This study has demonstrated for the first time that cryopreservation of primary immune cells modified their metabolism in a time-dependent fashion, indicated by attenuated aerobic respiration and enhanced glycolytic activity. Measurements were recorded using the Seahorse XFe96 extracellular flux analyser.

CLINICAL PERSPECTIVES

  • Freezing primary leucocytes in 50% complete RPMI, 40% autologous plasma and 10% DMSO did not alter cellular bioenergetics when maintained in LN2 for up to 4 weeks.

  • Long-term cryopreservation, which is routinely performed in the clinic, modulates immune cell bioenergetics and these cells become more glycolytic following revival.

  • Careful consideration of cryopreservation methods must be applied when using frozen leucocytes in the assessment of mitochondrial function or determination of BHI in the clinic.

INTRODUCTION

Peripheral blood mononuclear cells (PBMCs) and polymorphonuclear (PMN) cells play an import role in the innate and adaptive immune systems and therefore provide protection from invading micro-organisms such as bacteria and viruses [1]. However, these immune cells are also influential in the development and progression of inflammatory disorders, including diseases associated with the metabolic syndrome (MetS). It is widely accepted that development of obesity is accompanied by a chronic low-grade infiltration of immune cells into adipose tissue (comprehensively reviewed in [2]).

MetS is a major global health issue and is centralized around obesity, along with other key elements including hypertriglyceridaemia, low level of HDL (high-density lipoprotein) cholesterol, high blood pressure and elevated fasting glucose [3]. Since leucocytes circulate in the vasculature, they are exposed to a range of nutritional, metabolic and immunological stimuli that are derived from various tissues. Consequently, these cells are a particularly useful source for biomarkers in health and disease, as their isolation is relatively non-invasive with clear advantages over painful tissue biopsy. In addition, they also offer a tissue alternative to other inaccessible organs for diagnostic purposes, such as the brain in neurodegenerative disorders. Interestingly, it has been demonstrated that the transcriptome of PBMCs display a tight correlation with the transcriptome of solid tissues [4], including genes globally associated with immune function and amino acid metabolism in subcutaneous adipose tissue [5].

Many studies have explored the relationship between the total leucocyte number and the measurements of obesity and MetS (expertly reviewed in [2]). Due to inconsistencies with some data, these diagnostic methods have subsequently failed to translate to clinical usefulness [2]. Conversely, other investigators have instead attempted to associate the proportion of different leucocyte cell types, such as monocytes [6], lymphocytes [7,8] and neutrophils [7], with markers of MetS, including increased body mass index (BMI) and increased triglyceride levels. However, even though positive associations were found in several studies [68], examining immune cell subtype, such as CD14dimCD16+ monocytes [9], CD4+ [10] or CD8+ [11] T-cells, displayed better correlation with obesity and MetS, over total monocyte or lymphocyte populations [12,13]. The inconsistencies in the previous data may be dependent on other factors, for instance, age, sex, race and smoking status [2].

Previous studies have described that changes in gene expression [14,15], surface protein markers [911] or even bioenergetics [16] in white blood cells provides a more robust correlation with degree of, and propensity to develop, MetS, obesity or diabetes. Numerous studies have harnessed PBMCs as a potential tool to determine the inflammatory and metabolic status in a variety of different disease states, including sepsis [17], neurodegeneration [18], rheumatic disease [19], obesity [12,20], cardiovascular disease [21] and diabetes mellitus [16,22], all of which have been linked to mitochondrial dysfunction or altered bioenergetics. Moreover, Chacko et al. [23] have suggested that calculation of a bioenergetic health index (BHI), which incorporates various mitochondrial bioenergetic parameters, may be used as a potential prognostic or diagnostic biomarker in disease.

Cryopreservation of leucocytes is a practical procedure to allow long-term storage and analysis of phenotypic and functional changes in these cells at a later date. This routinely used technique is particularly useful in vaccine research and assessment of infectious disease in preserved samples [24]. Interestingly, most articles examining mitochondrial function and disease in primary immune cells have used freshly isolated cells [1622], which may present a practical and/or financial obstacle for research institutions or hospitals without access to busy blood donation networks. Consequently, the aim of the current validation study was to determine the influence of cryopreservation on leucocyte mitochondrial function and BHI, so that this method of cryopreservation can be used in the design of future studies. To the best of our knowledge, the impact of cryopreservation on leucocyte bioenergetics and BHI has not been previously described and this information may provide critical insights into the subsequent interpretation of data derived from cryopreserved samples in relation to diagnostic markers of disease risk, progression or remission.

METHODS

Participants’ characteristics and ethics

The present pilot study was conducted using circulating blood leucocytes from eight overweight participants (four men and four women; n=8), free of major illness and not taking medications. General characteristics of the patient profiles are presented in Table 1. Bio-impedance analysis (Model mBCA 514) (SECA) was used to evaluate body composition. Informed consent was obtained from all participants prior to beginning the study. Research assessments and protocols were approved by the Human Research Ethics Committee of Curtin University, Perth, Western Australia (ethics approval number SPH-31-2014).

Table 1
Clinical characteristics of participants involved in the study

Data are reported as mean ± S.D.; n=8.

VariableValue
Age (y) 28.8±2.4 
Weight (kg) 87.2±3.9 
BMI (kg/m227.7±1.0 
Fat free mass (kg) 60.7±3.0 
Skeletal muscle (kg) 30.5±1.8 
Fat mass (kg) 26.6±3.1 
Body fat (%) 30.3±2.6 
VariableValue
Age (y) 28.8±2.4 
Weight (kg) 87.2±3.9 
BMI (kg/m227.7±1.0 
Fat free mass (kg) 60.7±3.0 
Skeletal muscle (kg) 30.5±1.8 
Fat mass (kg) 26.6±3.1 
Body fat (%) 30.3±2.6 

Immune cell isolation, population determination and cryopreservation

Sixty millilitres of whole blood was drawn by venepuncture in EDTA–citrate vacutubes from patients fasting overnight and diluted 1:1 in PBS–EDTA (2 mM). The diluted blood was then applied to an equivalent volume of Histopaque 1077 (Sigma–Aldrich) and centrifuged at 600 g for 20 min with minimum acceleration and no braking. Autologous plasma samples (3 ml) were taken from the upper layer, whereas immune cells were isolated from the ‘buffy coat’ and washed with EDTA-free PBS. Washing and centrifugation was repeated at 300, 200 and 100 g for 10 min each, to remove contaminating platelets. The cell pellet was resuspended in 2.5 ml of warm Roswell Park Memorial Institute medium (RPMI)-1640 (10% FBS, 2 mM glutamine, 100 units/ml penicillin and 0.1 mg/ml streptomycin) and an aliquot taken to determine the cell number and percentage proportion of immune cells (lymphocytes, monocytes and granulocytes) using the automatic Mindray BC2800 haematological analyser. Finally, 2.5 ml of autologous plasma containing 20% DMSO was added to the cells in 2.5 ml RPMI, giving a final cell suspension of 5 ml containing 50% RPMI, 40% autologous plasma and 10% DMSO. The cell suspension was aliquotted in four 1-ml volumes, noting the total cell number in each and then frozen at −80°C overnight in an insulated Mr. Frosty container (Nalgene) containing propan-1-ol. The vials were then transferred to liquid nitrogen (LN2) at −196°C for 14, 28, 56 and 84 days prior to revival. The remaining 1 ml volume of cell suspension was further prepared as outlined below, seeded into the Seahorse assay XFe96 culture plate and represented bioenergetics analysis at day 0. All samples were processed within 5 h of blood collection. After completion of the cryopreservation validation study, fresh leucocytes were again isolated from returning patients (RETURN sample), analysed and compared with the initial day 0 fresh samples (INITIAL) to determine if the patient immune cell profile changed and to ensure reproducibility of the isolation technique.

Revival of cells and calculation of percentage recovery and percentage viability

Each vial containing 1 ml of cell suspension was revived at the appropriate time point by incubating the vial in a waterbath at 37°C for 2 min, with the exception of the day 0 sample which was immediately available for further preparation. The revived or day 0 aliquots were then transferred to a fresh tube with 3 ml of warm RPMI and centrifuged at 300 g for 10 min. The cell pellet was then resuspended in 500 μl of warm fresh RPMI and counted using a haemocytometer with Trypan Blue dye to determine the total cell number and the total viable cells. Percentage recovery and percentage viability were calculated as defined below. Cells were seeded at a density of 3.5×105 cells/well after revival, in a poly-D-lysine coated Seahorse XFe96 culture plate, as published previously [16] and allowed to adhere overnight before execution of the Seahorse stress tests.

Percentage recovery (% recovery)=[total no. of cells recovered after revival ÷ total no. of cells originally frozen] × 100

Percentage viability (% viability)=[no. of viable cells after revival ÷ total no. of cells after revival] × 100

Seahorse XFe96 measurements

The Seahorse Bioscience XFe96 Flux analyser was used according to manufacturer's instructions. The reagents used for performing the Mito and glycolytic stress tests were previously optimized to ensure that the lowest concentration yielded the maximum effect and all chemicals were obtained from Sigma–Aldrich. In brief, cells were seeded into 96-well plates at a density of 3.5×105 cells/well and allowed to adhere overnight. Cell density was previously optimized so that the oxygen consumption rate (OCR) and proton production rate (PPR) measurements met the manufacturer's criteria. On the day of the Seahorse analysis and stress tests, the spent culture medium was changed manually to serum-free Dulbecco's Modified Eagle's Medium (DMEM; pH 7.4) containing 1 mM sodium pyruvate, 2.5 mM glucose and without biocarbonate for the Mito stress test or to the same medium without glucose (0 mM) for the glycolytic stress test. Plates were then incubated for 60 min at 37°C in a non-CO2 incubator, to allow the cells to become equilibrated with the new medium. The XFe96 sensor cartridge which was pre-hydrated for 24 h prior to assay with calibrant solution at 37°C in a non-CO2 incubator, was inserted into the instrument and the calibration process initiated. Following successful calibration, the culture plate with cells was placed in the instrument. After recording of basal measurements, the Mito stress test injection strategy consisted of oligomycin (5 μM), Carbonyl cyanide 4-(trifluoromethoxy)phenylhydrazone (FCCP) (1.5 μM) and finally rotenone/antimycin A in combination (6 μM). The glycolytic stress test injection strategy consisted of DMEM with glucose (25 mM), oligomycin (5 μM) and finally 100 mM 2-deoxyglucose (2DG). OCR and PPR were measured using three 3.5-min cycles of mix and measurement following each injection. Normalization of leucocyte respiratory/glycolytic parameters was performed by assessing total protein concentration after the Seahorse experiment using the BCA protein assay (Thermo).

Seahorse data analysis

Data analysis was performed as previously described [25]. In brief, basal respiration was calculated by subtracting the minimum OCR following addition of rotenone/antimycin A (non-mitochondrial respiration) from the last OCR measurement recorded prior to addition of oligomycin. Proton leak was calculated by subtracting the minimum OCR following addition of rotenone/antimycin A (non-mitochondrial respiration) from the minimum OCR measurement recorded after addition of oligomycin. OCR related to ATP production (turnover) was calculated by the difference between the proton leak and basal respiration above. Coupling efficiency percentage was calculated by dividing the ATP turnover-dependent OCR by the basal respiration and multiplying by 100. Maximum (MAX) respiration was determined by subtracting the non-mitochondrial respiration OCR from the maximum OCR in response to FCCP, whereas reserve capacity was the difference between the basal respiration and the calculated MAX respiration. Extracellular acidification rate (ECAR) was converted into PPR by including the buffer capacity of the medium into the Seahorse software. Buffer capacity was determined by monitoring the pH change of DMEM following five additions of a known quantity of protons from 0.1 M hydrochloric acid. Basal glycolysis in the presence of 0 mM glucose was determined by the difference between the initial PPR and the PPR following 2DG addition. Glycolytic response to 25 mM glucose was determined by subtracting the maximum PPR following addition of glucose from the last PPR measurement prior to addition of glucose. Glycolytic capacity was measured by subtracting the minimum PPR following 2DG addition from the maximum PPR after injection of oligomycin. Finally, glycolytic reserve was determined from the difference between the glycolytic capacity and the glycolytic response to 25 mM glucose. Each treatment was measured in at least triplicate wells. Data represents mean mitochondrial or glycolytic parameters, calculated from eight independent patient samples (n=8)

Calculation of bioenergetic health index

The BHI of each sample was calculated as defined below and according to [23]. The BHI for all samples was averaged at each cryogenic time point for comparative purposes. Our data did not facilitate the weighting of each mitochondrial parameter using exponents as published previously [23]. Consequently, as a proof of concept, the data presented herein was calculated using the raw bioenergetic data, weighted with exponents of one and without the application of the log transfer.

BHI=[reserve capacity OCR × ATP-linked OCR] ÷ [non-Mito OCR × proton leak OCR]

Statistical analysis

Statistical analyses across the different times of cryopreservation for each individual bioenergetic parameter were performed using one-way ANOVA. Whenever P-values were less than 0.05, specific statistically significant time-dependent differences were identified by Tukey's (Tukey honest significant difference) test. For the initial (fresh) and cryopreserved (return) comparisons on immune cell composition, the unpaired parametric ttest was performed, with P-values less than 0.001 (Figure 1A). All statistical calculations and graphics were performed using GraphPad Prism software v. 6.0.

Immune cell composition and the effect of cryopreservation on cell recovery and viability

Figure 1
Immune cell composition and the effect of cryopreservation on cell recovery and viability

(A) After harvesting of blood, the percentage proportion of immune cells (lymphocytes, monocytes and granulocytes) was determined using the automatic Mindray BC2800 haematological analyser. Lymphocytes constituted the majority of the isolated population (71.0±2.0%), followed by granulocytes (24.6±2.0%) and then monocytes (9.3±0.8%). These populations did not change significantly when fresh RETURN samples were analysed after completion of the study. (B) Cryopreservation decreased the number of recovered cells, but only after day 14 in LN2. (C) Cryopreservation decreased the number of viable cells by approximately 15%, but this was independent of time in LN2. *Significantly different from day 0.

Figure 1
Immune cell composition and the effect of cryopreservation on cell recovery and viability

(A) After harvesting of blood, the percentage proportion of immune cells (lymphocytes, monocytes and granulocytes) was determined using the automatic Mindray BC2800 haematological analyser. Lymphocytes constituted the majority of the isolated population (71.0±2.0%), followed by granulocytes (24.6±2.0%) and then monocytes (9.3±0.8%). These populations did not change significantly when fresh RETURN samples were analysed after completion of the study. (B) Cryopreservation decreased the number of recovered cells, but only after day 14 in LN2. (C) Cryopreservation decreased the number of viable cells by approximately 15%, but this was independent of time in LN2. *Significantly different from day 0.

RESULTS

Anthropometric measurements and leucocyte composition in patients

Overweight patients were selected for the present study, with an average BMI of 27.7±1.0 kg/m2 (Table 1). The cohort consisted of four males and four females of similar age (28.8±2.4 y), all with elevated body fat (30.3±2.6%; Table 1). The population of leucocytes isolated from these subjects were comparable, with a low S.E.M. Lymphocytes were the main population isolated (71.0±2.0%), followed by granulocytes (24.6±2.0%) and then monocytes (9.3±0.8%; Figure 1A). These populations did not change significantly when fresh RETURN samples were analysed after completion of the study (Figure 1A).

The effect of cryopreservation on cell recovery and viability

Immune cells were cryopreserved using a combination of standard RPMI medium (50%), autologous plasma (40%) and DMSO (10%). As expected, after cryopreservation, the total cell number of cells recovered and the number of viable cells both decreased (Figure 1B and 1C). However, the percentage of recovered and viable cells from cryopreservation did not change significantly following revival, even after being frozen for up to 12 weeks (Figures 1B and 1C). The lowest average cell recovery and cell viability percentages were 71.8±4.7% and 82.2±2.3% respectively, after day 14 in LN2 (Figures 1B and 1C). Therefore, our method of cell cryopreservation, recovered at least 70% of cells, with at least 80% viability over the duration of the study (Figures 1B and 1C).

The effect of cryopreservation on leucocyte mitochondrial parameters

Several parameters of mitochondrial function are described in Figure 2. The basal OCR of fresh leucocytes was estimated to be approximately 4.5 pmoles O2/min/μg total protein (Figure 2A) and this parameter reflected the oxygen that is consumed during mitochondrial respiration. When measured in cells that were cryopreserved and normalized for total cellular protein, there was a time-dependent decrease in basal respiration that became significant following day 56 and 84 in LN2, to approximately 2.5 pmoles O2/min/μg total protein (Figure 2A). This trend was very similar to those found in other parameters, including the OCR associated with ATP production (Figure 2B), the MAX respiration of mitochondria (Figure 2C) and the reserve capacity of mitochondria for additional respiration (Figure 2D). Following day 56 of storage in LN2, OCR coupled to ATP production decreased significantly (<0.05) from 3.8 pmoles O2/min/μg total protein for fresh cells (day 0), to 1.5 pmoles O2/min/μg total protein (Fig-ure 2B). This decrease was also demonstrated in calculation of coupling efficiency, a ratio of basal compared with ATP-coupled respiration (Figure 2E). MAX respiration (after chemical uncoupling with FCCP), decreased from 20 pmoles O2/min/μg total protein for fresh cells (day 0), to 10 pmoles O2/min/μg total protein (Figure 2C), whereas the reserve capacity for respiration decreased from 17 pmoles O2/min/μg total protein for fresh cells (day 0), to 9 pmoles O2/min/μg total protein (Figure 2D). Interestingly, measurement of proton leak (uncoupled respiration) increased slightly but only significantly following day 84 in LN2 (Figure 2F). This was only significant in comparison with the data at day 14 and not with data from fresh cells (day 0). However, these data demonstrated that in most mitochondrial parameters, bioenergetics was significantly altered in leucocytes after storage in LN2 for greater than 1 month (day 28).

The effect of cryopreservation on leucocyte parameters of mitochondrial function

Figure 2
The effect of cryopreservation on leucocyte parameters of mitochondrial function

Cryopreservation decreased most parameters of mitochondrial function in a time-dependent manner, including basal respiration (A), ATP production (B), MAX respiration (C), reserve capacity (D) and coupling efficiency (E). Proton leak was elevated but only after day 84 (F). *Significantly different from day 0; #significantly different from day 14; &significantly different from day 28.

Figure 2
The effect of cryopreservation on leucocyte parameters of mitochondrial function

Cryopreservation decreased most parameters of mitochondrial function in a time-dependent manner, including basal respiration (A), ATP production (B), MAX respiration (C), reserve capacity (D) and coupling efficiency (E). Proton leak was elevated but only after day 84 (F). *Significantly different from day 0; #significantly different from day 14; &significantly different from day 28.

The effect of cryopreservation on leucocyte glycolytic parameters

The acute response of leucocytes to a stimulatory concentration of glucose (25 mM) and measurement of subsequent glycolytic parameters was also performed and the results are displayed in Figure 3. Basal glycolysis was a measurement of the rate of PPR when cells were in a minimal medium (DMEM), containing 0 mM glucose, but supplemented with 2 mM alanyl–glutamine and 1 mM sodium pyruvate. The PPR determined for fresh cells in these conditions was approximately 2 pmoles H+/min/μg total protein (Figure 3A). Similar PPR was observed for cells stored in LN2 for 14 and 28 days (Figure 3A). However, after the latter time point, the PPR reduced significantly to 1 pmoles H+/min/μg total protein for cells stored for 56 and 84 days in LN2. Interestingly, these cells responded better to glucose stimulation and the measurement of glycolytic response to 25 mM glucose showed a time-dependent increase in PPR from 2.5 pmoles H+/min/μg total protein for cells at day 0, to approximately 5 pmoles H+/min/μg total protein for cells in LN2 from day 28 to 84 (Figure 3B). However, even though there was no significant change in the glycolytic capacity of fresh or previously frozen cells (Figure 3C), predictably, due to the glycolytic response data described above, leucocytes maintained in LN2 demonstrated an impaired glycolytic reserve at day 56 and 84 (Figure 3D). Taken together, these data demonstrated again that cryopreservation induced significant modifications in leucocyte cellular metabolism, particularly following 1 month (day 28) in LN2.

The effect of cryopreservation on leucocyte glycolytic parameters

Figure 3
The effect of cryopreservation on leucocyte glycolytic parameters

Cryopreservation decreased basal glycolysis in the absence of glucose in a time-dependent manner (A), whereas the enhanced glycolytic response to 25 mM glucose was time-dependent (B). No significant change in glycolytic capacity was observed (C), whereas glycolytic reserve was increased but only upto day 28 (D). *Significantly different from day 0; #significantly different from day 14; &significantly different from day 28.

Figure 3
The effect of cryopreservation on leucocyte glycolytic parameters

Cryopreservation decreased basal glycolysis in the absence of glucose in a time-dependent manner (A), whereas the enhanced glycolytic response to 25 mM glucose was time-dependent (B). No significant change in glycolytic capacity was observed (C), whereas glycolytic reserve was increased but only upto day 28 (D). *Significantly different from day 0; #significantly different from day 14; &significantly different from day 28.

Comparison of OCR and PPR in leucocytes exposed to various concentrations of glucose (0, 2.5 and 25 mM)

We have performed a direct comparison of the corresponding OCR and PPR data obtained from cells exposed to 0, 2.5 or 25 mM glucose following storage for various periods from 0 to 84 days (Figures 4A–4C respectively). In all glucose concentrations, cells stored until day 56 or 84 demonstrated clearly different metabolic OCR/PPR profiles to the cells stored for shorter periods, reflecting a shift of aerobic to glycolytic metabolism as illustrated by increasing PPR. The OCR rates for cells demonstrated a bi-phasic response to glucose concentration (decreasing at 2.5 mM glucose, only to increase at 25 mM glucose) but the cells stored for shorter periods (0–28 days) always demonstrated higher OCR rates than cells stored for longer periods at all glucose concentrations tested. Of note, cells exposed to 0 mM glucose, displayed a higher OCR than cells exposed to 2.5 mM glucose which may indicate that these cells adapted to the 0 mM glucose condition by enhanced amino acid or lipid oxidation, but this oxidative capacity was impaired in day 56 and 84 cells (Figure 4A). Clearly, 25 mM glucose was able to restore OCR levels, as glucose became the primary fuel for oxidation. Overall, our data demonstrated that cryopreservation decreased OCR at the levels of glucose tested, whereas cells stored for longer periods (56 or 84 days) increased glycolytic output in response to glucose availability.

Comparison of OCR and PPR measurements in leucocytes exposed to various concentrations of glucose (0, 2.5 and 25mM)

Figure 4
Comparison of OCR and PPR measurements in leucocytes exposed to various concentrations of glucose (0, 2.5 and 25mM)

Simultaneous OCR and PPR measurements of leucocytes in the presence of 0 (A), 2.5 (B) or 25 mM (C) glucose. Cells stored until day 56 or day 84 clearly demonstrated different metabolic OCR/PPR profiles. *OCR significantly different from the group of [day 0, 14 and 28]; #PPR significantly different from the group of [day 0, 14 and 28]; θOCR significantly different from the group of [day 0 and 14]; &PPR significantly different from [day 0].

Figure 4
Comparison of OCR and PPR measurements in leucocytes exposed to various concentrations of glucose (0, 2.5 and 25mM)

Simultaneous OCR and PPR measurements of leucocytes in the presence of 0 (A), 2.5 (B) or 25 mM (C) glucose. Cells stored until day 56 or day 84 clearly demonstrated different metabolic OCR/PPR profiles. *OCR significantly different from the group of [day 0, 14 and 28]; #PPR significantly different from the group of [day 0, 14 and 28]; θOCR significantly different from the group of [day 0 and 14]; &PPR significantly different from [day 0].

Impact of cryopreservation on bioenergetic health index

Calculation of BHI was performed for all samples over the course of the study (Figure 5). A time-dependent decrease in BHI was observed following cryopreservation. Fresh leucocytes displayed a mean BHI measurement of approximately 25. However, this was significantly reduced to 15, after day 14. The BHI diminished further following 28 days in LN2 and appeared to plateau following 28, 56 and 84 days. The BHI at these latter time points were not significantly different from each other.

The effect of cryopreservation on calculated BHI

Figure 5
The effect of cryopreservation on calculated BHI

Calculation of BHI was performed for all samples over the course of the study and the mean results are shown in Figure 5. A time-dependent decrease in BHI was observed following cryopreservation. Fresh leucocytes displayed a mean BHI measurement of approximately 25. However, this was reduced to 15 after day 14 and declined further after day 28. However, the diminished BHI begun to plateau after day 28, 56 and 84. The BHI at these latter time points were not significantly different from each other. *Significantly different from day 0; #significantly different from day 14.

Figure 5
The effect of cryopreservation on calculated BHI

Calculation of BHI was performed for all samples over the course of the study and the mean results are shown in Figure 5. A time-dependent decrease in BHI was observed following cryopreservation. Fresh leucocytes displayed a mean BHI measurement of approximately 25. However, this was reduced to 15 after day 14 and declined further after day 28. However, the diminished BHI begun to plateau after day 28, 56 and 84. The BHI at these latter time points were not significantly different from each other. *Significantly different from day 0; #significantly different from day 14.

DISCUSSION

In the present study, we isolated peripheral white blood cells (lymphocytes, monocytes and granulocytes) from overweight individuals and measured the impact of cryopreservation on cell bioenergetics using the Seahorse Bioscience XFe96 flux analyser. Isolation of immune cells and assessment of the bioenergetic status in disease is not a new concept. Several articles have previously examined the extent of oxygen consumption in immune cells, such as monocytes or PBMCs, in sepsis [17], rheumatic disease [19] and diabetes mellitus [16]. In these cases, oxygen consumption in disease was generally elevated, particularly during basal and uncoupled respiration (as indicated by proton leak) and following stimulation of electron transport chain (ETC) activity with FCCP (MAX respiration). However, these studies were cross-sectional and performed using freshly isolated immune cells, which may have logistical disadvantages over frozen samples, for example, availability of donors and assay to assay variation. Therefore, if cryopreservation can be routinely employed without inducing significant changes in bioenergetics, this would offer an advantage in longitudinal studies, where samples can be analysed together to minimize assay variation, also providing flexibility for studies using different operators in multiple laboratories [24].

Cryopreservation of immune cells is a common practice in the clinic and is routinely used to preserve blood cells for future functional or immunological analysis, particularly in HIV diagnosis and research [15,2628]. However, cryopreservation can induce detrimental functional effects in cells, thus it is important that these effects do not influence the subsequent functional analysis following revival. The most common problem associated with cryopreservation is decreased cell viability, as assessed using Trypan Blue exclusion staining. Generally, cell viability is dependent on the type and concentration of cryoprotective agent (CPA) used (DMSO, ethyl glycol, propanediol etc.), the components of the freezing medium (with or without serum or serum albumin), the freezing method (rapid compared with gradual) and the time spent in long-term storage (LN2) before revival. Our results showed that our standard method of cryopreservation led to >70% recovery of cells over the 3-month period in LN2 and over 80% of these cells were viable (Figures 1B and 1C respectively). Aziz et al. [27] performed a similar protocol with respect to PBMCs, to that described herein, with leucocytes. PBMC's were isolated in RPMI (50% serum and 10% DMSO) and were frozen down gradually (−1°C/min) in an insulated container with propan-1-ol and thawed 1–4 months post cryopreservation. The average cell recovery was 80%, whereas the average cell viability was 95% [27]. The latter results are very similar to those described in the present study, even though slight differences exist with respect to blood processing, cell counting, revival and washing and freezing medium (50% serum compared with 40% serum).

Interestingly, it has been reported that cryopreservation can also affect cellular bioenergetics, but to date this has not been explored in isolated primary immune cells. The current investigation revealed that all parameters studied, with the exception of glycolytic capacity and non-mitochondrial respiration, were significantly altered following cryopreservation (summarized in Table 2). Most of these changes occurred between day 28 and 56 of storage in LN2. Basal respiration, basal glycolysis (0 mM glucose), ATP production, MAX respiration and reserve capacity were all reduced after day 56, whereas glycolytic response to 25 mM glucose was elevated (Figures 2 and 3). Proton leak was increased with time, but was significantly increased only after day 84 and in comparison with the day 14 time point (Figure 2F). Overall, these data indicated that parameters of efficient mitochondrial function were impaired after cryopreservation and subsequent revival, while the cells appeared to become more dependent on glycolysis which is less efficient, but can rapidly generate ATP (Table 2).

Table 2
Summary of cryopreservation-induced changes in leucocyte bioenergetics

↑, increased OCR/PPR; ↓, decreased OCR/PPR.

Bioenergetic parameterChange relative to fresh cells (day 0)Time of significant change
Basal Mito respiration ↓ Day 56 
ATP-coupled respiration ↓ Day 56 
Uncoupled respiration (proton leak) ↑ Day 84 
MAX respiration ↓ Day 56 
Reserve capacity ↓ Day 56 
Coupling efficiency ↓ Day 56 
Non-mitochondrial respiration No change No change 
Basal glycolysis (0 mM glucose) ↓ Day 56 
Glycolytic response (25 mM glucose) ↑ Day 28 
Glycolytic capacity No change No change 
Glycolytic reserve ↑ Day 28 
Bioenergetic parameterChange relative to fresh cells (day 0)Time of significant change
Basal Mito respiration ↓ Day 56 
ATP-coupled respiration ↓ Day 56 
Uncoupled respiration (proton leak) ↑ Day 84 
MAX respiration ↓ Day 56 
Reserve capacity ↓ Day 56 
Coupling efficiency ↓ Day 56 
Non-mitochondrial respiration No change No change 
Basal glycolysis (0 mM glucose) ↓ Day 56 
Glycolytic response (25 mM glucose) ↑ Day 28 
Glycolytic capacity No change No change 
Glycolytic reserve ↑ Day 28 

Mechanisms responsible for decreased ATP production from mitochondria can include low ATP demand, limited substrate availability or more likely, in the present study, damage to the oxidative phosphorylation (OxPhos) machinery [23]. Thus, the significant decrease in MAX respiration and reserve capacity indicated that the cells had reduced potential for extra energy production via OxPhos, possibly because their damaged (sub-optimal) mitochondria were already operating at their maximum rate, post revival (Figures 2C and 2D). One of the most interesting findings in the current study was that a metabolic switch appeared to occur from OxPhos to glycolysis following cell revival. This was probably an adaptive mechanism to compensate for the decreased mitochondrial activity, resulting in an ability to cope with cellular ATP demand. Indeed the PPR response of previously frozen cells to a stimulatory concentration of glucose (25 mM) was significantly higher for cells cryopreserved for longer, even though these cells displayed a lower initial basal glycolytic rate in the absence of glucose (Figure 3). As expected, when oligomycin was administered to completely block any additional ATP production from the mitochondria, fresh and previously frozen cells responded by increasing their glycolytic flux by about 5 pmole H+/min/μg protein. However, although cells frozen for 56 and 84 days were metabolizing the added glucose (25 mM) at a greater rate and generating more protons, they were still able to boost their glycolytic reserve to the same degree as fresh cells in the presence of oligomycin (Figure 3D). It is possible that although the previously frozen cells were more glycolytic, they were not operating at their maximum capacity for glycolysis.

On further analysis (Figure 4), OCR and PPR data from cells stored for various periods and subsequently exposed to 0, 2.5 and 25 mM glucose demonstrated a transition from OxPhos to glycolytic glucose metabolism with length of storage. Cells stored until day 56 and 84 demonstrated clearly different metabolic OCR/PPR profiles compared with cells stored for shorter periods. When fresh or stored cells were exposed to medium containing 0 mM glucose, it appeared that both glycolytic and oxidative cell metabolism were severely impacted at day 56 and 84, as exhibited by significantly lower OCR and PPR values in comparison with day 0, 14 and 28. In the presence of 25 mM glucose, OCR was increased in all samples compared with 2.5 mM glucose, demonstrating an increase in both oxidative and glycolytic metabolism although the capacity of cells stored for longer periods (56 or 84 days) to increase OxPhos was clearly impaired. We suggest that the cells stored for longer periods become more dependent on glycolysis to meet energy demand, due to increased levels of damaged mitochondria. Alternatively, storage of cells in LN2 may lead to the selection of a more glycolytic cell type from our mixed population (e.g. neutrophil compared with lymphocytes) that may be more resistant to the detrimental effects of cryopreservation. Flow cytometric analysis may be required to determine what subpopulation survives the freezing and revival process. However, it must also be noted that cryogenic storage can also alter the activity of ion transporters, such as Na+/H+ antiporter and HCO3/Cl exchangers [29] that regulate intracellular pH and this could possibly affect the extracellular pH measurements as detected by the Seahorse instrument.

Furthermore, we have also demonstrated for the first time that cryogenic storage-modulated BHI significantly, which is a mathematical expression of cell bioenergetic health (Figure 5). A low BHI is associated with increased uncoupled respiration and/or non-mitochondrial respiration, and although not well defined, can be connected to inflammatory processes such as NADPH, cytochrome P450 or cyclooxygenase activity [23]. Conversely, a high BHI is associated with a low uncoupled respiration, low non-mitochondrial respiration or an enhanced ability to meet energy demand via increased ATP-coupled respiration or reserve capacity [23]. Consequently, when cells were cryopreserved, the BHI decreased significantly which indicated that either defects were present in the ETC machinery or cells were adapting by enhancing their inflammatory status. However, the latter reason is unlikely as no significant change in non-mitochondrial respiration was observed (Table 2).

The mechanism responsible for mitochondrial functional changes is unknown at present, but we speculate that this is a result of mitochondrial freezing-injury, decreasing the number or efficiency of mitochondria. This would be expected as cryogenic processes have been shown to be detrimental to mitochondrial integrity, distribution and function in oocytes [30], sperm [31] and skeletal muscle [32] and, in some cases, can lead to the generation of reactive oxygen species (ROS) [3335], which compromises membrane integrity. Presumably, if probed further, the decrease in mitochondrial function in these latter investigations would manifest as impaired parameters of OxPhos, as measured and shown in the current study. However, data from the literature have also suggested that cryogenic processes can be optimized to prevent or reduce mitochondrial damage in various cell and tissue types, including skeletal muscle [36], hepatocytes [37] and ovarian tissue [38]. Rapid freeing techniques (vitrification) [38] and inclusion of antioxidants or mild uncoupling agents [33] have been reported to decrease ROS production during cryopreservation and may be beneficial when cells are revived. The impact of these techniques on frozen immune cell bioenergetics is currently being investigated by the authors.

We appreciate that limitations to the current study exist and are undergoing rigorous assessment by the authors. The present study used a relatively small sample size (n=8) and it would be interesting to assess whether similar results are found in a larger population. In addition, the authors are fully aware that the samples used contained a heterogeneous population of immune cells which, as eloquently presented by Chacko et al. [39] and Kramer et al. [40], have unique bioeneregtic profiles. Consequently, the authors intend to determine the influence of cryopreservation on bioenergetics in isolated and purified populations of immune cells, as the process of cryogenic storage may inadvertently have selected for the survival of more glycolytically-active cell subtypes such as neutrophils. Finally, the present study did not explore the changes in protein or gene expression due to cryogenic storage, particularly in relation to ETC proteins, glucose transporters and glycolytic enzymes, as the cellular material was limited. However, an examination of these factors is currently underway in the laboratory.

In conclusion, the present study showed for the first time that cryopreservation of primary immune cells, altered their metabolism in a time-dependent fashion. Taken together, these data illustrated that careful consideration regarding the method of cryopreservation and the components of freezing medium is required, if cryopreserved samples are to be used to calculate bioenergetic responses or BHI.

Abbreviations

     
  • 2DG

    2-deoxyglucose

  •  
  • BHI

    bioenergetic health index

  •  
  • BMI

    body mass index

  •  
  • DMEM

    Dulbecco's Modified Eagle's Medium

  •  
  • ETC

    electron transport chain

  •  
  • FCCP

    carbonyl cyanide 4-(trifluoromethoxy)phenylhydrazone

  •  
  • LN2

    liquid nitrogen

  •  
  • MAX

    maximum respiration

  •  
  • MetS

    metabolic syndrome

  •  
  • OCR

    oxygen consumption rate

  •  
  • OxPhos

    oxidative phosphorylation

  •  
  • PBMC

    peripheral blood mononuclear cell

  •  
  • PPR

    proton production rate

  •  
  • ROS

    reactive oxygen species

  •  
  • RPMI

    Roswell Park Memorial Institute medium

AUTHOR CONTRIBUTION

The present work was designed by Kevin Keane, Emily Calton, Mario Soares and Philip Newsholme. Initial manuscript preparation and draft was undertaken by Kevin Keane and revised by Emily Calton, Vinicius Cruzat, Mario Soares and Philip Newsholme. Patients were recruited at MJS laboratory and body composition parameters were measured and analysed by Emily Calton. Experiments and biochemical analysis were performed by Kevin Keane, Emily Calton and Vinicus Cruzat. Data analysis and statistics were made by Kevin Keane and Vinicus Cruzat. Figure preparation was done by Vinicus Cruzat. Supervision of the manuscript was performed by Philip Newsholme and Mario Soares. All authors approved the final version of the paper.

We thank Curtin University Schools of Biomedical Sciences and Public Health in the Faculty of Health Sciences for research support. We would also like to thank the Curtin Health Innovation Research Institute of Ageing and Chronic Disease for providing excellent facilities. Finally, we thank Mr. Rodrigo Carlessi for discussion in relation to statistical analysis.

FUNDING

The present work was supported by the Schools of Biomedical Sciences and Public Health in the Faculty of Health Sciences, Curtin University; the Australian postgraduate scholarship (to E.K.C.); and the Brazilian National Council for Scientific and Technological Development [grant number 245562/2012-5 (to V.F.C.)].

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