
                Author notes

                Competing Interests: The authors declare no conflict of interest.

                Author information
                https://orcid.org/0000-0002-3297-2459
                https://orcid.org/0000-0002-4470-542X
                https://orcid.org/0000-0002-0407-2488
                https://orcid.org/0000-0002-0054-4855
                Article
                PONE-D-23-39732
                10.1371/journal.pone.0300381
                10942031
                38489283
                b3da4270-f1ed-420d-b36f-133622cfa05d
                © 2024 Kudjordjie et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 28 November 2023
                : 26 February 2024
                Page count
                Figures: 5, Tables: 0, Pages: 15
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/501100022592, Grønt Udviklings- og Demonstrations Program;
                Award ID: 32002
                Award Recipient :
                The project was funded by the Grønt Udviklings-og DemonstrationsProgram (GUDP) project no. 32002. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology and Life Sciences
                Organisms
                Eukaryota
                Fungi
                Oomycetes
                Biology and Life Sciences
                Microbiology
                Oomycetes
                Biology and Life Sciences
                Agriculture
                Agricultural Methods
                Agricultural Irrigation
                Biology and Life Sciences
                Plant Science
                Plant Pathology
                Plant Pathogens
                Plant Fungal Pathogens
                Biology and Life Sciences
                Microbiology
                Medical Microbiology
                Microbial Pathogens
                Fungal Pathogens
                Medicine and Health Sciences
                Pathology and Laboratory Medicine
                Pathogens
                Microbial Pathogens
                Fungal Pathogens
                Biology and Life Sciences
                Mycology
                Fungal Pathogens
                Biology and life sciences
                Molecular biology
                Molecular biology techniques
                Sequencing techniques
                DNA sequencing
                Research and analysis methods
                Molecular biology techniques
                Sequencing techniques
                DNA sequencing
                Biology and Life Sciences
                Organisms
                Eukaryota
                Plants
                Fruits
                Tomatoes
                Biology and Life Sciences
                Organisms
                Eukaryota
                Fungi
                Oomycetes
                Phytophthora
                Biology and Life Sciences
                Microbiology
                Oomycetes
                Phytophthora
                Biology and Life Sciences
                Molecular Biology
                Molecular Biology Techniques
                Artificial Gene Amplification and Extension
                Polymerase Chain Reaction
                Research and Analysis Methods
                Molecular Biology Techniques
                Artificial Gene Amplification and Extension
                Polymerase Chain Reaction
                Custom metadata
                Sequence data are available in the Sequence Read Archive (SRA) database at NCBI under BioProject ID PRJNA1063628 with the accession numbers SUB14149061, SUB14149186, SUB14152390, SUB14152424, SUB14144130 and SUB14152446.

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