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Trisedta antigen retrieval buffer

Manufactured by Abcam

100× TrisEDTA Antigen Retrieval Buffer is a concentrated solution formulated for the retrieval of antigens in tissue sections prior to immunohistochemical staining. It is designed to be diluted to working concentration before use.

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2 protocols using trisedta antigen retrieval buffer

1

Antigen Retrieval for Immunohistochemistry

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Sections were deparaffinized in successive incubations with xylene and decreasing concentrations (100, 95, 75, 50, 0%) of ethanol. Antigen retrieval was achieved using either Abcam 100× Citrate Antigen Retrieval Buffer (pH = 6.00) for 20 min at 100 °C, followed by 20 min at ambient temperature or Abcam 100× TrisEDTA Antigen Retrieval Buffer (pH = 9) heated to 115 °C under high pressure. Sections were then washed in either a solution of 10 mM glycine and 0.2% sodium azide in phosphate buffered saline or PBS + 0.1% Tween20 before antibody staining.
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2

Multiplexed Immunofluorescence Imaging Analysis

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Sections were deparaffinized in successive incubations with xylene and decreasing concentrations (100, 95, 75, 50, 0%) of EtOH in ddH2O. Antigen retrieval utilized Abcam 100× TrisEDTA Antigen Retrieval Buffer (pH=9) heated under high pressure and washed in phosphate buffered saline (PBS)+0.1% Tween 20. Sections were blocked for 30 min with 10% goat serum in 1×PBS+0.1% Tween 20 before staining. Primary antibodies were used at a concentration of 1:100 (MHC-II) or 1:150 (CD8, TCF-1) and incubated for 1 hour at room temperature. Secondary antibodies were used at a concentration of 1:250 (A488, A568) or 1:500 (A647) and incubated for 30 min at room temperature. Details about antibodies used are listed in table 2. Sections were counterstained with 4’,6-diamidino-2-pehnylindole (DAPI) according to manufacturer instructions (Thermo Fisher). IF images were collected using a Zeiss Z.1 Slide Scanner equipped with a Colibri 7 Flexible Light Source, and Zeiss ZenBlue software was used for post-acquisition image processing. CellProfiler42 43 (link) and custom R and python scripts were used for image analysis, as previously described,44 (link) to determine the xy coordinates of cells within tissue slices, measure fluorescence intensity within each cell, calculate cellular density, and create spatial maps of features within the tissue.
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