Impact of single-cell RNA sequencing on understanding immune regulation

Single-Cell RNA Sequencing Reveals Alterations in Patient Immune Cells with Pulmonary Long COVID-19 Complications

Since the emergence of the COVID-19 pandemic, the effects of SARS-CoV-2 have been extensively researched. While much is already known about the acute phase of the infection, increasing attention has turned to the prolonged symptoms experienced by a subset of individuals, commonly referred to as long COVID-19 patients. This study aims to delve deeper into the immune landscape of patients with prolonged symptoms by implementing single-cell mRNA analysis. A 71-year-old COVID-19 patient presenting with persistent viral pneumonia was recruited, and peripheral blood samples were taken at 3 and 2 years post-acute infection onset. Patients and control peripheral blood mononuclear cells (PBMCs) were isolated and single-cell sequenced. Immune cell population identification was carried out using the ScType script. Three months post-COVID-19 patients' PBMCs contained a significantly larger immature neutrophil population compared to 2-year and control samples. However, the neutrophil balance shifted towards a more mature profile after 18 months. In addition, a notable increase in the CD8+ NKT-like cells could be observed in the 3-month patient sample as compared to the later one and control. The subsequent change in these cell populations over time may be an indicator of an ongoing failure to clear the SARS-CoV-2 infection and, thus, lead to chronic COVID-19 complications.

Manual cell selection in single cell transcriptomics using scSELpy supports the analysis of immune cell subsets

Introduction

Single cell RNA sequencing plays an increasing and indispensable role in immunological research such as in the field of inflammatory bowel diseases (IBD). Professional pipelines are complex, but tools for the manual selection and further downstream analysis of single cell populations are missing so far.

Methods

We developed a tool called scSELpy, which can easily be integrated into Scanpy-based pipelines, allowing the manual selection of cells on single cell transcriptomic datasets by drawing polygons on various data representations. The tool further supports the downstream analysis of the selected cells and the plotting of results.

Results

Taking advantage of two previously published single cell RNA sequencing datasets we show that this tool is useful for the positive and negative selection of T cell subsets implicated in IBD beyond standard clustering. We further demonstrate the feasibility for subphenotyping T cell subsets and use scSELpy to corroborate earlier conclusions drawn from the dataset. Moreover, we also show its usefulness in the context of T cell receptor sequencing.

Discussion

Collectively, scSELpy is a promising additive tool fulfilling a so far unmet need in the field of single cell transcriptomic analysis that might support future immunological research.

RevGel-seq: instrument-free single-cell RNA sequencing using a reversible hydrogel for cell-specific barcoding

Progress in sample preparation for scRNA-seq is reported based on RevGel-seq, a reversible-hydrogel technology optimized for samples of fresh cells. Complexes of one cell paired with one barcoded bead are stabilized by a chemical linker and dispersed in a hydrogel in the liquid state. Upon gelation on ice the complexes are immobilized and physically separated without requiring nanowells or droplets. Cell lysis is triggered by detergent diffusion, and RNA molecules are captured on the adjacent barcoded beads for further processing with reverse transcription and preparation for cDNA sequencing. As a proof of concept, analysis of PBMC using RevGel-seq achieves results similar to microfluidic-based technologies when using the same original sample and the same data analysis software. In addition, a clinically relevant application of RevGel-seq is presented for pancreatic islet cells. Furthermore, characterizations carried out on cardiomyocytes demonstrate that the hydrogel technology readily accommodates very large cells. Standard analyses are in the 10,000-input cell range with the current gelation device, in order to satisfy common requirements for single-cell research. A convenient stopping point after two hours has been established by freezing at the cell lysis step, with full preservation of gene expression profiles. Overall, our results show that RevGel-seq represents an accessible and efficient instrument-free alternative, enabling flexibility in terms of experimental design and timing of sample processing, while providing broad coverage of cell types.