Modelling of viral respiratory co-infection dynamics in human epithelium – MORIARTY

Every year, millions of people are infected by many different respiratory viruses, which can either be benign or severe, lead to local outbreaks or have pandemic potential. In recent years, the development of techniques allowing for the simultaneous detection of multiple viruses has revealed the frequent occurrence of co-infections, whereby otherwise benign viruses can be present in patients infected with more severe respiratory viruses, such as influenza or SARS-CoV-2. However, it is not clear how these viruses interact within patients and potentially modulate virulence, disease progression and transmissibility of each other, or impact the outcome of pharmacological interventions. To understand how respiratory viruses co-exist at the individual and population level, and how novel pandemic viruses, such as SARS-CoV-2, shape the landscape of respiratory pathogens, it is essential to address basic questions that have long been ignored for viruses causing seasonal infections, such as cell tropism, viral-specific transmission dynamics and host-pathogen interactions.
In this project, we will combine experimental approaches with novel analytical methods and mathematical modelling to (i) decipher viral replication dynamics of four main respiratory viruses of various severity, (ii) evaluate how co-infection modulate the individual viral dynamics, (iii) anticipate the efficacy of antiviral treatments, and (iv) understand the impact of co-infections on virulence and transmissibility in the population. Thereby, we will focus on human rhinovirus (HRV) and Respiratory Syncytial Virus (RSV) as models of highly circulating viruses, and on influenza A viruses (IAV) and SARS-CoV-2 as models of pandemic viruses. We will work with Air-liquid-interface cultures of reconstituted human airway epithelium and different animal models relying on immunohistochemical imaging and time course infection measurements to assess cell-type specific infectivity, viral replication kinetics, and innate immunity under physiological relevant conditions. Combining these data with detailed mathematical models on the dynamic processes, we will be able to quantify key parameters governing viral-specific replication, spread and innate immune stimulation on a single-cell level within tissue. By repeated iterations between mathematical modelling and in vitro and in vivo experiments, we will assess how these parameters are modulated in the case of co-infections, and how the efficacy of current antiviral treatments against IAV and SARS-CoV-2 will be affected. Finally, we will use our results to inform epidemiological models to understand how co-infection dynamics at a cellular level affect the ecology of viruses and their virulence in the population, and to predict possible impacts of broad exposure to treatment on the pathogenic landscape.