Spatial-CITE-seq: spatially resolved high-plex protein and whole transcriptome co-mapping

  1. Yang Liu
  2. Marcello DiStasio
  3. Graham Su
  4. Hiromitsu Asashima
  5. Archibald Enninful
  6. Xiaoyu Qin
  7. Yanxiang Deng
  8. Pino Bordignon
  9. Marco Cassano
  10. Mary Tomayko
  11. Mina Xu
  12. Stephanie Halene
  13. Joseph E. Craft
  14. David Hafler
  15. Rong Fan

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Abstract

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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  1. ScreenIT

    SciScore for 10.1101/2022.04.01.486788: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Ethicsnot detected.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Cell Line AuthenticationAuthentication: Fluorescent staining of human tonsil: Multiplex immunolabeling on FFPE human tonsil sections was performed by sequential IF staining on COMET™ using the FFeX technology previously described by Lunaphore Technologies13, 20.

    Table 2: Resources

    Antibodies
    SentencesResources
    DNA oligos and antibody-derived DNA tags: DNA oligos used were all synthesized by Integrated DNA Technologies with HPLC purification.
    antibody-derived DNA
    suggested: None
    Antibody-derived DNA tags for membrane proteins were purchased from Biolegend and listed in Table S5.
    Antibody-derived DNA tags
    suggested: None
    Software and Algorithms
    SentencesResources
    The product was purified with 1.6X SPRI beads and then quantified with QuBit and BioAnalyzer.
    BioAnalyzer
    suggested: (BioAnalyzer 2100, RRID:SCR_019715)
    Data preprocessing: For cDNAs derived from mRNAs, the raw fastq file of Read 2 containing the UMI, barcode A and barcode B regions, were first reformatted into the standard input format required by ST pipeline v1.7.2 21 using customized python script.
    python
    suggested: (IPython, RRID:SCR_001658)
    Using recommended ST pipeline parameters, the read 1 was STAR mapped to either the mouse genome (GRCm38) or the human genome (GRCh38).
    STAR
    suggested: (STAR, RRID:SCR_004463)
    All the heatmap was plotted using ggplot2. scRNA-seq and spatial data integration: The cell types of skin biopsy section were annotated through integration analysis using the matched scRNA-seq data as the reference.
    ggplot2
    suggested: (ggplot2, RRID:SCR_014601)

    Results from OddPub: Thank you for sharing your code.

    Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    Results from scite Reference Check: We found no unreliable references.

    About SciScore

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  2. Version published to 10.1101/2022.04.01.486788v1 on bioRxiv