Recovery from pneumococcal (Spn) pneumonia induces development of tissue resident memory CD4+ TRM cells, BRM cells, and antibody secreting plasma cells in experienced lungs. These tissue resident lymphocytes confer protection against subsequent lethal challenge by serotype mismatched Spn (termed as heterotypic immunity). While traditional flow cytometry and gating strategies support premeditated identification of cells using a limited set of markers, discovery of novel tissue resident lymphocytes necessitates stable platforms that can handle larger sets of phenotypic markers and lends itself to unbiased clustering approaches. In this report, we leverage the power of full spectrum flow cytometry (FSFC) to develop a comprehensive panel of phenotypic markers that allows identification of multiple subsets of tissue resident lymphocytes in Spn-experienced murine lungs. Using Phenograph algorithm on this multidimensional data, we identify unforeseen heterogeneity in lung resident adaptive immune landscape which includes unexpected subsets of TRM and BRM cells. Further, using conventional gating strategy informed by our unsupervised clustering data, we confirm their presence exquisitely in Spn-experienced lungs as potentially relevant to heterotypic immunity and define CD73 as a highly expressed marker on TRM cells. Thus, our study emphasizes the utility of FSFC for confirmatory and discovery studies relating to tissue resident adaptive immunity.
© 2021 International Society for Advancement of Cytometry.

Brain-immune cross-talk and neuroinflammation critically shape brain physiology in health and disease. A detailed understanding of the brain immune landscape is essential for developing new treatments for neurological disorders. Single-cell technologies offer an unbiased assessment of the heterogeneity, dynamics and functions of immune cells. Here we provide a protocol that outlines all the steps involved in performing single-cell multi-omic analysis of the brain immune compartment. This includes a step-by-step description on how to microdissect the border regions of the mouse brain, together with dissociation protocols tailored to each of these tissues. These combine a high yield with minimal dissociation-induced gene expression changes. Next, we outline the steps involved for high-dimensional flow cytometry and droplet-based single-cell RNA sequencing via the 10x Genomics platform, which can be combined with cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq) and offers a higher throughput than plate-based methods. Importantly, we detail how to implement CITE-seq with large antibody panels to obtain unbiased protein-expression screening coupled to transcriptome analysis. Finally, we describe the main steps involved in the analysis and interpretation of the data. This optimized workflow allows for a detailed assessment of immune cell heterogeneity and activation in the whole brain or specific border regions, at RNA and protein level. The wet lab workflow can be completed by properly trained researchers (with basic proficiency in cell and molecular biology) and takes between 6 and 11 h, depending on the chosen procedures. The computational analysis requires a background in bioinformatics and programming in R.
© 2022. Springer Nature Limited.