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. 2024 Aug 13:15:1432816.
doi: 10.3389/fimmu.2024.1432816. eCollection 2024.

Design and validation of novel flow cytometry panels to analyze a comprehensive range of peripheral immune cells in mice

Affiliations

Design and validation of novel flow cytometry panels to analyze a comprehensive range of peripheral immune cells in mice

Ainara Barco-Tejada et al. Front Immunol. .

Abstract

The use of flow cytometry in mice is constrained by several factors, including the limited availability of mouse-specific antibodies and the need to work with small volumes of peripheral blood. This is particularly challenging for longitudinal studies, as serial blood samples should not exceed 10% of the total blood volume in mice. To address this, we have developed two novel flow cytometry panels designed to extensively analyze immune cell populations in mice during longitudinal studies, using only 50 µL of peripheral blood per panel. Additionally, a third panel has been designed to conduct a more detailed analysis of cytotoxic and inhibitory markers at the end point. These panels have been validated on a lipopolysaccharide (LPS)-induced lung inflammation model. Two experiments were conducted to 1) validate the panels' sensitivity to immune challenges (n=12) and 2) to assess intrinsic variability of measurements (n=5). In both experiments, we collected 50 µL of peripheral blood for each cytometry panel from the maxillary venous sinus. All antibodies were titrated to identify the optimal concentration that maximized the signal from the positive population while minimizing the signal from the negative population. Samples were processed within 1 hour of collection using a MACSQuant Analyzer 16 cytometer. Our results demonstrate that these immunological panels are sensitive enough to detect changes in peripheral blood after LPS induction. Moreover, our findings help determine the sample size needed based on the immune population variability. In conclusion, the panels we have designed enable a comprehensive analysis of the murine immune system with a low blood volume requirement, enabling the measure of both absolute values and relative percentages effectively. This approach provides a robust platform for longitudinal studies in mice and can be used to uncover significant insights into immune responses.

Keywords: flow cytometry-methods; immune system; longitudinal studies; mice; peripheral blood.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Manual gating strategy by differential expression of extracellular markers for the myeloid panel (A, B). Representative examples of flow cytometry plots determined on whole blood labeled from one individual.
Figure 2
Figure 2
Manual gating strategy by differential expression of extracellular markers for the lymphoid panel. Representative examples of flow cytometry plots determined on whole blood labeled from one individual.
Figure 3
Figure 3
Intracellular panel at 72 hours post-injection (p.i.). This figure shows relative counts from the Intracellular panel in animals treated with LPS and in control animals at 72 hours post-injection. Only populations with significant differences between groups are presented. Significance levels are indicated as follows: *p ≤ 0.05; **p ≤ 0.01; ***p ≤ 0.001. (A) CD45 Leukocytes; (B) Monocyte type myeloid derived suppressor cell; (C) Lymphocytes; (D) Tcells; (E) CD4 Tcells; (F) CD4 Effector memory; (G) CD4 CD44 positive; (H) T Helper 9 Cells; (I) CD8 Tcells; (J) CD8 Central memory; (K) CD8 Effector activated; (L) lymphocytes B; (M) Natural Killers; (N) CD8 Effector memory; (O) plasma cells; (P) Natural killer T cell; (Q) CD172a myeloids cells.
Figure 4
Figure 4
Changes in myeloid and lymphoid populations at 24 Hours Post-Injection (p.i.). This figure illustrates the absolute numbers of myeloid and lymphoid populations in animals treated with LPS and in control animals, measured 24 hours post-injection. Only the populations with significant differences between the two groups are displayed. Significance levels are indicated as follows: *p ≤ 0.05; **p ≤ 0.01; ***p ≤ 0.001. (A) Natural killer perforin; (B) CD4 Tcell; (C) CD8 Tcells; (D) Cytotoxic CD8; (E) Tcells; (F) Natural killer activated perofin positive and granzyme B negative; (G) Natural killer T cell; (H) Natural killer T cell perofin negative and granzyme B positive; (I) CD4 Effector Regulatory T cell CCR5 positive.

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Grants and funding

The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This work was partially supported by MCIN and AEI (PID2019-110369RB-I00 MCIN/AEI/10.13039/501100011033, PRE2020-095268 MCIN/AEI/10.13039/501100011033 and ESF Investing in your future), by Comunidad de Madrid (S2022/BMD-7403 RENIM-CM) and by Instituto de Salud Carlos III (PT20/00044, PT23/00027 and PI23/00671), cofunded by European Union, European Regional Development Fund (ERDF, “A way of making Europe”). Also, this project has received funding from the European Union, Horizon Europe, number 101047008 -BIOMET4D (“Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or EISMEA. Neither the European Union nor the granting authority can be held responsible for them”). The CNIC is supported by the Instituto de Salud Carlos III (ISCIII), the Ministerio de Ciencia e Innovación (MCIN) and the Pro CNIC Foundation), and is a Severo Ochoa Center of Excellence (grant CEX2020-001041-S funded by MICIN/AEI/10.13039/501100011033). Ainara Barco has a PhD grant (PRE2020-095268) funded by MCIN/AEI/10.13039/501100011033 and by “ESF Investing in your future”.

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