Zaloguj się

Aby wyświetlić tę treść, wymagana jest subskrypcja JoVE. Zaloguj się lub rozpocznij bezpłatny okres próbny.

W tym Artykule

  • Podsumowanie
  • Streszczenie
  • Wprowadzenie
  • Protokół
  • Wyniki
  • Dyskusje
  • Ujawnienia
  • Podziękowania
  • Materiały
  • Odniesienia
  • Przedruki i uprawnienia

Podsumowanie

Monocytes are integral components of the human innate immune system that rely on glycolytic metabolism when activated. We describe a flow cytometry protocol to measure glucose transporter expression and glucose uptake by total monocytes and monocyte subpopulations in fresh whole blood.

Streszczenie

Monocytes are innate immune cells that can be activated by pathogens and inflammation associated with certain chronic inflammatory diseases. Activation of monocytes induces effector functions and a concomitant shift from oxidative to glycolytic metabolism that is accompanied by increased glucose transporter expression. This increased glycolytic metabolism is also observed for trained immunity of monocytes, a form of innate immunological memory. Although in vitro protocols examining glucose transporter expression and glucose uptake by monocytes have been described, none have been examined by multi-parametric flow cytometry in whole blood. We describe a multi-parametric flow cytometric protocol for the measurement of fluorescent glucose analog 2-NBDG uptake in whole blood by total monocytes and the classical (CD14++CD16-), intermediate (CD14++CD16+) and non-classical (CD14+CD16++) monocyte subpopulations. This method can be used to examine glucose transporter expression and glucose uptake for total monocytes and monocyte subpopulations during homeostasis and inflammatory disease, and can be easily modified to examine glucose uptake for other leukocytes and leukocyte subpopulations within blood.

Wprowadzenie

Monocytes are a major component of the human innate immune system that are rapidly mobilized to sites of infection and inflammation1. Activation of monocytes is critical for limiting acute damage by pathogens and is also central to the pathogenesis of several chronic diseases, including atherosclerosis2, cancer3, and HIV4,5.

The metabolism of resting and activated monocytes differs dramatically, with resting monocytes utilizing oxidative metabolism and activated monocytes utilizing glycolytic metabolism (i.e., fermentation of glucose to lactate)6. Activation of monocytes induces expression of glucose transporters that allows for increased glucose uptake for glycolytic metabolism7. Monocyte glucose transporter 1 (Glut1) is one such transporter upregulated during activation and its expression has been shown to lead to production of pro-inflammatory cytokines in vitro and in adipose tissue of obese mice8. Infection of a monocytic cell line by Kaposi sarcoma associated herpesvirus leads to cellular upregulation of Glut19, and we recently showed that during chronic HIV infection an increased percentage of Glut1-expressing monocytes are present during untreated and combination antiretroviral therapy-treated infection10. Taken together, these studies show that glucose uptake and glycolytic metabolism by monocytes are important aspects of many inflammatory diseases. Thus, a simple method to measure monocyte Glut1 expression and glucose uptake during homeostasis and inflammatory disease is likely to be of use to a wide range of researchers.

Human monocytes are heterogeneous, being comprised of three distinct subsets that can be examined by differential expression of the cell surface markers CD14 and CD1611,12. Classical monocytes express a high level of CD14 but do not express CD16 (CD14++CD16-), intermediate monocytes express a high level of CD14 and an intermediate level of CD16 (CD14++CD16+), and non-classical monocytes express a low level of CD14 and a high level of CD16 (CD14+CD16++). Monocytes that express CD16 are termed CD16+ monocytes, which compared to CD16- monocytes have high expression of inflammatory cytokines and the ability to more effectively present antigens13,14. Approximately 10% of monocytes express CD16 during homeostasis with higher percentages observed during inflammation15. Monocyte subpopulations are associated with certain disease states and could be useful biological markers of disease and disease progression16.

Our goal was to identify a method that can measure glucose transporter expression and glucose uptake by human monocytes and monocyte subpopulations in conditions as close to physiological conditions as possible. Previous studies measured monocyte glucose transporter expression and glucose uptake17,18, though these methods examined isolated monocytes that can have altered protein expression compared to physiological conditions19, and no previous study has examined human monocyte subpopulations. Using multi-parametric flow cytometry, we describe a method to examine glucose transporter expression and uptake of the fluorescent glucose analog 2-NBDG by total monocytes and monocyte subpopulations (based on CD14 and CD16 expression) within whole unmanipulated blood.

Protokół

NOTE: HIV-infected and HIV-uninfected subjects were recruited from the Infectious Diseases Unit at The Alfred Hospital in Melbourne, VIC, Australia, and from the local community, respectively. Informed consent was obtained from all participants, and the research was approved by The Alfred Hospital Research and Ethics Committee.

1. Glut1 Cell Surface Detection on Monocytes and Monocyte Subpopulations

  1. Collect blood in citrate ACD-B anticoagulant tubes and begin the experiments in a biological safety cabinet within 1 hr of collection.
  2. Add 100 µl of blood to polypropylene tubes. Add 2 ml of 1x lysing solution (see Materials Table) to tubes while on ice, pipetting gently to mix. Incubate for 15 min on ice. Centrifuge at 220 x g for 5 min.
  3. Decant and wash twice by adding approximately 2-4 ml of wash solution (0.5% BSA in 1x PBS) and centrifuging at 220 x g for 5 min.
  4. Use a pipette to carefully remove as much of the wash solution as possible. Place tubes on ice and re-suspend in 100 µl of wash solution.
  5. To identify specific monocyte subpopulations stain cells with the following volume of antibodies per 100 µl cell suspension prepared in step 1.4: 5 µl anti-CD3-PE, 5 µl anti-CD14-APC, 5 µl anti-CD16-PECy7, 5 µl Glut1-FITC or IgG2b-FITC (isotype control tube).
  6. Place on ice for 30 min in the dark. Wash 2 times with wash solution. Fix with 200-300 µl of 0.5% formaldehyde made in 1x PBS.
  7. Analyze on a flow cytometer capable of detecting 4 colors within 24 hr within the following excitation and emission wavelength: FITC (488, 530), PE (488, 575), PECy7 (488, 780), APC (633, 660)10.

2. Glucose Uptake by Monocytes

  1. Pipette 90 µl of blood collected in step 1.1 in polypropylene tubes. Add 10 µl of a 14.60 µM 2-NBDG working solution to the 90 µl of blood (1.46 mM final concentration) and flick gently to mix. It is critical to limit 2-NBDG exposure to light by covering tubes with aluminum foil.
  2. Incubate at 37 °C in the dark for 15-30 min and then immediately place on ice. Add 4 ml of 1x FACS lysing solution to tubes while on ice. Centrifuge at 220 x g at 4 °C for 5 min.
  3. Wash once by adding 4 ml of wash solution (0.5% BSA in 1x PBS). Centrifuge at 220 x g at 4 °C for 5 min. Decant and place on ice.
  4. Stain cells with antibodies: 5 µl anti-CD3-PE, 5 µl anti-CD14-APC and 5 µl anti-CD16-PECy7. Mix and place on ice for 30 min in the dark.
    NOTE: During this period make sure the flow cytometer is ready for immediate analysis. Acquire cells within the following excitation and emission wavelength: 2-NBDG (488, 530), PE (488, 575), PECy7 (488, 780), APC (633, 660).
  5. Add 4 ml of ice cold wash buffer (0.5% BSA in 1x PBS) to tubes. Wash once by centrifugation at 220 x g at 4 °C for 5 min. Decant and add 200-300 µl of ice old PBS and keep on ice in the dark (covered with aluminum foil). Analyze on a flow cytometer within 10 min using excitation and emission wavelength setting as in step 2.4.

3. Data Acquisition and Analysis

NOTE: A knowledge of flow cytometry and data analysis is assumed.

  1. Using a flow cytometer capable of at least 4-color analysis, set compensation using unstained and individually stained samples.
    NOTE: Single staining using a FITC-labelled CD4 and CD14 can be used for Glut1 and 2-NBDG compensation.
  2. Set up and label appropriate windows before acquiring samples. Draw a gate around the monocyte population, and acquire 100,000 to 300,000 events per sample at medium rate. 50,000 events per compensation sample is sufficient.
    NOTE: Compensation may be conducted prior to sample acquisition or in single cell analysis software, following standard procedures.
  3. Export and save data into an appropriate location. Open up single cell analysis software such as FlowJo or other analysis software (Supplemental Figure 1) and drag and drop samples as specified (Supplemental Figure 2).
  4. Double click to open file (Supplemental Figure 3). Draw a circle to gate monocytes based on forward and side scatter properties as shown in Figure 1A and Supplemental Figure 4. Double click the monocyte population. Observe and draw a box around the CD3- population (Supplemental Figure 4).
  5. Double click the CD3- population. To observe the monocyte subpopulations select CD14-APC on the 'x' axis, and CD16-PECy7 on the 'y'- axis, and label accordingly (Supplemental Figure 5).
  6. Where there are no distinct positive and negative populations, measure the expression of Glut1 or 2-NBDG uptake in the specific monocyte subpopulations. Determine the mean fluorescence intensities (MFI) of Glut1 and 2-NBDG by subtracting the isotype and no 2-NBDG background (Supplemental Figure 6).
  7. Where defined populations exist, use the IgG2b-FITC to set the gate, and determine the percentage positive cells (Figure 3).
    NOTE: Use this procedure to analyze total CD14+ monocytes. Since 2-NBDG uptake is usually marked by a shift in fluorescence intensities the data is best represented by MFI and histograms.

Wyniki

Compensation must be performed for individual fluorochromes to prevent fluorescence spillover. Monocytes are first enriched by gating based on forward and side scatter. The plots presented are representatives of at least six independent experiments conducted on whole blood from six or more participants as previously reported10. Figure 1A shows the initial gating of monocytes by cell scatter and exclusion of T cells by gating within the CD3- populatio...

Dyskusje

The protocol described here details a simple method to examine glucose transporter expression and fluorescent glucose analog uptake by monocyte and monocyte subpopulations in whole blood. By assessing 2-NBDG uptake in whole blood, this technique allows for conditions similar to those in vivo. A previous study examined 6-NBDG uptake in monocytes separated from whole blood by density centrifugation17. However, this study did not examine monocyte subpopulations and separation of monocytes from whole bloo...

Ujawnienia

The authors have nothing to disclose.

Podziękowania

This research was funded by the Australian Centre for HIV and Hepatitis Virology Research (ACH2) and a 2010 developmental grant (CNIHR) from the University of Washington Center for AIDS Research (CFAR), an NIH funded program under award number AI027757 which is supported by the following NIH Institutes and Centers (NIAID, NCI, NIMH, NIDA, NICHD, NHLBI, NIA). C.S.P is a recipient of the CNIHR and ACH2 grant. SMC is a recipient of a National Health and Medical Research Council of Australia (NHMRC) Principal Research Fellowship. The authors gratefully acknowledge the contribution to this work of the Victorian Operational Infrastructure Support Program received by the Burnet Institute. We acknowledge the assistance of Geza Paukovic and Eva Orlowski-Oliver from the AMREP Flow Cytometry Core Facility for flow cytometry training and technical advice. We thank Angus Morgan for media coaching and organization of the video shoot.  Our gratitude to Jesse Masson and Jehad Abdulaziz K. Alzahrani for lab assistance during the video shoot. We thank the efforts of Dr David Simar at the School of Medical Sciences, UNSW, Australia who offered critical methodological advice. C.S.P would like to thank www.nice-consultants.com for graphic consultations.

AUTHORS' CONTRIBUTION:

C.S.P conceived the project, designed and conducted experiments, analyzed and interpreted data, and wrote the manuscript. J.J.A interpreted data and wrote the manuscript. T.R.B wrote the manuscript. J.M.M interpreted data, made critical intellectual suggestions, and reviewed the manuscript. S.M.C interpreted data, made critical intellectual suggestions and reviewed the manuscript.

Materiały

NameCompanyCatalog NumberComments
VACUETT Tube 9 ml ACD-B anticoagulant tubesGreiner Bio-One GmbH455094
5 ml sterile polypropylene tubesBD Biosciences352063
Albumin from Bovine Serum (BSA)Sigma-AldrichA7906
16% formaldehyde solutionElectron Microscopy Science15710
BD FACS lysing solution (10X)BD Biosciences349202Dilute BD FACS lysing solution 1/10 with deionized water for working concentration (store for up to 1 week at 4°C)
anti-CD3-PEBD Biosciences555340
anti CD14-APCBD Biosciences555399
anti-CD16-PECy7BD Biosciences557744
anti-Glut1-FITCR & D SystemsFAB1418F
IgG2b-FITCR & D SystemsIC0041F
2-NBDGLife technologiesN13195Suspend 5 mg of 2-NBDG into 1 ml of deionized water to make a 14.60 mM stock solution (keep for up to 6 months at 4°C). To make the working 2-NBDG concentration, dilute stock 1/100 with 1X DPBS. Cover with foil. (store for up to 1 week at 4°C)
Dulbecco’s Phosphate Buffered Saline (1X)Life technologies14190-144To make wash solution, add 0.5 g BSA per 100 ml DPBS (store for up to 2 weeks at 4°C)

Odniesienia

  1. Shi, C., Pamer, E. G. Monocyte recruitment during infection and inflammation. Nat Rev Immunol. 11, 762-774 (2011).
  2. Woollard, K. J., Geissmann, F. Monocytes in atherosclerosis: subsets and functions. Nat Rev Cardiol. 7, 77-86 (2010).
  3. Richards, D. M., Hettinger, J., Feuerer, M. Monocytes and macrophages in cancer: development and functions. Cancer Microenviron. 6, 179-191 (2013).
  4. Anzinger, J. J., Butterfield, T. R., Angelovich, T. A., Crowe, S. M., Palmer, C. S. Monocytes as regulators of inflammation and HIV-related comorbidities during cART. J Immunol Res. 2014, 569819 (2014).
  5. Palmer, C., Cherry, C. L., Sada-Ovalle, I. Glucose Metabolism in T Cells and Monocytes: New Perspectives in HIV Pathogenesis. EBioMedicine. , (2016).
  6. Cheng, S. C., et al. mTOR- and HIF-1alpha-mediated aerobic glycolysis as metabolic basis for trained immunity. Science. 345, 1250684 (2014).
  7. Maratou, E., et al. Glucose transporter expression on the plasma membrane of resting and activated white blood cells. Eur J Clin Invest. 37, 282-290 (2007).
  8. Freemerman, A. J., et al. Metabolic reprogramming of macrophages: glucose transporter 1 (GLUT1)-mediated glucose metabolism drives a proinflammatory phenotype. J Biol Chem. 289, 7884-7896 (2014).
  9. Gonnella, R., et al. Kaposi sarcoma associated herpesvirus (KSHV) induces AKT hyperphosphorylation, bortezomib-resistance and GLUT-1 plasma membrane exposure in THP-1 monocytic cell line. J Exp Clin Cancer Res. 32, 79 (2013).
  10. Palmer, C. S., et al. Glucose transporter 1-expressing proinflammatory monocytes are elevated in combination antiretroviral therapy-treated and untreated HIV+ subjects. J Immunol. 193, 5595-5603 (2014).
  11. Wong, K. L., et al. Gene expression profiling reveals the defining features of the classical, intermediate, and nonclassical human monocyte subsets. Blood. 118, e16-e31 (2011).
  12. Ziegler-Heitbrock, L., et al. Nomenclature of monocytes and dendritic cells in blood. Blood. 116, e74-e80 (2010).
  13. Belge, K. U., et al. The proinflammatory CD14+CD16+DR++ monocytes are a major source of TNF. J Immunol. 168, 3536-3542 (2002).
  14. Frankenberger, M., Sternsdorf, T., Pechumer, H., Pforte, A., Ziegler-Heitbrock, H. W. Differential cytokine expression in human blood monocyte subpopulations: a polymerase chain reaction analysis. Blood. 87, 373-377 (1996).
  15. Ziegler-Heitbrock, L. The CD14+ CD16+ blood monocytes: their role in infection and inflammation. J Leukoc Biol. 81, 584-592 (2007).
  16. Ziegler-Heitbrock, L. . Macrophages: Biology and Role in the Pathology of Diseases. , 3-36 (2014).
  17. Dimitriadis, G., et al. Evaluation of glucose transport and its regulation by insulin in human monocytes using flow cytometry. Cytometry A. 64, 27-33 (2005).
  18. Fu, Y., Maianu, L., Melbert, B. R., Garvey, W. T. Facilitative glucose transporter gene expression in human lymphocytes, monocytes, and macrophages: a role for GLUT isoforms 1, 3, and 5 in the immune response and foam cell formation. Blood Cells Mol Dis. 32, 182-190 (2004).
  19. Stibenz, D., Buhrer, C. Down-regulation of L-selectin surface expression by various leukocyte isolation procedures. Scand J Immunol. 39, 59-63 (1994).
  20. Ahmed, N., Kansara, M., Berridge, M. V. Acute regulation of glucose transport in a monocyte-macrophage cell line: Glut-3 affinity for glucose is enhanced during the respiratory burst. Biochem J. 327 (Pt 2), 369-375 (1997).
  21. Cutfield, W. S., Luk, W., Skinner, S. J., Robinson, E. M. Impaired insulin-mediated glucose uptake in monocytes of short children with intrauterine growth retardation). Pediatr Diabetes. 1, 186-192 (2000).
  22. Yoshioka, K., et al. A novel fluorescent derivative of glucose applicable to the assessment of glucose uptake activity of Escherichia coli. Biochim Biophys Acta. 1289, 5-9 (1996).
  23. Speizer, L., Haugland, R., Kutchai, H. Asymmetric transport of a fluorescent glucose analogue by human erythrocytes. Biochim Biophys Acta. 815, 75-84 (1985).
  24. Palmer, C. S., et al. Increased glucose metabolic activity is associated with CD4+ T-cell activation and depletion during chronic HIV infection. AIDS. 28, 297-309 (2014).
  25. Palmer, C. S., Ostrowski, M., Balderson, B., Christian, N., Crowe, S. M. Glucose metabolism regulates T cell activation, differentiation, and functions. Frontiers in immunology. 6, (2015).
  26. Palmer, C. S., et al. Regulators of glucose metabolism in CD4 and CD8 T cells. International reviews of immunology. , 1-12 (2015).
  27. Palmer, C. S., Crowe, S. M. How does monocyte metabolism impact inflammation and aging during chronic HIV infection?. AIDS research and human retroviruses. 30, 335-336 (2014).
  28. McFadden, K., et al. Metabolic stress is a barrier to Epstein-Barr virus-mediated B-cell immortalization. Proceedings of the National Academy of Sciences of the United States of America. 113, E782-E790 (2016).
  29. Gamelli, R. L., Liu, H., He, L. K., Hofmann, C. A. Augmentations of glucose uptake and glucose transporter-1 in macrophages following thermal injury and sepsis in mice. Journal of leukocyte biology. 59, 639-647 (1996).
  30. Yin, Y., et al. Glucose Oxidation Is Critical for CD4+ T Cell Activation in a Mouse Model of Systemic Lupus Erythematosus. Journal of immunology. , 80-90 (2016).
  31. Yang, Z., Matteson, E. L., Goronzy, J. J., Weyand, C. M. T-cell metabolism in autoimmune disease. Arthritis research & therapy. 17, 29 (2015).
  32. Yin, Y., et al. Normalization of CD4+ T cell metabolism reverses lupus. Science translational medicine. 7, 274ra218 (2015).
  33. Barbera Betancourt, A., et al. Inhibition of Phosphoinositide 3-Kinase p110delta Does Not Affect T Cell Driven Development of Type 1 Diabetes Despite Significant Effects on Cytokine Production. PloS one. 11, e0146516 (2016).
  34. Barron, C. C., Bilan, P. J., Tsakiridis, T., Tsiani, E. Facilitative glucose transporters: Implications for cancer detection, prognosis and treatment. Metabolism: clinical and experimental. 65, 124-139 (2016).
  35. Hegedus, A., Kavanagh Williamson, M., Huthoff, H. HIV-1 pathogenicity and virion production are dependent on the metabolic phenotype of activated CD4+ T cells. Retrovirology. 11, 98 (2014).
  36. Taylor, H. E., et al. Phospholipase D1 Couples CD4+ T Cell Activation to c-Myc-Dependent Deoxyribonucleotide Pool Expansion and HIV-1 Replication. PLoS Pathog. 11, e1004864 (2015).
  37. Loisel-Meyer, S., et al. Glut1-mediated glucose transport regulates HIV infection. Proc Natl Acad Sci U S A. 109, 2549-2554 (2012).
  38. Palmer, C. S., et al. Emerging Role and Characterization of Immunometabolism: Relevance to HIV Pathogenesis, Serious Non-AIDS Events, and a Cure. J Immunol. 196 (11), 4437-4444 (2016).

Przedruki i uprawnienia

Zapytaj o uprawnienia na użycie tekstu lub obrazów z tego artykułu JoVE

Zapytaj o uprawnienia

Przeglądaj więcej artyków

Keywords Flow CytometryGlucose UptakeGlucose TransporterMonocyte SubpopulationsWhole BloodImmunologyCell MetabolismDisease OutcomesAntibodiesFluorescent Glucose AnalogFACS

This article has been published

Video Coming Soon

JoVE Logo

Prywatność

Warunki Korzystania

Zasady

Badania

Edukacja

O JoVE

Copyright © 2025 MyJoVE Corporation. Wszelkie prawa zastrzeżone