No abstract

As the global COVID-19 pandemic continues to escalate, no effective treatment has yet been developed for the severe respiratory complications of this disease. This may be due in large part to the unclear immunopathological basis for the development of immune dysregulation and acute respiratory distress syndrome (ARDS) in severe and critical patients. Specifically, it remains unknown whether the immunological features of the disease that have been identified so far are compartment-specific responses or general features of COVID-19. Additionally, readily detectable biological markers correlated with strata of disease severity that could be used to triage patients and inform treatment options have not yet been identified. Here, we leveraged publicly available single-cell RNA sequencing data to elucidate the common and compartment-specific immunological features of clinically severe COVID-19. We identified a number of transcriptional programs that are altered across the spectrum of disease severity, few of which are common between the lung and peripheral immune environments. In the lung, comparing severe and moderate patients revealed severity-specific responses of enhanced interferon, A20/IκB, IL-2, and IL-6 pathway signatures along with broad signaling activity of IFNG, SPP1, CCL3, CCL8, and IL18 across cell types. These signatures contrasted with features unique to ARDS observed in the blood compartment, which included depletion of interferon and A20/IκB signatures and a lack of IL-6 response. The cell surface marker S1PR1 was strongly upregulated in patients diagnosed with ARDS compared to non-ARDS patients in γδ T cells of the blood compartment, and we nominate S1PR1 as a potential marker for immunophenotyping ARDS in COVID-19 patients using flow cytometry.HIGHLIGHTSCOVID-19 disease severity is associated with a number of compositional shifts in the cellular makeup of the blood and lung environments.Transcriptional data suggest differentially expressed cell surface proteins as markers for COVID-19 immunophenotyping from BALF and PBMC samples.Severity-specific features COVID-19 manifest at the pathway level, suggesting distinct changes to epithelia and differences between local and systemic immune dynamics.Immune-epithelial cellular communication analysis identifies ligands implicated in transcriptional regulation of proto-oncogenes in the lung epithelia of severe COVID-19 patients.Network analysis suggests broadly-acting dysregulatory ligands in the pulmonary microenvironment as candidate therapeutic targets for the treatment of severe COVID-19.

Severe COVID-19 is accompanied by rampant immune dysregulation in the lung and periphery, with immune cells of both compartments contributing to systemic distress. The extent to which immune cells of the lung and blood enter similar or distinct pathological states during severe disease remains unknown. Here, we leveraged 96 publicly available single-cell RNA sequencing datasets to elucidate common and compartment-specific features of severe-to-critical COVID-19 at the levels of transcript expression, biological pathways, and ligand-receptor signaling networks. Comparing severe patients to milder and healthy donors, we identified distinct differential gene expression signatures between compartments but a core set of co-directionally regulated surface markers. A majority of severity-enriched pathways were shared, while TNF and interferon responses were polarized. Severity-specific ligand-receptor networks appeared to be differentially active in both compartments. Overall, our results describe a nuanced response during severe COVID-19 where compartment plays a role in dictating the pathological state of immune cells.

Lysogens are bacterial cells that have survived after being infected by bacterial viruses called bacteriophages. Instead of being killed by the virus, the infected cell survives by integrating the viral DNA into its own genome. This is only possible with "temperate" bacteriophages which do not always lyse their host to reproduce, but sometimes replicate passively using the lysogenic pathway. After an infection resulting in lysogeny, the lysogen continues to grow and divide normally, seemingly unaffected by the integrated viral genome which is now referred to as a prophage. However, the prophage can have an impact on the host's phenotype and overall fitness in certain environments. This makes competition between the lysogen and its nonlysogen counterpart possible because both cells have different genomes and potentially different growth rates. Additionally, the prophages within the lysogens are capable of spontaneously reverting back to the lytic pathway via spontaneous prophage induction (SPI), causing death of the lysogen and the release of new progeny phages. These new phages can then lyse or lysogenize other susceptible nonlysogens, thereby impacting the competition between lysogens and nonlysogens. In a scenario with differing growth rates, it is not clear whether SPI would be beneficial or detrimental to the lysogens since it directly causes cell death but also attacks nonlysogenic competitiors, either lysing or lysogenizing them. In this work we study the evolutionary dynamics of a mixture of lysogens and nonlysogens and derive general conditions on the rate of SPI resulting in lysogens displacing nonlysogens. We show that there exists an optimal SPI rate, and apply the model to bacteriophage λ. We find that the model can explain why the experimentally measured SPI rate for phage λ is so low. We also investigate the impact of stochasticity and conclude that even at low copy numbers the SPI rate can still be fairly low while still providing an advantage to the lysogens.