Quantitative analysis of phagocytosis in whole blood using double staining and visualization

Cover Page

Cite item

Full Text

Open Access Open Access
Restricted Access Access granted
Restricted Access Subscription Access

Abstract

Phagocytosis is an essential innate immunity function in humans and animals. A decrease in the ability to phagocytize is associated with many diseases and aging of the immune system. Assessment of phagocytosis dynamics requires quantification of bacteria inside and outside the phagocyte. Although flow cytometry is the most common method for assessing phagocytosis, it does not include visualization and direct quantification of location of bacteria. Here, we used double-labeled Escherichia coli cells to evaluate phagocytosis by flow cytometry (cell sorting) and confocal microscopy, as well as employed image cytometry to provide high-throughput quantitative and spatial recognition of the double-labeled E. coli associated with the phagocytes. Retention of pathogens on the surface of myeloid and lymphoid cells without their internalization was suggested to be an auxiliary function of innate immunity in the fight against infections. The developed method of bacterial labeling significantly increased the accuracy of spatial and quantitative measurement of phagocytosis in whole blood and can be recommended as a tool for phagocytosis assessment by imaging flow cytometry.

Full Text

Restricted Access

About the authors

Е. V. Lysakova

Sirius University of Science and Technology

Email: rybtsov.sa@talantiuspeh.ru

Division Immunobiology and Biomedicine, Center for Genetics and Life Sciences

Russian Federation, 354340, Sirius, Krasnodar Region

A. N. Shumeev

Sirius University of Science and Technology

Email: rybtsov.sa@talantiuspeh.ru

Resource Center for Cell Technologies and Immunology

Russian Federation, 354340, Sirius, Krasnodar Region

S. А. Chuvpilo

Sirius University of Science and Technology

Email: rybtsov.sa@talantiuspeh.ru

Division Immunobiology and Biomedicine, Center for Genetics and Life Sciences

Russian Federation, 354340, Sirius, Krasnodar Region

V. S. Laktyushkin

Sirius University of Science and Technology

Email: rybtsov.sa@talantiuspeh.ru

Resource Center for Cell Technologies and Immunology

Russian Federation, 354340, Sirius, Krasnodar Region

N. A. Arsentieva

Saint-Petersburg Pasteur Institute

Email: rybtsov.sa@talantiuspeh.ru
Russian Federation, 197101, St. Petersburg

M. Yu. Bobrov

Sirius University of Science and Technology

Email: rybtsov.sa@talantiuspeh.ru

Division Immunobiology and Biomedicine, Center for Genetics and Life Sciences

Russian Federation, 354340, Sirius, Krasnodar Region

S. А. Rybtsov

Sirius University of Science and Technology

Author for correspondence.
Email: rybtsov.sa@talantiuspeh.ru

Resource Center for Cell Technologies and Immunology

Russian Federation, 354340, Sirius, Krasnodar Region

References

  1. Lancaster, C. E., Ho, C. Y., Hipolito, V. E., Botelho, R. J., and Terebiznik, M. R. (2019) Phagocytosis: what’s on the menu? Biochem. Cell Biol., 97, 21-29, https://doi.org/10.1139/bcb-2018-0008.
  2. Carneiro, V. M. A., Bezerra, A. C. B., Guimarães, M. D. C. M., and Muniz-Junqueira, M. I. (2012) Decreased phagocytic function in neutrophils and monocytes from peripheral blood in periodontal disease, J. Appl. Oral Sci., 20, 503-509, https://doi.org/10.1590/s1678-77572012000500002.
  3. Singh, R., Belchamber, K. B. R., Fenwick, P. S., Chana, K., Donaldson, G., Wedzicha, J. A., Barnes, P. J., Donnelly, L. E., and COPDMAP consortium (2021) Defective monocyte-derived macrophage phagocytosis is associated with exacerbation frequency in COPD, Respirat. Res., 22, 1-11, https://doi.org/10.1186/s12931-021-01718-8.
  4. Nakahashi-Oda, C., Fujiyama, S., Nakazawa, Y., Kanemaru, K., Wang, Y., Lyu, W., Shichita, T., Kitaura, J., and Shibuya, A. (2021) CD300a blockade enhances efferocytosis by infiltrating myeloid cells and ameliorates neuronal deficit after ischemic stroke, Sci. Immunol., 6, eabe7915, https://doi.org/10.1126/sciimmunol.abe7915.
  5. Kelley, S. M., and Ravichandran, K. S. (2021) Putting the brakes on phagocytosis: “don’t‐eat‐me” signaling in physiology and disease, EMBO Rep., 22, e52564, https://doi.org/10.15252/embr.202152564.
  6. Tang, Z., Davidson, D., Li, R., Zhong, M. C., Qian, J., Chen, J., and Veillette, A. (2021) Inflammatory macrophages exploit unconventional pro-phagocytic integrins for phagocytosis and anti-tumor immunity, Cell Rep., 37, https:// doi.org/10.1016/j.celrep.2021.110111.
  7. Uribe-Querol, E., Rosales, C. (2017) Control of phagocytosis by microbial pathogens, Front. Immunol., 8, 1368, https://doi.org/10.3389/fimmu.2017.01368.
  8. Gagnon, E., Duclos, S., Rondeau, C., Chevet, E., Cameron, P. H., Steele-Mortimer, O., Paiement, J., Bergeron, J. J. M., and Desjardins, M. (2002) Endoplasmic reticulum-mediated phagocytosis is a mechanism of entry into macrophages, Cell, 110, 119-131, https://doi.org/10.1016/s0092-8674(02)00797-3.
  9. Dempsey, L. A. (2019) Inhibiting phagocytosis, Nat. Immunol., 20.9, 1089-1089, https://doi.org/10.1038/s41590-019-0485-z.
  10. Cruz, F. M., Chan, A., and Rock, K. L. (2023) Pathways of MHC I cross-presentation of exogenous antigens, Semin. Immunol., 66, 101729, https://doi.org/10.1016/j.smim.2023.101729.
  11. Porpodis, K., Domvri, K., Zarogoulidis, P., Petridis, D., Tsirgogianni, K., Papaioannou, A., Hatzizisi, O., Kioumis, I., Liaka, A., Kikidaki, V., Lampaki, S., Organtzis, J., and Zarogoulidis, K. (2015) Roflumilast, a phosphodiesterase-4 inhibitor, induces phagocytic activity in Greek COPD patients, Int. J. Chron. Obstruct. Pulmon. Dis., 10, 1123-1128, https://doi.org/10.2147/COPD.S83205.
  12. Morais, T. C., Honorio-França, A. C., Fujimori, M., de Quental, O. B., Pessoa, R. S., França, E. L., and de Abreu, L. C. (2019) Melatonin action on the activity of phagocytes from the colostrum of obese women, Medicina, 55, 625, https://doi.org/10.3390/medicina55100625.
  13. Garcia‐Seyda, N., Seveau, V., Manca, F., Biarnes‐Pelicot, M., Valignat, M. P., Bajenoff, M., and Theodoly, O. (2021) Human neutrophils swim and phagocytise bacteria, Biol. Cell, 113, 28-38, https://doi.org/10.1111/boc.202000084.
  14. Li, W. (2013) Phagocyte dysfunction, tissue aging and degeneration, Ageing Res. Rev., 12, 1005-1012, https:// doi.org/10.1016/j.arr.2013.05.006.
  15. Ciabattini, A., Nardini, C., Santoro, F., Garagnani, P., Franceschi, C., and Medaglini, D. (2018) Vaccination in the elderly: the challenge of immune changes with aging, Semin. Immunol., 40, 83-94, https://doi.org/10.1016/j.smim. 2018.10.010.
  16. Robinson, J. P., Carter, W. O., and Narayanan, P. (1997) Functional assays by flow cytometry, in Manual of Clinical Laboratory Immunology. Volume Immune Cell Phenotyping and Flow Cytometric Analysis: Am. Soc. Microbiol. (Rose, Ed., Folds, J. D., Lane, H. C., and Nakumura, R., eds) 5, pp. 245-254.
  17. Serrander, L., Skarman, P., Rasmussen, B., Witke, W., Lew, D. P., Krause, K. H., Stendahl, O., and Nüße, O. (2000) Selective inhibition of IgG-mediated phagocytosis in gelsolin-deficient murine neutrophils, J. Immunol., 165, 2451-2457, https://doi.org/10.4049/jimmunol.165.5.2451.
  18. Lindner, B., Burkard, T., and Schuler, M. (2020) Phagocytosis assays with different pH-sensitive fluorescent particles and various readouts, Biotechniques, 68, 245-250, https://doi.org/10.2144/btn-2020-0003.
  19. Yang, F., Zhang, F., Yang, L., Li, H., and Zhou, Y. (2021) Establishment of the reference intervals of whole blood neutrophil phagocytosis by flow cytometry, J. Clin. Lab. Analysis, 35, e23884, https://doi.org/10.1002/jcla.23884.
  20. Jackaman, C., Tomay, F., Duong, L., Razak, N. B. A., Pixley, F. J., Metharom, P., and Nelson, D. J. (2017) Aging and cancer: the role of macrophages and neutrophils, Ageing Res. Rev., 36, 105-116, https://doi.org/10.1016/j.arr. 2017.03.008.
  21. DeLoid, G. M., Sulahian, T. H., Imrich, A., and Kobzik, L. (2009) Heterogeneity in macrophage phagocytosis of Staphylococcus aureus strains: high-throughput scanning cytometry-based analysis, PLoS One, 4, e6209, https://doi.org/ 10.1371/journal.pone.0006209.
  22. Laitinen, O. H., Kuusela, T. P., Kukkurainen, S., Nurminen, A., Sinkkonen, A., and Hytönen, V. P. (2021) Bacterial avidins are a widely distributed protein family in Actinobacteria, Proteobacteria and Bacteroidetes, BMC Ecol. Evol., 21, 1-14, https://doi.org/10.1186/s12862-021-01784-y.

Supplementary files

Supplementary Files
Action
1. JATS XML
Download
2. Fig. 1. Scheme of fluorescent labeling of bacteria. E. coli was conjugated with FITC and then biotin in order to distinguish bacteria inside and outside phagocytic cells. The sequence of conjugations and quality control of the E. coli preparation are shown. The concentration of bacteria was calculated by optical density (a) according to a pre-built calibration curve (b). After conjugation of E. coli with FITC, control flow cytometry (c) was performed to check the uniformity of conjugation (FITC+ 99.7%). After further conjugation of E. coli with biotin was checked for labeling uniformity in the AF405 and FITC channels – conjugation homogeneity was 98.7% (DP) for two labels (d). Before freezing the mother suspension of finished bacteria, their concentration was calculated by DIC and fluorescence in a given volume calculated based on known parameters of the depth of focus and the size of the field of view (e)

Download (241KB)
Indexing metadata
3. Fig. 2. The analysis and gating strategy for the Sony SH800 sorter: leukocytes (CD45+) were isolated from single cells (Singlets gate), then this population was sorted by fluorescence intensity and localization of bacteria (E. coli) into the following categories: DN – double negative population (non–phagocytic cells); Dim cells, fluorescence which are no more than a decade higher than DN; Mid – cells with moderate fluorescence intensity (more than a decade than Dim); Bright – cells with the highest fluorescence intensity; DP is a double FITC and AF405 positive bacterial population on the surface (lower panel on the left). For subpopulation analysis, cells were gated by granularity (SSC) and size (FSC) into granulocytes (GR), monocytes (MO) and lymphocytes (LY). The extended information on the testing strategy is shown in Fig. P2 Applications

Download (354KB)
Indexing metadata
4. Fig. 3. Scheme of the experiment on sorting phagocytic leukocyte populations (CD45+) and analysis of sorted fractions on a confocal microscope. Sorted populations (a) were analyzed using confocal microscopy (b), where DN is a double negative population (0 bacteria); Dim cells whose fluorescence intensity is no more than a decade higher than that of DN (autofluorescence is 0 bacteria); Mid cells with moderate fluorescence intensity, within decades higher than Dim (1-5 bacteria inside the cell); DP is a population that is double positive for FITC and AF405 (heterogeneous – bacteria inside and/or on the cell surface). The overlap of fluorescent images (FITC, AF405) and DIC is indicated as Merge (b). The red numbers on the graph on the right indicate the average values of the number of E. coli inside (IN) and outside (OUT) leukocytes, the data spread is shown in parentheses. Individual cell images are examples of cells with different amounts of E. coli in populations (b, c). The number of independent experiments is n = 3

Download (185KB)
Indexing metadata
5. Fig. 4. Gating strategy for a flow cytometer with Amnis FlowSight visualization and a generalized representation of the visualization results. The numbers indicate the percentage of cells in the population and the number of bacteria inside (IN) and outside (OUT) cells. Up to 352 cells were analyzed for individual populations (Fig. P3 of the Appendix). The number of independent experiments n = 3

Download (468KB)
Indexing metadata
6. Fig. 5. Localization of bacteria relative to cells based on the analysis of the built-in Amnis program and double staining. a – Bacteria that were detected by the program as being outside the cells. 94.9% of these cells were indeed positive for both FITC and AF405, that is, the bacteria adhered to the surface of phagocytes. b – Bacteria that were detected by the program as being inside cells. However, 70.4% of these cells were positive for both FITC and AF405, which, according to double staining, indicates the localization of bacteria on the cell surface. b – Lymphocytic (LY) gate. Although the program detects some cells in the lymphocyte population as phagocytic, all 1.28% of the cells, according to double staining, were on the surface. The upper panels illustrate (from left to right) the channels: FITC (E. coli), Brightfield 1, AF405 (biotin-streptavidin, E. coli), Brightfield 2 and the overlay of all channels. The right panels visualize the cells shown as dots on flow cytometry graphs. The blue line is a scale ruler for cell images. Samples of cell-by-cell image analysis are shown in Fig. P3 Applications

Download (209KB)
Indexing metadata
7. Supplement
Download (956KB)
Indexing metadata

Copyright (c) 2024 Russian Academy of Sciences