Martyn, J. E. | bioRxiv Science

bioRxiv2024

Backtracking Metabolic Dynamics in Single Cells Predicts Bacterial Replication in Human Macrophages

Accurately tracking dynamic state transitions is crucial for modeling and predicting biological outcomes, as it captures heterogeneity of cellular responses. To build a model to predict bacterial infection in single cells, we have monitored in parallel infection progression and metabolic parameters in thousands of human primary macrophages infected with the intracellular pathogen Legionella pneumophila. By combining livecell imaging with a novel tool for classifying cells based on infection outcomes, we were able to trace the specific evolution of metabolic parameters linked to distinct outcomes, such as bacterial replication or cell death. Our findings revealed that early changes in mitochondrial membrane potential ({Delta}{psi}m) and in the production of mitochondrial Reactive Oxygen Species (mROS) are associated with macrophages that will later support bacterial growth. We used these data to train an explainable machine-learning model and achieved 83% accuracy in predicting L. pneumophila replication in single, infected cells before bacterial replication starts. Our results highlight backtracking as a valuable tool to gain new insights in host-pathogen interactions and identify early mitochondrial alterations as key predictive markers of success of bacterial infection.

microbiology↗

bioRxiv2020

The role of toxin:antitoxin systems and insertion sequences in the loss of virulence in Shigella sonnei

The Shigella plasmid, pINV, contains a 30 kb pathogenicity island (PAI) encoding a Type III secretion system (T3SS) which is essential for virulence. During growth in the laboratory, avirulent colonies of Shigella (which do not express a T3SS) arise spontaneously. Avirulence in Shigella flexneri mostly follows loss of the PAI, following recombination between insertion sequences (ISs) on pINV; toxin:antitoxin (TA) systems on pINV promote its retention through post-segregational killing (PSK). We show that avirulence in Shigella sonnei mainly results from plasmid loss, consistent with previous findings; IS-mediated PAI deletions can occur in S. sonnei, but through different ISs than in S. flexneri. We investigated the molecular basis for frequent loss of the S. sonnei plasmid, pINVSsonn. Introduction into pINVSsonn of CcdAB and GmvAT, toxin:antitoxin TA systems in pINV from S. flexneri but not S. sonnei, reduced plasmid loss and the emergence of avirulent bacteria. However, plasmid loss remained the leading cause of avirulence. We show that a single amino acid difference in the VapC toxin of the VapBC TA system in pINV also contributes to high frequency plasmid loss in S. sonnei compared to S. flexneri. Our findings demonstrate that the repertoire of ISs, complement of TA systems, and polymorphisms in TA systems influence plasmid dynamics and virulence loss in S. sonnei. Understanding the impact of polymorphisms should be informative about how TA systems contribute to PSK, and could be exploited for generating strains with stable plasmids.

microbiology↗