OMAP-10: Multiplexed Antibody-Based Imaging of Human Palatine Tonsil with MACSima v1.0

OMAP-10 was designed for MACSima (MACSima imaging cyclic staining) imaging of paraformaldehyde (PFA)-fixed human tonsil samples. The MACSima technology is described in detail in the following publication (https://doi.org/10.1038/s41598-022-05841-4). Most, but not all, antibodies in this panel are recombinant antibodies with a mutated human IgG1 constant region. The described mutation removes the Fc receptor binding capacity of human IgG1, eliminating the need for additional blocking steps and reducing non-specific binding of human antibodies on human tissues. Highly multiplexed imaging is achieved through cycles of immunolabeling with FITC, PE, and APC conjugated antibodies and photobleaching to eliminate fluorescence signal between imaging cycles. The panel contains 30 antibodies and the nuclear marker DAPI for image alignment and nuclear segmentation. This OMAP provides a spatial context for all anatomical structures and most cell types present in the ASCT+B tonsil table, v1.0 (submitted for review). OMAP-10 follows closely OMAP-1 described for human lymph nodes (https://hubmapconsortium.github.io/ccf-releases/v1.3/docs/omap/omap-1-human-lymph-node-ibex.html). The initial dataset associated with OMAP-10 can be found in this dataset. All reagents were obtained from Miltenyi Biotec and have been rigorously tested through an internal quality control system to have minimal variation between lots. For this reason, lot information is not included in the table below. Analysis was performed by an accompanied software package MACSIQ View Analysis also described in the MACSima publication (https://doi.org/10.1038/s41598-022-05841-4). The plan was to also include the data analysis in the uploaded dataset. However mixing the original data with analyses data would lead to confusion. Therefore only the original image files are included here. This is in brief the image analysis pipeline: the software processes the raw images of the MACSima run, generates stitched images, and then allows downstream analysis including cell segmentation, cell gating, data normalization, dimension reduction plots (tSNE, UMAP), heat maps, distance analyses and cluster analyses, all of which are interactively linked together. The MACSima system is continuously evolving, and this is the first OMAP dataset generated by using the MACSima system (Instrument, Reagents and Software).

The images enclosed are in OME-tif format (16 bit depth). The optical resolution is 0.17 micron/pixel. The imaged area size is 1.6 mm x 1.3 mm. This Data is currently under review by the OMAP community and changes are still possible in the follow up version. The image contains stichted images of 9 fields of view. The complete runtime on the MACSima for this image dataset was about 12 hours on the instrument. The OMAP description also links to the ASCT+B table for the palatine tonsil.

Anatomical Structures, Cell Types, plus Biomarkers (ASCT+B) table for Palatine Tonsil v1.0

Description

Anatomical Structures, Cell Types, plus Biomarkers (ASCT+B) tables aim to capture the nested part of structure of anatomical human body parts, the typology of cells, and biomarkers used to identify cell types. The tables are authored and reviewed by an international team of experts. The Palatine Tonsil ASCT+B table is derived from published literature, public datasets, and unpublished studies from table authors. The Palatine Tonsil is part of the tonsiluar ring of Waldeyer network. In comparison to other Tonsils the Palatine Tonsil has an enlarged lymphoid tissue.

The gene biomarkers are primarily derived from a preprint on an Atlas of Cells of the human tonsil (Ramon Massoni-Badosa et al 2022). The tonsil azimuth data set can be explored here .Cell phenotypes, especially for antibody-based assays like the MACSima are very complex and in its first version, only the basic cell types are listed with many more to be included in the next iteration of the ASCT+B table.  The correlation between protein detection and RNA expression data at the single cell level needs to be established.  In total, this table reports 13 anatomical structures, 17 cell types, and 30 biomarkers. 

The following list contains the file name and the target name of the antibody used in a given staining:

ACTIN_REAL650/ACTA2

Bcl2_REA872/BCL2

CD11c_REAL235/ITGAX

CD138_REA929/SDC1

CD15_VIMC6/FUT4

CD19_REAL106/CD19

CD1c_REA694/CD1C

CD209_REAL1087/CD209

CD20_REA1087/MS4A1

CD21_REA940/CR2

CD274_PDL1/CD274

CD279_REAL531/PDCD1

CD27_REA499/CD27

CD39_REA739/ENTPD1

CD3_REAL1097/CD3E

CD44_REA690/CD44

CD4_REA1307/CD4

CD68_REA1306/CD68

CD79a_REA1142/CD79A

CD8_REA734/CD8A

CollagenIV_REAL1212/COL4A1

Cytokeratin_CK36H5/KRT7,KRT8,KRT18,KRT19

FoxP3_REA1253/FOXP3

HLADR_REAL550/HLA-DRA

IgD_REA740/IGHD

IgM_REAL689/IGHM

Ki67_REA183/MKI67

PlasmaCell_REA908/CKAP4

Vimentin_REA409/VIM