Flow cytometry profiling of cellular immune response in COVID-19 infected, recovered and vaccinated individuals

A single-cell RNA sequencing dataset of peripheral blood cells in long COVID patients on herbal therapy

Following the coronavirus disease 2019 (COVID-19) pandemic, the rise of long COVID, characterized by persistent respiratory and cognitive dysfunctions, has become a significant health concern. This leads to an increased role of complementary and alternative medicine in addressing this condition. However, our comprehension of the effectiveness and safety of herbal medicines for long COVID remains limited. Here, we present a single-cell RNA sequencing (scRNA-seq) dataset of peripheral whole blood cells derived from participants in a clinical study involving three commercially available herbal medicines, targeting fatigue and brain fog in long COVID. The dataset comprises 181,205 quality control (QC)-passed cells, along with clinical metadata, enabling a comparative analysis of immune cell populations before and after treatment. To ensure the technical validity of our dataset, we implemented rigorous quality checks throughout stages of the study, including sample preparation, sequencing, and bioinformatic data analysis levels. This transcriptomic data may serve as a resource to deepen our insights into the role of herbal medicines in management of long COVID.

COVID-19 vaccines: Immune correlates and clinical outcomes

Severe disease due to COVID-19 has declined dramatically as a result of widespread vaccination and natural immunity in the population. With the emergence of SARS-CoV-2 variants that largely escape vaccine-elicited neutralizing antibody responses, the efficacy of the original vaccines has waned and has required vaccine updating and boosting. Nevertheless, hospitalizations and deaths due to COVID-19 have remained low. In this review, we summarize current knowledge of immune responses that contribute to population immunity and the mechanisms how vaccines attenuate COVID-19 disease severity.

Applications of Flow Cytometry in Drug Discovery and Translational Research

Flow cytometry is a mainstay technique in cell biology research, where it is used for phenotypic analysis of mixed cell populations. Quantitative approaches have unlocked a deeper value of flow cytometry in drug discovery research. As the number of drug modalities and druggable mechanisms increases, there is an increasing drive to identify meaningful biomarkers, evaluate the relationship between pharmacokinetics and pharmacodynamics (PK/PD), and translate these insights into the evaluation of patients enrolled in early clinical trials. In this review, we discuss emerging roles for flow cytometry in the translational setting that supports the transition and evaluation of novel compounds in the clinic.

Analysis of Leukocyte Subpopulations by Flow Cytometry during Hospitalization Depending on the Severity of COVID-19 Course

The mechanisms underlying the immune response to coronavirus disease 2019 (COVID-19) and the recovery process have not been fully elucidated. The aim of the study was to analyze leukocyte subpopulations in patients at significant time points (at diagnosis, and 3 and 6 months after infection) selected according to the analysis of changes in the lungs by the CT classification system, considering the severity of the disease. The study groups consisted of severe and non-severe COVID-19 patients. There was a significant decrease in CD8+ T cells, NK and eosinophils, with an increasing percentage of neutrophils during hospitalization. We noticed lower levels of CD4 and CD8 T lymphocytes, eosinophils, basophils, and CD16+ monocytes and elevated neutrophil levels in severe patients relative to non-severe patients. Three months after infection, we observed higher levels of basophils, and after 6 months, higher CD4/CD8 ratios and T cell levels in the severe compared to non-severe group. Non-severe patients showed significant changes in the leukocyte populations studied at time of hospitalization and both within 3 months and 6 months of onset. The CT CSS classification with parameters of the flow cytometry method used for COVID-19 patients determined changes that proved useful in the initial evaluation of patients.