Cited by 119Single-cell and spatial transcriptomicsAdvanced Proteomics Techniques and ApplicationsMolecular Biology Techniques and Applications

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Combined quantification of intracellular (phospho-)proteins and transcriptomics from fixed single cells

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Abstract

Environmental stimuli often lead to heterogeneous cellular responses and transcriptional output. We developed single-cell RNA and Immunodetection (RAID) to allow combined analysis of the transcriptome and intracellular (phospho-)proteins from fixed single cells. RAID successfully recapitulated differentiation-state changes at the protein and mRNA level in human keratinocytes. Furthermore, we show that differentiated keratinocytes that retain high phosphorylated FAK levels, a feature associated with stem cells, also express a selection of stem cell associated transcripts. Our data demonstrates that RAID allows investigation of heterogeneous cellular responses to environmental signals at the mRNA and phospho-proteome level.

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Crossref · 10.1038/s41598-018-37977-7

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Figures

Figure 1 Schematic overview of the RAID workflow. Cells are crosslinked, permeabilized and stained with Antibody RNA-Barcode Conjugates (ARCs) in suspension. Hereafter, cells are sorted into 384-wells plates where crosslinking is reversed and cDNA synthesis is performed using CELseq2 compatible dTV primers. Finally, single-cell samples are pooled and sequencing library preparation is performed using an adapted CELseq2 protocol to incorporate ARC measurements in the library.
Figure 1 Schematic overview of the RAID workflow. Cells are crosslinked, permeabilized and stained with Antibody RNA-Barcode Conjugates (ARCs) in suspension. Hereafter, cells are sorted into 384-wells plates where crosslinking is reversed and cDNA synthesis is performed using CELseq2 compatible dTV primers. Finally, single-cell samples are pooled and sequencing library preparation is performed using an adapted CELseq2 protocol to incorporate ARC measurements in the library.CC BY · PubMed Central
Figure 2 Combined single-cell transcriptomics and antibody-barcode conjugate (ARC) detection from unfixed keratinocytes. (A) Boxplot showing mass spectrometry based analysis of the EGFR to ITGA6 ratio from bulk samples. AG1478 induced differentiation leads to a reduction of the EGFR to ITGA6 ratio. Experiment was performed in triplicate. (B,C) Single-cell analysis of unfixed keratinocytes stained with ARCs for EGFR and ITGA6. Cell were untreated or treated with the EGFR inhibitor AG1478 to induce differentiation. (B) Scatterplot shows the total number of UMI counts that were detected per cell from the transcriptome and from ARCs. Cells that passed the count thresholds for the mRNA (10,000) and ARCs (2,750) are indicated in green. (C) tSNE visualization using principal component 1 to 8 of the variable transcripts. Untreated and AG1478 treated cells form distinct clusters. Different batches of cells are color coded. (D) Featureplot showing the ratio of the UMI counts of EGFR-ARC and ITGA6-ARC for each cell projected on the tSNE coordinates from (C). (E) Ratio of the UMI counts of EGFR-ARC and ITGA6-ARC for control and AG1478 treated cells represented in violin plot.
Figure 2 Combined single-cell transcriptomics and antibody-barcode conjugate (ARC) detection from unfixed keratinocytes. (A) Boxplot showing mass spectrometry based analysis of the EGFR to ITGA6 ratio from bulk samples. AG1478 induced differentiation leads to a reduction of the EGFR to ITGA6 ratio. Experiment was performed in triplicate. (B,C) Single-cell analysis of unfixed keratinocytes stained with ARCs for EGFR and ITGA6. Cell were untreated or treated with the EGFR inhibitor AG1478 to induce differentiation. (B) Scatterplot shows the total number of UMI counts that were detected per cell from the transcriptome and from ARCs. Cells that passed the count thresholds for the mRNA (10,000) and ARCs (2,750) are indicated in green. (C) tSNE visualization using principal component 1 to 8 of the variable transcripts. Untreated and AG1478 treated cells form distinct clusters. Different batches of cells are color coded. (D) Featureplot showing the ratio of the UMI counts of EGFR-ARC and ITGA6-ARC for each cell projected on the tSNE coordinates from (C). (E) Ratio of the UMI counts of EGFR-ARC and ITGA6-ARC for control and AG1478 treated cells represented in violin plot.CC BY · PubMed Central
Figure 3 Effect of the RAID procedure on single-cell transcriptomics quality. Comparison of single-cell transcriptomics quality between unfixed cells and cells that passed the complete RAID procedure including DSP/SPDP based fixation and mock ARC staining. Comparison is based on 40,000 sampled UMI counts per cell. (A) Boxplots showing a mild reduction of the gene complexity after the complete RAID procedure. (B) Scatterplot showing the average expression of genes in unfixed cells and RAID cells. Red line represents the x = y function as a visual aid. (C) Scatterplot showing the relation between the gene detection rate and the average gene expression in unfixed (blue dots) and RAID cells (red circles). (D) Scatterplot showing the relation between the coefficient of variation and the average gene expression in unfixed (blue dots) and RAID cells (red dots). R denotes Pearson Correlation.
Figure 3 Effect of the RAID procedure on single-cell transcriptomics quality. Comparison of single-cell transcriptomics quality between unfixed cells and cells that passed the complete RAID procedure including DSP/SPDP based fixation and mock ARC staining. Comparison is based on 40,000 sampled UMI counts per cell. (A) Boxplots showing a mild reduction of the gene complexity after the complete RAID procedure. (B) Scatterplot showing the average expression of genes in unfixed cells and RAID cells. Red line represents the x = y function as a visual aid. (C) Scatterplot showing the relation between the gene detection rate and the average gene expression in unfixed (blue dots) and RAID cells (red circles). (D) Scatterplot showing the relation between the coefficient of variation and the average gene expression in unfixed (blue dots) and RAID cells (red dots). R denotes Pearson Correlation.CC BY · PubMed Central
Figure 4 RAID analysis shows association of FAK phosphorylation with the expression of stem cell marks. RAID was performed with ARC-based quantification of six antibodies from fixed keratinocytes. Cells were untreated or treated with the EGFR inhibitor AG1478 to induce differentiation. (A) tSNE visualization using principal component 1 to 8 of the variable transcripts. Untreated and AG1478 treated cells form distinct clusters. Different batches of cells are color coded. (B) Violin plots representing the ARC UMI counts for the indicated antibodies, based on a total of 400 sampled ARC counts per cell. (C) Featureplots showing data from B, projected on the tSNE embeddings from (A). (D–G) From the AG1478 treated cells, 50 cells were selected with the highest and lowest pFAK-ARC counts (pFAK-high and pFAK-low, respectively) and analyzed based on proteomic and transcriptomic features. (D) Histograms showing the distribution of UMI counts for the indicated ARCs in pFAK-high (orange) and pFAK-low cells (grey). (E) Boxplots showing the differentiation scores of pFAK-high and pFAK-low cells. (F) Boxplots showing the stem cell scores of pFAK-high and pFAK-low cells. The stem cell score is significantly higher in pFAK-high cells based on two tailed t-test (p = 0.0023). (G) Histograms showing distribution of UMI counts of the indicated integrin substrates per ten cells after 1000x random sampling from pFAK-high (orange), pFAK-low cells (grey) and total AG1478 treated cells (blue dashed line). Transcript UMI counts are based on 4,500 sampled UMI counts per single cell.
Figure 4 RAID analysis shows association of FAK phosphorylation with the expression of stem cell marks. RAID was performed with ARC-based quantification of six antibodies from fixed keratinocytes. Cells were untreated or treated with the EGFR inhibitor AG1478 to induce differentiation. (A) tSNE visualization using principal component 1 to 8 of the variable transcripts. Untreated and AG1478 treated cells form distinct clusters. Different batches of cells are color coded. (B) Violin plots representing the ARC UMI counts for the indicated antibodies, based on a total of 400 sampled ARC counts per cell. (C) Featureplots showing data from B, projected on the tSNE embeddings from (A). (D–G) From the AG1478 treated cells, 50 cells were selected with the highest and lowest pFAK-ARC counts (pFAK-high and pFAK-low, respectively) and analyzed based on proteomic and transcriptomic features. (D) Histograms showing the distribution of UMI counts for the indicated ARCs in pFAK-high (orange) and pFAK-low cells (grey). (E) Boxplots showing the differentiation scores of pFAK-high and pFAK-low cells. (F) Boxplots showing the stem cell scores of pFAK-high and pFAK-low cells. The stem cell score is significantly higher in pFAK-high cells based on two tailed t-test (p = 0.0023). (G) Histograms showing distribution of UMI counts of the indicated integrin substrates per ten cells after 1000x random sampling from pFAK-high (orange), pFAK-low cells (grey) and total AG1478 treated cells (blue dashed line). Transcript UMI counts are based on 4,500 sampled UMI counts per single cell.CC BY · PubMed Central

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Metadata

Authors
Gerlach, J. P., van Buggenum, J. A. G., Tanis, S. E. J., Hogeweg, M., Heuts, B. M. H., Muraro, M. J., Elze, L., Rivello, F., Rakszewska, A., van Oudenaarden, A., Huck, W. T. S., Stunnenberg, H. G., & Mulder, K. W.
Affiliations
  • Radboud University Nijmegen (NL)
  • Royal Netherlands Academy of Arts and Sciences (NL)
Corresponding author
Mulder, Klaas W.
Venue
Scientific Reports
Published
2019-02-06
Volume
9
Issue
1
Pages
1469-1469
ISSN
2045-2322 (ISSN-L)
OpenAlex
W2810689242
Cited by
104
References
35
Citations by year
2026: 10 · 2025: 11 · 2024: 13 · 2023: 21 · 2022: 15 · 2021: 20 · 2020: 8 · 2019: 5
FWCI
3.97
Type
journal article
Language
en
Open access
Locations
  • Scientific Reports (publishedVersion, cc-by)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion)
  • Europe PMC (PubMed Central) (publishedVersion, other-oa)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • KNAW research portal (Royal Academy of Art and Sciences (KNAW)) (publishedVersion, other-oa)
  • Data Archiving and Networked Services (DANS) (submittedVersion, other-oa)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
  • Radboud Repository (Radboud University) (submittedVersion)
  • Radboud Repository (Radboud University) (submittedVersion, other-oa)
Funders
  • EC | European Research Council (339431)
  • Nederlandse Organisatie voor Wetenschappelijk Onderzoek (864.12.010)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
  • Physical Sciences › Chemistry › Spectroscopy › Advanced Proteomics Techniques and Applications
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Molecular Biology Techniques and Applications
Keywords
single-cell proteomics, phosphoproteomics, transcriptome, protein expression, keratinocytes, keratinocyte differentiation, focal adhesion kinase phosphorylation, stem cell markers, cellular heterogeneity, environmental stimuli
MeSH terms
Cell Differentiation, Cells, Cultured, Gene Expression Regulation, Humans, Phosphorylation, Quinazolines, Keratinocytes, Tissue Fixation, Tyrphostins, Gene Expression Profiling, Proteomics, Focal Adhesion Kinase 1, Single-Cell Analysis

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