System and transcript dynamics of cells infected with severe acute respiratory syndrome virus 2 (SARS-CoV-2)

Statistical laws arise in many complex systems and can be explored to gain insights into their structure and behavior. Here, we investigate the dynamics of cells infected with severe acute respiratory syndrome virus 2 (SARS-CoV-2) at the system and individual gene levels; and demonstrate that the statistical frameworks used here are robust in spite of the technical noise associated with single-cell RNA sequencing (scRNA-seq) data. A biphasic fit to Taylors power law was observed, and it is likely associated with the larger sampling noise inherent to the measure of less expressed genes. The type of the distribution of the system, as assessed by Taylors parameters, varies along the course of infection in a cell type-dependent manner, but also sampling noise had a significant influence on Taylors parameters. At the individual gene level, we found that genes that displayed signals of punctual rank stability and/or long-range dependence behavior, as measured by Hurst exponents, were associated with translation, cellular respiration, apoptosis, protein-folding, virus processes, and immune response. Author summaryViruses replicate within susceptible cells by exploiting the cellular machinery. Consequently, cells initiate defenses against the virus and signal other cells, notably immune cells. This ongoing battle prompts significant alterations in the cells gene expression patterns throughout the infection process. In this study, we apply statistical principles from complex systems theory to analyze gene expression data from individual cells infected with SARS-CoV-2. Our research aims to elucidate how viral infection impacts cells at both systemic and individual gene levels. Our primary findings are twofold: (i) the virus influences the distribution of gene transcripts over the course of infection, varying depending on cell type. (ii) As the infection progresses, numerous genes associated with critical cellular functions and immunity exhibit signs of punctual instability and/or autocorrelation, indicating their response to viral infection at various stages of the process.