neissflow: Streamlining Genomic Epidemiology of Neisseria gonorrhoeae with Nextflow

Antimicrobial-resistant Neisseria gonorrhoeae (Ng) poses a growing global public health threat. Existing tools available for Ng genome analysis carry notable limitations, including incomplete resistance marker coverage, absence of species identification, and lack of phylogenetic capability. We developed neiss-flow, a highly parallelized Nextflow pipeline for Ng genome analysis that integrates five subworkflows: read preprocessing, species identification, de novo assembly, antimicrobial resistance (AMR) profiling, and recombination-aware phylogenetic analysis with outbreak detection. neissflow performs extensive quality control on reads, assemblies, variant calls, and phylogenetic results. Validation was performed on two datasets: a mixed-species dataset (n=158; 105 Ng and 53 non-gonococcal species) for sensitivity/specificity assessment, and a reproducibility dataset (n=283 replicate sequences from 17 reference strains) for consistency and phylogenetic validation. neissflow achieved 100% sensitivity and specificity for Ng species identification compared with MALDI-TOF and PubMLST methods. All nine AMR and typing analytes demonstrated [≥]98.1% concordance with PubMLST genotype calls. Genotype-phenotype validation confirmed perfect concordance for key resistance determinants including gyrA mutations with ciprofloxacin resistance, 23S rRNA mutations with high-level azithromycin resistance, and tetM plasmid gene with high-level tetracycline resistance. Reproducibility analysis demonstrated 99.97% concordance across 3,093 analyte calls. Phylogenetic validation demonstrated 100% accuracy for both strain-level and intra-MLST clustering. neissflow is a robust, accessible, and standardized pipeline, positioning it as a valuable tool for public health laboratories engaged in Ng AMR monitoring and outbreak investigations. ImportanceNeisseria gonorrhoeae (Ng) is the second most common reported bacterial sexually transmitted infection and has developed resistance to all clinically relevant antibiotics. Surveillance of Ng resistance informs clinical recommendations for treatment of gonococcal infections. Whole genome sequencing (WGS) offers powerful insights into resistance mechanisms and transmission dynamics. However, many public health laboratories lack the resources needed to analyze these data effectively. We developed neissflow as an end-to-end, accessible Ng WGS analysis pipeline. neissflow demonstrated exceptional accuracy and reproducibility across diverse reference datasets. neissflow enables broader adoption of whole-genome sequencing-based surveillance and supports timely public health responses to emerging antimicrobial resistance in Ng by lowering technical barriers.