SEAR: Search Engine for Antimicrobial Resistance

SEAR detects and analyzes horizontally acquired antibiotic resistance genes (ARGs) from raw next-generation sequencing datasets, reconstructing gene sequences and estimating their abundance.

Key Features:

• Raw sequencing detection: Identifies horizontally acquired antibiotic resistance genes (ARGs) directly from raw next-generation sequencing datasets.
• Abundance estimation and sequence reconstruction: Estimates ARG abundance and reconstructs full-length gene sequences from sequencing reads.
• Clustering and read mapping annotation: Uses clustering and read mapping to annotate full-length ARGs relative to a user-defined database.
• Local alignment to online databases: Performs local alignments of annotated genes against multiple online databases to provide additional annotation and links.
• Support for metagenomic and isolate data: Applicable to environmental metagenomes, human faecal microbiome samples, and clinical isolates such as Shigella sonnei.

Scientific Applications:

• Environmental metagenomics: Determination of ARG diversity and abundance in environmental metagenomic datasets.
• Microbiome research: Profiling and quantification of ARGs in human faecal microbiome samples.
• Clinical isolate analysis and surveillance: Characterization of ARGs in clinical isolates (for example, Shigella sonnei) to support surveillance and investigation of antimicrobial resistance.

Methodology:

From raw next-generation sequencing datasets, SEAR performs clustering, read mapping and annotation of full-length ARGs relative to a user-defined database, reconstructs gene sequences, estimates gene abundance, and conducts local alignments of annotated genes against multiple online databases.