<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>SAP and EAT-2 are intracellular adaptor proteins that link SLAMF receptors to downstream intracellular signalling pathways. Their expression and functions vary among different types of hematopoietic cells. The roles of SAP and EAT-2 in haematological malignancies are poorly understood. Here, we attempted to optimise a method for the detection of intracellular SAP and EAT-2 by flow cytometry. We found that using PerFix EXPOSE kit for cell fixation and permeabilization ensures optimal results in terms of staining intensity and signal-to-noise ratio.</p>
</abstract>

SAP and EAT-2 are intracellular adaptor proteins that link SLAMF receptors to downstream intracellular signalling pathways. Their expression and functions vary among different types of hematopoietic cells. The roles of SAP and EAT-2 in haematological malignancies are poorly understood. Here, we attempted to optimise a method for the detection of intracellular SAP and EAT-2 by flow cytometry. We found that using PerFix EXPOSE kit for cell fixation and permeabilization ensures optimal results in terms of staining intensity and signal-to-noise ratio.


<div xmlns="http://www.w3.org/1999/xhtml">
<sec id="j_afpuc-2022-0007_s_001"><div>INTRODUCTION</div>
<p>The SLAM (Signalling Lymphocyte Activation Molecule) family is a group of nine surface receptors (SLAMF1-9) expressed mainly on hematopoietic cells, that regulate the activation and differentiation of a wide range of immune cells involved in both innate and adaptive immune responses (<a ref-type="bibr" href="#j_afpuc-2022-0007_ref_001">Calpe et al., 2008</a>; <a ref-type="bibr" href="#j_afpuc-2022-0007_ref_002">Cannons et al., 2011</a>; <a ref-type="bibr" href="#j_afpuc-2022-0007_ref_003">Detre et al., 2012</a>). SLAMF receptors interact with intracellular SLAM-associated protein (SAP)-related molecules that link SLAMF receptors to downstream intracellular signalling pathways. In T, NK, and NKT cells, SLAMF receptors interact with SAP. In mature B cells, SLAMF receptors induce a downstream cascade through EAT-2 (<a ref-type="bibr" href="#j_afpuc-2022-0007_ref_007">Tangye et al., 2002</a>; <a ref-type="bibr" href="#j_afpuc-2022-0007_ref_008">Veillette, 2006</a>; <a ref-type="bibr" href="#j_afpuc-2022-0007_ref_005">Radomir et al., 2017</a>). This work’s aim is the optimisation of flow cytometry method for the detection of intracellular SAP and EAT-2.</p>
</sec>
<sec id="j_afpuc-2022-0007_s_002"><div>MATERIAL AND METHODS</div>
<p>Peripheral blood was obtained from a healthy donor (M.S., corresponding author). The expression of intracellular/cytoplasmic SAP (cySAP) and EAT-2 (cyEAT-2) was studied with multiparametric flow cytometry. Samples were stained with combinations of monoclonal antibodies as shown in <a ref-type="table" href="#j_afpuc-2022-0007_tab_001">Table 1</a>. Rat anti-SAP-PE monoclonal antibody (Invitrogen, USA) and rabbit anti-EAT-2 antibody (Proteintech, UK) with secondary donkey anti-rabbit IgG-PE antibody (BioLegend, USA) were used for the detection of cySAP and cyEAT-2, respectively. Four different commercial kits were employed for cell fixation and permeabilization: Fix &amp; Perm Cell Permeabilization Reagents (Invitrogen, USA), Transcription Factor Buffer Set (BD Pharmingen, USA), IntraPrep Permeabilization Reagent and PerFix EXPOSE Kit (both Beckman Coulter, USA). Manufacturers’ instructions were closely followed. Samples were acquired using Navios EX flow cytometer (Beckman Coulter, USA). Data were analysed using Infinicyt software (Cytognos, Spain). The intensity of cySAP and cyEAT-2 expression was expressed as MFI (mean fluorescence intensity) value.</p>
<table-wrap id="j_afpuc-2022-0007_tab_001" position="float"><label>Table 1</label><caption><p>Panel of antibodies.</p></caption>
<table frame="box" rules="all">
<thead>
<tr>
<th align="center" valign="middle"></th>
<th colspan="10" align="center" valign="middle"><bold>Antibodies and fluorochromes</bold></th>
</tr>
<tr>
<th align="center" valign="middle"><bold>Tube No.</bold></th>
<th align="center" valign="middle"><bold>PB</bold></th>
<th align="center" valign="middle"><bold>KO</bold></th>
<th align="center" valign="middle"><bold>FITC</bold></th>
<th align="center" valign="middle"><bold>PE</bold></th>
<th align="center" valign="middle"><bold>ECD</bold></th>
<th align="center" valign="middle"><bold>PC5.5</bold></th>
<th align="center" valign="middle"><bold>PC7</bold></th>
<th align="center" valign="middle"><bold>APC</bold></th>
<th align="center" valign="middle"><bold>APC-A700</bold></th>
<th align="center" valign="middle"><bold>APC-A750</bold></th>
</tr>
</thead>
<tbody>
<tr>
<td align="center" valign="middle">1</td>
<td align="center" valign="middle">CD4 + CD20</td>
<td align="center" valign="middle">CD45</td>
<td align="center" valign="middle">-</td>
<td align="center" valign="middle">cyCTRL</td>
<td align="center" valign="middle">-</td>
<td align="center" valign="middle">CD5</td>
<td align="center" valign="middle">CD10</td>
<td align="center" valign="middle">CD3</td>
<td align="center" valign="middle">CD19</td>
<td align="center" valign="middle">CD8</td>
</tr>
<tr>
<td align="center" valign="middle">2</td>
<td align="center" valign="middle">CD4 + CD20</td>
<td align="center" valign="middle">CD45</td>
<td align="center" valign="middle">-</td>
<td align="center" valign="middle">cySAP</td>
<td align="center" valign="middle">-</td>
<td align="center" valign="middle">CD5</td>
<td align="center" valign="middle">CD10</td>
<td align="center" valign="middle">CD3</td>
<td align="center" valign="middle">CD19</td>
<td align="center" valign="middle">CD8</td>
</tr>
<tr>
<td align="center" valign="middle">3</td>
<td align="center" valign="middle">CD4 + CD20</td>
<td align="center" valign="middle">CD45</td>
<td align="center" valign="middle">-</td>
<td align="center" valign="middle">cyCTRL +sec.Ab</td>
<td align="center" valign="middle">-</td>
<td align="center" valign="middle">CD5</td>
<td align="center" valign="middle">CD10</td>
<td align="center" valign="middle">CD3</td>
<td align="center" valign="middle">CD19</td>
<td align="center" valign="middle">CD8</td>
</tr>
<tr>
<td align="center" valign="middle">4</td>
<td align="center" valign="middle">CD4 + CD20</td>
<td align="center" valign="middle">CD45</td>
<td align="center" valign="middle">-</td>
<td align="center" valign="middle">cyEAT-2 +sec.Ab</td>
<td align="center" valign="middle">-</td>
<td align="center" valign="middle">CD5</td>
<td align="center" valign="middle">CD10</td>
<td align="center" valign="middle">CD3</td>
<td align="center" valign="middle">CD19</td>
<td align="center" valign="middle">CD8</td>
</tr>
</tbody>
</table>
</table-wrap>
</sec>
<sec id="j_afpuc-2022-0007_s_003"><div>RESULTS AND DISCUSSION</div>
<p>Flow cytometric detection of intracellular (cytoplasmic or nuclear) versus cell surface antigens is significantly more laborious and time-consuming. It requires cell fixation, usually with paraformaldehyde, followed by permeabilization with Triton-X or saponin. Unfortunately, these procedures lead to significant cell damage, changes in forward and side scatter characteristics of cells and increased autofluorescence, which may complicate subsequent data analysis. Here, we compared four different commercial fixation and permeabilization kits with the aim to optimise methodology for the detection of intracellular/cytoplasmic SAP and EAT-2 proteins by flow cytometry.</p>
<p>In clinical flow cytometry laboratories, Fix &amp; Perm and IntraPrep reagents belong to the most widely used kits for the detection of diagnostically important intracellular antigens. In our study, Fix &amp; Perm showed unsatisfactory performance when used for cySAP staining as reflected by the very low MFI of stained cells (<a ref-type="fig" href="#j_afpuc-2022-0007_fig_001">Figure 1</a>, <a ref-type="table" href="#j_afpuc-2022-0007_tab_002">Table 2</a>). For that reason, it was not further evaluated for cyEAT-2 detection. In contrast, the usage of IntraPrep resulted in a significantly stronger cySAP and cyEAT-2 staining in terms of MFI and a good signal-to-noise ratio. TFBS reagent led to a stronger cySAP staining than Fix &amp; Perm but weaker than IntraPrep. Since the staining procedure using TFBS versus other reagents is significantly more time-consuming (approximately 3 hours versus approximately 1 hour), we decided not to evaluate it further. Finally, we used the PerFix kit. Originally developed for the detection of phosphorylated intracellular antigens, PerFix gave the best results in terms of cySAP and cyEAT-2 staining intensity and signal-to-noise ratio. Furthermore, it enabled separation of T cells, B cells, and NK cells based on the intensity of cySAP and cyEAT-2 expression. Previously, other authors who analysed cySAP and/or cyEAT-2 by flow cytometry reported only on the use of the traditional paraformaldehyde/Triton-X method (<a ref-type="bibr" href="#j_afpuc-2022-0007_ref_006">Schlums et al., 2015</a>; <a ref-type="bibr" href="#j_afpuc-2022-0007_ref_005">Radomir et al., 2017</a>; <a ref-type="bibr" href="#j_afpuc-2022-0007_ref_004">Gyurova et al., 2019</a>). To conclude, we identified the staining procedure employing PerFix EXPOSE kit for cell fixation and permeabilization as the optimal method for cySAP and cyEAT-2 detection.</p>
<figure id="j_afpuc-2022-0007_fig_001" position="float" fig-type="figure"><h2>Figure 1</h2>
<figCaption><p>Illustrative bivariate dotplots showing the results of cySAP (A) and cyEAT-2 (B) analysis by flow cytometry: control (unstained) cells (grey), T cells (light green), B cells (dark green), NK cells (blue), monocytes (yellow), neutrophils (violet) and eosinophils (pink).</p></figCaption>
<img xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="graphic/j_afpuc-2022-0007_fig_001.jpg" src="https://sciendo-parsed.s3.eu-central-1.amazonaws.com/6470850a71e4585e08a9f127/j_afpuc-2022-0007_fig_001.jpg?X-Amz-Algorithm=AWS4-HMAC-SHA256&amp;X-Amz-Date=20240518T105321Z&amp;X-Amz-SignedHeaders=host&amp;X-Amz-Expires=18000&amp;X-Amz-Credential=AKIA6AP2G7AKP25APDM2%2F20240518%2Feu-central-1%2Fs3%2Faws4_request&amp;X-Amz-Signature=7b975438c263a46252466d282adb95eda03d9c2fb471b4da5b5609da61bcea05" class="mw-100"/>
</figure>
<table-wrap id="j_afpuc-2022-0007_tab_002" position="float"><label>Table 2</label><caption><p>Flow cytometric analysis of SAP and EAT-2 adaptor proteins in lymphocytes.</p></caption>
<table frame="box" rules="all">
<thead>
<tr>
<th align="center" valign="middle"></th>
<th align="center" valign="middle"></th>
<th align="center" valign="middle"></th>
<th colspan="3" align="center" valign="middle"><bold>MFI control (unstained) cells</bold></th>
<th colspan="3" align="center" valign="middle"><bold>MFI stained cells</bold></th>
</tr>
<tr>
<th align="center" valign="middle"></th>
<th align="center" valign="middle"></th>
<th align="center" valign="middle"></th>
<th align="center" valign="middle"><bold>Mean</bold></th>
<th align="center" valign="middle"><bold>SD</bold></th>
<th align="center" valign="middle"><bold>CV</bold></th>
<th align="center" valign="middle"><bold>Mean</bold></th>
<th align="center" valign="middle"><bold>SD</bold></th>
<th align="center" valign="middle"><bold>CV</bold></th>
</tr>
</thead>
<tbody>
<tr>
<td align="center" valign="middle" rowspan="12"><bold>cySAP</bold></td>
<td align="center" valign="middle" rowspan="4">T cells</td>
<td align="center" valign="middle">Fix&amp;Perm</td>
<td align="center" valign="middle">3.1</td>
<td align="center" valign="middle">1.2</td>
<td align="center" valign="middle">39.6</td>
<td align="center" valign="middle">4.8</td>
<td align="center" valign="middle">1.6</td>
<td align="center" valign="middle">32.7</td>
</tr>
<tr>
<td align="center" valign="middle">TFBS</td>
<td align="center" valign="middle">2.7</td>
<td align="center" valign="middle">1.3</td>
<td align="center" valign="middle">47.9</td>
<td align="center" valign="middle">17.1</td>
<td align="center" valign="middle">11.5</td>
<td align="center" valign="middle">67.5</td>
</tr>
<tr>
<td align="center" valign="middle">IntraPrep</td>
<td align="center" valign="middle">3.8</td>
<td align="center" valign="middle">0.9</td>
<td align="center" valign="middle">22.6</td>
<td align="center" valign="middle">23.9</td>
<td align="center" valign="middle">10.3</td>
<td align="center" valign="middle">43.1</td>
</tr>
<tr>
<td align="center" valign="middle">PerFix</td>
<td align="center" valign="middle">4.9</td>
<td align="center" valign="middle">2.0</td>
<td align="center" valign="middle">41.3</td>
<td align="center" valign="middle">73.9</td>
<td align="center" valign="middle">54.2</td>
<td align="center" valign="middle">73.3</td>
</tr>
<tr>
<td align="center" valign="middle" rowspan="4">B cells</td>
<td align="center" valign="middle">Fix&amp;Perm</td>
<td align="center" valign="middle">1.6</td>
<td align="center" valign="middle">0.6</td>
<td align="center" valign="middle">36.9</td>
<td align="center" valign="middle">4.0</td>
<td align="center" valign="middle">1.9</td>
<td align="center" valign="middle">47.3</td>
</tr>
<tr>
<td align="center" valign="middle">TFBS</td>
<td align="center" valign="middle">1.1</td>
<td align="center" valign="middle">0.2</td>
<td align="center" valign="middle">15.2</td>
<td align="center" valign="middle">10.0</td>
<td align="center" valign="middle">7.0</td>
<td align="center" valign="middle">70.3</td>
</tr>
<tr>
<td align="center" valign="middle">IntraPrep</td>
<td align="center" valign="middle">3.5</td>
<td align="center" valign="middle">1.0</td>
<td align="center" valign="middle">26.8</td>
<td align="center" valign="middle">15.7</td>
<td align="center" valign="middle">12.2</td>
<td align="center" valign="middle">77.9</td>
</tr>
<tr>
<td align="center" valign="middle">PerFix</td>
<td align="center" valign="middle">2.7</td>
<td align="center" valign="middle">0.7</td>
<td align="center" valign="middle">27.1</td>
<td align="center" valign="middle">28.9</td>
<td align="center" valign="middle">27.3</td>
<td align="center" valign="middle">94.8</td>
</tr>
<tr>
<td align="center" valign="middle" rowspan="4">NK cells</td>
<td align="center" valign="middle">Fix&amp;Perm</td>
<td align="center" valign="middle">1.8</td>
<td align="center" valign="middle">0.6</td>
<td align="center" valign="middle">30.9</td>
<td align="center" valign="middle">4.5</td>
<td align="center" valign="middle">2.4</td>
<td align="center" valign="middle">54.0</td>
</tr>
<tr>
<td align="center" valign="middle">TFBS</td>
<td align="center" valign="middle">1.2</td>
<td align="center" valign="middle">0.4</td>
<td align="center" valign="middle">32.3</td>
<td align="center" valign="middle">18.9</td>
<td align="center" valign="middle">9.1</td>
<td align="center" valign="middle">48.1</td>
</tr>
<tr>
<td align="center" valign="middle">IntraPrep</td>
<td align="center" valign="middle">4.0</td>
<td align="center" valign="middle">0.8</td>
<td align="center" valign="middle">19.5</td>
<td align="center" valign="middle">22.6</td>
<td align="center" valign="middle">9.5</td>
<td align="center" valign="middle">42.1</td>
</tr>
<tr>
<td align="center" valign="middle">PerFix</td>
<td align="center" valign="middle">2.4</td>
<td align="center" valign="middle">0.6</td>
<td align="center" valign="middle">23.4</td>
<td align="center" valign="middle">49.9</td>
<td align="center" valign="middle">22.6</td>
<td align="center" valign="middle">45.4</td>
</tr>
<tr>
<td align="center" valign="middle" rowspan="12"><bold>cyEAT-2</bold></td>
<td align="center" valign="middle" rowspan="4">T cells</td>
<td align="center" valign="middle">Fix&amp;Perm</td>
<td align="center" valign="middle">ND</td>
<td align="center" valign="middle">ND</td>
<td align="center" valign="middle">ND</td>
<td align="center" valign="middle">ND</td>
<td align="center" valign="middle">ND</td>
<td align="center" valign="middle">ND</td>
</tr>
<tr>
<td align="center" valign="middle">TFBS</td>
<td align="center" valign="middle">ND</td>
<td align="center" valign="middle">ND</td>
<td align="center" valign="middle">ND</td>
<td align="center" valign="middle">ND</td>
<td align="center" valign="middle">ND</td>
<td align="center" valign="middle">ND</td>
</tr>
<tr>
<td align="center" valign="middle">IntraPrep</td>
<td align="center" valign="middle">4.0</td>
<td align="center" valign="middle">0.9</td>
<td align="center" valign="middle">21.7</td>
<td align="center" valign="middle">83.9</td>
<td align="center" valign="middle">46.3</td>
<td align="center" valign="middle">55.1</td>
</tr>
<tr>
<td align="center" valign="middle">PerFix</td>
<td align="center" valign="middle">5.8</td>
<td align="center" valign="middle">2.1</td>
<td align="center" valign="middle">36.8</td>
<td align="center" valign="middle">192.5</td>
<td align="center" valign="middle">64.6</td>
<td align="center" valign="middle">33.6</td>
</tr>
<tr>
<td align="center" valign="middle" rowspan="4">B cells</td>
<td align="center" valign="middle">Fix&amp;Perm</td>
<td align="center" valign="middle">ND</td>
<td align="center" valign="middle">ND</td>
<td align="center" valign="middle">ND</td>
<td align="center" valign="middle">ND</td>
<td align="center" valign="middle">ND</td>
<td align="center" valign="middle">ND</td>
</tr>
<tr>
<td align="center" valign="middle">TFBS</td>
<td align="center" valign="middle">ND</td>
<td align="center" valign="middle">ND</td>
<td align="center" valign="middle">ND</td>
<td align="center" valign="middle">ND</td>
<td align="center" valign="middle">ND</td>
<td align="center" valign="middle">ND</td>
</tr>
<tr>
<td align="center" valign="middle">IntraPrep</td>
<td align="center" valign="middle">3.7</td>
<td align="center" valign="middle">0.9</td>
<td align="center" valign="middle">24.2</td>
<td align="center" valign="middle">63.1</td>
<td align="center" valign="middle">37.3</td>
<td align="center" valign="middle">59.1</td>
</tr>
<tr>
<td align="center" valign="middle">PerFix</td>
<td align="center" valign="middle">3.7</td>
<td align="center" valign="middle">1.3</td>
<td align="center" valign="middle">35.2</td>
<td align="center" valign="middle">189.0</td>
<td align="center" valign="middle">60.9</td>
<td align="center" valign="middle">32.2</td>
</tr>
<tr>
<td align="center" valign="middle" rowspan="4">NK cells</td>
<td align="center" valign="middle">Fix&amp;Perm</td>
<td align="center" valign="middle">ND</td>
<td align="center" valign="middle">ND</td>
<td align="center" valign="middle">ND</td>
<td align="center" valign="middle">ND</td>
<td align="center" valign="middle">ND</td>
<td align="center" valign="middle">ND</td>
</tr>
<tr>
<td align="center" valign="middle">TFBS</td>
<td align="center" valign="middle">ND</td>
<td align="center" valign="middle">ND</td>
<td align="center" valign="middle">ND</td>
<td align="center" valign="middle">ND</td>
<td align="center" valign="middle">ND</td>
<td align="center" valign="middle">ND</td>
</tr>
<tr>
<td align="center" valign="middle">IntraPrep</td>
<td align="center" valign="middle">4.2</td>
<td align="center" valign="middle">1.0</td>
<td align="center" valign="middle">24.0</td>
<td align="center" valign="middle">211.2</td>
<td align="center" valign="middle">178.6</td>
<td align="center" valign="middle">84.6</td>
</tr>
<tr>
<td align="center" valign="middle">PerFix</td>
<td align="center" valign="middle">3.1</td>
<td align="center" valign="middle">0.7</td>
<td align="center" valign="middle">23.1</td>
<td align="center" valign="middle">537.7</td>
<td align="center" valign="middle">227.3</td>
<td align="center" valign="middle">42.3</td>
</tr>
</tbody>
</table>
</table-wrap>
</sec>
</div>

Optimisation of flow cytometric detection of intracellular SLAMF receptor-associated adaptor proteins SAP and EAT-2

Department of Pharmacology, Faculty of Medicine

Department of Hematology and Oncohematology, L. Pasteur University Hospital and Faculty of Medicine

Department of Pharmaceutical Technology, Pharmacognosy and Pharmaceutical Botany

University of Veterinary Medicine and Pharmacy

European Pharmaceutical Journal

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

SAP and EAT-2 are intracellular adaptor proteins that link SLAMF receptors to downstream intracellular signalling pathways. Their expression and functions vary...

Optimisation of flow cytometric detection of intracellular SLAMF receptor-associated adaptor proteins SAP and EAT-2

Article Category: Short communication

Publié en ligne: 18 juin 2022

Pages: 87 - 89

Reçu: 21 avr. 2022

Accepté: 10 mai 2022

DOI: https://doi.org/10.2478/afpuc-2022-0007

Mots clés
SLAMF receptors, SAP, EAT-2, lymphocytes, flow cytometry

© 2022 Mykhailo Huniadi et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Figure 1

Flow cytometric analysis of SAP and EAT-2 adaptor proteins in lymphocytes.

Panel of antibodies.

			MFI control (unstained) cells			MFI stained cells
			Mean	SD	CV	Mean	SD	CV
cySAP	T cells	Fix&Perm	3.1	1.2	39.6	4.8	1.6	32.7
		TFBS	2.7	1.3	47.9	17.1	11.5	67.5
		IntraPrep	3.8	0.9	22.6	23.9	10.3	43.1
		PerFix	4.9	2.0	41.3	73.9	54.2	73.3
	B cells	Fix&Perm	1.6	0.6	36.9	4.0	1.9	47.3
		TFBS	1.1	0.2	15.2	10.0	7.0	70.3
		IntraPrep	3.5	1.0	26.8	15.7	12.2	77.9
		PerFix	2.7	0.7	27.1	28.9	27.3	94.8
	NK cells	Fix&Perm	1.8	0.6	30.9	4.5	2.4	54.0
		TFBS	1.2	0.4	32.3	18.9	9.1	48.1
		IntraPrep	4.0	0.8	19.5	22.6	9.5	42.1
		PerFix	2.4	0.6	23.4	49.9	22.6	45.4
cyEAT-2	T cells	Fix&Perm	ND	ND	ND	ND	ND	ND
		TFBS	ND	ND	ND	ND	ND	ND
		IntraPrep	4.0	0.9	21.7	83.9	46.3	55.1
		PerFix	5.8	2.1	36.8	192.5	64.6	33.6
	B cells	Fix&Perm	ND	ND	ND	ND	ND	ND
		TFBS	ND	ND	ND	ND	ND	ND
		IntraPrep	3.7	0.9	24.2	63.1	37.3	59.1
		PerFix	3.7	1.3	35.2	189.0	60.9	32.2
	NK cells	Fix&Perm	ND	ND	ND	ND	ND	ND
		TFBS	ND	ND	ND	ND	ND	ND
		IntraPrep	4.2	1.0	24.0	211.2	178.6	84.6
		PerFix	3.1	0.7	23.1	537.7	227.3	42.3

	Antibodies and fluorochromes
Tube No.	PB	KO	FITC	PE	ECD	PC5.5	PC7	APC	APC-A700	APC-A750
1	CD4 + CD20	CD45	-	cyCTRL	-	CD5	CD10	CD3	CD19	CD8
2	CD4 + CD20	CD45	-	cySAP	-	CD5	CD10	CD3	CD19	CD8
3	CD4 + CD20	CD45	-	cyCTRL +sec.Ab	-	CD5	CD10	CD3	CD19	CD8
4	CD4 + CD20	CD45	-	cyEAT-2 +sec.Ab	-	CD5	CD10	CD3	CD19	CD8

Optimisation of flow cytometric detection of intracellular SLAMF receptor-associated adaptor proteins SAP and EAT-2

Article Category: Short communication

Publié en ligne: 18 juin 2022

Pages: 87 - 89

Reçu: 21 avr. 2022

Accepté: 10 mai 2022

DOI: https://doi.org/10.2478/afpuc-2022-0007

Mots clésSLAMF receptors, SAP, EAT-2, lymphocytes, flow cytometry

© 2022 Mykhailo Huniadi et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Figure 1

Flow cytometric analysis of SAP and EAT-2 adaptor proteins in lymphocytes.

Panel of antibodies.

Mots clés
SLAMF receptors, SAP, EAT-2, lymphocytes, flow cytometry