Fluorescence Intensity Normalisation: Correcting for Time Effects in Large-Scale Flow Cytometric Analysis

A next step to interpret the findings generated by genome-wide association studies is to associate molecular quantitative traits with disease-associated alleles. To this end, researchers are linking disease risk alleles with gene expression quantitative trait loci (eQTL). However, gene expression at the mRNA level is only an intermediate trait and flow cytometry analysis can provide more downstream and biologically valuable protein level information in multiple cell subsets simultaneously using freshly obtained samples. Because the throughput of flow cytometry is currently limited, experiments may need to span over several weeks or months to obtain a sufficient sample size to demonstrate genetic association. Therefore, normalisation methods are needed to control for technical variability and compare flow cytometry data over an extended period of time. We show how the use of normalising fluorospheres improves the repeatability of a cell surface CD25-APC mean fluorescence intensity phenotype on CD4+ memory T cells. We investigate two types of normalising beads: broad spectrum and spectrum matched. Lastly, we propose two alternative normalisation procedures that are usable in the absence of normalising beads

Fluorescence intensity normalisation: correcting for time effects in large-scale flow cytometric analysis.

A next step to interpret the findings generated by genome-wide association studies is to associate molecular quantitative traits with disease-associated alleles. To this end, researchers are linking disease risk alleles with gene expression quantitative trait loci (eQTL). However, gene expression at the mRNA level is only an intermediate trait and flow cytometry analysis can provide more downstream and biologically valuable protein level information in multiple cell subsets simultaneously using freshly obtained samples. Because the throughput of flow cytometry is currently limited, experiments may need to span over several weeks or months to obtain a sufficient sample size to demonstrate genetic association. Therefore, normalisation methods are needed to control for technical variability and compare flow cytometry data over an extended period of time. We show how the use of normalising fluorospheres improves the repeatability of a cell surface CD25-APC mean fluorescence intensity phenotype on CD4(+) memory T cells. We investigate two types of normalising beads: broad spectrum and spectrum matched. Lastly, we propose two alternative normalisation procedures that are usable in the absence of normalising beads.Peer Reviewe

Single-cell transcriptomic analysis of retinal immune regulation and blood-retinal barrier function during experimental autoimmune uveitis

Uveitis is characterised by breakdown of the blood-retinal barrier (BRB), allowing infiltration of immune cells that mediate intraocular inflammation, which can lead to irreversible damage of the neuroretina and the loss of sight. Treatment of uveitis relies heavily on corticosteroids and systemic immunosuppression due to limited understanding of disease pathogenesis. We performed single-cell RNA-sequencing of retinas, as well as bulk RNA-sequencing of retinal pigment epithelial (RPE) cells from mice with experimental autoimmune uveitis (EAU) versus healthy control. This revealed that the Th1/Th17-driven disease induced strong gene expression changes in response to inflammation in rods, cones, Müller glia and RPE. In particular, Müller glia and RPE cells were found to upregulate expression of chemokines, complement factors, leukocyte adhesion molecules and MHC class II, thus highlighting their contributions to immune cell recruitment and antigen presentation at the inner and outer BRB, respectively. Additionally, ligand-receptor interaction analysis with CellPhoneDB revealed key interactions between Müller glia and T cell / natural killer cell subsets via chemokines, galectin-9 to P4HB/TIM-3, PD-L1 to PD-1, and nectin-2/3 to TIGIT signalling axes. Our findings elucidate mechanisms contributing to breakdown of retinal immune privilege during uveitis and identify novel targets for therapeutic interventions

hadge: a comprehensive pipeline for donor deconvolution in single-cell studies

Single-cell multiplexing techniques (cell hashing and genetic multiplexing) combine multiple samples, optimizing sample processing and reducing costs. Cell hashing conjugates antibody-tags or chemical-oligonucleotides to cell membranes, while genetic multiplexing allows to mix genetically diverse samples and relies on aggregation of RNA reads at known genomic coordinates. We develop hadge (hashing deconvolution combined with genotype information), a Nextflow pipeline that combines 12 methods to perform both hashing- and genotype-based deconvolution. We propose a joint deconvolution strategy combining best-performing methods and demonstrate how this approach leads to the recovery of previously discarded cells in a nuclei hashing of fresh-frozen brain tissue

Panpipes: a pipeline for multiomic single-cell and spatial transcriptomic data analysis

Single-cell multiomic analysis of the epigenome, transcriptome, and proteome allows for comprehensive characterization of the molecular circuitry that underpins cell identity and state. However, the holistic interpretation of such datasets presents a challenge given a paucity of approaches for systematic, joint evaluation of different modalities. Here, we present Panpipes, a set of computational workflows designed to automate multimodal single-cell and spatial transcriptomic analyses by incorporating widely-used Python-based tools to perform quality control, preprocessing, integration, clustering, and reference mapping at scale. Panpipes allows reliable and customizable analysis and evaluation of individual and integrated modalities, thereby empowering decision-making before downstream investigations

An immunodominant NP105-113-B*07:02 cytotoxic T cell response controls viral replication and is associated with less severe COVID-19 disease.

Funder: RCUK | Medical Research Council (MRC); doi: https://doi.org/10.13039/501100000265Funder: Chinese Academy of Medical Sciences (CAMS); doi: https://doi.org/10.13039/501100005150Funder: Wellcome Trust (Wellcome); doi: https://doi.org/10.13039/100004440NP105-113-B*07:02-specific CD8+ T cell responses are considered among the most dominant in SARS-CoV-2-infected individuals. We found strong association of this response with mild disease. Analysis of NP105-113-B*07:02-specific T cell clones and single-cell sequencing were performed concurrently, with functional avidity and antiviral efficacy assessed using an in vitro SARS-CoV-2 infection system, and were correlated with T cell receptor usage, transcriptome signature and disease severity (acute n = 77, convalescent n = 52). We demonstrated a beneficial association of NP105-113-B*07:02-specific T cells in COVID-19 disease progression, linked with expansion of T cell precursors, high functional avidity and antiviral effector function. Broad immune memory pools were narrowed postinfection but NP105-113-B*07:02-specific T cells were maintained 6 months after infection with preserved antiviral efficacy to the SARS-CoV-2 Victoria strain, as well as Alpha, Beta, Gamma and Delta variants. Our data show that NP105-113-B*07:02-specific T cell responses associate with mild disease and high antiviral efficacy, pointing to inclusion for future vaccine design

The role and uses of antibodies in COVID-19 infections: a living review

Coronavirus disease 2019 has generated a rapidly evolving field of research, with the global scientific community striving for solutions to the current pandemic. Characterizing humoral responses towards SARS-CoV-2, as well as closely related strains, will help determine whether antibodies are central to infection control, and aid the design of therapeutics and vaccine candidates. This review outlines the major aspects of SARS-CoV-2-specific antibody research to date, with a focus on the various prophylactic and therapeutic uses of antibodies to alleviate disease in addition to the potential of cross-reactive therapies and the implications of long-term immunity

T cell phenotypes in COVID-19 - a living review

COVID-19 is characterized by profound lymphopenia in the peripheral blood, and the remaining T cells display altered phenotypes, characterized by a spectrum of activation and exhaustion. However, antigen-specific T cell responses are emerging as a crucial mechanism for both clearance of the virus and as the most likely route to long-lasting immune memory that would protect against re-infection. Therefore, T cell responses are also of considerable interest in vaccine development. Furthermore, persistent alterations in T cell subset composition and function post-infection have important implications for patients’ long-term immune function. In this review, we examine T cell phenotypes, including those of innate T cells, in both peripheral blood and lungs, and consider how key markers of activation and exhaustion correlate with, and may be able to predict, disease severity. We focus on SARS-CoV-2-specific T cells to elucidate markers that may indicate formation of antigen-specific T cell memory. We also examine peripheral T cell phenotypes in recovery and the likelihood of long-lasting immune disruption. Finally, we discuss T cell phenotypes in the lung as important drivers of both virus clearance and tissue damage. As our knowledge of the adaptive immune response to COVID-19 rapidly evolves, it has become clear that while some areas of the T cell response have been investigated in some detail, others, such as the T cell response in children remain largely unexplored. Therefore, this review will also highlight areas where T cell phenotypes require urgent characterisation

A blood atlas of COVID-19 defines hallmarks of disease severity and specificity.

Treatment of severe COVID-19 is currently limited by clinical heterogeneity and incomplete description of specific immune biomarkers. We present here a comprehensive multi-omic blood atlas for patients with varying COVID-19 severity in an integrated comparison with influenza and sepsis patients versus healthy volunteers. We identify immune signatures and correlates of host response. Hallmarks of disease severity involved cells, their inflammatory mediators and networks, including progenitor cells and specific myeloid and lymphocyte subsets, features of the immune repertoire, acute phase response, metabolism, and coagulation. Persisting immune activation involving AP-1/p38MAPK was a specific feature of COVID-19. The plasma proteome enabled sub-phenotyping into patient clusters, predictive of severity and outcome. Systems-based integrative analyses including tensor and matrix decomposition of all modalities revealed feature groupings linked with severity and specificity compared to influenza and sepsis. Our approach and blood atlas will support future drug development, clinical trial design, and personalized medicine approaches for COVID-19