Integrating genomic and Tn-Seq data to identify common

Sepsis, a life-threatening organ dysfunction, is due to an unregulated immune response to infection. Bacteremia is a leading cause of sepsis, and members of the Enterobacterales cause nearly half of bacteremia cases annually. Although previous Tn-Seq studies identified novel bacteremia-fitness genes, evidence for common pathways across species is lacking. To identify common fitness pathways in five bacteremia-causing Enterobacterales species, we utilized our pan-genome pipeline to integrate Tn-Seq fitness data with multiple available functional data types. Core genes from species pan-genomes were used to construct a multi-species core pan-genome, producing 2,850 core gene clusters found in four of five species. Integration of Tn-Seq fitness data identified 373 protein clusters conserved in all five species and a fitness gene in at least one of them. A scoring rubric was applied to these clusters, which incorporated Tn-Seq fitness defects, operon localization, and antibiotic susceptibility data, which reduced the number of bacteremia-fitness genes and identified seven common fitness mechanisms. Independent mutational validation of one prioritized fitness gene, IMPORTANCE: Bacteremia is a leading cause of sepsis, a life-threatening condition where an unregulated immune response to infection causes systemic organ failure. Nearly half of bacteremia cases are caused by members of the Gram-negative bacterial taxonomic order Enterobacterales. Given the public health impact of bacteremia and the reduction of existing antibiotic treatment options, novel strategies are needed to combat these infections. In this study, pan-genome software was used to predict seven shared fitness pathways in these bacteria that may serve as novel targets for the treatment of bacteremia. Briefly, a scoring rubric was applied to shared pan-genome clusters, which incorporated multiple data types, including Tn-Seq fitness defects, operon localization, and antibiotic susceptibility data to rank and prioritize fitness genes. To validate one of our predictions, mutations were constructed in