Image Analysis to Characterize uNK Cell Subtypes in Early Pregnancy Using Multiplex Immunohistochemistry

To begin, image the endometrial tissue sections after staining with appropriate antibodies. To import multispectral images, navigate to File and then Open image in the software interface. Click Select Fluorophores and choose the appropriate spectral library to unmix the fluorophores and click OK to confirm.

Isolate the autofluorescence spectrum using the AF eyedropper tool to sample a representative tissue area from the AF image and label the four cell surface markers and assign specific colors for identification. Click Prepare Image or Prepare All to finalize preparation. For tissue segmentation, manually delineate three to five regions per tissue type, including epithelial, stromal, and blank areas.

Adjust regions and parameters as needed to improve the training dataset, enhancing the software's accuracy in identifying tissue structures. Under segment cells, select Nuclei and Membrane. Choose DAPI to identify cell nuclei and adjust the intensity setting to detect all cell nuclei without background noise.

Select CD16, CD49A, and CD56 signals to find the membrane and assist in nuclear splitting. Use the nuclear component splitting feature to distinguish closely-located nuclei. In the phenotyping scheme, adopt the CD56, CD49A, CXCR4, and CD16 markers for cell phenotyping.

Use the Add button to categorize cells as positively or negatively expressing each marker. Manually label at least five cells for each phenotype during the training process. After configuring cell phenotyping, the software will indicate the expression of surface markers for each cell.

Export the data to a spreadsheet for further analysis. The novel classification strategy identified four NK cell subtypes based on the expression of CD49A and CXCR4.