biostudies-literatureYang JDOD | Defense Advanced Research Projects Agencye2112886119https://www.ebi.ac.uk/biostudies/studies/S-EPMC9168455biostudies-literatureUnknown119(14)Bacterial pathogen identification, which is critical for human health, has historically relied on culturing organisms from clinical specimens. More recently, the application of machine learning (ML) to whole-genome sequences (WGSs) has facilitated pathogen identification. However, relying solely on genetic information to identify emerging or new pathogens is fundamentally constrained, especially if novel virulence factors exist. In addition, even WGSs with ML pipelines are unable to discern phenotypes associated with cryptic genetic loci linked to virulence. Here, we set out to determine if ML using phenotypic hallmarks of pathogenesis could assess potential pathogenic threat without using any sequence-based analysis. This approach successfully classified potential pathogenetic threat assoProceedings of the National Academy of Sciences of the United States of AmericaPhenotype-Based Threat Assessment.PMC9168455W911NF1920013140D6319C0029Roberts AJZhang DFaghihi KVolkova ADas MSamuel JEMoore RKServetas SObanor OAlaniz RCWattam ARPaterson HChen SYang JCucinell CCoburn Svan Schaik EJKendziorski JDootz JChen YPHan AWeston MQin QMde Figueiredo PDickerman AEslami MMaples JfalsePhenotype-Based Threat Assessment.Bacterial pathogen identification, which is critical for human health, has historically relied on culturing organisms from clinical specimens. More recently, the application of machine learning (ML) to whole-genome sequences (WGSs) has facilitated pathogen identification. However, relying solely on genetic information to identify emerging or new pathogens is fundamentally constrained, especially if novel virulence factors exist. In addition, even WGSs with ML pipelines are unable to discern phenotypes associated with cryptic genetic loci linked to virulence. Here, we set out to determine if ML using phenotypic hallmarks of pathogenesis could assess potential pathogenic threat without using any sequence-based analysis. This approach successfully classified potential pathogenetic threat asso2022-01-01T00:00:00Z2022 Apr2026-07-14T15:52:27.586Z2026-06-20T03:11:55.556ZS-EPMC91684553536356910.1073/pnas.2112886119