Impact of SARS-CoV-2 infection on the recovery of peripheral blood mononuclear cells by density gradient

doi:10.21203/rs.3.rs-75145/v1

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Impact of SARS-CoV-2 infection on the recovery of peripheral blood mononuclear cells by density gradient

https://doi.org/10.21203/rs.3.rs-75145/v1

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published 28 Feb, 2021

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SARS-CoV-2 virus infection is responsible for coronavirus disease (COVID-19), which is characterised by a hyperinflammatory response that plays a major role in determining the respiratory and immune-mediated complications of this condition.

While isolating peripheral blood mononuclear cells (PBMCs) from whole blood of COVID-19 patients by density gradient centrifugation, we noticed some changes in the floating properties and in the sedimentation of the cells on density medium. Investigating this further, we found that in early phase COVID-19 patients, characterised by reduced circulating lymphocytes and monocytes, the PBMC fraction contained surprisingly high levels of neutrophils. Furthermore, the neutrophil population exhibited alterations in the cell size and in the internal complexity, consistent with the presence of low density neutrophils (LDNs) and immature forms which may explain the shift seen in the floating abilities and that may be predictive of the severity of the disease. The percentage of this subset of neutrophils found in the PBMC band was rather spread (35.4±27.2%, with a median 28.8% and IQR 11.6-56.1, Welch’s t-test early phase COVID-19 versus blood donor healthy controls P<0.0001).

Results confirm the presence of an increased number of LDNs in patients with early stage COVID-19, which correlates with disease severity and may be recovered by centrifugation on a density gradient together with PBMCs.

General Biochemistry

Virology

General Cell Biology & Physiology

Immunology

SARS-CoV-2 virus

cell separation

PBMC

inflammation

The novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is an enveloped single-stranded RNA virus belonging to the subfamily Coronavirinae in the family of Coronaviridae of the order Nidovirales (1). SARS-CoV-2 virus binds the Angiotensin-converting enzyme 2 (ACE2) as receptor for cell entry and the transmembrane protein serine protease TMPRSS2 for S protein priming (2, 3). One peculiarity of SARS-CoV-2 is represented by its particular tropism for type I and type II pneumocytes, alveolar macrophages and mucus cells in the nasal cavity (4), although beyond the respiratory disease, systemic disorders have also been reported (5). It is the etiologic agent of the severe acute respiratory syndrome (6) named Corona Virus Disease (COVID)-2019.

Besides the cytokines storm (7-9), the impaired interferon response found in severe COVID-19 patients (10-12) and the viral inhibition of type I and type III interferons previously described for Middle East Respiratory Syndrome (MERS) (13), conclusive studies on the immune response to SARS-CoV-2 infection are still underway. Coagulation factors, antibodies or complement on the surface of red cells and antiphospholipid antibodies may also play a role in the complicated puzzle of the COVID-19 immune response (14-19). The development of autoimmune responses can contribute to the severity of COVID-19 (20, 21) and on the other hand the occurrence of autoantibodies in viral infections is well-established (22-27). The contribution of cell- mediated immunity, both innate and acquired, is yet unclear, though lymphopenia appears to be one of the main features of this viral disease (28, 29) and also the presence of an atypical monocyte population (30).

Peripheral Blood Mononuclear Cells (PBMCs) are an attractive tissue source for immunological, molecular and pharmacogenomic studies. PBMCs from peripheral blood consist in a heterogeneous cell population with a round nucleus (i.e. lymphocytes, monocytes, natural killer cells (NK cells) or dendritic cells). It has been shown that PBMCs are permissive to SARS-CoV infection and support viral replication (31-33), and have been used for transcriptomics evaluations in the current pandemic (34-36).

Sedimentations on density gradient are well-established techniques to isolate cells and cellular organelles (37-44). The sedimentation rate of the cells strongly depends on their size (44). Lymphoprep™ density gradient medium, which has a density of 1077 g/ml, is widely used for the isolation of mononuclear cells from human blood. Having most of the mononuclear cells (i.e. lymphocytes and monocytes) a lower buoyant density than erythrocytes and granulocytes (or polymorphonuclear cells, PMNs), can be recovered, after centrifugation, at the interface between the sample and the density medium, while PMNs and erythrocytes are usually found at the bottom of the centrifuge tube. According to Graham (38) monocytes, being larger (15-20 µm) than lymphocytes (6-20 µm) sediment to a slightly lower density, i.e. ρ=1064 g/ml the former and ρ=1072 g/ml the latter. Hence, the peripheral blood monocytes usually form a sharp cloudy band above the lymphocytes and polymorphonuclear leukocytes. Instead, the granulocytes, which have a relative higher density, penetrate through the isosmotic medium and sediment above the red blood cells layer. PMNs in the bloodstream refer to neutrophils, eosinophils and basophils. PMNs and especially neutrophils are resolved in a gradient of density around 1088 g/ml (38, 44).

Neutrophils are the most abundant circulating phagocytes and their activity is also exerted through the release of soluble cytotoxic proteins and peptides from their granules, the production of reactive oxygen species by a membrane-bound NADPH oxidase and the formation of neutrophil extracellular traps (NETs) (45-47). Neutrophils are short- lived, front-line effectors of acute inflammation and first responders against a wide range of pathogens including bacteria, fungi, and protozoa. As they are quickly recruited at the inflammatory site, neutrophils have been latterly implicated in the antiviral immune response (48). It has been recently reported that neutrophils with immunomodulatory capabilities can shift to a low buoyant density (49). However prolonged activation of neutrophils can have detrimental effects contributing to lung injuries (50) and the NET formation may have played a crucial role in the exacerbation of the lung disease and in the mortality of COVID-19 patients (51).

However neutrophils display a morphological, phenotypical, functional heterogeneity and a subset of these cells, defined as low density neutrophils (LDNs) have the ability to partition with PBMC fraction after density gradient centrifugation (49). LDNs showed in vitro increased activation markers comparable to those seen in patients with chronic inflammatory diseases (49). The appearance of immature neutrophils or LDNs in COVID-19 patients has also been postulated by Wilk et al. and by Schulte- Schrepping at al. (35, 36).

Density gradient qualitative evaluation

Patients were stratified according to their clinical status and the specimens were grouped in accordance with the time of sampling i.e. within 24 h from admission (early phase COVID-19) or 14 days after discharge. As healthy controls we took samples from blood donors at the time of the donation. As expected, the typical mononuclear population from control blood donors, isolated Lymphoprep™, was recovered at the interface between the density medium and the sample (Fig. 1A). By contrast the vast majority of PBMCs derived from patients with an early phase of COVID-19 floated quite differently. Some samples from this first COVID-19 cohort (within 24 h from hospitalisation) showed a thicker and fluffier band of mononuclear cells, mostly lower than usual, sometimes stickier, often decorated underneath by a dispersed fine crown of red blood cells or with erythrocyte aggregates (Fig. 1B). A number of times the density medium also appeared rather cloudy or less transparent than usual. The buoyant density of the PBMCs was restored in samples collected 14 d post-discharge (recovered COVID- 19 cohort; Fig. 1C), although a slightly thicker band was often observed. Comparison between one sample at day 14 post-discharge and four samples collected at the admission, processed simultaneously and under the same conditions, are shown in figure 1D. For a better appreciation, magnification of a 14 d post-discharge sample (recovered COVID-19 cohort) and a sample taken within 24 h from admission (early phase COVID- 19 cohort) are displayed in figure 1E, while figure 1F is a closer view of two samples taken at the time of admission into hospital. Occasionally a dual band one right at the interface between the sample and the medium and a second within the density medium itself was also observed (Fig. 1, panels G, H and I).

Population dynamics study

To assess the differential count of cell populations (neutrophils, lymphocytes, monocytes) in the band isolated on the density gradient, an automated haematology cell analyser was used. To have an estimate of the variation in cell composition in the collected fraction also cell ratios were determined.

The neutrophils in the samples of early phase of COVID-19 (taken within 24 h from hospitalisation) heavily outnumbered in percentage those of the convalescent patients (14 d after discharge) as well as those from healthy controls (Fig. 2A). In patients from the 24 h cohort, the amount of neutrophils found in the PBMC band was of 35.4±27.2% (mean±SD; t-test versus healthy controls P<0.0001), with a median value of 28.8% (IQR 11.6-56.1), thus indicating that the number of neutrophils varied extensively among the different COVID patients, probably depending from the severity of the disease at the time of hospitalisation. The neutrophil data distribution was less spread out in the cohort of patients who had the samples taken 14 days after being released from hospital. The mean value in the discharged patients group was 7.4±9.2% (t-test versus blood donor controls P=0.0469; median of 3.8%; IQR 2.5-7.9) while a range much narrower displayed by the healthy controls i.e. 5.4±5.2% (with a median of 3.3 %; IQR 2.3-6.8).

Conversely, the percentage of lymphocytes showed an opposite trend across the different cohorts as compared to what it was observed for the neutrophil populations. Indeed, at admission, the average percentage of the lymphocytes was completely reverted compared with the post-discharge samples and those from blood donors, displaying mean values of 47.3±2.4% (t-test vs healthy controls P<0.0001; median 46.9%; IQR 28.2-67.4) the former and, 73.0±10.8% (t-test vs blood donor controls P=0.8120; median 74.7%;IQR 70.1-80.1) and 72.6±8.3% (median 74.3%; IQR 68.0-78.2) the latter two, respectively (Fig. 2B). Thus, the percentage of lymphocytes, collected post-gradient separation, returned to normal levels at 14 d post-discharge as suggested by the comparison with the values found for the blood donors.

Although still statistically meaningful, the differences in the percentage of monocytes among the three groups were less remarkable (Fig. 2C). The pattern of monocyte distribution, expressed as mean percentage was 17.3±10.9% (Welch’s t-test vs healthy controls P=0.0034; median 15.0%; IQR 8.4-23.0) for the early phase COVID cohort (i.e. samples within 24 h from hospital admission) and 19.6±6.9% (t-test vs blood donor controls P=0.0447; median 18.9%; IQR 15.2-23.2) for the COVID recovered group, whereas healthy controls showed a percentage of 22.0±7.5% (median 20.5%; IQR 16.7-24.6).

To determine the efficiency of the enrichment in the PBMC fraction from the samples of the three different cohorts, we measured the total cell counts that somehow provide the yield of the separation method. The total number of cell recovered were 22.6*10⁶±21.5 cells (t-test vs blood donor controls P=0.2935; median 15.4; IQR 8.8- 29.9) recovered at 24 h, 24.9*10⁶±15.5 cells (t-test vs healthy controls P=0.7595: median 22.4; IQR 15.8-32.8) collected at 14 d post-discharge and 25.5*10⁶±10.9 cells (median 24.2; IQR 18.4-32.2) retrieved from the healthy controls, respectively (Fig. 2D).

The enrichment in terms of total number of cells recovered was not too dissimilar in the three groups and an optimal yield of the mononuclear cells should not account for more than 5% of granulocytes. To assess the effectiveness of the PBMC recovery after the isolation and to evaluate the distribution pattern of the prevailing cell types post-separation through density gradient, we determined the neutrophil-to-lymphocyte ratio (NLR-PBMC, Fig. 2E) and lymphocyte-to-monocyte ratio (LMR-PBMC, Fig. 2F) in the samples of the three cohorts. Although the three different patient cohorts were all statistically different (Fig. 2E), the cells collected from the 24 h group were highly unbalanced towards neutrophils. The NLR-PBMC of 2.1±4.2 (SD; early phase COVID- 19 versus blood donors t-test P<0.0001) demonstrated that, in the early phase of the disease, the PBMC fraction was heavily contaminated by neutrophils, while the ratios of the other two groups were much more close to each other. The post-separation cells collected from the 14 d post-discharge cohort displayed a mean of 0.13±0.21 (14 d discharged versus blood donors t-test P=0.0165) whereas the cell ratio from the blood donor group had values ranging from 0.08±0.08. The LMR-PBMC (Fig. 2F) of the control cohort showed a mean of 3.7±1.3, while the mean ratio of cells collected from COVID patients at 24 h were 3.5±2.7 (Welch’s t-test vs blood donors P=0.6203) and those from patients 14 days after dismissal were 4.3±2.2 (t-test vs healthy controls P=0.0132). Thus indicating that the distribution pattern of mononuclear cells in the density band was similar and the collected fractions contained similar amount of lymphocytes and monocytes. However it is worth to mention that in the present context the above NLR-PBMC and LMR-PBMC are calculated on recovered cells and provide only a parameter of the cell distribution within the enriched fractions following the separation medium centrifugation.

Flow cytometry analysis

Whole blood leftovers were used to analyze leukocyte population of COVID-19 patients (N=13) and healthy blood donors (N=10) by flow cytometry. Cell populations were assessed after red blood cell lysis. Representative forward scatter (FSC) versus side scatter (SSC) dot plots from the three cohorts are depicted in Figure 3A, B and C. In particular, FSC parameter is proportional to the cells size, while SSC reflects the internal cell complexity (i.e. nuclear morphology and granularity). Leukocyte morphological properties from patient samples taken 24 h from hospitalisation (Fig. 3B) clearly exhibited a shift down in the granulocyte population distribution, probably indicating a lack/loss of granularity, when compared to those from both healthy controls (Fig. 3A) and patient at discharge (Fig. 3C). In addition, a diminished number of lymphocytes and an alteration of the monocyte population was observed in the early phase of infection. The post-dismissal specimen (Fig. 3C) showed that the cell distribution pattern returned almost back to normal, though with still a slight increased number of events in the granulocyte region.

The box-and-whisker chart (Fig. 3D) of the median channel intensity (MCI) in the forward scatter (FSC) indicated that there are some significant differences in the cell sizes, indeed the MCI was lower in the 24 h cohort (159221 MCI, Mann–Whitney U test vs blood donors P=0.0070) and tended to raise again in the 14 d discharged patient group (165465 MCI, Mann–Whitney U test vs healthy blood donor controls P=0.0236) to levels close to normality (healthy controls median=168870 MCI), although not completely back to normal. However, the most striking difference was observed instead in the granularity (Fig. 3E), where the internal macromolecular complexity of the cells had a massive impact despite the fact that the side scatter (SSC) is measured at a ninety degree angle on the laser light and its signal is weaker than the FSC. The cells from early phase of COVID-19 patients (within 24 h) showed a marked decrease in the SSC compared with the blood donors (U test vs blood healthy controls P=0.0001). The internal complexity was only partially restored 14 d after hospital-dismissal (Mann–Whitney test vs blood donors P=0.0378).

Morphological inspection of COVID-19 samples

Blood smears and PBMCs from density gradient spotted onto glass slides were fixed and stained with May–Grünwald Giemsa for a simple cytology evaluation. In figure 4, (panels A-D) we showed the blood smears from four different COVID-19 patients within 24 h from hospitalisation. Those samples confirmed the presence of excessive number of mix-shape neutrophils in peripheral blood. Some of these neutrophils had either a ribbon-shaped or a horseshoe-shaped nucleus suggesting that these are immature forms. Neutrophils are still present in blood smears (Fig. 4E, F and G), from specimen taken after 14 days post-discharge, though mostly in the mature form. The panels H and I in figure 4 are examples of the mononuclear cell enrichment prior to the last centrifugation to remove cell debris and blood residues

Blood cell counts

Almost all the COVID patients and the blood donors had a complete blood count (CBC) test done at the same time or on the same day at which the samples for biobanking were taken. Therefore we have retrieved and retrospectively analysed these data to compare them with the results obtained from the gradient centrifugation.

Early phase COVID patients showed elevated levels of neutrophils i.e. 73.3±14.4% (mean±SD; Welch’s t-test vs blood donors P<0.0001), with a median value of 76.0% (IQR 62.9-84.7) whereas the frequency of neutrophils 14 d post-discharge was 56.4±9.8% (t-test vs healthy controls P=0.4141; median 57.6%; IQR 50.4-62.5) and in the whole blood of healthy donors was 57.6±8.5% (median value of 57.7%; IQR 51.2- 63.8; Fig. 5A).

The lymphocytes detected at 24 h showed a downward trend (Fig.5B), confirming the inversion previously seen in the enriched populations (Fig. 2B). These leukocytes displayed a mean of 18.2±12.2% (t-test vs blood donors P<0.0001; median 16.1%; IQR 8.1-23.1) early in the SARS-Cov-2 infected individuals which rose to 30.7±7.6% (t-test vs healthy controls P= 0.8089; median 30.0%; IQR 25.6-36.7) in the discharged patients and was comparable to the values, 31.0±8.6% (median 31.5%; IQR 24.2-36.2), found in the healthy blood volunteers.

The whole blood monocytes showed fewer fluctuations (Fig. 5C) than the enriched fractions in figure 3C. The populations were more compact in all three cohorts and displayed mean percentage values of 7.3±3.3 (Welch’s t-test vs healthy controls P= 0.0055; median 6.8%; IQR 4.9-9.5) at 24 h from admission, with a slight increase in the discharged patients to 8.7±1.9% (t-test vs blood donors P=0.5707; median 8.7%; IQR 7.3-10.2) and 8.5±1.8% (median 8.3%; IQR 7.0-9.6) in the blood donors.

A white blood cell (WBC) count measures the number of leukocytes in the blood and showed minor differences (Fig. 5D). As expected the percentage of circulating white blood cells was slightly higher in the early phase of the infection 7.1±3.2% (t-test vs blood donors P=0.0077; median 6.7%; IQR 4.8-8.8) and in the recovered patients (14 d post-dismissal) 7.0±2.7 (t-test vs healthy controls P= 0.0010; median 6.4%; IQR 5.5-8.0) and dropped to 6.0±1.5% (median 5.7%; IQR 5.0-6.8) in the healthy blood donor controls.

Since the neutrophil-to-lymphocyte ratio (NLR) and lymphocyte-to-monocyte ratio (LMR) are predictive of inflammatory dysfunctions and have prognostic significance of disease severity and outcome for several infections, malignancies and beyond, we report here mean±SD and median with IQR of these biological markers determined in our cohorts (Fig. 5E and F). COVID patients within 24 h from hospitalisation (panel 5E) showed NLR levels of 6.9±5.6 (Welch’s t-test vs healthy controls P<0.0001; median 4.9; IQR 2.9-10.7), which decreased to 2.2±1.2 (t-test vs blood donors P=0.8274; median 1.9; IQR 1.4-2.5) in those measured 14 d post-recovery. The latter cohort displayed values similar to the healthy blood donor controls, whose levels were 2.1±0.8 (median 1.8; IQR 1.4-2.7). Conversely LMR levels were higher in the blood donors i.e. 3.7±1.1 (median 3.6; IQR 2.8-4.8) and in recovered patients at 14 days post-discharged 3.8±1.9 (t-test vs healthy controls P= 0.9123; median 3.5; IQR 2.9- 4.2), while in the early COVID were 2.8±2.8 (Welch’s t-test vs blood donors P=0.0065; median 2.4; IQR 1.4-3.3). Thus both biological marker levels, i.e. NLR and LMR, differed between the groups and were altered in the early phase of the SARS-Cov-2 infection.

Monocytes usually float to a density between 1.079-1.089 g/ml followed by the lymphocytes, therefore the band we collected should have accounted mostly for mono/lymphocyte populations. The cloudy and sticky area might be due to activated monocytes, but also to a massive mobilisation of activated macrophages and mature dendritic cells, which have entered the circulation to reach peripheral tissues. What is the cause that led the erythrocytes to decorate the lymphocytes band is unclear. However, erythrocyte rosetting (E-rosetting) is an immunological reaction occurring between receptors or antibodies on the lymphocyte plasma membrane and epitopes on the erythrocytes where red blood cells arrange themselves in petal-like flower. Immature B- lymphocytes may be also present in the lymphocyte pool and can express membrane- bound IgD able to capture foreign and self-antigens or activate other immune effectors. Hemadsorption and hemagglutionation are abilities not new to bacteria and parasites (e.g. Treponema pallidum, Plasmodium spp.). Furthermore many viruses, Orthomyxoviridae, Paramyxoviridae, Matonaviridae (i.e. Rubella) among others, can attach to molecules present on the surface of the erythrocytes, thus eventually leading them to agglutinate. CR1/CD35 and CR2/CD21 are complement receptors for C3b/C4b and C3d expressed by several cell populations within the PBMC pool. It is also possible that anti SARS-CoV-2 antibodies, appearing during early seroconversion, show some sort of cross-reactivity and recognition of self-epitopes. Indeed, it is worthwhile mentioning that the excessive cell deaths occurring during the infection may determine the release of unprecedented amount of DNA, histones and cell debris, which in turn could lead to a hyperproliferation of self-reactive lymphocytes and/or, as consequence of extensive cell damage, to the production of autoantibodies.

The abnormal amount of neutrophils collected in the density gradient may be misleading, because we are dealing with isolated PBMCs rather than with the whole blood. However, why neutrophils are present in such numbers in the gradient band remains an open question. They could have been trapped within the complex web of complement components, fibrinogen, fibrin and platelets. Neutrophils might also been kept floating while expelling DNA and proteins, which instead of baiting pathogens might have been recognised by other immunological effectors e.g. lymphocytes. The excessive formation of NETs may act as parachute, thus keeping most of the neutrophils in suspension, allowing them to float in the density medium rather than sinking and sedimenting on top of the erythrocytes layer.

Last, but not least, they might well be exhausted neutrophils after degranulation or, consistent with early stage responses to infection and inflammation where the bone marrow is stimulated to release blood-forming stem cells, low density neutrophils. The recruitment of immunological effectors at the active site of infection i.e. the lungs might have triggered an enhanced mobilisation of immature or naïve neutrophils to compensate the depletion of the circulating primed and activated forms. Incomplete granulopoiesis might confer to immature neutrophils a lower density allowing the flotation onto or within the separation medium.

Density is defined as mass per volume and blood density is somehow proportional to haematocrit. Changes in the circulating cell populations in COVID-19 patients may affect the total protein concentration of blood, determine a variation in blood density and inhibit an optimal mononuclear cell separation through the density gradient. Therefore the simplest explanation for the modification of the buoyant density of PBMCs is the result of the massive alteration in the cell composition of the circulating blood that occurs in COVID patients.

Although the traits of the outliers were more pronounced and their features appeared, up to a certain extent, amplified, the population dynamics of the cells enriched after fractionation on density medium, traced in essence the distribution pattern of the circulating blood. Conversely, the ratios, i.e. NLR and LMR, in the whole blood allow a better resolution and provide a better appreciation of the cell distribution.

In conclusion, our results show that the infection of SARS-CoV-2 strongly affects the sedimentation of neutrophils on density gradients. The imbalanced recovery of “alleged” mononuclear cells in COVID patients, containing a large amount of LDNs and a diminished number of lymphocytes, confirms what seen by us and others in the whole blood.

Patient population

The study was conducted after obtaining the Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico Ethics Committee approval (COVID-19_Network IRB #241_2020) and the patient informed consents for research studies and biobanking.

Two hundred eighty-one samples were collected and harvested at the Processing Facility and Biobank POLI-MI from April the 1^st until April the 30^th 2020, during the SARS-CoV-2 pandemic. Seventeen samples gave insufficient material or the patients had duplicate samples, and have been excluded from the data analysis. In that period we received samples from two hundred seventy patients ranging between 24 and 99 years of age and, as some progressed towards the recovery, for ten patients we had also follow-up samples. All the patients were diagnosed with COVID-19, had SARS-CoV-2 positive nasopharyngeal swab detected through real-time reverse transcription–polymerase chain reaction (real-time RT-PCR) and were hospitalised in the different COVID-19 Units of IRCCS Ca' Granda Ospedale Maggiore Policlinico. Blood samples were taken either within 24 h from the admission into the Unit and/or at day 14 after hospital discharge.

The healthy control samples were kindly provided by registered blood donors visiting our Blood Transfusion Centre for their regular blood donations (after written informed consent and within the approved protocol CoDS).

Demographics of the patients and of the blood donors are shown in Table 1.

Table 1: Patient and donor demographics

Parameter

COVID +

Blood donors

24 h

14 d

Total

Number of patients

101

179

270*

Number of samples

102

179

281

Male (%)

67.8

64.4

Age (Median)

45.8

A total number of 90 early phase COVID and 174 COVID recovered patients were finally included in the analysis. *Ten of patients had follow-up samples i.e. at the admission and 14 days post-discharge.

Isolation of Peripheral Blood Mononuclear Cells

Peripheral blood samples were drawn into EDTA vacutainer tubes. PBMCs were isolated by polysaccharide density gradient centrifugation (Lymphoprep™ - Axis-Shield Alere Technologies AS, Oslo, Norway) as described previously (52) with minor modifications. Briefly, after centrifugation at 1560 g for 10 min at 20˚C, plasma was removed from blood samples and snap-frozen in LN2 for further studies. The remaining buffy coats (i.e. leukocyte concentrates) from the same patient samples were pooled together and then diluted 1:2 (vol:vol) in 0.9% Sodium Chloride Injection solution, USP (Baxter S.p.A., Rome, Italy) prior to be layered onto the density gradient medium. The samples were then centrifuged at 900 g for 20 min without brake. PBMC isolation procedure was performed at 20˚C to avoid any possible variation in the density of the density gradient medium. The PBMC rings were collected, resuspended and washed twice with saline by centrifugation at 450 g and 350 g, respectively. Cell pellets were then suspended again in freezing medium for storage.

Cell populations and flow cytometry analysis

Cell counts were performed by running the samples through an automated haematology cell analyser (Sysmex XN-1000™ DASIT S.p.A., Cornaredo, Italy), in body fluid or complete blood count (CBC; for the clinical samples) mode.

Peripheral blood samples leftover were analysed within 24 hours from withdrawal after lysing the erythrocytes with lysing solution (BD Pharm Lyse™, BD Biosciences). After washing, the samples were acquired with a BD FACSLyric flow cytometer equipped a 405 nm violet laser, a 488 nm blue laser and a 647 nm red laser. For each tube 50,000 events in the lymphocyte gate, forward scatter (FSC) versus side scatter (SSC), were acquired and the data were analysed using FACSSuite software (BD Biosciences). An automatic standard setup was applied for each acquisition. Internal quality assurance procedures included BD cytometer setup and tracking beads, according to the manufacturer’s instructions.

May-Grünwald Giemsa staining

Whole blood smears and cell suspensions spotted onto glass slides were air dried under the safety cabinet II and fixed in 100% methanol for 30 min prior to staining. The slides were stained with May-Grünwald working solution for 15 min, rinsed with water, immerged in Giemsa working solution for 20 min, rinse thoroughly with water and air dried. The glass slides were imaged with an Olympus BX S3 microscope equipped with a Sony CCD 3 camera, objective magnification at 10X, 20X, 40X, 60X oil and 100X oil. All images were acquired with Sysmex LAFIA, version 2, blood image filing software.

Statistical analysis

All graphs display mean and standard deviation (SD). Statistical analysis was performed using the Welch’s t-test, for unequal sample sizes, or Mann–Whitney U test and one-way ANOVA to calculate statistically significant differences and individual P values using GraphPad Prism version 5.00 (GraphPad Software, San Diego California, USA, www.graphpad.com). Statistically significant differences were expressed as * for P≤ 0.05, ** for P≤ 0.01, *** for P≤ 0.001 and **** for P≤ 0.0001, not statistically significant differences are indicated as n.s. for P> 0.05.

Acknowledgements

This work was funded by a grant “COVID-19 Biobank” from the Scientific Direction, Foundation IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milano, Italy (LV and DP). The authors thank Dr. Anna Chiara Migliorini - U.O.C. Haematology and Dr. Marco Maggioni - U.O.C. Pathological Anatomy - Foundation IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milano, for the use of their equipment and for helpful suggestions. We are also grateful all the colleagues and co-workers of the Milano Cord Blood Bank, Processing Facility and Biobank POLI-MI for their support. The authors greatly appreciate the collaboration of Drs Valeria Pastore, Roberta Massafra and Teresa Itri, the staff of Transfusion Medicine and Haematology and the all the personnel in the COVID wards and the COVID-19 Network, who made the sample collection possible. Our sincere and deepest gratitude goes also to the blood donors and the COVID patients who, in spite of the difficulties of the moment, gave their consent for research studies and biobanking.

Footnotes

Author Contributions: Experiments were designed by M.D.I. M., and G.L. Experiments were carried out by M.D.I.M., G.L., F.F., E.T., M.B., L.S. and G.B.. Data analysis was performed by M.D.I.M., G.L., F.F., E.T., A.C. and M.T.. Samples and/or data collection were performed or organised by E.E., C.B., M.O., L.V., A.B., A.G., L.P. and D.P.. Manuscript was written by M.D.M. , G.L. and E.T.. L.V. and D.P. supervised the work.

DISCLOSURE

The authors have no financial relationships to disclose.

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Impact of SARS-CoV-2 infection on the recovery of peripheral blood mononuclear cells by density gradient

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