A new flow cytometry method to measure oxidative status: The Peroxidation of Leukocytes Index Ratio (PLIR)

Journal of Immunological Methods 390 (2013) 113–120

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Research paper

A new flow cytometry method to measure oxidative status: The Peroxidation of Leukocytes Index Ratio (PLIR) Ilaria Peluso a,⁎, Gaspare Adorno b, Anna Raguzzini a, Lourdes Urban a, Andrea Ghiselli a, Mauro Serafini a a b

Agricultural Research Council (CRA), ex National Institute for Food and Nutrition Research (INRAN), Rome, Italy Department of Biomedicine & Prevention, Faculty of Medicine, Tor Vergata University, Rome, Italy

a r t i c l e

i n f o

Article history: Received 19 December 2012 Received in revised form 4 February 2013 Accepted 13 February 2013 Available online 20 February 2013 Keywords: Peroxidation of Leukocytes Index Ratio (PLIR) Oxidative stress Immune-metabolism Immune-nutrition

a b s t r a c t Background and aim: A complex relationship between immune system and metabolic pathway exists and can induce oxidative stress. The objective of this study was to design a new methodology allowing the measurement of oxidative status of leukocytes. Methods and results: We developed a flow cytometry technique, based on C11-BODIPY 581/591 staining, to evaluate peroxidation in leukocytes. We defined the Peroxidation of Leukocytes Index Ratio (PLIR) as the ratio between the damage after AAPH-induced and PMA-induced peroxidation, using Trolox as standard antioxidant. Sensitivity of the method was assessed by correlating results with plasma antioxidant capacity (TRAP and FRAP), levels of endogenous antioxidants (uric acid and sulfhydryls) and markers of metabolic status (cholesterol, triglycerides, glucose and insulin). PLIR measures the ratio between the resistance to exogenous and endogenous ROS injury, independently from baseline level of oxidation, which was directly correlated with plasma cholesterol on lymphocytes (0.738, p=0.029), monocytes (0.691, p=0.047) and neutrophils (0.690, p=0.047). PLIR of lymphocytes was inversely correlated with uric acid (−0.810, p=0.009) and FRAP (−0.738, p=0.029) levels. On the other hand, PLIR of monocytes was directly correlated with the total scavenger antioxidant capacity attributable to nutritional antioxidants (0.738, p= 0.029), calculated as the difference between TRAP and the contribution of uric acid and sulfhydryls to its value. Conclusions: This study reports a feasible and reproducible new flow cytometry assay for assessing the leukocytes redox status. PLIR discriminates between reducing and scavenger activities and is able to appreciate the potentially dangerous effect of uric acid on innate immune response. © 2013 Elsevier B.V. All rights reserved.

1. Introduction During the acute phase response against pathogens, the increased generation of reactive oxygen species (ROS), resulting from respiratory burst, is an essential defense mechanism; however severe inflammatory states like sepsis produce excessive ROS production with subsequent injury to tissues (Magrone and Jirillo, 2012). On the other hand, chronic low grade inflammation can induce oxidative stress, in particular ⁎ Corresponding author at: CRA exINRAN, Via Ardeatina, 546, 00178 Rome, Italy. Tel.: +39 0651494468; fax: +39 0651494550. E-mail address: [email protected] (I. Peluso). 0022-1759/$ – see front matter © 2013 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.jim.2013.02.005

lipid peroxidation, increasing the risk of many diseases (Candore et al., 2010). Dietary habit may regulate the complex relationship between immune system and metabolic pathway, affecting both the metabolic and inflammatory markers associated with low grade systemic inflammation (Calder et al., 2009, 2011). Besides, dietary intervention studies have shown that consumption of plant foods is able to modulate plasma non enzymatic antioxidant capacity (NEAC) (Serafini et al., 2011). However, no methods are available to appreciate cellular lipid peroxidative damage in human intervention studies (Albers et al., 2005). Therefore, there is a great need to defining methods capable of evaluating the complex relationship between immune system, metabolism and nutrition in living cells.

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Leukocytes are a suitable target to study lipid peroxidation in human studies and they are a mixed population comprising both ROS-producing and non-producing cells. Fluorescent intracellular probes have been described for detecting respiratory burst activity in white blood cell suspensions (Walrand et al., 2003; Vowells et al., 1995), however these probes do not supply any information on peroxidative status of cell membrane. C11-BODIPY 581/591 [4,4-difluoro-5-(4-phenyl-1,3butadienyl)-4-bora-3a,4a-diaza-s-indacene-3-undecanoic acid] is an oxidation-sensitive fluorescence dye (Drummen et al., 2002). This lipophilic probe can be incorporated readily into lipid bilayers by its fatty acyl chain and monitors the oxidation of poly-unsaturated fatty acids (PUFAs) in the lipid bilayer (Pap et al., 1999). The use of C11-BODIPY 581/591 probe is a more sensitive analysis than malondialdehyde (MDA) assessment by the thiobarbituric acid reactive substances (TBARS) assay method (Domínguez-Rebolledo et al., 2010) and cis-parinaric acid (Pap et al., 1999) due to the fact that its sensitivity to oxidation is similar to that of endogenous PUFAs (Pap et al., 1999). Oxidative stress at the lipid membrane compartment was evaluated using C11-BODIPY in many cellular models (Caro et al., 2011; Iwase et al., 2007; Levraut et al., 2003; Cuddihy et al., 2008). In particular, the ischemia reperfusion injury has been assessed in cardiomyocytes (Iwase et al., 2007; Levraut et al., 2003) and the myeloperoxidase-dependent phenolinduced lipid peroxidation in HL-60 cells (Cuddihy et al., 2008). In addition, C11-BODIPY was used to detect

differences in the oxidative status of RAW264.7 macrophages transfected with either apoE3 or apoE4 in baseline condition (Jofre-Monseny et al., 2007). C11-BODIPY was also able to evaluate hydrogen sulfide cytotoxicity in HepG2 hepatocytes overexpressing cytocrome P450 2E1 (Caro et al., 2011), involved in non alcoholic fatty acid liver disease (NAFALD) in obese women (Varela et al., 2008). This evidence indicates C11-BODIPY as a useful reporter molecule of lipid peroxidation in leukocytes associated with NAFALD and metabolic syndrome symptoms, such as hypercholesterolemia, insulinresistance and oxidative stress condition (Scorletti et al., 2011). From a methodological point of view, oxidation of C11BODIPY causes a shift in fluorescence from red (591) to green (581) (Drummen et al., 2002). Changes in green fluorescence were monitored by flow cytometry in chondrocytes (Dombrecht et al., 2006), spermatozoa (Domínguez-Rebolledo et al., 2010; Brouwers and Gadella, 2003; Partyka et al., 2011), HL60 (Cuddihy et al., 2008) and HepG2 (Caro et al., 2011) cells. Ratio-fluorescence microscopy (Domínguez-Rebolledo et al., 2010; Pap et al., 1999) and spectrofluorimetry (Jofre-Monseny et al., 2007) were used for detection of cellular lipid peroxidation. The aim of this study was to evaluate the use of C11-BODIPY 581/591 as probe to appreciate both exogenous-induced and oxidative burst-induced lipid peroxidation in leukocytes, analyzing the oxidized/reduced fluorescence ratio by flow cytometry in order to normalize for cell incorporation into membrane. We aimed also to define a new index of redox

Fig. 1. Typical dot plots side scatter (SS) versus RATIO [green fluorescence (C11-BODIPY-oxidized)/red fluorescence (C11-BODIPY-reduced)] of leucocytes unstimulated (Unst, A) or treated with AAPH (10 mM, B), PMA (1 μg/ml, C), Trolox (10 μM, C), AAPH and Trolox (D), PMA and Trolox (D) for 30 min. Lymphocytes (R1), monocytes (R2) and neutrophils (R3).

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status of leukocytes to be able to appreciate the effect of differences in antioxidant and metabolic status on cell responses. 2. Material and methods 2.1. Sample stains and treatment Human leukocytes were isolated from buffy coats derived from blood and from whole venous peripheral blood. 50 μl of blood for each condition in duplicate were incubated for 10 min with lysis buffer (1 l of distilled water, 8.02 g of ammonium chloride, 0.84 g of sodium bicarbonate, and 0.37 g EDTA), then the cells were washed twice with phosphate buffered saline (PBS, Sigma). The pellet was suspended in 1 ml of PBS. In preliminary experiments we established an optimal C11-BODIPY (Molecular probes) concentration, loading time and temperature. Leucocyte staining was performed in PBS with C11-BODIPY (1 μM) for 30 min at 37 °C. Phorbol 12-myristate 13-acetate (PMA, Sigma) was used to induce oxidative burst, while water soluble 2,2′-azobis(2methylpropionamidine) dihydrochloride (AAPH, Wako Chemical) was used as free radical generating system, since it generates peroxyl radicals with defined reaction. Total amount of radical (TAR) formed at 37 °C is calculated from the equation: TAR ¼ 1:36  10–6½AAPH  t; where t is time in seconds and the concentration of AAPH is reported as concentration in molar (Packer and Glazer, 1990). The oxidation rate of C11-BODIPY by AAPH is linear between 10 and 30 min, both in terms of increase at 581 nm and decrease at 591 nm of fluorescence (Drummen et al., 2002). Oxidative burst results were evaluated also as previously described using dihydrorhodamine123 (DHR, Sigma) as probe and PMA for activation with lymphocytes as internal standard (Peluso et al., 2012a). The 6-hydroxy-2,5,7,8-tetramethylchroman-2-carboxylic acid (Trolox, Fluka), an analog of vitamin E, was used as standard antioxidant in this method because it inhibits C11-BODIPY oxidation both in the hydrophilic and lipophilic compartments (Caro et al., 2011), as well as in living cells (Dombrecht et al., 2006). After staining, leucocytes were split into different aliquots of 500 μl containing or not (Unst) PMA 1 μg/ml or different concentrations of AAPH and Trolox. The final method requires 300 μl of blood, lysed, washed and re-suspended in 6 ml of C11-BODIPY 1 μM in PBS (DMSO 0.1%) for 6 conditions (Unst, Trolox 10 μM, AAPH 10 mM, AAPH 10 mM+ Trolox 10 μM, PMA 1 μg/ml, PMA 1 μg/ml+ Trolox 10 μM). After 30 min at 37 °C cells were stored in ice, to stop reactions, and rapidly analyzed on a Coulter Epics XL-MCL with Cell Analysis software (Bekman Coulter). 2.2. Flow cytometry acquisition and analysis Forward scatter (FS) and side scatter (SS) were acquired on a linear scale and fluorescence was acquired on a logarithmic scale. Lymphocytes, monocytes and neutrophils were selected by live gates (FS versus SS) as previously described (Peluso et al., 2012a).

Fig. 2. Line plots show the changes in RATIO [green fluorescence (C11-BODIPY-oxidized)/red fluorescence (C11-BODIPY-reduced)] of lymphocytes (A), monocytes (B) and neutrophils (C), isolated from fresh blood (FB) or buffy coat (BC), after treatment with different concentrations of AAPH for 30 min. Data are expressed as means ± standard errors (n = 4). Two way repeated measure ANOVA followed by Student-Newman–Keuls post-hoc analysis: •••p b 0.001 single concentration versus baseline within FB; ***p b 0.001 single concentration versus baseline within BC; and †p b 0.05 FB versus BC within single concentration.

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C11-BOPIPY oxidized (581) and reduced (591) were excited using 488 nm laser and the emission of fluorescence was collected using green (FL1) and red (FL3) filters, respectively. Ratio of fluorescence FL1/FL3 reflecting the oxidized/reduced C11-BODIPY ratio (RATIO) was acquired on single cells to normalize for cell incorporation into membranes. After acquisition, all data were analyzed with Cell analysis software. Representative dot plots of RATIO versus SS were presented in Fig. 1. Comparing with unstimulated cells (Fig. 1A), AAPH or PMA treatment increased fluorescence RATIO, in different manner, showing that all cells are sensitive to exogenous ROS injury (Fig. 1B), while oxidative burst induced ROS production is more evident on neutrophil membranes (Fig. 1C). Trolox, unaffecting baseline level of oxidation (Fig. 1D), inhibits both the peroxidation of C11-BODIPY of leukocytes exposed to AAPH free radicals generating system (Fig. 1E) and after PMA-induced oxidative burst (Fig. 1F). All tests were performed in duplicate and the intra-test variability was b5% for treated and b10% for untreated cells.

(TC) and glucose were quantified enzymatically using colorimetric kits (Sentinel CH). Plasma insulin was measured with an enzyme immunoassay (EIA) kit (TEMA ricerca). Homeostasis model assessment for insulin resistance (HOMA-IR) was also calculated (Yokoyama et al., 2003). The total radical-trapping antioxidant parameter (TRAP) (Ghiselli et al., 1995) and the ferric reducing antioxidant potential (FRAP) (Benzie and Strain, 1996) were used to measure the “chain-breaking” and “ferric-reducing” antioxidant capacities, respectively, of plasma. Determination of sulfhydryls (SHs) was performed using 5,5′-dithiobis-(2-nitrobenzoic acid) (DTNB) (Ellman, 1959). From the relative activity of major endogenous plasma antioxidants previously described (Ghiselli et al., 1995; Benzie and Strain, 1996), we calculate also TRAP-SH-UA and FRAP-UA as scavenger antioxidant capacity and ferric reducing activity derived from nutritional antioxidants, such as ascorbic acid and phenolics, applying the formulas:

2.3. Method sensitivity

FRAP  UA ¼ FRAPμM–2 UAμM:

Sensitivity of the method was assessed by correlating results with common used methods to evaluate antioxidant capacity, as well as with markers of metabolic status. Venous peripheral blood from 8 volunteers (2 men and 6 women, aged between 26–48 years) was collected after an overnight fasting. The plasma was separated by centrifugation at 1300 ×g at 4 °C for 15 min and stored at −80 °C. Plasma levels of uric acid (UA), triglycerides (TG), total cholesterol

TRAP  SH  UA ¼ TRAPμM–0:66 SHμM–1:7 UAμM

2.4. Statistics Data are presented as means±SEM. Statistical analysis was carried out with two way repeated measures (Two Factor Repetition) analysis of variance (2W RM ANOVA), with treatment, type of sample or cell type as within-subjects factors. Student-Newman–Keuls post hoc analysis was used to isolate

Fig. 3. Line plots show the changes in RATIO [green fluorescence (C11-BODIPY-oxidized)/red fluorescence (C11-BODIPY-reduced)] of lymphocytes (A, D), monocytes (B, E) and neutrophils (C, F). Line plots in A, B and C show the competition between AAPH and Trolox, using two concentration of AAPH (10 and 20 mM) and different concentrations of Trolox (5–40 μM) on leukocytes isolated from buffy coat (BC, n= 7). Line plots in D, E and F show the dose response curve of Trolox on AAPH (10 mM) induced oxidation in fresh blood (FB) or BC (n = 6). Data are expressed as means ± standard errors. Two way repeated measure ANOVA followed by Student-Newman–Keuls post-hoc analysis: •p b 0.05, and •••p b 0.001 single concentration versus baseline within FB; *p b 0.05, **p b 0.01; and ***p b 0.001 single concentration versus baseline within BC; †p b 0.05, ††p b 0.01 and †††p b 0.001 FB versus BC within single concentration.

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differences between groups. Linear and second order polynomial regressions were used to evaluate dose response curves. Spearman correlation was used to evaluate relationships between variables. 3. Results and discussion In the first step, the concentration–response relation of AAPH was determined in both fresh blood (FB) and buffy coat (BC) (Fig. 2). Raising baseline levels of oxidation, were found in lymphocytes (FB 473.0± 40.5, BC: 394.1 ±40.8, Fig. 2A), monocytes (FB: 591.0 ±49.1, BC: 518.6 ± 30.1, Fig. 2B) and neutrophils (FB: 632.0± 33.2, BC: 566.3 ± 33.8, Fig. 2C), as expected by their intrinsic ROS production. In the regression analysis for both FB and BC there was a significant correlation with a second order polynomial regression (Fig. 2). At each point of the dose response 2W RM ANOVA showed no differences between FB and BC except for a 20 mM of AAPH on neutrophils (Fig. 2C). For subsequent experiments we chose AAPH concentrations which led to a maximum oxidation (10 mM and 20 mM). This was done to ensure antioxidant effect of the standard Trolox. The latter was tested as a competitor of AAPH-induced oxidation by changing the ratio of AAPH/Trolox concentration on BC samples (Fig. 3A, B and C). Linear regression revealed a similar slope for both concentrations but with higher R2 for AAPH 10 mM. Therefore, we compared the effect of different concentrations of Trolox on 10 mM AAPH-induced lipid peroxidation on FB and BC derived leukocytes (Fig. 3D, E and F). The antioxidant effect of Trolox was higher in BC compared with FB at all doses tested and the slope was higher for lymphocytes (Fig. 3D), which do not produce ROS themselves, compared with monocytes (Fig. 3E) and neutrophils (Fig. 3F). At 10 μM of Trolox, differences between neutrophils and other leukocytes also appeared, probably due to the improving effect of antioxidant on innate immune response (Webb and Villamor, 2007). To test this hypothesis, we compared the effect of Trolox on PMA-induced ROS production in FB (Fig. 4A) using DHR assay as control test (Fig. 4B). However, no differences in oxidative burst were detected after Trolox treatment with both methods. Finally, we compared the effect of Trolox on both AAPH and PMA induced peroxidation in FB and BC (Fig. 5). We tried to evaluate free radicals generated by oxidative burst as AAPH mM equivalents (AAPHeq) using the formula:

RATIO AAPH=RATIO UNST : ½AAPH ¼ RATIO PMA=RATIO UNST : AAPHeq

However, even though this value discriminates between the different leukocytes (Fig. 5A) it is biased by the effect of ROS generated by oxidative burst and by the baseline levels of lipid peroxidation. The former produced significant increase in RATIO of fluorescence in non ROS-producing lymphocytes (Fig. 5B), while the latter was slightly higher in FB compared with BC and does not differentiate lipid peroxidation in neither monocytes and neutrophils after PMA-activation versus unstimulated cells (Fig. 5C and D), nor in neutrophils after the two methods of ROS generating systems (Fig. 5D).

Fig. 4. Vertical bars depict the data obtained after PMA (1 μg/ml) induced oxidative burst in leukocytes isolated from fresh blood, with the two ROS-sensitive probes: membrane permeating C11-BODIPY (A) and intracellular DHR (B). RATIO = [green fluorescence (C11-BODIPY-oxidized)/red fluorescence (C11-BODIPY-reduced)]. Data are means ± SEM (n = 8). Two way repeated measure ANOVA followed by Student-Newman–Keuls post-hoc analysis, treatment versus respective control (Unst: •p b 0.05, ••p b 0.01, •••p b 0.001; Trolox: *p b 0.05, **p b 0.01, ***p b 0.001) within cells: monocytes and neutrophils. Cells within treatment are significantly different (p b 0.001) with both probes.

Therefore, considering the differences in Trolox responses and in order to evaluate the leukocyte oxidative status, we used the ratio between the lipid peroxidative damage induced by exogenous peroxyl radicals and oxidative burst induced ROS in the presence and absence of this standard antioxidant and defined this ratio as Peroxidation of Leukocytes Index Ratio (PLIR). From the formulas: RATIO AAPH Trolox=RATIO Trolox : ½Trolox ¼ RATIO AAPH=RATIO UNST : ½TxeqAAPH RATIO PMA Trolox=RATIO Trolox : ½Trolox ¼ RATIO PMA=RATIO UNST : ½TxeqPMA PLIR ¼ ½TxeqAAPH=½TxeqPMA PLIR ¼ ðRATIO AAPH  RATIO PMA TroloxÞ= ðRATIO AAPH Trolox  RATIO PMAÞ This index measures the ratio between the resistance to exogenous (Trolox μM equivalents AAPH, TxeqAAPH) and endogenous (Trolox μM equivalents PMA, TxeqPMA) ROS

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Fig. 5. Vertical bars depict the data obtained with leukocytes from fresh blood (FB) or buffy coat (BC). Vertical bars in A show the AAPHeq mM after PMA (1 μg/ml) induced oxidative burst in lymphocytes, monocytes and neutrophils. Vertical bars in B, C and D show the changes in RATIO=[green fluorescence (C11-BODIPY-oxidized)/red fluorescence (C11-BODIPY-reduced)] of leucocytes unstimulated (Unst) or treated with AAPH (10 mM), PMA (1 μg/ml), Trolox (10μM), AAPH and Trolox, PMA and Trolox for 30 min. Data are means±SEM (n=4). Two way Repeated Measure ANOVA followed by Student-Newman–Keuls post-hoc analysis: ••pb 0.01, •••pb 0.001 cells (A) or treatment (B,C,D) within FB, and **pb 0.01; ***pb 0.001 cells (A) or treatment (B,C,D) within BC. †pb 0.05 FB versus BC within treatment.

injury and is independent from baseline levels of oxidation and Trolox concentration but takes into account also the potential effect of antioxidant on oxidative burst. Comparing the results on FB and BC (Figs. 2 and 3) we suppose that the RATIO AAPH should be only slightly variable and that the RATIO AAPH Trolox could be related to NEAC values. The latter is affected by physical activity (Kavouras et al., 2010), smoking (Bloomer, 2007) and dietary habits (Kavouras et al., 2010). On the other hand, a defective neutrophil function can contribute to inflammatory disease progression and is associated with the process of aging (Magrone and Jirillo, 2012), potentially decreasing RATIO PMA. Besides, antioxidants could improve innate immunity (Webb and Villamor, 2007), increasing RATIO PMA and decreasing the effect of Trolox. To validate the method and evaluate the sensitivity of PLIR to cellular redox status, we correlated the results with common used methods to measure antioxidant capacity, as well as with markers of metabolic status associated with low grade inflammation. In Table 1 we present plasma levels of different biomarkers of the subjects and their coefficients of correlation (CC) with PLIR. This index of lymphocytes and monocytes is inversely correlated with uric acid levels, while in neutrophils

the correlation is near to significance (Table 1). This evidence is in agreement with the hypothesis that uric acid is one of the main endogenous danger signals for the immune system (Shi et al., 2003). Besides, uric acid exerts both antioxidant or pro-oxidant effect on oxidative burst induced LDL oxidation and its reducing activity on iron could increase Fenton reaction subsequent to hydrogen peroxide production induced by oxidative burst (Peluso et al., 2012b). In agreement with this hypothesis, also inverse correlations were observed between the PLIR of lymphocytes and FRAP and FRAP-UA, significant and near to significance respectively (Table 1). The absence of correlation of ferric reducing activity with monocytes and neutrophils PLIR could be due to their high content of GPX and catalase, respectively (Peluso et al., 2012b). Contrarily with FRAP, based on chemical reaction involved a single electron transfer (SET), TRAP measures the “chain-breaking” antioxidant capacity by a hydrogen atom transfer (HAT) reaction, (Serafini et al., 2011). TRAP values were unrelated with PLIR, however, not only uric acid but also endogenous antioxidant SH presented an inverse correlation near to significance with PLIR (Table 1). A possible explanation

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Table 1 Values of antioxidant and metabolic markers and their correlation with PLIR.

SH μM UA μM FRAP μM TRAP μM FRAP-UA μM TRAP-SH-UA μM TG mg/dl TC mg/dl Glucose mg/dl Insulin mU/l Homa-IR

PLIR-L Range 0.69–1.64

PLIR-M Range 0.84–1.26

PLIR-N Range 0.84–1.15

MEAN ± SEM (n = 8)

CC (p)

CC (p)

CC (p)

540.2 ± 32.1 270.2 ± 8.3 848.3 ± 59.9 1177.2 ± 64.9 307.9 ± 44.5 361.3 ± 47.2 152.5 ± 10.0 173.3 ± 5.9 81.3 ± 2.0 10.2 ± 1.3 2.0 ± 0.2

−0.611 (0.089) −0.810 (0.009) −0.738 (0.029)

−0.690 (0.047)

−0.667 (0.059)

−0.643 (0.072) 0.738 (0.029)

CC = correlation coefficient. Only correlation significant or near to significance were reported.

of this effect could be found in the recent findings that thiols shift the T helper (Th)1/Th2 balance toward a Th1 phenotype, increasing IFN-γ production (Hoffmann et al., 2010). Considering that the great majority of antioxidant compounds has multiple antioxidant properties, not only reducing but also chain breaking activities, we calculate also TRAP-SH-UA to evaluate the effect of nutritional scavengers. The latter was directly correlated with PLIR of monocytes (Table 1). This finding is suggestive of further investigation considering the differential response of monocytes and neutrophils in some conditions, such as hypercholesterolemia (Peluso et al., 2012a) and diabetes (Noritake et al., 1992). No correlation were found between PLIR and markers of glucose and lipid metabolism (Table 1), however this was not the aim of the present work where we chose subjects with biochemical parameter in normal range to validate the methods. Therefore, we observed a correlation between plasma cholesterol and baseline levels of lipid peroxidation of lymphocytes (RATIO Range: 384–583; CC: 0.738, p=0.029), monocytes (RATIO Range 512–692; CC: 0.691, p=0.047) and neutrophils (RATIO Range: 560–731; CC: 0.690, p=0.047). The correlation is present also in lymphocytes which do not produce ROS, further strengthening the hypothesis that plasma-membrane C11-BODIPY probe supply additional information that could be integrated with those obtained with intracellular ROS-sensitive probes. 4. Conclusion In summary, this study defined a new method and the appropriate experimental conditions, with C11-BODIPY as a reporter molecule, for evaluating the leukocytes redox status by flow cytometry. Using the ratio between lipid peroxidative damage induced by exogenous peroxyl radicals and oxidative burst in the presence and absence of a standard antioxidant we defined the PLIR. The latter, supplies additional information with respect to commonly used methods to assess antioxidant status and reflects the complex relationship between scavenger and reducing antioxidant activities with leukocytes responses and lipid peroxidation. In particular, PLIR is able to appreciate the potentially dangerous effect of uric acid on innate immune response. For this reason, this new method could be useful to evaluate the redox status of leukocytes in both pathological conditions

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