Centriflaken: An automated data analysis pipeline for assembly and in silico analyses of foodborne pathogens from metagenomic samples - Kranti Konganti; Julie A. Kase; Narjol Gonzalez-Escalona (PLoS ONE, 2025)
Rapid and comprehensive analysis of metagenomic data from samples associated with foodborne outbreaks is of critical importance in food safety. Equally important is the need for automated analysis pipelines that allow the rapid and effective construction of metagenomic assembled genomes (MAGs) to enable bacterial source-tracking from metagenomic data. Here, we present centriflaken, an automated precision metagenomics pipeline for detecting and characterizing Shiga toxin-producing Escherichia coli (STEC) from metagenomic data. centriflaken streamlines the process of generating metagenome-assembled genomes (MAGs) and conducting in silico analyses of STECs, significantly reducing the time and manual effort required for comprehensive pathogen profiling. centriflaken was validated using Oxford Nanopore long-read sequencing data from agricultural water enrichments, successfully reproducing results from our previous study that involved multiple manual bioinformatics steps (Maguire et al., 2021). The tool’s efficacy was further demonstrated through its application to ZymoBIOMICS microbial community standards and 21 additional irrigation water samples, completing STEC precision metagenomics analyses in less than 7 hours per sample. centriflaken’s versatility allows for the analysis of user-defined taxa beyond STEC, including other foodborne pathogens like Listeria monocytogenes or Salmonella . The pipeline generates comprehensive summary plots and tables, accessible through a MultiQC HTML report. Designed for portability, centriflaken packages all software dependencies within containers and virtual environments. This open-source tool is available on GitHub under the MIT license ( https://github.com/CFSAN-Biostatistics/centriflaken ), offering a powerful resource for rapid, automated pathogen detection and characterization in food safety applications.