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. Author manuscript; available in PMC: 2020 May 8.
Published in final edited form as: J Immunol. 2019 Sep 9;203(8):2088–2099. doi: 10.4049/jimmunol.1900637

IL-10 Has Differential Effects on the Innate and Adaptive Immune Systems of Septic Patients

Monty Mazer *, Jaqueline Unsinger †, Anne Drewry †, Andrew Walton †, Dale Osborne †, Theresa Blood †, Richard Hotchkiss †, Kenneth E Remy *,†
PMCID: PMC7206829  NIHMSID: NIHMS1575195  PMID: 31501258

Abstract

Sepsis, a disease of divergent pro- and anti-inflammatory–mediated pathways, has a high prevalence of morbidity and mortality, yet an understanding of potential unifying mediators between these pathways that may improve clinical outcomes is largely unclear. IL-10 has classically been designated an immunosuppressive cytokine, although recent data suggest that under certain conditions IL-10 can be immune stimulatory. We sought to further investigate the effect of IL-10 on innate and adaptive immunity in an in vitro human observational cohort study in patients with sepsis via modulation of IL-10 on IFN-γ production by T cells and TNF-α production and HLA-DR expression by monocytes. These results were compared with critically ill nonseptic patients and healthy volunteers. ELISpot analysis was performed using PBMC fraction from patient whole-blood samples. Finally, to provide additional potential clinical relevance, we examined the effect of IL-10 on T cell IFN-γ production in an in vivo cecal ligation and puncture model of sepsis using C57 black/J6 female mice. We found that inhibition of IL-10 significantly increased both production of T cell IFN-γ and monocyte TNF-α, whereas addition of IL-10 increased T cell IFN-γ production but decreased monocyte production of TNF-α and HLA-DR expression. There was no significant effect of IL-10 on control cohorts. IL-10–treated septic mice demonstrated increased IFN-γ production in splenocytes. Thus, IL-10 demonstrates both pro- and anti-inflammatory effects in the septic microenvironment, which is likely cell and context dependent. Further elucidation of relevant signaling pathways may direct future therapeutic targets.

Sepsis is a life-threatening organ dysfunction characterized by a dysregulated host immune response to infection and remains a leading cause of mortality with an estimated annual mortality of 5.3 million deaths worldwide (1, 2). The dysregulated host response that occurs in sepsis is frequently manifested by an initial hyperinflammatory phase typified by fever, shock, and respiratory failure (3, 4). Systemic circulation of specific proinflammatory cytokines and chemokines such as TNF-α, IL-1β, IL-6, IL-8, and CXCL1 mediate this initial response to infection (4–7). If sepsis persists, patients develop a phase of immunosuppression characterized by lymphocyte apoptosis and immune cell anergy (3, 8–12). During this immunosuppressive phase, patients are particularly vulnerable to hospital-acquired secondary infections often because of opportunistic type pathogens including fungal organisms and multidrug resistant bacteria. The fact that patients are susceptible to these relatively weakly virulent pathogens highlights the profound degree of their impaired immunity (8, 11–14).

One of the most important recent scientific advances has been the discovery that immunotherapy to boost host immunity can improve survival in patients with a variety of different types of cancer (15). The awarding of the 2018 Nobel Prize in Physiology and Medicine to investigators who were pioneers in the immunotherapy field emphasizes the impact of this advance in medicine (16, 17). Studies testing a myriad of different immunotherapies that target cells of the innate and adaptive immune system are currently being tested in cancer patients. Remarkably, recent clinical trials of IL-10 in patients with metastatic pancreatic cancer, a malignancy that has been refractory to most conventional cancer therapies, showed efficacy with a reduction in tumor burden in a significant percentage of patients (18–20). IL-10 is a pleiotropic cytokine that has traditionally been considered to exert immunosuppressive effects because of its action to inhibit production of proinflammatory cytokines, including TNF-α and IL-1 (6, 20–25). The surprising findings in metastatic pancreatic cancer have challenged conventional thinking that IL-10 has an overriding immunosuppressive effect and indicate that IL-10 can, in some settings, actually enhance host immunity (25). Furthermore, recent studies in murine tumor models indicate that IL-10 can increase production of the proinflammatory cytokine IFN-γ in CD8 T cells (20, 22–24). Because cancer and sepsis share many of the same immunologic perturbations, understanding IL-10 activity may provide insights into a therapeutic pathway in sepsis (26–28).

The inhibitory effects of IL-10 explain its original name of “cytokine synthesis inhibitory factor” (29). Although IL-10 is produced by almost all immune effector cells, it is initially secreted in largest quantities by monocytes, macrophages, endothelial, and dendritic cells in response to a systemic or local inflammatory process (23, 25, 30). IL-10 binds to its receptor on T regulatory cells, inducing activation, maturation, and proliferation. T regulatory cells subsequently secrete IL-10, which binds to IL-10 receptors on cells of the innate and adaptive immune systems.

IL-10 is thought to be an important mediator of the compensatory anti-inflammatory response that occurs in response to intense inflammation. Because of its ability to dampen inflammation, IL-10 has been tested in a variety of animal models of sepsis (21, 24). Results from these animal models demonstrate that IL-10 can either improve sepsis survival or worsen mortality. These conflicting results are likely due to the type of sepsis animal model, the particular pathogens (intracellular versus extracellular organisms), and the degree of hypercytokinemia-induced inflammation that is specific to each animal model of sepsis. The potentially critical pathophysiologic role of IL-10 is underscored by studies demonstrating that patients with sepsis who have elevated levels of IL-10 have increased mortality (23, 27, 31, 32).

Given the potential key pathophysiologic role of IL-10 in modulating the immune response in sepsis, the conflicting results of studies examining IL-10 modulation in animal models of sepsis, and the unexpected findings that administration of IL-10 can enhance tumor killing in selected cancer patients, we undertook an examination of the effect of IL-10 on immune cells from septic patients. The purpose of this investigation was to examine the effect of IL-10 on both innate and adaptive immunity in effector cells from patients with sepsis. Decreased T cell production of IFN-γ is a hallmark of sepsis and likely a key pathophysiologic abnormality (3, 8, 11, 14). Using samples from septic patients and controls, we sought to determine the impact of IL-10 on IFN-γ production by T cells from septic patients. Finally, we examined IL-10’s immunosuppressive impact on innate immunity by quantitating its effect on monocyte TNF-α production and HLA-DR expression. Previous studies have shown that IL-10 potently suppresses monocyte function and decreases monocyte Ag presentation by reducing HLA-DR expression (33, 34). This study sets out to confirm or challenge these findings in patients with sepsis. Developing a better understanding of the theorized effects of IL-10 could expand mechanistic understandings of how this cytokine may play a role in impairing or ameliorating host ability to combat invading pathogens.

Materials and Methods

Study design

We performed a prospective in vitro trial comparing septic patients with nonseptic critically ill patients and healthy volunteers on the impact of IL-10 on sepsis using patient samples obtained from the medical and surgical intensive care units (ICU) at Barnes-Jewish Hospital, the main academic teaching hospital of Washington University in St. Louis, MO. Samples were obtained between January and December of 2018. Data collection and analysis were approved by the Human Research Protection Office at Washington University and approved by the Institutional Review Board (protocol no. 201211101). Informed consent for participation was provided and signed by all patients and healthy volunteers or their legally authorized representatives.

Patient data, including clinical course, relevant laboratory testing, development of secondary infections, hospital readmissions, and mortality, were collected and de-identified. Complete blood counts were recorded at the time closest to point of blood sample for immune functional testing. Samples from patients with sepsis were drawn within the first 3 d of diagnosis with an option for a redraw at 1 wk if the patient remained in the ICU. Critically ill nonseptic (CINS) patient samples were drawn at any point during their ICU admission. Clinical data such as daily laboratory values, vital signs, and clinical outcomes, including the development of secondary hospital-acquired infections, were determined by review of hospital patient records were obtained. Patients were judged to have a secondary hospital-acquired infection if their treating physician initiated additional antibiotic therapy for a new proven or suspected infection.

Inclusion criteria

Patients hospitalized in the ICU who were 18 y of age or greater were eligible for inclusion. Sepsis, for the purposes of this study, was defined based on the 2001 Sepsis-2 criteria, and only patients who met criteria for severe sepsis and septic shock were enrolled. Patients were included in the study if they had a clinical or microbiologically suspected infection, three or more vital sign or laboratory changes in accordance with the systemic inflammatory syndrome criteria, with signs of organ dysfunction or hemodynamic instability (35).

Exclusion criteria

To minimize confounding effects of immunosuppressive medications or underlying immunologic disease on the findings from the present investigation, patients with the following criteria were excluded: HIV, organ or bone marrow transplantation, current use of high-dosage corticosteroid regimens that were greater than or equivalent to 300 mg/d of hydrocortisone or other immunosuppressive medications, current use of immune-modifying biological agents including inhibitors of TNF-α or other cytokines, viral hepatitis, or systemic autoimmune diseases.

Control subjects

CINS patients.

Control subjects consisted of CINS patients admitted to the medical or surgical ICU who were not suspected of having infection. These patients included recent major surgery or had been involved in traumatic injuries including, for example, motor vehicle accidents or gunshot or knife wounds. Patients were included in this group who had clinical acuity requiring management in the ICU without any evidence of infection. Samples were drawn for this group at any time during their ICU stay. Exclusion criteria were identical to that for patients with sepsis.

Healthy age-matched control patients

Age-matched healthy control volunteers were also enrolled into the study to provide information on the immune phenotype in the noninflamed state. Exclusion criteria were identical to that for patients with sepsis.

Primary laboratory outcomes

The primary outcomes of this study are changes in T cell and monocyte function in vitro in patients with sepsis in response to manipulation of the IL-10 signaling pathway. The functional immunologic readouts for these outcomes are alteration in the production of IFN-γ and TNF-α, respectively, and monocyte HLA-DR surface expression.

PBMC fractionation

PBMCs were harvested as previously described (36). Briefly, whole-blood samples were collected in sodium heparin tubes, and the PBMC fraction was isolated via gradient density using Ficoll-Paque PLUS (GE Healthcare, Stockholm, Sweden) within 90 min of collection. Number of total PBMCs were determined with a Vi-CELL viability analyzer (Beckman Coulter, Brea, CA).

PBMC culture conditions

PBMCs were plated into 96-well ELISpot culture plates and were cultured overnight, plated into each well in quantities of 5 × 104 cells per well in total 200 μl for IFN-γ analysis, and 5 × 103 cells per well for TNF-α analysis. Cells in the IFN-γ wells were stimulated with anti-CD3 (clone HIT3a; BioLegend) and anti-CD28 (clone CD28.2; BioLegend) Abs, and the cells in the TNF-α wells were stimulated with LPS (Escherichia coli serotype 055:B55; Invitrogen). Anti-CD3 with anti-CD28 or LPS were used as positive controls to evaluate the function of T cells and monocytes, respectively, in terms of their ability to produce and secrete IFN-γ and TNF-α. Cells were cultured overnight for 18–20 h in a 37°C, 5% CO2 incubator, and all cultures were performed in duplicate. Cells were stimulated with their positive control, and treatment samples were also cultured with either 100 ng/ml of an inhibitory anti–IL-10 Ab (MAD217; R&D) or with human rIL-10 (rhIL-10) in concentrations of 50 or 100 ng/ml (product 217-IL; R&D systems, Minneapolis, MN).

ELISpot quantitation of T cell IFN-γ– and monocyte TNF-α–producing cells

Quantitation of the number of IFN-γ–producing T cells and TNF-α–producing monocytes were assessed by enzyme linked ImmunoSpot (ELISpot) analysis (R&D Systems), as previously described (36). Cytokine production data via ELISpot is presented in two different manners. Capture Ab precoated 96-well strip plates were used for single-color enzymatic assay (ImmunoSpot by Cellular Technology Limited). Samples were visualized and analyzed using the ImmunoSpot Analyzer (Cellular Technology Limited, Cleveland, OH). BioSpot and ImmunoSpot software from Cellular Technology Limited were used to quantify ELISpot data by mechanically counting total number of positive spots per well as well as calculating the average spot size per well. The number of spots in a well indicate individual cells that are producing and secreting IFN-γ or TNF-α, and the spot size indicates the magnitude of the secretory response to treatment at the single-cell level. Because patient samples were incubated with and without treatment with anti–IL-10 or rhIL-10, we were able to compare untreated and treated response of each individual paired sample. The cutoff used for a positive response to in vitro stimulation is considered an increase in number of spots or mean spot size by 20% or more when comparing a treatment sample to its own positive control (34), and a negative response is considered with a 20% or more decrease in number of spots or mean spot size. Additionally, results are presented as a percentage of the cohort that responded positively or negatively to in vitro stimulation. This can then be compared with the response between septic, critically ill, and healthy cohorts. Both of these methods of analysis are used to describe our findings.

ELISA quantitation of IFN-γ and TNF-α

Cytokine kits for human and murine TNF-α and IFN-γ were obtained from BioLegend and R&D Systems, respectively. Assays were performed as per the manufacturer’s instructions and as previously described (36).

Monocyte HLA-DR surface expression

Surface levels of HLA-DR were examined on monocytes using flow cytometry after overnight incubation in RPMI 1640. PBMCs were cultured overnight in 18-well plates with similar conditions to the ELISpot cultures. Anti-CD3 and anti-CD28 was used as stimulant, and 3–4 h before cell harvest, brefeldin A (1 ml/ml), monensin (1 ml/ml), PMA (2 ml/ml), and ionomycin (1 ml/ml) were added to cultures. Cells were harvested, and Accutase (Invitrogen, Innovated Cell Technologies, San Diego, CA) was applied to wells to remove the monocyte adherent layer. Cells were stained with QuantiBRITE Anti–HLADR-PE/Anti–Monocyte-PerCP/Cy5.5 (BD Biosciences). Samples were acquired on FACScan as previously described (36). Abs bound per cell were calculated by using the QuantiBRITE PE Fluorescence Quantitation Kit (BD Biosciences) as a standard.

Examination of IL-10’s effect on T cell IFN-γ production in a murine sepsis model

The cecal ligation and puncture (CLP) model was used to induce poly-microbial sepsis as previously described. Eight- to ten-week-old C57BL/6J female mice (The Jackson Laboratory) were anesthetized with isoflurane, and a midline abdominal incision was performed. The cecum was ligated and punctured twice with a 27-γauge needle. Expected mortality using this method is 50%. The abdomen was closed in two layers, and 1.0 ml of 0.9% normal saline mixed with 0.05 mg/kg bodyweight buprenorphine (PharmaForce, Columbus, OH) was administered s.c. to ensure hydration and provide pain control. CLP-operated mice were treated 6, 24, 48, and 72 h after CLP with s.c. 1 or 10 μg of murine rIL-10 (PeproTech, Rocky Hill, NJ). On day 5, mice were then anesthetized using isoflurane and sacrificed via cervical dislocation prior to undergoing splenectomy. Splenocytes were then harvested and prepared by erythrocyte lysis and diluted to 5 × 106 cells/ml concentration. Cells were then divided for analysis using both ELISA and ELISpot. Both assays were used to evaluate T cell and monocyte activity in treated versus untreated mice. For ELISA staining, splenocytes were incubated overnight with LPS to stimulate monocyte activation for TNF-α analysis, and with anti-mouse CD3 and CD28 Abs for T cell activation and IFN-γ analysis. Supernatant was collected the following morning, and ELISA analysis was performed. Overnight culture of splenocytes with stimulation using LPS or anti-CD3/CD28 was also performed in Cellular Technology Limited ELISpot strip plates after being coated with TNF-α and IFN-γ capture Ab. ELISpot analysis was performed as described above. Animal experimentation was undertaken in accordance with Minimum Quality Threshold in Preclinical Sepsis Studies guidelines (37).

Statistical analysis

Data were analyzed using the statistical software Prism (GraphPad, San Diego, CA). Mean percentage change in spot number and spot size were calculated by dividing the difference between the control and treatment sample by the value of the control. Statistical analysis of ELISpot data were performed using paired analysis with the nonparametric Wilcoxon signed-rank test. In this test, each patient sample is compared with its own control, and these changes are compared for the entire group to determine statistical significance. When more than one sample was drawn from a single patient, these experiments were analyzed as a separate individual sample in the paired analysis. Mann–Whitney U tests were used to compare the mean change from the control between two different cohorts, and one-way ANOVA was used to assess overall difference between the response in all three cohorts (septic, CINS, and healthy volunteers). Data comparing subsets within each cohort (mortality and secondary infections) were assessed using χ2 analysis. For ELISpot data, the entire cohort is analyzed using a nonparametric paired analysis, whereby the author can assess the overall effect of the intervention on the cohort when compared with each individual’s own control. The χ2 analysis was performed to compare percentage responders between the cohorts. Paired Wilcoxon test was used to assess the statistical significance of changes in spot number or size from positive control. One-way ANOVA was used to compare percentage increase between the cohorts. The numerical values for each of these data points are presented in Supplemental Table I and described in detail in the Results section. Mouse data were analyzed using unpaired t test. A p value <0.05 was considered statistically significant.

Results

Clinical and laboratory parameters

Thirty-nine septic, twenty CINS, and twelve healthy control patients met enrollment criteria and are presented in Table I Patients enrolled in the septic cohort compared with the CINS group were of younger age (48 versus 62, p = 0.002) and trended toward fewer males (54% versus 70%, p > 0.2). Healthy controls were of similar age to the septic cohort (p = 0.1) and contained 41% males. There was a higher incidence of patients with diabetes and substance abuse in the sepsis cohort compared with the CINS group, although the difference did not reach statistical significance (p > 0.1, p > 0.05; Table I); there was no difference observed between other comorbidities as well.

Table I.

Patient demographic and clinical characteristics

Septic Patients (n = 39) CINS (n = 20) Healthy (n = 12)
Age, mean (range) 48 (18–89) 62 (28–81) 39 (25–76)
Male/female 21/18 14/6 5/7
Comorbidities no. (percent)
 Cancer 1 (2.6%) 1 (5%)
 Diabetes 7 (17.9%) 1 (5%)
 Cardiovascular disease 5 (12.8%) 6 (30%)
 Morbid obesity 1 (2.6%) 2 (10%)
 Renal disease 2 (5.1%) 2 (10%)
 Neurologic disease 4 (10.3%) 2 (10%)
 Respiratory disease 5 (12.8%) 6 (30%)
 Hepatic disease 2 (5.1%) 1 (5%)
 Substance abuse 10 (25.6%) 1 (5%)
Primary diagnosis no. (percent)
 Trauma 9 (23%) 5 (25%)
 Cardiovascular disease 0 7 (35%)
 Respiratory disease 5 (13%) 3 (15%)
 Neurologic disease 5 (13%) 0
 Sepsis/septic shock 5 (13%) 0
 Spinal complications 0 3 (15%)
 Gastrointestinal disease 13 (33%) 1 (5%)
 Splenic injury 0 1 (5%)
 Necrotizing fasciitis 2 (5%) 0
SOFA score at initial blood draw, mean (range) 8 (0–18) N/A
APACHE II score at initial blood draw, mean (range) 20 (7–29) N/A
Length of ICU stay in days, mean (minimum, maximum) 20.2 (2, 47) 2.7 (1, 6)
90 d Readmission (no. of patients) 9 (23%) 0
90 d Readmission (no. of admissions) 14 0
30 d Mortality 4 (10%) 0
31–90 d Mortality 2 (5%) 0
Total 90 d Mortality 6 (15%) 0
No. of patients who sustained secondary infections during initial hospitalization 22 (56.4%) 0
No. of patients who sustained secondary infections within 90 d 27 (69.2%) 0
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Demographic data comparing septic and CINS patient cohorts with healthy volunteers. Clinical data include comorbidities and admission diagnosis, SOFA score, and APACHE score for septic patients.

APACHE, acute physiology, age, chronic health evaluation; SOFA, severity of organ failure assessment.

In the septic cohort, the sources of infection were pneumonia (n = 15), peritonitis/intra-abdominal infection (n = 10), necrotizing fasciitis (n = 3), urinary tract infection (n = 3), skin and soft tissue/wound infection (n = 2), septic embolus (n = 1), central line–related infection (n = 1), and unknown source of infection (n = 4). Septic patients had higher total WBC counts compared with CINS patients (20 × 103/μl ± 1.5 versus 9.65 × 103/μl ± 0.7, respectively; p < 0.01). There was no difference in the mean absolute lymphocyte counts of septic versus CINS patients (1.5 × 103/μl ± 0.13 versus 1.48 × 103/μl ± 0.19; p = 0.8). There was a significantly higher mean absolute monocyte count in septic patients compared with CINS (1.23 × 103/μl ± 0.09 versus 0.9 × 103/μl ± 0.1; p = 0.01) (Supplemental Fig. 1). The mean length of ICU stay for patients was higher in the septic cohort with a larger variation compared with CINS (20.2 d, range 2–27 d versus 2.7 d, range 1–6 d, respectively).

Circulating IL-10 concentrations were elevated in septic versus CINS patients

The circulating serum levels of IL-10 drawn within 48 h of admission were significantly higher in septic versus CINS patients (30.7 pg/ml ± 4.6 versus 16.23 pg/ml ± 2.8, respectively; p = 0.02) (Supplemental Fig. 1).

IFN-γ production is reduced in septic and CINS patients compared with healthy controls

PBMCs from septic, CINS, and healthy control subjects were stimulated overnight with αCD3/αCD28 to activate T cells and the number of IFN-γ–positive spots was measured by ELISpot as both spot number and spot size. The number of IFN-γ–producing cells in healthy controls was 3-fold greater compared with both septic and CINS patients; p < 0.001; (Fig. 1A) but no difference was found between the CINS and septic groups. Whereas each spot represents a cell that secretes IFN-γ, the size of each spot reflects the amount of IFN-γ produced by each cell. There was no difference in the average spot size in septic patients versus healthy controls, the spot size in CINS patients was smaller compared with healthy controls (septic mean 8.1 μm2 ± 0.6, CINS mean 7 μm2 ± 0.9, and healthy mean 9.3 μm2 ± 0.8; p < 0.03; Fig. 1B).

FIGURE 1.

FIGURE 1.

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Baseline function of innate and adaptive immune system in septic, CINS, and healthy persons. Difference in the baseline production of IFN-γ and TNF-α between the three study cohorts. ELISpot quantification of the number of cells producing the given cytokine (A and C) as well as the magnitude of response by average the spot sizes (B and D) following overnight stimulation with a positive control (αCD3/αCD28 or LPS, respectively). HC, healthy control. *p < 0.05, **p < 0.01, ****p < 0.0001.

TNF-α production is reduced in septic, but not CINS, patients versus controls

PBMCs from septic, CINS, and healthy control subjects were stimulated overnight with LPS to activate monocytes for ELISpot. Both number and size of TNF-α–positive spots were quantitated. Patients with sepsis had fewer number of TNF-α–producing cells compared with both CINS and healthy controls (septic mean 323 ± 41, CINS mean 492 ± 99, and healthy mean 446 ± 41; p < 0.01), (Fig. 1C). There was a statistically significant increase in mean spot size in TNF-α–secreting cells in septic versus CINS patients (septic mean 9.9 μm2 ± 0.85, CINS mean 6.8 μm2 ± 0.8, and healthy mean 7.6 μm2 ± 0.6; p < 0.05) (Fig. 1D).

Inhibition of IL-10 increases T cell IFN-γ production in septic patients

Fig. 2A represents the ELISpot depiction of a septic patient who positively responded to IL-10 inhibition by increasing the number of cells secreting, and the average spot size (magnitude) of response, for IFN-γ. Ex vivo inhibition of IL-10 increased IFN-γ production by >20% from positive control in 45% of septic patients (Fig. 2B). Overall, septic patients had a significant increase in number of cells producing IFN-γ when compared with their positive controls (32.6% ± 7.7; p < 0.001). Only 24% of CINS had positive response, and 24% of CINS patients negatively responded to IL-10 inhibition with decreased IFN-γ production (Fig. 2C). There was no significant difference in number of IFN-γ–producing cells between the positive control and stimulated cells for the CINS cohort (p = 0.2). There were no responders to IL-10 inhibition among the 12 healthy volunteers, and no change from the positive control with IL-10 inhibition (p < 0.9999) (Fig. 2D). Comparison of the mean percentage response to IL-10 inhibition between the three groups using one-way ANOVA showed a significant difference (p < 0.0001). Mean spot size was increased by >20% in 50% of septic patients, 18% of CINS patients, and none of the healthy controls. Only septic patients had an overall significant increase in mean spot size compared with their positive control (p < 0.0001). There was a statistically significant difference in the septic group when compared against the changes in CINS and healthy controls (p < 0.0001) (Supplemental Fig. 2).

FIGURE 2.

FIGURE 2.

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IL-10 inhibition increases IFN-γ production in patients with sepsis, but not CINS or healthy controls. (A) Depiction of positively responding patient with sepsis shown in duplicate, with positive response for both spot number and size. A total of 5 × 105 cells plated for IFN-γ immunostaining. (B–D) Bar graph representation of the percentage change in response of individual patients; sepsis (B), CINS (C), and healthy subjects (D) to treatment when compared with their own positive control samples. All samples were prepared in duplicates, and the results were averaged together. Responders to treatment (>20% increase) are displayed in solid black color, whereas nonresponders are displayed in light gray. Percentage change was calculated by dividing the difference between the treatment sample and control sample by the control sample response.

Inhibition of IL-10 increases TNF-α production in septic patients

Fig. 3A depicts two septic patients who responded positively to IL-10 inhibition by increased TNF-α production, both number of spots and spot size. In the septic cohort, 15% of patients had response to IL-10 inhibition with >20% increased number of TNF-α producing monocytes, whereas 22% of CINS cohort and 8% of the healthy cohort responded (Fig. 3B–D). Despite the modest number of septic patients who had >20% increase in production, 71% of septic patients had an increase in TNF-α–producing cells with an overall significant change from positive control (11.7% ± 3.45; p < 0.0001). Additionally, in terms of mean spot size of TNF-α production, 32% of septic patients, 28% of CINS, and 33% of healthy volunteers had a >20% increase. When compared with their positive controls, septic (p = 0.0003) and CINS (p = 0.01) had significant increases in TNF-α spot size, and healthy controls (p = 0.3) had no difference (Supplemental Fig. 2).

FIGURE 3.

FIGURE 3.

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IL-10 inhibition increases TNF-α production in patients with sepsis, but not CINS or healthy controls. (A) Depiction of positively responding patient with sepsis shown in duplicate, with positive response for both spot number and size. A total of 5 × 104 cells plated for the TNF-α immunostaining. (B–D) Bar graph representation of the percentage change in response of individual patients; sepsis (B), CINS (C), and healthy subjects (D) to treatment when compared with their own positive control samples. All samples were prepared in duplicates, and the results were averaged together. Responders to treatment (>20% increase) are displayed in solid black color, whereas nonresponders are displayed in light gray. Percentage change was calculated by dividing the difference between the treatment sample and control sample by the control sample response.

IL-10 increases T cell IFN-γ production in patients with sepsis

Fig. 4A represents the ELISpot depiction of representative septic patients who positively respond to ex vivo addition of IL-10 by increasing the number of cells secreting IFN-γ as well as an increase in mean spot size. Two dosages of rhIL-10 were used: 50 and 100 ng/ml. The addition of IL-10 to PBMCs in septic patients increased IFN-γ production, whereas the addition of IL-10 to CINS and healthy samples did not increase the overall number of IFN-γ–producing T cells. The number of positive responders to stimulation with IL-10 included 43% of septic patients receiving low dosage, 64% of septic patients receiving the high dosage, 33% of CINS receiving low dosage, and 50% of CINS receiving high dosage, and 8% of the healthy controls who received high-dosage IL-10 (Fig. 4B–E). Only the septic patient samples that received 100 ng/ml rhIL-10 had an overall significant increase in number of IFN-γ–producing cells compared with the positive control (50 ng/ml = 26.7% ± 7.29; p = 0.07; 100 ng/ml = 54.4% 6 10.32; p = 0.007). There was a trend toward a dosage-dependent response within the septic cohort, as the mean increase in number of cells was 26.7% ± 7.3 for the low dosage and 54.4% ± 10.3 for the high dosage.

FIGURE 4.

FIGURE 4.

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IL-10 addition increases IFN-γ production in patients with sepsis, but not in CINS or healthy controls. (A) Two distinct patient samples, prepared in duplicate, displaying a response to treatment with rhIL-10 in patients with sepsis, evidenced by >20% increase in the number of IFN-γ–producing cells (number of spots). The response to IL-10 is dosage dependent, with a greater increase in number of spots with 100 ng/ml treatment as opposed to 50 ng/ml rhIL-10. There is also an increased mean spot size with the treated sample. A total of 5 × 105 cells plated for IFN-γ immunostaining. (B–E) Bar graph representation of the percentage change in response of individual patients; sepsis (B and C), CINS (D), and healthy subjects (E) to treatment when compared with their own positive control samples. All samples were prepared in duplicates, and the results were averaged together. Responders to treatment (>20% increase) are displayed in solid black color, whereas nonresponders are displayed in light gray. Percentage change was calculated by dividing the difference between the treatment sample and control sample by the control sample response. Two distinct dosages of rhIL-10 were used: 50 and 100 ng/ml.

IL-10 decreases monocyte TNF-α production

Fig. 5A represents the ELISpot depiction of representative septic patients who positively respond to ex vivo addition of IL-10 by increasing the number of cells secreting TNF-α as well as an increase in mean spot size. Ex vivo addition of IL-10 decreased monocyte function by decreasing the number of TNF-α–producing cells by >20% in 29% of septic patients for both the low and high dosage, 29 and 21% in the CINS cohort for both respective treatment dosages, and 33% in the healthy cohort (Fig. 5B–E). Within the overall cohort of septic patients, both the low-dosage and high-dosage IL-10 significantly decreased number of TNF-α–producing cells (50 ng/ml = −10% ± 2.8; p = 0.03; 100 ng/ml = −10.4% ± 2.35; p = 0.008). Although a percentage of CINS patients had decreased production of TNF-α, within the overall cohort, there was no significant decrease when compared with the positive control. There was a significant decrease in the healthy control cohort (p = 0.002). Mean spot size was significantly decreased by IL-10 in septic (p = 0.0004, p < 0.0001) and CINS (p = 0.01, p = 0.02) cohorts and trended toward a decrease in the healthy controls (p = 0.06) as well (Supplemental Fig. 3).

FIGURE 5.

FIGURE 5.

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IL-10 addition decreases production of TNF-α. (A) Two distinct patient samples, prepared in duplicate, displaying a response to treatment with rhIL-10 in patients with sepsis, evidenced by >20% increase in the number of TNF-α–producing cells (number of spots). The response to IL-10 is not dosage dependent, with no significant decrease in the number of spots between both treatment with 50 and 100 ng/ml of rhIL-10. There is also an increased mean spot size with the treated sample. A total of 5 × 104 cells plated for the TNF-α immunostaining. (B–E) Bar graph representation of the percentage change in response of individual patients; sepsis (B and C), CINS (D), and healthy subjects (E) to treatment when compared with their own positive control samples. All samples were prepared in duplicates, and the results were averaged together. Percentage change was calculated by dividing the difference between the treatment sample and control sample by the control sample response. Two distinct dosages of rhIL-10 were used: 50 and 100 ng/ml.

HLA-DR expression

The geometric mean fluorescence intensity was compared against a standard curve derived from a concurrent panel of BD Biosciences QuantiBRITE beads. The result of this comparison is a value defined, by the manufacturer, as Abs bound per cell. Anti–IL-10 inhibitory Ab caused a slight overall decrease in mean fluorescence intensity of HLA-DR expression in septic patients (mean: −7.76% ± 3.8, p = 0.02), whereas overnight incubation with IL-10 induced a profound decrease in expression (mean: −40% ± 2.8, p < 0.0001). rIL-10 (rhIL-10) also decreased expression of HLA-DR in the CINS and healthy controls as well (CINS mean: −44 ± 5.6, p = 0.007; HC mean −27.3 ± 5, p = 0.0005). Inhibition of IL-10 in CINS had a nonspecific trend toward increased HLA-DR expression (mean 20.4 ± 15.22, p = 0.5) and IL-10 inhibition had essentially no effect on healthy control samples (mean 0.51 ± 1.86, p = 0.9) (Fig. 6).

FIGURE 6.

FIGURE 6.

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Flow cytometry expression of monocyte HLA-DR. Analysis of monocyte HLA-DR expression in response to in vitro culture with IL-10 inhibition or IL-10 addition to PBMCs in patients with sepsis, CINS, and healthy subjects. Positive control incubated with anti-CD3/CD28. (A) Gating strategy used for the QuantiBRITE Anti-HLADR/Anti-Monocyte stain. (B and C) Graphical histogram representation of the effect of both treatments on patients with sepsis. (D) Mean change in Abs bound per cell for IL-10 inhibition. *p = 0.02. (E) Mean change in Abs bound per cell for rhIL-10 addition. **p = 0.007, ***p = 0.0005, ****p < 0.0001.

Splenocytes from septic mice treated in vivo with IL-10 increase IFN-γ production

To provide additional potential clinical relevance, we examined the effect of IL-10 on T cell IFN-γ production in an in vivo model of murine sepsis using CLP. CLP was performed on C57BL/6 female mice which were subsequently treated with or without IL-10 and splenocytes were harvested on day 5. Twelve mice received only saline, six received 1 μg, and 13 received 10 μg IL-10. Splenocytes harvested from mice treated in vivo with IL-10 were then incubated for overnight culture in ELISpot wells and culture plates for ELISA analysis to compare treated to untreated mice in reference to the number of activated T cells and monocytes as well as quantity of IFN-γ and TNF-α production. These results reflect conditions of treated mice rather than in vitro–treated splenocytes. There was no statistical difference, rather a trend toward increase, in IFN-γ production (number of spots) in septic mice in either treatment group (dosage 1 or 10 μg) compared with placebo (saline mean 810 ± 40.5, n = 12; 1 μg mean 874 ± 73, n = 6; 10 μg mean 906 ± 53, n = 13; p = 0.4). ELISA quantification of IFN-γ produced following overnight incubation of splenocytes showed no difference in production of IFN-γ in the low-dosage treatment (1 μg) versus control group; however, with an increased dosage (10 μg), there was an increased production of IFN-γ in the treatment group compared with control (saline mean 1313 pg/ml ± 308, n = 12; 1 μg mean 1665.5 pg/ml ± 782, n = 6; 10 μg mean 3231 pg/ml ± 481, n = 13; p = 0.002) (Fig. 7). ELISpot results for TNF-α production demonstrated a 27% decrease in number of spots for the 1 μg–treated mice (p = 0.07) and 10% decrease with the 10 μg–treated mice (p = 0.3). ELISA results for TNF-α production revealed an 8.6% decrease in secreted TNF-α for the 1 μg treatment group (p = 0.5) and a 10% increase in production of TNF-α in the 10 μg treatment group (p = 0.4).

FIGURE 7.

FIGURE 7.

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IFN-γ effect of in vivo treatment with IL-10 in CLP model of murine sepsis. (A) ELISpot quantification of IFN-γ–producing spot numbers versus (B) ELISA quantification of INF-γ, comparing negative control with different dosages of IL-10 in septic mice. **p = 0.002.

Discussion

IL-10 has been shown to have an immunosuppressive effect on innate immunity via decreased TNF-α production and HLA-DR expression in classical monocytes (23, 33, 34). However, the impact of IL-10 on the innate and adaptive immune system and the potential cross-talk between the innate and adaptive immune systems is unclear. In our study, we demonstrate in both human (ex vivo) and mouse (in vivo) studies that in the sepsis environment IL-10 has a potent effect and plays an important immunomodulatory role in both the innate as well as the adaptive immune systems. Namely, we demonstrate that 1) IL-10 inhibition has a positive effect on the stimulation of both the innate and adaptive immune systems by increasing T cell IFN-γ and monocyte TNF-α production in patients with sepsis; 2) IL-10 addition to PBMCs from septic patients has opposing effects on the innate and adaptive immune systems by both increasing T cell IFN-γ production and decreasing TNF-α production as well as surface expression of HLA-DR; 3) IL-10 effects on the innate system are uniform throughout all cohorts; however, the effects on adaptive IFN-γ production were only seen with septic patients; and 4) confirmation of our findings in a murine model of sepsis in which administration of IL-10 produced higher levels of IFN-γ than in untreated mice.

Early findings following the discovery of IL-10 generated the belief that IL-10 was exclusively a cytokine that promotes immune suppression and downregulation of all inflammatory processes. In this context, the findings of the current study showing that IL-10 has immunostimulatory properties on T cells in sepsis is surprising. Whereas IL-10 antagonism increased IFN-γ production in T cells from patients with sepsis, incubation of the same patients’ PBMCs with IL-10 also increased IFN-γ, demonstrating broad effects upon two separate effector immune cells.

To further investigate this putative immunostimulatory role of IL-10, we administered IL-10 to mice with sepsis and verified an increase in splenocyte IFN-γ production (Fig. 7). These provocative findings are consistent with new clinical trials in oncology, demonstrating that IL-10 enhances T cell tumor surveillance and IFN-γ production, leading to tumor reduction or remission. Mumm et al. (22) report that IL-10 directly and specifically activate Ag-specific, IFN-γ–producing CD8+ T cells. They describe that treatment of tumor-specific CD8+ T cells with IL-10 will specifically stimulate production and secretion of IFN-γ in the recognized tumor environment to a greater extent than when incubated with unknown tumor cells (22).

The fact that IL-10 antagonism improves T cell function in patients with sepsis, but does not have a robust effect in patient samples from subjects without sepsis can be explained by the fact that the cells from a septic environment are likely primed with IL-10 and removal of this stimulus will restore function to suppressed cells. It is more surprising that our findings show such a pronounced increase in IFN-γ–producing cells after IL-10 addition only in the septic patients and not in the other cohorts. This surely indicates an underlying change in the state of septic T cells that are more sensitive to stimulation with IL-10.

A second seemingly paradoxical finding in our study was the observation that both administration of IL-10 and inhibition of IL-10 both increased IFN-γ production in stimulated T cells from the same patient. One potential explanation for these seemingly contradictory findings (i.e., both IL-10 and anti–IL-10 increase IFN-γ), is that they are acting on different cell types included in the PBMC fraction, including CD8+ T cells, CD4+ T cells, T regulator cells, monocytes, or NK cells. In the cancer field, administration of IL-10 appears to increase IFN-γ production by cytotoxic CD8+ T cells, leading to enhanced killing of tumor cells (22). Thus, one potential cell type that could be targeted by IL-10 in sepsis is CD8+ T cells. Another cell that might be impacted by anti–IL-10 are T regulatory cells. In sepsis, there is upregulation of T regulatory cells that are potent producers of IL-10 (23, 27, 28, 31, 32, 38, 39). Thus, anti–IL-10 could be acting on T regulatory cells to suppress the amount of IL-10 produced, thereby unleashing the inhibition of IL-10 on Th1 CD4+ cells and enabling them to produce more IFN-γ. In this existing ex vivo model, there are some patients’ PBMC fractions that responded to antagonism with anti–IL-10, IL-10 agonism with rhIL-10 addition, both molecules, and neither of the treatments. The implication of these data are crucial in our understanding of many of the immune pathways at play during sepsis. There are likely differential effects of sepsis on the various cell types that vary depending upon the time course of sepsis and the cellular context.

The role of IL-10 has also been intensively investigated in infectious disease (40, 41). It is generally considered that high levels of IL-10 induce a state of immune latency, whereby viruses can evade immune surveillance and remain undiscovered by the immune system for many years. Selected viruses have the ability to seize the host cell’s genetic machinery and induce production of IL-10, thereby enabling them to evade detection and elimination. The role of IL-10 in sepsis has been controversial. High-circulating levels of IL-10 have been associated with mortality and poor outcomes in patients with acute infections/sepsis. The implications of these findings are poorly understood. Howard et al. (24) used IL-10 to protect mice from a lethal dosage of endotoxin. Mouse rIL-10 was administered 30 min prior to or at the time of LPS injection, and mice treated with IL-10 had a significantly increased survival rate with a decreased production of TNF-α (24). Nicoletti et al. (42) confirmed these findings by proving that pretreatment with rIL-10 before injection of LPS protected mice from lethality. Blocking IL-10 with a mAb increased death in these mice. TNF-α was decreased in IL-10–treated mice and increased in anti–IL-10 mice (42). In addition to mouse models of sepsis, studies were performed on humans with induced endotoxemia to evaluate the effect of IL-10 on sepsis. Lauw et al. (43) found that treatment with rhIL-10 following induction of endotoxemia caused increased levels of IFN-γ and soluble granzymes. In contrast to the studies showing a beneficial effect of IL-10 in endotoxin models of sepsis, Kalechman et al. (21) showed that blocking production of IL-10 in mice 12 h after CLP improved the immune response as well as overall survival. The current work supports opposing effect of IL-10 in patients with sepsis, likely making use of different cell types and acting at variable time points in the progression of the disease.

Similar to previously described results in other models or disease processes, monocytes from patients with sepsis respond to IL-10 by both decreasing production of TNF-α as well as expression of the cell surface Ag presenting molecule HLA-DR (44, 45). In contrast, blocking IL-10 increases TNF-α production. When considering the potential therapeutic immunomodulatory effects of targeting the IL-10 pathway, further investigation will be needed to evaluate the consequences of ameliorating the adaptive response at the expense of downregulation of critical innate immune functions. It is possible that different time points in the course of sepsis will respond differently to blocking or increasing IL-10.

A strength of the study is that we examined the contrasting effects of both inhibiting IL-10 as well as administering IL-10 in PBMCs obtained from patients with ongoing sepsis. Furthermore, IL-10 was studied in an in vivo model to determine if the in vitro findings in patients’ PBMCs were reproduced in a clinically relevant murine model of sepsis. Using ELISpot, the study emulates the effect over time after treatment with our target molecule. Accessing patients with sepsis of varying etiology and severity plays into the heterogeneity of sepsis, allowing for investigation into potential differing responses among patients. The addition of a healthy population to this study aided in ensuring a baseline immune response to IL-10 in addition to the CINS controls.

Although this study provides new and exciting findings for IL-10 in sepsis, there are a number of limitations. First, the findings are derived from in vitro responses and may not truly reflect, nor can they be replicated under in vivo conditions. Second, the study can only be interpreted as hypothesis generating given the small sample size, it is underpowered to investigate effects on morbidity and mortality. Individual responses to treatment were able to be measured and scrutinized, understanding that aggregating all the responses together would not consider the vast heterogeneity of the underlying disease process. Given the small sample size, there was great heterogeneity in study subjects in each cohort, namely differences in age (which may have different IL-10 responses), development of secondary infections, and length of stay; all confounding variables on our primary outcome variables. Our study was underpowered to establish a robust correlation between clinical outcomes and in vitro response. Additionally, our CINS cohort lacked information for severity of illness scoring, precluding multivariate analysis of sepsis versus CINS as a function of severity of illness on our immunologic readouts. Likewise, the patient’s in our surgical ICU had a much higher length of stay and incidence of secondary infections. This atypical high rate of secondary infections occurred among patients who had undergone severe trauma or were admitted because of a severe infection requiring surgical intervention. Many of these patients remained critically ill in the ICU requiring mechanical ventilation for an extended period of time and therefore sustained resistant wound infections and ventilator-associated pneumonias with increasing antibiotic resistance as well as fungal infections. Nonetheless, our study can only demonstrate associative properties without clear delineation of causal pathways. Additionally, although the ELISpot assay demonstrates increased cell spot number and size, it is only a surrogate of the amount of cytokine produced (46, 47). Previous studies have demonstrated that the reliability of ELISpot spot number as a surrogate to quantitate cytokine production via standard ELISA testing is high (48). Finally, our study scrutinized a single time point in the course of the patients’ illness and does not consider the temporal evolution of disease. Evaluating our current findings must be done with caution as the differential effects of IL-10 on innate/adaptive cross-talk may vary over time and in context of disease state.

Our findings explore a unique phenomenon of differential effector cell response even within and between sepsis patients. Our study’s findings exploit a unique clinical platform to evaluate innate and adaptive immune function using the ELISpot assay. The ELISpot quantitates the number of T cells and monocytes that respond to stimulation by producing IFN-γ and TNF-α, respectively, two cytokines that are critical for host defense. Further, the ELISpot assay also quantitates the relative amount of cytokine produced on a cellular basis as indicated by area of the cytokine spot detected by computer analysis, (see Figs. 2–5). Therefore, this assay is an excellent means to assess innate and adaptive immunity response by analyzing the functional status (i.e., cytokine secretion of monocytes and T cells, respectively) and can be directly used in further translational evaluations of IL-10 modulation and other therapeutic targets.

In conclusion, we demonstrate that IL-10 inhibition has a positive effect on the stimulation of both the innate and adaptive immune systems by increasing T cell IFN-γ and monocyte TNF-α production in patients with sepsis. This effect is not seen in the CINS and healthy control cohorts. Addition of IL-10 in patients with sepsis also has a positive effect on the activation of the adaptive immune system by improving T cell IFN-γ production. In contrast, addition of IL-10 to patients with sepsis diminishes the activity of the innate immune system by decreasing TNF-α production as well as surface expression of HLA-DR. Whereas the negative effects on the innate immune system are consistent throughout the three experimental cohorts, the positive effect on the adaptive immune system was only seen with the septic patients. The surprising positive effect of IL-10 addition on septic patient IFN-γ production was supported by our mouse model data in which splenocytes from CLP-induced mice treated with 10 μg IL-10 produced higher levels of IFN-γ than untreated mice. By elucidating the context of these differential IL-10 effects on both innate and adaptive effector immune cells, future directions could expand a more mechanistic understanding of related cross-talk pathways in efforts to potentially influence the development of secondary infections. A future mechanistic approach of using IL-10 has the potential to be applied to divergent sepsis hyper- and hypoinflammatory states, which could be assessed and evaluated through serial ELISpot assays as a measure of immune phenotype and response to therapy. Future studies are warranted to evaluate specific IL-10 signaling causal pathways and associated clinical phenotypes to outcomes.

Supplementary Material

1

Acknowledgments

We acknowledge Nemani Nateri for assistance in animal sepsis studies and Jane Blood for assistance with all institutional review board regulatory relevant considerations.

This work was supported by R35 (Maximizing Investigators’ Research Award) GM126928-01 from the National Institute of General Medical Sciences (to R.H.).

Abbreviations used in this article:

CINS

critically ill nonseptic

CLP

cecal ligation and puncture

ICU

intensive care unit

rhIL-10

human rIL-10

Footnotes

The online version of this article contains supplemental material.

Disclosures

The authors have no financial conflicts of interest.

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