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Anti mouse cd16 32 clone 13

Manufactured by BioLegend

Anti-mouse CD16/32 (clone 93) is a monoclonal antibody that binds to the mouse CD16 and CD32 cell surface antigens. It is commonly used in flow cytometry applications to block Fc receptors.

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2 protocols using anti mouse cd16 32 clone 13

1

Single-cell Lymph Node and Tumor Profiling

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Single-cell suspensions from draining lymph nodes or tumor cell suspensions were incubated with anti-mouse CD16/32 (clone 13; BioLegend) to block Fc receptors for 10 min on ice and fixed for 20 min at room temperature, followed by washing with permeabilization buffer (Foxp3/Transcription Factor Staining Buffer Kit; TONBO). Cells were incubated with fluorescent antibodies in a permeabilization buffer for either 1 h at room temperature or overnight at 4°C. FACS Abs were purchased from BioLegend, Cell Signaling Technology, or Santa Cruz Biotechnology and included CD3 (145-2C11), Tubulin (YOL 1/34), CD8b (YTS156.7.7), PD-1 (RMP-1-30), and TCF1 (C63D9). Following staining, cells were washed with permeabilization buffer and stained in 0.01 mg/ML DAPI (Thermo Fisher) for 5 min before suspending in PBS for analysis using the Amnis ImageStreamX MkII imaging cytometer. Images were collected at 60× magnification, compensated using single stain controls from the spleen of tumor-challenged mice, and gated and processed using the IDEAS V6.2 software.
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2

Multiparametric Flow Cytometry Profiling

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Single cell suspensions from murine peripheral blood or tumor cell suspensions were incubated with anti-mouse CD16/32 (clone 13; BioLegend) to block Fc receptors and stained with fluorescent-labeled antibodies. Prior to staining intracellular proteins, cells were fixed and permeabilized by FoxP3/Transcription Factor Staining Buffer Kit (TONBO). FACS antibodies were purchased from BioLegend, Cell Signaling Technology, Invitrogen, or BD Biosciences and included: CD3 (145–2C11), CD8b (YTS156.7.7), CD4 (RM4–5), CD62L (MEL-14), CD44 (IM7), TCF1 (C63D9), FoxP33 (MF-14), pS63 (D57.2.E). Flow cytometric data was analyzed with Flowjo V10.
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