ASGARD+: A New Modular Platform for Bacterial Antibiotic-Resistant Analysis.

ASGARD+ (Accelerated Sequential Genome-analysis and Antibiotic Resistance Detection) is a command-line platform for automatic identification of antibiotic-resistance genes in bacterial genomes, providing an easy-to-use interface to process big batches of sequence files from whole genome sequencing, with minimal configuration. It also provides a CPU-optimization algorithm that reduces the processing time. This tool consists of two main protocols. The first one, ASGARD, is based on the identification and annotation of antimicrobial resistance elements directly from the short reads using different public databases. SAGA, enables the alignment, indexing, and mapping of whole-genome samples against a reference genome for the detection and call of variants, as well as the visualization of the results through the construction of a tree of SNPs. The application of both protocols is performed using just one short command and one configuration file based on JSON syntax, which modulates each pipeline step, allowing the user to do as many interventions as needed on the different software tools that are adapted to the pipeline. The modular ASGARD+ allows researchers with little experience in bioinformatic analysis and command-line use to quickly explore bacterial genomes in depth, optimizing analysis times and obtaining accurate results. © 2023 Wiley Periodicals LLC. Basic Protocol 1: ASGARD+ installation Basic Protocol 2: Configuration files general setup Basic Protocol 3: ASGARD execution Support Protocol: Results visualization with Phandango Basic Protocol 4: SAGA execution Alternative Protocol 1: Container installation Alternative Protocol 2: Run ASGARD and SAGA in container.

Phylogeographic and Phylogenomic Structure of the Quarantine Plant Pathogen Colletotrichum liriopes, Including New Reports in the United States.

Global agricultural trade has accelerated the emergence and re-emergence of new plant pathogens. In the United States, the fungal pathogen Colletotrichum liriopes is still considered a foreign quarantine pathogen that affects ornamental plants (i.e., Liriope spp.). Even though this species has been reported in East Asia on various asparagaceous hosts, its first and only report in the United States was in 2018. However, that study used only ITS nrDNA for identification, and no available culture or voucher specimen was maintained. The main objective of the present study was to determine the geographic and host distribution of specimens identified as C. liriopes. To accomplish this, new and existing isolates, sequences, and genomes obtained from various hosts and geographic locations (i.e., China, Colombia, Mexico, and the United States) were compared with the ex-type of C. liriopes. Multilocus phylogenetic (ITS, Tub2, GAPDH, CHS-1, and HIS3), phylogenomic, and splits tree analyses revealed that all the studied isolates/sequences form a well-supported clade with little intraspecific variation. Morphological characterizations support these findings. The minimum spanning network, low nucleotide diversity, and negative Tajima's D from both multilocus and genomic data suggest that there was a recent movement/invasion of a few East Asian genotypes to other countries where the ornamental plants are produced (e.g., South America) and subsequently to the importing countries, such as the United States. The study reveals that the geographic and host distribution of C. liriopes sensu stricto is expanded to the United States (i.e., at least Maryland, Mississippi, and Tennessee) and on various hosts in addition to Asparagaceae and Orchidaceae. The present study produces fundamental knowledge that can be used in efforts to reduce costs or losses from agricultural trade and to expand our understanding of pathogen movement.

Step-by-Step Pipeline for the Ecological Analysis of Endophytic Fungi using ITS nrDNA Data.

The nuclear ribosomal DNA internal transcribed spacer (ITS) is accepted as the genetic marker or barcode of choice for the identification of fungal samples. Here, we present a protocol to analyze fungal ITS data, from quality preprocessing of raw sequences to identification of operational taxonomic units (OTUs), taxonomic classification, and assignment of functional traits. The pipeline relies on well-established and manually curated data collections, namely the UNITE database and the FUNGuild script. As an example, real ITS data from culturable endophytic fungi were analyzed, providing detailed descriptions for every step, parameter, and downstream analysis, and finishing with a phylogenetic analysis of the sequences and assigned ecological roles. This article constitutes a comprehensive guide for researchers that have little familiarity with bioinformatic analysis of essential steps required in further ecological studies of fungal communities. © 2020 by John Wiley & Sons, Inc. Basic Protocol 1: Raw sequencing data processing Support Protocol: Building a BLAST database Basic Protocol 2: Obtaining information from databases Basic Protocol 3: Phylogenetic analysis.