Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2025 Jan 31;26(3):1272.
doi: 10.3390/ijms26031272.

Unveiling the Phenotypic Variability of Macrophages: Insights from Donor Diversity and Pooling Strategies

Affiliations

Unveiling the Phenotypic Variability of Macrophages: Insights from Donor Diversity and Pooling Strategies

Bartłomiej Taciak et al. Int J Mol Sci. .

Abstract

Macrophages are key players in inflammation and immune responses due to their phenotypic plasticity. This study examined the effects of pooling donor-derived macrophages on their phenotype and function, focusing on murine bone marrow-derived macrophages (BMDMs) and human monocyte-derived macrophages (hMDMs). Murine BMDMs were generated using L929-conditioned media and compared across single and pooled donors (two-to-five mice). Similarly, hMDMs cultured with M-CSF from individual donors were compared to pooled cultures. Pooling macrophages did not alter core phenotypic markers (CD11b, F4/80, CD64) or functional outputs such as cytokine secretion and nitric oxide production. In hMDMs, pooling reduced variability and led to slightly elevated or more-uniform marker expression. These findings demonstrate that pooling macrophages minimizes inter-individual variability without compromising cellular stability or function, enhancing reproducibility in immunological research while maintaining the option of single-donor studies for personalized analyses.

Keywords: BMDM; donor diversity; macrophages.

PubMed Disclaimer

Conflict of interest statement

The authors declare no conflicts of interest.

Figures

Figure 1
Figure 1
Bone marrow (a,b) and bone marrow-derived macrophage (ce) cell characteristics: (a) Number of cells isolated from the bone marrow of individual mice, expressed as the mean ± SEM from three biological replicates; (b) Viability of cells isolated from the bone marrow of individual mice, expressed as the mean ± SEM from three biological replicates; (c) Number of BMDMs, expressed as the mean number of cells from individually cultured subjects and mean ± SEM cell count in various experimental combinations; (d) Viability of BMDMs, expressed as the mean ± SEM viability of cells from individually cultured subjects and mean ± SEM viability of cells in various experimental combinations; (e) Size of BMDMs, expressed as the mean ± SEM size of cells derived from individual subjects and the mean size of cells in various experimental combinations; (f) Representative microscopy images of BMDMs. The left panel shows BMDMs cultured individually from different subjects, while the right panel illustrates BMDMs in various experimental setups. Each image includes a scale bar representing 50 µm for size comparison. Individual data points are shown as dots. Statistical analysis was performed using one-way ANOVA with Tukey’s multiple comparisons test.
Figure 2
Figure 2
Expression of surface markers on BMDMs in experimental combinations. (a) The bar graphs show the mean ± SEM fluorescence intensity (MFI) and the mean ± SD percentage of positive cells for various surface markers across different groups and individuals. Each marker is represented by two graphs: the upper row for the MFI and the lower row for the percentage of positive cells. The markers analyzed include CD11B, TLR2, TLR4, F4/80, CD64, and Ly6C. (b) Representative scatter plot of analyzed cells showing SSC-A vs. Anti-Ly6C-APC-A. The plot displays three distinct populations based on Ly6C receptor expression: Ly6C-negative (Ly6C FMO), Ly6C-low, and Ly6C-high. The accompanying graphs on the right illustrate the percentage of positive cells for the Ly6C-low and Ly6C-high populations. Data are presented as the mean ± standard deviation (SD) from three biological replicates. Individual data points are shown as dots. Statistical analysis was performed using one-way ANOVA with Tukey’s multiple comparisons test.
Figure 3
Figure 3
Average ± SD of relative gene expression in BMDMs under various experimental conditions. Data are presented from three biological replicates. Individual data points are shown as dots. Statistical analysis was performed using one-way ANOVA with Tukey’s multiple comparisons test; * indicates p < 0.05.
Figure 4
Figure 4
Cytokine secretion levels by BMDMs across different experimental conditions, presented as the mean ± SD (pg/mL). Data represent the average of three independent biological replicates. Individual data points are shown as dots. Statistical analysis was performed using one-way ANOVA with Tukey’s multiple comparisons test.
Figure 5
Figure 5
Functional characteristics of BMDMs. (a) Nitrite concentration in the culture medium (µM), presented as the mean ± SD across different experimental conditions; (b) Phagocytic capacity of BMDMs, expressed as relative values and presented as the mean ± SD for various experimental conditions. Data are presented from three biological replicates. Individual data points are shown as dots. Statistical analysis was performed using one-way ANOVA with Tukey’s multiple comparisons test; * indicates p < 0.05.
Figure 6
Figure 6
Expression of surface markers on hMDMs in experimental combinations. The bar graphs show the mean ± SD fluorescence intensity (MFI) and the percentage of positive cells for various surface markers across different groups and individuals. Each marker is represented by two graphs: the upper row for the MFI and the lower row for the percentage of positive cells. The markers analyzed include CD11B, CD14, 25f9, CD115, CD163, CD172, CD206, CD280, and SR-A1. Data are presented as the mean ± standard deviation (SD) from three biological replicates. Individual data points are shown as dots.

References

    1. Sreejit G., Fleetwood A.J., Murphy A.J., Nagareddy P.R. Origins and Diversity of Macrophages in Health and Disease. Clin. Transl. Immunol. 2020;9:e1222. doi: 10.1002/cti2.1222. - DOI - PMC - PubMed
    1. Mass E., Nimmerjahn F., Kierdorf K., Schlitzer A. Tissue-Specific Macrophages: How They Develop and Choreograph Tissue Biology. Nat. Rev. Immunol. 2023;23:563–579. doi: 10.1038/s41577-023-00848-y. - DOI - PMC - PubMed
    1. Poltavets A.S., Vishnyakova P.A., Elchaninov A.V., Sukhikh G.T., Fatkhudinov T.K. Macrophage Modification Strategies for Efficient Cell Therapy. Cells. 2020;9:1535. doi: 10.3390/cells9061535. - DOI - PMC - PubMed
    1. Zhang W., Wang M., Tang W., Wen R., Zhou S., Lee C., Wang H., Jiang W., Delahunty I.M., Zhen Z., et al. Nanoparticle-Laden Macrophages for Tumor-Tropic Drug Delivery. Adv. Mater. 2018;30:1805557. doi: 10.1002/adma.201805557. - DOI - PMC - PubMed
    1. Moroni F., Dwyer B.J., Graham C., Pass C., Bailey L., Ritchie L., Mitchell D., Glover A., Laurie A., Doig S., et al. Safety Profile of Autologous Macrophage Therapy for Liver Cirrhosis. Nat. Med. 2019;25:1560–1565. doi: 10.1038/s41591-019-0599-8. - DOI - PubMed

LinkOut - more resources