Christina Camell

The elderly and those with chronic diseases demonstrate a two to ten-fold increased risk of hospitalization and elevated mortality in the setting of multiple types of infections, including SARs-CoV-2, influenza, and pneumonia. Co-infections or secondary infections are also more abundant in the elderly and contribute to excessive mortality. This is especially evident in the COVID-19 pandemic, where the elderly are among the most at risk groups for mortality and morbidity upon infection with SARs-COV-2. The precise mechanisms behind infection-related mortality in elderly individuals are unknown, but elevated inflammatory factors suggests that mortality might be due, in part, to a virus-activated cytokine storm. Death from cytokine storm and associated acute respiratory distress syndrome (ARDS) and myocarditis are seen in older and chronically ill individuals.

These researchers have taken advantage of a unique mouse model that exposes mice to multiple microbes (termed normal microbial experience; NME) at the University of Minnesota. Critically, the NME model generates functional T cell memory without exhaustion in young mice and leads to a more diverse immune system. Aged mice that are exposed to NME show 100% mortality. Mortality can be reduced using senolytics to deplete senescent cells (REF) or immunotherapeutics to target immune cells. The data show the liver is a major site of viral infection, including infection with the coronavirus and mouse hepatitis virus. There are increases in inflammatory markers, an elevated frequency of immune cell infiltrates, and increased expression of markers for senescence cells in the liver of the aged NME-exposed mice as compared to the young NME-exposed mice. These are all contributing components to the cytokine storm and mortality seen in the aged NME exposed mice. These are all contributing components to the cytokine storm and mortality seen in the aged NME exposed mice. With the University of Minnesota Genomics Center, the researchers performed bulk sequencing on the livers of young and old, specific pathogen free (SPF) or NME-exposed mice. This analysis has the advantage of containing the transcriptional profile of all cells, including hepatocytes and senescent cells, which are lost during single cell preparation from the liver, but they are unable to identify the cell type to which specific genes belong to.

To address this lack of specificity in the bulk RNA sequencing data, the reseachers are working with the MSI Bioinformatics staff, who perform cell type deconvolution on bulk RNA-seq data to differentiate non-immune (largely hepatocyte) and immune cells. If possible, they differentiate immune cells and non-immune cells further into sub-types. Bulk deconvolution can accurately decompose bulk RNA-seq samples into their component parts, at least into immune vs. non-immune cell types, and ideally more specifically into more detailed sub-types of immune and non-immune cells. These deconvoluted datasets can then be used successfully to analyze differential expression of specific cell types (at least immune cells or non-immune cells, but ideally more specific) between combinations of young and old and SPF and dirty groups of mice. The analysis proposes to use already published reference datasets for liver cells, including the Tabula muris scenis and scRNA-seq dataset from Dr. Sara Hamilton Hart, the director of the Dirty Mouse Core, and expert in using the NME model. The deconvolution is required analysis for this project, because it is the only path that will analyze all cell types and has the additional benefiting of avoiding any tissue manipulation.

Research by this group was featured on the MSI website in September 2022: Deconvolution of Inflammation During Infection-Related Mortality.