AcinetoScope: a computational pipeline for rapid, comprehensive Acinetobacter baumannii outbreak investigation and resistance gene tracking

Acinetobacter baumannii is a critical nosocomial pathogen whose genomic surveillance is hindered by fragmented workflows and manual integration of separate analysis tools. We present AcinetoScope, a dedicated aggregation pipeline that automates quality control, dual-scheme MLST, capsule typing, antimicrobial resistance detection, virulence and plasmid profiling, and screening for environmental co-selection markers (heavy metals, biocides), and compiles all results into a single interactive HTML report featuring a gene-centric table and cross-genome pattern discovery. The pipeline is designed for low-resource settings: it runs on standard laptops (4 GB RAM, 2 CPU cores) and accepts assembled genomes. Validation against an independent published dataset of 140 A. baumannii clinical isolates (BioProject PRJNA573295) showed 100% concordance for reported MLST, capsule types, and resistance and virulence genes. A separate demonstration on 145 randomly selected A. baumannii assemblies (N50 range 8 kb to 4,179 kb) completed without runtime errors; outputs recapitulated known epidemiology (ST2 and ST1 predominance, significant ST-capsule associations, bla OXA-23 in 62.8%, bla NDM-1 in 17.9%). On a 16-core server, AcinetoScope processed the 145 demonstration genomes in 1 h 24 min. AcinetoScope is implemented in Python and is freely available at https://github.com/bbeckley-hub/acinetoscope .