Relapsing bacterial infections require prolonged and repetitive antibiotic treatment schedules associated with the emergence of antibiotic resistance. Small reservoirs of bacteria called persisters underlie relapsing infections. Persisters are genetically antibiotic-sensitive bacterial cells that transiently enter a non-proliferative state marked by low drug susceptibility. Persisters often reside in macrophages where they are protected from drug-mediated killing.
Using invasive non-typhoidal Salmonella as a model, we aim to identify host-targeted perturbations that can disrupt the persister-permissive macrophage niche and promote persister eradication without inducing immunopathology. If successful, this will pave the way for development of next-generation immunomodulatory therapies to treat relapsing bacterial infections.
Projects

Build and validate mechanistic models of persister-permissive macrophage gene regulatory networks.
To rationally design host-directed therapies to eradicate relapsing bacterial infections, it is first necessary to define: 1) what host phenotypes enable survival of persisters; and 2) how are these persister-permissive macrophage phenotypes established and sustained over time (i.e. what are the underlying gene regulatory networks). We are using a regulatory genomics approach to achieve this, defining the hierarchal network of transcription factors, chromatin regulators and immune effector proteins controlling the phenotype of Salmonella persister-harbouring macrophages.

Identify macrophage-targeted perturbations to eradicate Salmonella antibiotic persisters.
We are using large-scale CRISPR interference and activation screens to identify loss-of-function and gain-of-function host perturbations that drive immune- and/or antibiotic-mediated killing of Salmonella persisters in macrophages. For the most promising candidates, we are exploring if these perturbations can increase the efficacy of antibiotic treatment and therefore limit the duration and frequency that antimicrobial therapy is needed for invasive salmonellosis.

Predict the impact of macrophage-targeted perturbations in patients suffering from invasive salmonellosis.
In collaboration with Malick Gibani (Imperial College London) and Brendan Frey (Vector Institute), we are combining deep learning approaches and transcriptional profiling of immune cells isolated from the blood of patients participating in the invasive non-typhoidal Salmonella human challenge study to infer a mechanistic model of the host immune response during Salmonella infection and antibiotic treatment. By generating such a mechanistic model, we will be able to predict how therapeutic perturbations are likely to impact immune cell phenotype in patients. In turn, this will provide critical information into whether such therapeutic perturbations are likely to be associated with immunopathology or not.
Projects

Build and validate mechanistic models of persister-permissive macrophage gene regulatory networks.
To rationally design host-directed therapies to eradicate relapsing bacterial infections, it is first necessary to define: 1) what host phenotypes enable survival of persisters; and 2) how are these persister-permissive macrophage phenotypes established and sustained over time (i.e. what are the underlying gene regulatory networks). We are using a regulatory genomics approach to achieve this, defining the hierarchal network of transcription factors, chromatin regulators and immune effector proteins controlling the phenotype of Salmonella persister-harbouring macrophages.

Identify macrophage-targeted perturbations to eradicate Salmonella antibiotic persisters.
We are using large-scale CRISPR interference and activation screens to identify loss-of-function and gain-of-function host perturbations that drive immune- and/or antibiotic-mediated killing of Salmonella persisters in macrophages. For the most promising candidates, we are exploring if these perturbations can increase the efficacy of antibiotic treatment and therefore limit the duration and frequency that antimicrobial therapy is needed for invasive salmonellosis.

Predict the impact of macrophage-targeted perturbations in patients suffering from invasive salmonellosis.
In collaboration with Malick Gibani (Imperial College London) and Brendan Frey (Vector Institute), we are combining deep learning approaches and transcriptional profiling of immune cells isolated from the blood of patients participating in the invasive non-typhoidal Salmonella human challenge study to infer a mechanistic model of the host immune response during Salmonella infection and antibiotic treatment. By generating such a mechanistic model, we will be able to predict how therapeutic perturbations are likely to impact immune cell phenotype in patients. In turn, this will provide critical information into whether such therapeutic perturbations are likely to be associated with immunopathology or not.