ACDTree: a bioinformatics toolkit to support the development and long-term sustainability of pathogen genomic surveillance workflows

PREPRINT ARTICLE ACDTree: a bioinformatics toolkit to support the development and long-term sustainability of pathogen genomic surveillance workflows Abstract Whole-Genome Sequencing (WGS) has revolutionized infectious disease surveillance, providing high-resolution data for outbreak detection, insights into pathogen population structure, and improved public health decision-making. In bacteria, core- and whole-genome Multilocus Sequence Typing (cg/wgMLST) has become a standard typing approach, but its development, implementation, and ongoing maintenance remain challenging and variable across laboratories, undermining comparability and coordination of genomic surveillance at both national and international levels. To address these challenges, we present the first implementation of ACDTree, an open-source bioinformatics toolkit comprising three complementary tools (EvalTree, DownTree, and PanTree) designed to support key stages across the lyfe-cycle of a genomic surveillance workflow, in strong interoperability with ReporTree. EvalTree enables systematic workflow benchmarking by assessing clustering behavior, stability and congruence, thus supporting pipeline design, validation and inter-laboratory comparability. DownTree facilitates the selection of representative genomes from large datasets, assisting cg/wgMLST schema development and scalable routine analyses. PanTree gathers information about locus diversity, prevalence and presence/absence profile in a species tree, enabling the rational selection of loci for wgMLST implementation. In summary, ACDTree is a modular, pathogen-agnostic toolkit that streamlines genome selection, schema design, and comparative performance assessments of genome-scale typing workflows, thus supporting their deployment and long-term sustainability, as well as inter-laboratory pipeline comparability. Keywords: typing workflows; genomic surveillance; outbreak detection; cluster congruence; cg/wgMLST