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COVID-19, a disease caused by the SARS-CoV-2 virus, poses significant threats to the respiratory system and other vital organs. Long non-coding RNAs have emerged as influential epigenetic regulators and promising biomarkers in respiratory ailments. The objective of this study was to identify candidate lncRNAs in SARS-CoV-2-positive individuals compared to SARS-CoV-2-negative individuals and investigate their potential association with ARDS-CoV-2 (acute respiratory distress syndrome). Employing qRT-PCR, we meticulously examined the expression profiles of a panel comprising 84 inflammation-related lncRNAs in individuals presenting upper respiratory infection symptoms, categorizing them into those testing negative or positive for SARS-CoV-2. Notably, first-phase PSD individuals exhibited significantly elevated levels of AC000120.7 and SENP3-EIF4A1. In addition, we measured the expression of two lncRNAs, AC000120.7 and SENP3-EIF4A1, in patients with ARDS unrelated to SARS-CoV-2 (n = 5) and patients with ARDS induced by SARS-CoV-2 (ARDS-CoV-2, n = 10), and interestingly, expression was also higher among patients with ARDS. Intriguingly, our interaction pathway analysis unveiled potential interactions between lncRNA AC000120.7, various microRNAs, and genes associated with inflammation. This study found higher expression levels of lncRNAs AC000120.7 and SENP3-EIF4A1 in the context of infection-positive COVID-19, particularly within the complex landscape of ARDS.

Despite advances in diagnosing latent Mycobacterium tuberculosis infection (LTBI), we still lack a diagnostic test that differentiates LTBI from active tuberculosis (TB) or predicts the risk of progression to active disease. One reason for the absence of such a test may be the failure of current assays to capture the dynamic complexities of the immune responses associated with various stages of TB, since these assays measure only a single parameter (release of IFN-γ) and rely on prolonged (overnight) T cell stimulation. We describe a novel, semi-automated RNA flow cytometry assay to determine whether immunological differences can be identified between LTBI and active TB. We analyzed antigen-induced expression of Th1 cytokine mRNA after short (2- and 6-h) stimulation with antigen, in the context of memory T cell immunophenotyping. IFNG and TNFA mRNA induction was detectable in CD4+ T cells after only 2 h of ex vivo stimulation. Moreover, IFNG- and TNFA-expressing CD4+ T cells (Th1 cells) were more frequent in active TB than in LTBI, a difference that is undetectable with conventional, protein-based cytokine assays. We also found that active TB was associated with higher ratios of effector memory to central memory Th1 cells than LTBI. This effector memory phenotype of active TB was associated with increased T cell differentiation, as defined by loss of the CD27 marker, but not with T cell exhaustion, as determined by PD-1 abundance. These results indicate that single-cell-based, mRNA measurements may help identify time-dependent, quantitative differences in T cell functional status between latent infection and active tuberculosis.