Biomonitoring of Fungal and Oomycete Plant Pathogens by Using Metabarcoding.
Émilie D TremblayGuillaume J BilodeauPublished in: Methods in molecular biology (Clifton, N.J.) (2022)
Fungal and oomycete plant pathogens are responsible for the devastation of various ecosystems such as forest and crop species worldwide. In an effort to protect such natural resources for food, lumber, etc., early detection of non-indigenous phytopathogenic fungi in new areas is a key approach in managing threats at their source of introduction. A workflow was developed using high-throughput sequencing (HTS), more specifically metabarcoding, a method for rapid and higher throughput species screening near high-risk areas, and over larger geographical spaces. Biomonitoring of fungal and oomycete entities of plant pathogens (e.g., airborne spores) regained from environmental samples and their processing by metabarcoding is thoroughly described here. The amplicon-based approach goes from DNA and sequencing library preparation using custom-designed polymerase chain reaction (PCR) fusion primers that target the internal transcribed spacer 1 (ITS1) from fungi and oomycetes and extends to multiplex HTS with the Ion Torrent platform. In addition, a brief and simplified overview of the bioinformatics analysis pipeline and other available tools required to process amplicon sequences is also included. The raw data obtained and processed enable users to select a bioinformatics pipeline in order to directly perform biodiversity, presence/absence, geographical distribution, and abundance analyses through the tools suggested, which allows for accelerated identification of phytopathogens of interest.
Keyphrases
- bioinformatics analysis
- cell wall
- climate change
- gram negative
- high throughput sequencing
- antimicrobial resistance
- human health
- high throughput
- electronic health record
- genetic diversity
- multidrug resistant
- single cell
- particulate matter
- single molecule
- big data
- real time pcr
- antibiotic resistance genes
- cell free
- molecularly imprinted
- data analysis
- wastewater treatment