Strategies for optimizing CITE-seq for human islets and other tissues
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA932439 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR23363368.fastq.gz | Fastqsanger.gz | |||
| SRR23363369.fastq.gz | Fastqsanger.gz | |||
| SRR23363370.fastq.gz | Fastqsanger.gz | |||
| SRR23363371.fastq.gz | Fastqsanger.gz |
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Project description:Defining the immunological landscape of human tissue is an important area of research, but challenges include the impact of tissue disaggregation on cell phenotypes and the low abundance of immune cells in many tissues. Here, we describe methods to troubleshoot and standardize Cellular Indexing of Transcriptomes and Epitopes by sequencing (CITE-seq) for studies involving enzymatic digestion of human tissue. We tested epitope susceptibility of 92 antibodies commonly used to differentiate immune lineages and cell states on human peripheral blood mononuclear cells following treatment with an enzymatic digestion cocktail used to isolate islets. We observed CD4, CD8a, CD25, CD27, CD120b, CCR4, CCR6, and PD1 display significant sensitivity to enzymatic treatment, effects that often could not be overcome with alternate antibodies. Comparison of flow cytometry-based CITE-seq antibody titrations and sequencing data supports that for the majority of antibodies, flow cytometry accurately predicts optimal antibody concentrations for CITE-seq. Comparison by CITE-seq of immune cells in enzymatically digested islet tissue and donor- matched spleen not treated with enzymes revealed little digestion-induced epitope cleavage, suggesting increased sensitivity of CITEseq and/or that the islet structure may protect resident immune cells from enzymes. Within islets, CITEseq identified immune cells difficult to identify by transcriptional signatures alone, such as distinct tissue-resident T cell subsets, mast cells, and innate lymphoid cells (ILCs). Collectively this study identifies strategies for the rational design and testing of CITE-seq antibodies for single-cell studies of immune cells within islets and other tissues.
2023-02-12 | GSE224767 | GEO
Project description:Defining the immunological landscape of human tissue is an important area of research, but challenges include the impact of tissue disaggregation on cell phenotypes and the low abundance of immune cells in many tissues. Here, we describe methods to troubleshoot and standardize Cellular Indexing of Transcriptomes and Epitopes by sequencing (CITE-seq) for studies involving enzymatic digestion of human tissue. We tested epitope susceptibility of 92 antibodies commonly used to differentiate immune lineages and cell states on human peripheral blood mononuclear cells following treatment with an enzymatic digestion cocktail used to isolate islets. We observed CD4, CD8a, CD25, CD27, CD120b, CCR4, CCR6, and PD1 display significant sensitivity to enzymatic treatment, effects that often could not be overcome with alternate antibodies. Comparison of flow cytometry-based CITE-seq antibody titrations and sequencing data supports that for the majority of antibodies, flow cytometry accurately predicts optimal antibody concentrations for CITE-seq. Comparison by CITE-seq of immune cells in enzymatically digested islet tissue and donor-matched spleen not treated with enzymes revealed little digestion-induced epitope cleavage, suggesting increased sensitivity of CITE-seq and/or that the islet structure may protect resident immune cells from enzymes. Within islets, CITE-seq identified immune cells difficult to identify by transcriptional signatures alone, such as distinct tissue-resident T cell subsets, mast cells, and innate lymphoid cells (ILCs). Collectively this study identifies strategies for the rational design and testing of CITE-seq antibodies for single-cell studies of immune cells within islets and other tissues.
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Project description:Developing & Optimizing Acute Myeloid Leukemia Specific Therapeutic Antibodies [CITE-seq]
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Project description:Single-cell RNA-sequencing (scRNA-Seq) is widely used to characterize immune cell populations. However, mRNA levels correlate poorly with expression of surface proteins, which are well established to define immune cell types. CITE-Seq (cellular indexing of transcriptomes and epitopes by sequencing) utilizes oligonucleotide-tagged antibodies to simultaneously analyze surface phenotypes and transcriptomes. Considering the high costs of adding surface phenotyping to scRNA-Seq, we aimed to determine which of 188 tested CITE-Seq antibodies can detect their antigens on human peripheral blood mononuclear cells (PBMCs), a commonly interrogated cell population in immunology, and find the optimal concentration for staining. The recommended concentration was optimal for 76 antibodies, whereas staining quality of 7 antibodies improved when the concentration was doubled. 33 and 8 antibodies still worked well when the concentration was reduced to 1/5 or 1/25, respectively. 64 antigens were not detected at any antibody concentration. Optimizing the antibody panel by removing antibodies not able to detect their target antigens and adjusting concentrations of the remaining antibodies could enable a cost reduction of almost 50%. In conclusion, our data are a resource for building an informative and cost-effective panel of CITE-Seq antibodies and use them at their optimal concentrations in future CITE-seq experiments on human PBMCs.
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Project description:While great efforts are being made to establish single-cell transcriptomics profiling of clinical material, protein expression of clinically relevant biomarkers has been harder to integrate into existing pipelines. CITE-seq bridges the RNA-protein gap, but has so far primarily been applied to liquid biopsies, which do not require tissue dissociation. Processing of solid biopsies to characterize the tumor microenvironment is an essential next step in applying single-cell technologies to translational studies. Here, we demonstrate CITE-seq performance and protocol customizations on dissociated tissues such as human skin and primary and metastatic melanoma biopsies on a total of 52,672 cells from 11 solid and 6 liquid primary samples. Analogous to fluorescently activated cell sorting (FACS), we describe gating of cell populations based on transcriptome signatures and setting thresholds for protein expression using cell type-aware ridge plot visualization. For a panel of 97 antibodies, we report on gene and protein expression correlation in liquid and solid sample cohorts. Using peripheral blood mononuclear cells (PBMCs) as a model, we show the effect of enzymatic digestion on transcriptome and epitope expression in immune cell populations. Additionally, we optimized digestion protocols for healthy skin and tumor tissues that yield various cell populations within a given tissue type. Finally, we demonstrate the applicability of CITE-seq for biomarker discovery on metastatic melanoma. Our work provides a blueprint and pipeline for CITE-seq to a broad range of clinically relevant samples, thus allowing for an increasingly detailed resolution of solid tissue specimens and enabling translational studies where protein biomarker profiling could provide better functional descriptions of cell states. We believe that the described protocol will find wide-ranging applications for basic and clinical research.
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Project description:Type 1 Diabetes is still an incurable disease characterized by autoimmune destruction of insulin-producing beta cells within the islet of Langerhans in the pancreas. Currently, there are no methods to monitor beta-cell mass in humans or deliver therapeutics specifically to beta cells. Here we performed Cluster Systematic Evolution of Ligands by Exponential Enrichment (SELEX) experiments and toggle SELEX experiments to identify RNA aptamers specific for human islets. In the cluster SELEX, we started from a random library of RNA nucleotides composed of a 40 nucleotide long variable region flanked by two constant regions. We performed eight selection cycles using hand-picked islets and islet-depleted acinar tissue from 4 cadaveric human donors as positive and negative selectors. In the toggle SELEX, we conducted eight cycles of selection using islets and acinar tissue from mice, followed by two cycles of selection using human tissues. The polyclonal libraries from the two selection strategies showed a convergent evolution of ligands and increased specificity for human islets.
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Project description:We present spatial-CITE-seq for high-plex protein and whole transcriptome co-mapping, which was firstly demonstrated for profiling 189 proteins and transcriptome in multiple mouse tissue types. It was then applied to human tissues to measure 273 proteins and transcriptome that revealed spatially distinct germinal center reaction in tonsil and early immune activation in skin at the COVID-19 mRNA vaccine injection site. Spatial-CITE-seq may find a range of applications in biomedical research.
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Project description:In this study we used single cell multi-omics profiling to create an atlas of the human YS to gain insights into its haematopoietic, metabolic and nutritive functions during early embryonic development. This contains fetal liver CITE-seq (surface protein and cytosolic RNA content) data from six biological replicates. Pooled lanes were demultiplexed using SoupOrCell (for alignment and demultiplexing software and version numbers, please see accompanying manuscript and protocols within this accession). Raw count files provided are directly as output by alignment software, without any quality control applied. Quality control is described in accompanying manuscript methods. Metadata by barcode are provided as supplementary tables in accompanying manuscript.
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