Natural killer (NK) cells with downregulated activating receptors and IL-10 production promote Trypanosoma cruzi T-cell responses in subjects in the Chronic phase of Trypanosoma cruzi infection: An exploratory immunological analysis

María J. Elias; Gonzalo Cesar; María G. Alvarez; Ariel Podhorzer; María B. Caputo; Constanza Lopez Albizu; Máximo Carrega; Flavio A. Tomán Conte; María A. Natale; María C. Albareda; Bruno Lococo; Susana A. Laucella

doi:10.1371/journal.pntd.0014622

Abstract

Background

Subjects with chronic Chagas disease and no signs of heart disease exhibit decreased NKp46 expression, high CD57 expression, and IL-10 production by NK cells. This study provides a detailed characterization of the phenotype and function of NK cells according to the severity of heart disease, and evaluates how these changes following treatment with benznidazole, as well as their association with Trypanosoma cruzi-specific T-cell responses.

Methods

The phenotype and function of NK cells in a cohort of 51 subjects infected with Trypanosoma cruzi and exhibiting varying degrees of heart disease were evaluated using high-dimensional flow cytometry and Boolean gating analysis. ELISPOT assays were performed to measure IFN-γ and IL-2 production in response to T. cruzi antigens, using CD56, CD4 and CD8-depleted PBMC.

Results

In contrast to individuals without heart disease, those with advanced cardiomyopathy have an increased number of NK cells that express the activating receptors NKp46 and CD16, as well as the differentiation marker CD57. NK cells in subjects with advanced cardiomyopathy were also found to be enriched in CD56⁺CD107⁺granzyme B⁺TNF-α⁺ cells and depleted of CD56⁺IL-10⁺ cells. The function of NK cells shifted towards monofunctionality in subjects with declining T. cruzi-specific antibodies following treatment with benznidazole. Eliminating CD56⁺ cells significantly decreased the number of IFN-γ-producing cells in response to T. cruzi.

Conclusions

In chronic T. cruzi infection, NK-cell function may be balanced by the downregulation of activating receptors and IL-10 production, However, parasite persistence may desensitize the regulation of NK activating receptors, enabling NK cells to exert a potent polyfunctional cytotoxicity that potentially induce tissue damage.

Author summary

While T cells are known to play a key role in the immune response against Trypanosoma cruzi, the contribution of natural killer (NK) cells—immune cells that provide early defense against pathogens and help to regulate immune responses—remains unclear. In this study, we evaluated the NK-cell phenotype and function in patients with different clinical forms of chronic Chagas disease and examined how they are affected by etiological treatment, as well as their association with Trypanosoma cruzi-specific T-cell responses. We found that individuals without cardiac disease exhibited NK cells with reduced expression of activating receptors and increased production of the regulatory cytokine IL-10, suggesting a role in controlling excessive immune responses. By contrast, patients with cardiomyopathy exhibited NK cells with an exacerbated functional profile. We also found evidence that NK cells support parasite-specific T-cell responses and that successful benznidazole treatment is associated with a shift toward a resting status of these cells. Together, these results highlight NK cells as important modulators of immunity and disease progression in chronic Chagas disease.

Citation: Elias MJ, Cesar G, Alvarez MG, Podhorzer A, Caputo MB, Lopez Albizu C, et al. (2026) Natural killer (NK) cells with downregulated activating receptors and IL-10 production promote Trypanosoma cruzi T-cell responses in subjects in the Chronic phase of Trypanosoma cruzi infection: An exploratory immunological analysis. PLoS Negl Trop Dis 20(8): e0014622. https://doi.org/10.1371/journal.pntd.0014622

Editor: Grace Adira Murilla, KARI-Trypanosomiasis Res Centre, KENYA

Received: February 13, 2026; Accepted: July 27, 2026; Published: August 12, 2026

Copyright: © 2026 Elias et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the manuscript and its Supporting Information files.

Funding: This work was supported by the National Institute of Allergy and Infectious Diseases at the National Institutes of Health (grants R01143496 to S. A. L); the National Fund for Science and Technology of Argentina (PICT 2018–01522 to S. A. L.); the Ministerio de Salud de la Nación, Argentina; and the Ministerio de Salud de la Provincia de Buenos Aires, Argentina. M. C. A., C. P. and S. A. L. are in the payroll of the National on Scientific and Technical Research Council, Argentina. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The authors have declared that no competing interests exist.

Background

Chagas disease is a potentially life-threatening illness that affects approximately 6–7 million people [1,2]. Initially, the disease was confined to endemic areas, primarily in Latin America, but due to increased population mobility in recent decades, most infected individuals now reside in urban areas. Consequently, the infection has been increasingly detected in non-endemic countries, transforming it into a global public health concern [2–4].

T. cruzi-specific T cell responses in chronic Chagas disease are critical for infection control [5]. A low level of detectable T. cruzi-specific T cells, along with a predominance of monofunctional cytokine-producing T cells, is found in the circulation of subjects with long-term T. cruzi infections, particularly those with more advanced cardiac disease [6]. Innate immune cells play an integral role in the host's defense against pathogens. Among them natural killer (NK) cells served to control the burden of intracellular pathogens by lysing infected cells or producing effector cytokines until adaptive immune responses develop in acute infections [7]. NK cells may also exert regulatory functions on T cells [8,9], and thus may play a key role also in chronic infections [10,11].

The function of NK cells is regulated by the integration of activating and inhibitory receptors. Reduced or weakened signals from activating receptors allow inhibitory signals to dominate, thereby decreasing NK-cell functionality [12,13]. Several reports have demonstrated that, in the context of chronic infections, NK cells exhibit a state of exhaustion similar to that of exhausted T cells, displaying altered function and phenotype [12–14].

We have shown that NK cells in subjects with chronic Chagas disease who have not yet developed cardiac alterations exhibit decreased expression of the activating receptor NKP46, high expression of the differentiation marker CD57 and produce IL-10 [15] supporting a regulatory role of NK cells in chronic Chagas disease.

The present study evaluated the relationship between adaptive and innate immune responses in relation to cardiac dysfunction, and how these responses are modulated by etiological treatment. The hypothesis to be assessed is whether NK-cell function becomes exhausted in more severe stages of chronic T. cruzi infection, or whether it is exacerbated.

Methods

Ethic statement

This study was approved by the Institutional Review Board of the Hospital Interzonal General de Agudos Eva Perón, Buenos Aires, Argentina (Memorandum No. 19/19). All patients signed informed consent forms prior to inclusion in the study.

Selection of study population

Patients who tested positive for at least two out of three serological tests for T. cruzi infection (i.e., indirect immunofluorescence assays, hemagglutination and ELISA tests), known as “conventional serology”, were considered to be infected [2]. Subjects were clinically evaluated and grouped according to a modified version of the Kuschnir grading system [16,17]: group 0 (G0), seropositive individuals exhibiting a normal electrocardiogram (ECG) and normal echocardiograph; group 1 (G1), seropositive individuals with a normal echocardiograph but abnormalities in the ECG; group 2 (G2), seropositive individuals with ECG abnormalities and heart enlargement; and group 3 (G3), seropositive individuals with ECG abnormalities, heart enlargement and clinical or radiological evidence of heart failure. Groups 2 and 3 were presented together because both groups showed evidence of cardiac muscle compromise, as confirmed by echocardiography. When treatment with benznidazole was indicated, this was administered at 5mg/kg body weight per day for30days [18]. All the subjects that were treated belonged to the G0 group. Monitoring of T. cruzi-specific antibodies were performed at 6 months post-treatment and once a year thereafter up to 48 months of follow-up. Treatment was considered successful when at least one of the following criteria for conventional serology was fulfilled — conversion of positive serology to negative results on three or two tests performed and decrease in titers on at least 2 tests out of the three tests (i.e., 30% reduction in ELISA titers, and a 2-fold dilution by indirect immunofluorescence assays or hemagglutination) [17,19] — or when a 50% reduction in the reactivity of at least two proteins in the Luminex-based, multiantigen serological assay was observed [17,20,21]. Unchanged T. cruzi-specific antibody levels post-treatment, positive findings using qPCR [22,23], or disease progression during post-treatment follow-up was considered treatment failure. Age-matched uninfected subjects from Buenos Aires who have always resided in nonendemic areas and with negative serological findings for T. cruzi infection served as the uninfected control group. The study population characteristics are summarized in Table 1.

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Table 1. Baseline characteristics of study population in Trypanosoma cruzi-infected subjects and uninfected controls.

https://doi.org/10.1371/journal.pntd.0014622.t001

Collection of peripheral blood mononuclear cells (PBMC)

Approximately 50 mL of blood was drawn by venipuncture into heparinized tubes (Vacutainer, BD Biosciences) and PBMC isolated as previously described [24].

NK-cell phenotype and high dimensional analysis

One a half million PBMC were stained with a combination of monoclonal antibodies specific for CD56, CD16, CD3, CD57, CD127, KIR2DL2, NKp46, NKG2D and a dump channel for CD14 and CD19 with the addition of a viability dye [S1 Table]. The gating strategy for the selection of CD56^bright and CD56^dim NK-cell subsets is shown in S1.

Approximately 500,000 events were acquired per sample in a FACSAria II flow cytometer (BD Biosciences, USA). A high-dimensional analysis was carried out that consisted of the following steps: FlowAI (v.2.3.1) was used to discard anomalous events (setting: all checks, second fraction FR = 0.1, alpha FR = 0.01, maximum changepoints = 3, changepoint penalty = 200, and dynamic range check side = both). Then, the CD56⁺ NK population was selected using a manual gating strategy, excluding doublets, dead cells and CD3⁺ lymphocytes. DownSample (v.3.3) was used to even the number of events represented by each FCS file. Clinical parameter categorical values for each sample were added to downsampled populations as metadata to enable identification of these groups, and these were then concatenated for analysis. A dimension reduction analysis was performed using tSNE. For dimension reduction and clustering algorithms, all parameters were analyzed except for live/ dead NIR, CD3 and CD56. Those samples that had mean fluorescence intensity (MFI) values higher than two standard deviations away from the parameter mean (calculated from all samples) in two or more of the parameters considered for the high-dimensional analysis were excluded from the study to ensure the consistency of the analysis. An arbitrary cut-off point was set, whereby samples in which the number of events in the CD56^bright and CD56^dim NK-cell subpopulations did not reach 300 and 2,500, respectively, were excluded from the analysis. For analysis of the data, only clusters over 2.5% frequency were selected.

NK-cell function

For NK-cell function, 3x10⁶ PBMCs were cultured with phorbol 12-myristate 13-acetate (PMA, 10 ng/ml, Sigma‒Aldrich) and ionomycin (1 μg/ml, Sigma‒Aldrich) in the presence of brefeldin A (10 μg/ml, Sigma‒Aldrich) for 4 hours [15,25]. Anti-CD107a was added at the onset of incubation. Unstimulated PBMC did not receive any treatment and served as controls. Surface staining was conducted using anti-human antibodies specific for CD56, CD16 and CD3, with the addition of a viability dye [S1 Table]. Following permeabilization using Cytofix/Cytoperm buffer (BD Biosciences), staining was conducted using a cocktail of antibodies specific for granzyme B, interferon (IFN)-γ, interleukin (IL)-10 and tumor necrosis factor (TNF)-α [S1 Table]. Unstained and fluorescence minus one (FMO) sample were used as gating controls. Approximately 600 000 events were collected per sample in the FACSAria II flow cytometer, and data were analyzed by FlowJo software (Version 10.8). Cytokine coexpression profiles of CD56⁺ NK cells were determined using the Boolean gating function of FlowJo software. Background responses detected in unstimulated control samples were subtracted from those detected in PMA/ionomycin-stimulated samples for every functional combination. NK cell responses were considered positive when cytokine production in the stimulated samples was at least double that obtained with the media alone, and when at least five events, or at least three events for single and polyfunctional responses, were present [15].

ELISPOT assays following CD56 or CD4/CD8 depletion

Ten million PBMC were incubated with anti-human CD56 magnetic particles (BD Biosciences) according to the manufacturer’s instructions and the depleted fraction was collected using a cell separation magnet. This process was repeated twice, after which the cell suspensions were counted [S2 Fig]. A second fraction of 1 x 10⁷ PBMC was depleted using a mixture of anti-human CD4 and anti-human CD8 particles (BD Biosciences) [S3 Fig]. Whole PBMC, as well as those depleted of CD56 and CD4/CD8, were stained with monoclonal antibodies to CD56, CD4, CD8 and CD3 to measure the efficiency of depletion. Afterwards, ELISPOT assays were conducted using a commercial kit (ELISPOT Human IFN-γ or IL-2 ELISPOT Set; BD Biosciences, USA), as described elsewhere [26]. Briefly, whole or depleted PBMC, were seeded at a concentration of 4x10⁵ cells/well and stimulated with 10 µg/mL T. cruzi lysate from the Brazil strain or RPMI for 16–20 hr at 37°C and 5% CO2. Spot forming cells (SFCs) were automatically enumerated using ImmunoSpot analyzer (CTL). The mean number of spots in duplicate wells was obtained for each condition, and the number of specific IFN-γ and IL-2-secreting T-cells was calculated by subtracting the value of the wells containing media alone from the antigen-stimulated spot count. Responses were considered positive if (1) a minimum of 10 SFC/4 × 10⁵ PBMC were present per well and (2) this number was at least twice the value of wells with media alone [26].

Statistics

Normal distribution was assessed using the Shapiro–Wilk test. The Kruskal-Wallis test and analysis of variance were used for multiple comparisons. Changes in cytokine producing NK cells post-treatment were evaluated using principal component analysis (PCA). The correlations between variables was determined by a Spearman or Pearson test, as appropriate. Two-tailed P < 0.05 were considered statistically significant. Statistical analysis was conducted using Analytical Software Statistix 10.0 and Graphpad 10.4.1

Results

NK-cell phenotype according to the severity of chronic Chagas disease

Regardless of their clinical status, T. cruzi-infected subjects had decreased levels of CD56^bright and increased percentages of CD56^dim compared with seronegative subjects [S4 A and S4B Fig and S2 Table]. The NK-cell phenotype was evaluated based on the expression of the following markers: activating receptors (NKG2D and NKp46); inhibition (KIR2D); immaturity (CD127); differentiation (CD57); exhaustion (PD-1) and cytotoxicity (CD16) on CD56^bright and CD56^dim NK-cell subsets [15,27]. An unsupervised analysis was performed using the Phenograph tool, followed by FlowSOM clustering after concatenating all samples from all clinical groups. This identified 16 clusters of CD56^bright [Fig 1A] and 20 clusters of CD56^dim [Fig 1C] NK cells expressing one or more of the selected markers. Six of these clusters were found in CD56^bright [Fig 1B] and nine in CD56^dim [Fig 1D] NK cells, with a mean abundance greater than 2.5% and were selected for further analysis. S3 Table and S4 Table summarize the findings of the heat maps, which show the relative expression of each marker in each cluster, as well as their functional roles. Subsequently, the data were divided into clinical groups. It was found that, compared with patients with heart disease (groups G1 and G2/G3) and uninfected controls, subjects in the G0 group without cardiac alterations showed an increased percentage of CD56^bright NK cells with low expression of the activating receptor NKp46 and no expression of the cytotoxic receptor CD16 (cluster #4 in Fig 1B and S3 Table; Fig 2A and S5 Table), as well as a decreased percentage of CD56^bright NK cells with high expression of NKp46 and CD16 (cluster ≠5 in Fig 1B and S3 Table; Fig 2A, S5 Table). Conversely, subjects with mild (group G1) or advanced heart disease (group G2/G3) showed increased percentages of CD56^dim cells co-expressing the activating receptor NKG2D and the differentiation marker CD57 [cluster #1 in Fig 1D and S4 Table; Fig 2B and S5 Table], as well as the inhibitory receptor KIR2DL2 [cluster #4 in Fig 1D and S4 Table; Fig 2B, S5 Table], compared with uninfected subjects. Regardless the clinical stage, T. cruzi-infected individuals showed decreased percentages of CD56^dimNKG2D⁺CD16⁺ [cluster # 11 of Fig 1D and S4 table, Fig 2B, S5 table] However, a significant linear trend in the percentage of cluster # 11 was observed alongside increasing disease severity (P < 0.0001). Subjects in the G0 group exhibited decreased levels of CD56^dimNKp46⁺NKG2D⁺CD16⁺ [cluster # 18 of Fig 1D and S4 Table, Fig 2B, S5 Table] NK cells, than to those with severe heart disease or uninfected subjects.

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Fig 1. Unsupervised high-dimensional analysis of CD56⁺ NK-cell phenotype in subjects with chronic T. cruzi infection.

PBMC were stained with a panel of monoclonal antibodies specific for surface markers and adquired by flow cytometry. Phenograph followed by FlowSOM clustering algorithms was applied on PBMC samples of T. cruzi-infected subjects (G0, n = 11; G1, n = 7; G2-G3, n = 9), and uninfected subjects (n = 15) The percentages of the CD56^bright (A) and CD56^dim (C) clusters that are higher or lower than 2.5% are shown in white or grey, respectively. Hierarchical clustering heatmaps showing the expression of the indicated proteins in the clusters identified on pre-gated CD56^bright (B) or CD56^dim (D) NK cells.

https://doi.org/10.1371/journal.pntd.0014622.g001

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Fig 2. Unsupervised high-dimensional analysis of CD56⁺ NK-cell phenotype in T. cruzi infected subjects according to disease severity.

Phenograph followed by FlowSOM clustering algorithms was applied on PBMC samples (G0, n = 11; G1, n = 7; G2-G3, n = 9; uninfected controls, UI, n = 15). Percentages of individual CD56^bright (A) or CD56^dim (B) clusters. Expression of the mean fluorescence intensity (MFI) for individual surface markers (C-D). Data are presented as median with interquartile range (A and B) or box and whiskers with 10-90 percentile (C-D). Differences among groups were evaluated by ANOVA or the Kruskal–Wallis test followed by posttests. **** P < 0.0001, *** P < 0.001, ** P < 0.01, * P < 0.05.

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Analysis of mean fluorescence intensity of the different markers in each cluster showed that patients with more advanced heart disease exhibited higher expression of NKp46 in CD56^bright[Fig 2C, clusters #1, #4 of Fig 1B, S3 Table and S6 Table] and CD56^dim [Fig 2D, cluster #18 of Fig 1D and S4 Table] as well as CD16 in CD56^dim NK cells [Fig 2D, cluster # 6 of Fig 1D and S4 Table and S6 Table] compared with those with no signs of heart disease. The manual gating strategy confirmed that, compared to subjects with advanced heart disease [right panel of S5 Fig], those with no or mild heart disease had decreased percentages of CD56^brightCD16⁺NKp46⁺CD57^—[Fig 3A, left panel of S5 Fig and S7 Table] and CD56^dimCD16⁺NKp46⁺NKG2D⁺CD57^— NK cells [Fig 3C, right panel of S5 Fig and S7 Table] as well as lower NKp46 expression [Fig 3B]

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Fig 3. Manual gating strategy for the identification of NK cells with activating and cytotoxic phenotype.

PBMC from T. cruzi-infected subjects (G0, n = 16; G1, n = 13; G2-G3, n = 9) and uninfected controls (UI, n = 15) were stained with a panel of monoclonal antibodies specific for NK cell surface markers and adquired by flow cytometry. Manual gating was used to select CD56^brightCD16^— (A) and CD56^dimCD16⁺ (C) NK cells, which express NKp46/NKG2D but not CD57. (B) Expression of the mean fluorescence intensity (MFI) of NkP46 in A. Data in A and C are presented as median with interquartile range and as box and whiskers in B. Differences among groups were evaluated by ANOVA or the Kruskal–Wallis test followed by posttests. ** P < 0.01, * P < 0.05.

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NK-cell function according to the severity of chronic Chagas disease

We then evaluated the function of NK cells in the different clinical groups using Boolean gating analysis after stimulation with PMA/ionomycin which enabled us to categorize cytokine-producing NK cells into 31 different subsets, each consisting of one to five cytokine-producing populations. Subjects with more advanced heart disease (groups G1 and G2–G3) showed higher percentages of NK cells exhibiting four or three functions, compared to subjects without cardiac disease (group G0) [Fig 4A]. NK cells with two, three or four functions in subjects infected with T. cruzi and suffering from mild or advanced heart disease were found to be deprived of IL-10-producing cells, compared with subjects infected with T. cruzi but not suffering from heart disease, and uninfected subjects [see arches in Fig 4A]. Significant differences were found in five of the 31 possible co-expression profiles when the contribution of each subset to the total NK-cell response was analyzed individually. Patients with cardiomyopathy (groups G1 and G2-G3) had lower percentages of CD56⁺granzyme B⁺IL-10⁺, monofunctional CD56⁺IL-10⁺ and monofunctional CD56⁺CD107a⁺ NK cells than subjects with no signs of heart disease or infection [Fig 4B and S8 Table]. Conversely, NK cells in patients with cardiomyopathy were enriched in CD56⁺CD107⁺granzyme B⁺TNF-α⁺ and CD56⁺CD107⁺ TNF-α⁺ NK cells [Fig 4B and S8 Table]. Of note, the percentage of monofunctional CD56⁺IL-10⁺ cells was found to be inversely correlated with the levels of cluster #11 of CD56dim NK cells, which express NKp46 and NKG2D (R = −0.44, P = 0.04), while CD56⁺ cells with dual function (granzyme B⁺IL-10⁺) were found to be inversely correlated with CD56dim cells expressing NKG2D (R = −0.47, P = 0.03).

NK-cell function after treatment with benznidazole

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Fig 4. NK-cell function in T. cruzi-infected subjects with different degrees of heart disease.

PBMC of T. cruzi-infected subjects in the G0 (n = 16), G1 (n = 13), G2/G3 (n = 9) clinical groups, as well as from uninfected subjects (UI, n = 15), were stimulated with PMA/ionomycin for 4 h and analyzed by flow cytometry for intracellular expression of CD107a, granzyme B, IFN-γ, IL-10 and TNF-α. A. Lymphocytes were gated based on forward scatter (FSC) and side scatter (SSC) parameters, and analysed for viable CD14^—CD19^—CD3^—CD56⁺ cells versus each marker using Zombie Aqua. The coexpression profiles of one to five functions were identified using the Boolean gating function of the FlowJo software. The contribution of each molecule-producing subset to the total NK-cell response was assessed in donors with positive responses in the intracellular staining assay as indicated in the Materials and Methods. Then, the average for each combination out of 31 possible combinations was calculated. (A) The data are summarized by the pie charts, in which each slice of the pie represents the fraction of the total response that consists of CD56⁺ T-cells positive for one to five functions. The arches indicate the proportion of CD56⁺ T-cells that express IL-10 in each slice of the pie. (B) The bars indicate the percentage of the total response contributed by CD56⁺ NK cells with a given co-expression profile. The results are presented as box and whiskers with 10-90 percentile. Only the cytokine subsets showing significant differences between clinical groups out of the 31 analyzed are depicted. The values obtained in unstimulated samples were subtracted. Differences among groups were assessed using a Kruskal–Wallis test, with p values adjusted for multiple comparisons using Dunn's posttest. *. **** P < 0.0001, *** P < 0.001, ** P < 0.01, * P < 0.05.

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PCA analysis was conducted to evaluate differences in NK-cell cytokine expression profiles in chronic Chagas disease patients before and after treatment with benznidazole. NK-cell cytokine expression cytokine profiles in PC1 could distinguish before and after treatment status in subjects with declining T. cruzi-specific antibodies after benznidazole treatment [Fig 5A]. The PC1, PC2 loading factors indicate that in this analysis differential expression of CD107⁺granzyme B⁺IFN-γ^—IL-10^—TNF- α⁺, CD107⁺granzyme B^—IFN-γ^—IL-10^—TNF-α^—, CD107^—granzyme B⁺IFN-γ^—IL-10^—TNF-α⁺ and CD107^—granzyme B^—IFN-γ^—IL-10^—TNF-α⁺ strongly influences segregation of pre-treatment from post-treatment cytokine profile in these subjects (e.g., loading factor >0.4 or <−0.4). Conversely, PCA analysis of NK-cell cytokine expression profiles was unable to separate pre-treatment and post-treatment status in subjects with unchanged serological titers after treatment, albeit undetectable parasite DNA [Fig 5B]. The levels of T. cruzi-specific antibodies in subjects with declining serology post-treatment were inversely associated with monofunctional TNF-α-secreting NK cells [Fig 5C and 5D], whereas in subjects with unaltered serology post-treatment, they were positively associated with dual-function granzyme B⁺TNF-α⁺ NK cells [Fig 5E].

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Fig 5. Principal component analysis of NK-cell function in T. cruzi-infected subjects following benznidazole treatment.

PBMC were stimulated with PMA/ionomycin for 4 h and analyzed by flow cytometry for intracellular expression of CD107a, granzyme B, IFN-γ, IL-10 and TNF-α. Coexpression profiles with one to five functions using the Boolean gating function of FlowJo software. The contribution of each molecule-producing subset to the total NK-cell response was assessed in donors with positive responses in the intracellular staining assay as indicated in the Materials and Methods. Then, the average for each combination was calculated. The values obtained in unstimulated samples were subtracted. Following log transformation, the principal components were extracted with eigenvalues of 1.0. Factor loadings >0, 4 or <-0.4 were considered as influential mediators (filled symbols). NK cell functional profiles plotted based on the first 2 extracted principal components PC1 and PC2 prior to treatment (circle symbols) or following 48 months post-treatment with benznidazole (triangle symbols). T. cruzi-infected subjects with declining (A, n = 8) and or unchanged (B, n = 5) T. cruzi-specific antibodies following 48 months post-treatment. The Spearman test was applied to assess the correlation between the percentages of monofunctional and polyfunctional CD56⁺CD3-CD107-GB-IFN-gamma-IL-10-TNF-alpha⁺^— cells and T. cruzi-specific antibody levels measured by ELISA (C and E) and hemagglutination (D) in subjects with declining (C and D) or unchanged (E) serology for T. cruzi infection posttreatment.

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Contribution of NK cells to the T-cell response specific for T. cruzi,

T-cell responses specific for T. cruzi in subjects with chronic Chagas disease are impaired in terms of both function and magnitude [24,28,29], but it remains unclear whether CD56⁺ (NK/NKT) cells may regulate these responses. To address this, the production of IFN-γ and IL-2 by PBMC from T. cruzi-infected subjects with no signs of cardiac disease was evaluated in response to a T. cruzi lysate, in the presence or absence of CD56⁺ cells. Due to the low frequencies of T. cruzi-specific T cells in the chronic phase, the ELISPOT technique was the most suitable method for addressing this question. The elimination of 85% of CD56⁺ cells, on average, [S2 Fig] resulted in a significant decrease in the number of T. cruzi-specific IFN-γ-producing cells [Fig 6]. To rule out the possibility that the decrease was due to IFN-γ production by CD56⁺ cells, an enriched sample of CD56⁺ cells, obtained after the depletion of CD4⁺ and CD8⁺ T lymphocytes (with average depletions of 90% and 82%, respectively; [Fig 3), was stimulated with T. cruzi lysate, and the number of IFN-γ- and IL-2-producing cells was measured. Enrichment of the CD56⁺ sample was found to be skewed towards NK cells, and the number of IFN-γ-producing cells was found to be below the positivity cut-off level for the ELISPOT technique [Fig 6]. Although the levels were lower than IFN-γ, the production of T. cruzi-specific IL-2 also decreased in the absence of CD56⁺ cells [Fig 6].

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Fig 6. No. of interferon IFN-γ-secreting cells in response to T. cruzi lysate before and after depletion of CD56⁺ NK cells.

Whole PBMC, CD56-depleted PBMC or double CD4 and CD8 depleted PBMC using magnetic beads were seeded at a concentration of 4x10⁵ cells/well and stimulated with 10 mg/mL T. cruzi lysate from the Brazil strain for 16–20 hours. Each point represents the mean number of spots in duplicate wells for each patient and experimental condition, connected by a line.* P < 0.05,**P < 0.01, ***, P < 0.001.

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Discussion

Here, we demonstrate distinctive phenotypic and functional signatures in NK cells from different chronically T. cruzi-infected patient groups. The downregulation of activating receptors in NK cells of subjects infected with T. cruzi without signs of heart disease contrasts with the profile observed in NK cells of subjects with heart disease, which are enriched in cells expressing activating, cytotoxic and differentiation NK receptors, alongside low IL-10 production and polyfunctional NK cells skewed towards cytotoxic capacity. In addition, a decline in T. cruzi-specific antibody levels following benznidazole treatment was associated with an increase in monofunctional NK cells.

The induction and potency of NK-cell responses depend on their activation state, which is regulated by signals transmitted through activating and inhibitory receptors. Early after infection, the inflammatory response may lead to the overexpression of activating receptors on NK cells or their ligands on target cells [30] positively modulating dendritic cell function and secreting cytokines that promote Th1 cell responses. The chronic engagement of NK receptor ligands by NK cells may result in the modulation of activating receptors, thereby limiting NK-cell cytotoxic potential. Several mechanisms have been described, such as downregulation of activating receptors [31–35], downregulation of activating receptor ligands [36] and shedding of the activating receptors themselves [37,38]. The down-modulation of activating NK-cell receptors may depend not only on the nature of the ligand and the length of receptor stimulation, but also on the concurrent action of cytokines. TGF-β and IL-10 have been shown to decrease the expression of NKG2D and NKp30 [32,39,40]. Therefore, it can be reasoned that, in subjects infected with T. cruzi who show no signs of heart disease, NK-cell function may be balanced by the downregulation of activating receptors and IL-10 production. Herein, we have demonstrated that NK cells in T. cruzi-infected individuals without heart disease exhibit an increased presence of IL-10-producing NK cells.

Due to the prolonged nature of chronic T. cruzi infection, it is likely that the downregulation of activating receptors and IL-10 production is disrupted. This means that NK cells become dependent on direct contact with target cells for activation and subsequent potent cytotoxicity, a hypothesis that is consistent with our findings [41,42]. Other studies have shown a positive correlation between IL-10 and IFN-γ levels in the serum of subjects infected with T. cruzi without heart disease, whereas this correlation was not observed in patients with advanced cardiomyopathy. [43]. Overall, the NK cells of symptomatic patients are not exhausted, but rather unregulated.

We have demonstrated that, in patients with more advanced heart disease, T cells lose the ability to regulate IL-7R components [44,45], which is associated with a decrease in T. cruzi-specific IFN-γ-producing T cells [24,45]. This raises the question of whether, as with other chronic infections, NK cells are also involved in impairing parasite-specific T cells in chronic Chagas disease [13]. Infection with a virulent T. cruzi strain has been shown to alter NK cell-mediated regulation of the adaptive immune response induced by dendritic cells in an experimental infection in mice [46]. Studies performed on subjects with chronic T. cruzi infection support that NK cells not only have a regulatory function [47,48], but also increased expression of genes associated with cytotoxic and apoptotic responses of these cells was associated with heart disease [49,50]. A recent study supports that NK CD56^dim cells are highly found in the left ventricle of patients with idiopathic dilated cardiomyopathy associated to high expressions of granzyme B and other genes related with cytotoxicity [51]. However, other studies have shown that NK cells might limit cardiac inflammation and fibrosis [52]. In the present study, NK cells in subjects without heart disease appeared to positively regulate T. cruzi-specific T cell responses, as evidenced by the decrease in T. cruzi-specific IFN-γ- and IL-2-producing cells following CD56 depletion in this patient group.

Although CD56⁺ cell depletion was incomplete, we demonstrated that, following the depletion of CD4⁺ and CD8⁺ cells, samples enriched in CD56⁺ cells did not produce IFN-γ in response to T. cruzi antigens. Therefore, T cells were the primary source of IFN-γ-producing cells, as previously reported [24]. It is more likely that NK-antigen presenting cell cross-talk and cytokine-dependent mechanisms (e.g., IL-12/IL-18) mediate NK-cell activation, which in turn promotes parasite-specific T-cell responses [41,42]. Several mechanisms by which NK cells promote T-cell responses have been described, involving co-stimulatory molecules, cytokine secretion, and improved antigen presentation [41,42]. In addition to NK cells other immunoregulatory mechanisms may shape T-cell responses in individuals without heart disease, as high levels of Tregs and IL-10-producing CD4⁺ T cells have been observed in this patient group compared to those with advanced cardiomyopathy [53,54]. Since CD56-depletion did not discriminate between NK and NKT cells and despite NKT cells being a minor cell subset, we cannot rule out a positive effect of NKT cells on T. cruzi-specific T-cell responses [55]. However, direct functional validation through NK-T cell interaction assays will further confirm the effect of NK cells on parasite-specific T-cell function.

Treatment with benznidazole modulates NK-cell function, with declining T. cruzi-specific antibodies associated with monofunctional TNF-α-producing NK cells. This supports the idea that a more quiescent NK-cell function is induced upon T. cruzi clearance. These results are consistent with studies in adult subjects showing that the function of memory CD4⁺ T cells improves after benznidazole treatment [56,57], alongside a decline in inflammatory cytokines [44,57].

One limitation of the study is the small number of samples in the cardiac disease and treatment groups. The G2/G3 also has a higher proportion of male subjects than female subjects. Accordingly, cardiomyopathy in the chronic phase of T. cruzi infection is more frequently observed in males while females show slower progression [58]. Therefore, gender imbalance may be a potential confounding factor that could be addressed in future studies with larger sample sizes. The findings of this study may have therapeutic implications, as regulating inflammation could strike a balance between clearing infections and causing tissue damage. This may be particularly important for older patients, who may have additional health conditions such as atherosclerosis and coronary artery disease.

Supporting information

S1 Table. Antibodies used for surface and intracellular staining assays by flow cytometry.

https://doi.org/10.1371/journal.pntd.0014622.s001

(DOCX)

S2 Table. The frequency of NK-cell subsets in subjects with chronic Chagas disease.

PBMC samples from T. cruzi infected subjects with no signs (G0, n = 15), with mild (G1, n = 13) or severe (G2-G3, n = 9) heart disease and uninfected controls (UN, n = 15) were stained with a panel of monoclonal antibodies specific for NK cells as described in Material and Methods and analyzed by flow cytometry. The frequency of CD56^brightCD16^+/— and CD56^dimCD16^+/— NK-cell subsets as a proportion of total NK cells are shown Differences among groups were assessed using a Kruskal‒Wallis test or ANOVA, with P values adjusted for multiple comparisons using Dunn’s or Holm‒Sidak posttest.

https://doi.org/10.1371/journal.pntd.0014622.s002

(DOCX)

S3 Table. The phenotype and function of CD56^bright clusters identified by Phenograph and FlowSOM algorithm in subjects with chronic Chagas disease.

Description of each cluster's function based on the expression (+) or non-expression (-) patterns of different markers.

https://doi.org/10.1371/journal.pntd.0014622.s003

(DOCX)

S4 Table. The phenotype and function of CD56^dim clusters identified by Phenograph and FlowSOM algorithm in subjects with chronic Chagas disease.

Description of each cluster's function based on the expression (+) or non-expression (-) patterns of different markers.

https://doi.org/10.1371/journal.pntd.0014622.s004

(DOCX)

S5 Table. Percentages of individual CD56^bright and CD56^dim clusters identified by unsupervised high-dimensional analysis.

Phenograph followed by FlowSOM clustering algorithms was applied on PBMC samples (G0, n = 11; G1, n = 7; G2-G3, n = 9; uninfected controls, UI, n = 15).Data are show as median percentages and range in each group of CD56^bright or CD56^dim clusters. Differences among groups were evaluated by ANOVA or the Kruskal–Wallis test followed by posttests.

https://doi.org/10.1371/journal.pntd.0014622.s005

(DOCX)

S6 Table. Expression of the mean fluorescence intensity (MFI) for individual surface markers of the indicated cluster identified by unsupervised high-dimensional analysis.

Phenograph followed by FlowSOM clustering algorithms was applied on PBMC samples (G0, n = 11; G1, n = 7; G2-G3, n = 9; uninfected controls, UI, n = 15). Data are show as median (range) expression of the mean fluorescence intensity (MFI) for individual surface markers. Differences among groups were evaluated by ANOVA or the Kruskal–Wallis test followed by posttests.

https://doi.org/10.1371/journal.pntd.0014622.s006

(DOCX)

S7 Table. Manual gating strategy for the identification of NK cells with activating and cytotoxic phenotype.

PBMC from T. cruzi-infected subjects (G0, n = 16; G1, n = 13; G2-G3, n = 9) and uninfected controls (UI, n = 15) were stained with a panel of monoclonal antibodies specific for NK cell surface markers and adquired by flow cytometry. Manual gating was used to select CD56^brightCD16^—and CD56^dimCD16⁺ NK cells, which express NKp46/NKG2D but not CD57. Data are presented as median (range). Differences among groups were evaluated by ANOVA or the Kruskal–Wallis test followed by posttests.

https://doi.org/10.1371/journal.pntd.0014622.s007

(DOCX)

S8 Table. Percentage of the total response contributed by CD56⁺ NK cells with given co-expression profile in subjects chronically infected with T. cruzi.

PBMC of T. cruzi-infected subjects in the G0 (n = 16), G1 (n = 13), G2/G3 (n = 9) clinical groups, as well as from uninfected subjects (UI, n = 15), were stimulated with PMA/ionomycin for 4 h and analyzed by flow cytometry for intracellular expression of CD107a, granzyme B, IFN-γ, IL-10 and TNF-α. The data is show as median % (range) of the total response contributed by CD56⁺ NK cells with a given co-expression profile. Differences among groups were assessed using a Kruskal–Wallis test, with p values adjusted for multiple comparisons using Dunn's posttest.

https://doi.org/10.1371/journal.pntd.0014622.s008

(DOCX)

S1 Fig. Gating strategy for NK cells in a representative donor.

PBMC were stained for Zombie Aqua fixable viability stain and a combination of monoclonal antibodies anti-CD3 PerCP, anti-CD14 APC-Cy7, anti-CD16 BV785, CD19 APC-Cy7 and anti-CD56 BV605 and analyzed by flow cytometry. Lymphocytes were gated based on forward scatter area and side scatter area parameters, followed by forward scatter area vs. forward scatter height parameters and side scatter area vs. side scatter weight for doublet discrimination (single cells). Subsequent analyses were performed on viable (Zombie Aqua^—) and CD14^—CD19^—CD3^—CD56⁺ cells to identify CD56^brightCD16^+/— and CD56^dimCD16^+/— NK cells.

https://doi.org/10.1371/journal.pntd.0014622.s009

(DOCX)

S2 Fig. Depletion of human CD56⁺ NK cells from PBMC derived from a T. cruzi infected donor.

The PBMC were labelled with BD IMag anti-Human CD56 magnetic particles, separated using the BD IMag cell separation magnet and the negative (CD56^—) fraction was collected. The process was repeated, after which the whole PBMC and the negative fractions of the first and second depletion steps were stained with anti-human CD56. The percentage of CD56⁺ cells is shown.

https://doi.org/10.1371/journal.pntd.0014622.s010

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S3 Fig. Human CD4⁺ and CD8⁺ T cells were depleted from peripheral blood PBMC derived from one T. cruzi-infected donor.

The PBMC were labelled with a mixture of BD IMag anti-human CD4 and CD8 magnetic particles, separated using a BD IMag cell separation magnet and the negative (CD4^— and CD8^—) fractions were collected. The process was repeated, after which the whole PBMC and the negative fractions of the first and second depletion steps were stained with anti-human monoclonal antibodies specific for CD4, CD8 and CD3. The percentages of CD56⁺CD3^—, CD56⁺CD3⁺, CD4⁺CD3⁺ and CD8⁺CD3⁺ cells are displayed. The numbers in brackets indicate the percentage depletion of the corresponding cell population.

https://doi.org/10.1371/journal.pntd.0014622.s011

(DOCX)

S4 Fig. The frequency of NK-cell subsets in subjects with chronic Chagas disease.

PBMC samples from T. cruzi infected subjects with no signs (G0, n = 15), with mild (G1, n = 13) or severe (G2-G3, n = 9) heart disease and uninfected controls (UN, n = 15) were stained with a panel of monoclonal antibodies specific for NK cells as described in Material and Methods and analyzed by flow cytometry. The frequency of CD56^brightCD16^+/— (A) and CD56^dimCD16^+/— (B) NK-cell subsets as a proportion of total NK cells are shown. Each symbol represents the value for a single subject. The bars indicate the median values and the interquartile range. Differences among groups were assessed using a Kruskal‒Wallis test or ANOVA, with P values adjusted for multiple comparisons using Dunn’s or Holm‒Sidak posttest. **** P < 0.0001, ** P < 0.01 and * P < 0.05.

https://doi.org/10.1371/journal.pntd.0014622.s012

(DOCX)

S5 Fig. Representative manual gating strategy for the expression of NK activating receptors in subjects with chronic Chagas disease.

PBMC from one T. cruzi-infected subject without heart disease (i.e., G0 clinical group A–D) or with severe cardiomyopathy (i.e., G3 clinical group E–H) were stained with a panel of monoclonal antibodies specific for the NK-cell lineage in combination with markers of NK cell activation, differentiation, immune inhibition and exhaustion, and acquired by flow cytometry, as described in the Materials and Methods section. A. CD56^brightCD16^+/— and CD56^dimCD16^+/— NK cells were selected as described in S1B Fig. NKp46⁺CD57^— cells were selected from CD56^brightCD16⁺ cells. C. NKp46⁺CD57^— cells were selected from CD56^dimCD16⁺ cells followed by expression of NKG2D (D).The percentages of selected cell populations are shown.

https://doi.org/10.1371/journal.pntd.0014622.s013

(DOCX)

Acknowledgments

We thank the staff and patients of the Instituto Nacional de Parasitologia Dr Mario Fatala Chaben and the Hospital Eva Perón who provided blood samples; Placida Baz and Ariel Billordo from the INIGEM, University of Buenos Aires, CONICET for their technical assistance; the Diagnostic and Clinical Departments of the Instituto Nacional de Parasitología Dr. Mario Fatala Chaben, Argentina, for clinical evaluation and serological tests respectively; and Pablo Viotti for data management.

References

1. Hochberg NS, Montgomery SP. Chagas disease. Ann Intern Med. 2023;176:ITC17–32.
- View Article
- Google Scholar
2. World Health Organization. Chagas disease (also known as American trypanosomiasis). 2024. Accessed 2025 December 11.
3. Irish A, Whitman JD, Clark EH, Marcus R, Bern C. Updated estimates and mapping for prevalence of chagas disease among adults, United States. Emerg Infect Dis. 2022;28(7):1313–20. pmid:35731040
- View Article
- PubMed/NCBI
- Google Scholar
4. Gonzalez-Sanz M, Crespillo-Andújar C, Chamorro-Tojeiro S, Monge-Maillo B, Perez-Molina JA, Norman FF. Chagas disease in Europe. TropicalMed. 2023;8:513.
- View Article
- Google Scholar
5. Martin D, Tarleton R. Generation, specificity, and function of CD8 T cells in Trypanosoma cruzi infection. Immunological Reviews. 2004;201:304–17.
- View Article
- Google Scholar
6. Alvarez MG, Postan M, Weatherly DB, Albareda MC, Sidney J, Sette A, et al. HLA Class I-T cell epitopes from trans-sialidase proteins reveal functionally distinct subsets of CD8+ T cells in chronic Chagas disease. PLoS Negl Trop Dis. 2008;2(9):e288. pmid:18846233
- View Article
- PubMed/NCBI
- Google Scholar
7. Chen S, Zhu H, Jounaidi Y. Comprehensive snapshots of natural killer cells functions, signaling, molecular mechanisms and clinical utilization. Signal Transduct Target Ther. 2024;9(1):302. pmid:39511139
- View Article
- PubMed/NCBI
- Google Scholar
8. Maucourant C, Filipovic I, Ponzetta A, Aleman S, Cornillet M, Hertwig L, et al. Natural killer cell immunotypes related to COVID-19 disease severity. Sci Immunol. 2020;5(50):eabd6832. pmid:32826343
- View Article
- PubMed/NCBI
- Google Scholar
9. Jain A, Pasare C. Innate control of adaptive immunity: beyond the three-signal paradigm. J Immunol. 2017;198(10):3791–800. pmid:28483987
- View Article
- PubMed/NCBI
- Google Scholar
10. Cimpean M, Cooper MA. Metabolic regulation of NK cell antiviral functions during cytomegalovirus infection. J Leukoc Biol. 2023;113(5):525–34. pmid:36843434
- View Article
- PubMed/NCBI
- Google Scholar
11. Lenart M, Rutkowska-Zapała M, Siedlar M. NK-cell receptor modulation in viral infections. Clin Exp Immunol. 2024;217(2):151–8. pmid:38767592
- View Article
- PubMed/NCBI
- Google Scholar
12. Roe K. NK-cell exhaustion, B-cell exhaustion and T-cell exhaustion-the differences and similarities. Immunology. 2022;166(2):155–68. pmid:35266556
- View Article
- PubMed/NCBI
- Google Scholar
13. Ivanova DL, Krempels R, Denton SL, Fettel KD, Saltz GM, Rach D, et al. NK cells negatively regulate CD8 T cells to promote immune exhaustion and chronic Toxoplasma gondii infection. Front Cell Infect Microbiol. 2020;10:313. pmid:32733814
- View Article
- PubMed/NCBI
- Google Scholar
14. Gigley JP, Bhadra R, Moretto MM, Khan IA. T cell exhaustion in protozoan disease. Trends Parasitol. 2012;28(9):377–84. pmid:22832368
- View Article
- PubMed/NCBI
- Google Scholar
15. Elias MJ, Cesar G, Caputo MB, De Rissio AM, Alvarez MG, Lococo B, et al. Increased Natural Killer (NK)-cell cytotoxicity and Trypanosoma cruzi-specific memory B cells in subjects with discordant serology for Chagas disease. Biochim Biophys Acta Mol Basis Dis. 2024;1870(6):167237. pmid:38750768
- View Article
- PubMed/NCBI
- Google Scholar
16. Kuschnir E, Sgammini H, Castro R, Evequoz C, Ledesma R, Brunetto J. Valoración de la función cardíaca por angiografía radioisotópica, en pacientes con cardiopatía chagásica crónica. Arq Bras Cardiol. 1985;45:249–56.
- View Article
- Google Scholar
17. Viotti R, Vigliano C, Alvarez MG, Lococo B, Petti M, Bertocchi G, et al. Impact of aetiological treatment on conventional and multiplex serology in chronic Chagas disease. PLoS Negl Trop Dis. 2011;5(9):e1314. pmid:21909451
- View Article
- PubMed/NCBI
- Google Scholar
18. Viotti R, Vigliano C, Lococo B, Bertocchi G, Petti M, Alvarez MG, et al. Long-term cardiac outcomes of treating chronic Chagas disease with benznidazole versus no treatment: a nonrandomized trial. Ann Intern Med. 2006;144(10):724–34. pmid:16702588
- View Article
- PubMed/NCBI
- Google Scholar
19. Viotti R, Alarcón de Noya B, Araujo-Jorge T, Grijalva MJ, Guhl F, López MC, et al. Towards a paradigm shift in the treatment of chronic Chagas disease. Antimicrob Agents Chemother. 2014;58(2):635–9. pmid:24247135
- View Article
- PubMed/NCBI
- Google Scholar
20. Laucella SA, Mazliah DP, Bertocchi G, Alvarez MG, Cooley G, Viotti R, et al. Changes in Trypanosoma cruzi-specific immune responses after treatment: surrogate markers of treatment efficacy. Clin Infect Dis. 2009;49(11):1675–84. pmid:19877967
- View Article
- PubMed/NCBI
- Google Scholar
21. Cooley G, Etheridge RD, Boehlke C, Bundy B, Weatherly DB, Minning T, et al. High throughput selection of effective serodiagnostics for Trypanosoma cruzi infection. PLoS Negl Trop Dis. 2008;2(10):e316. pmid:18841200
- View Article
- PubMed/NCBI
- Google Scholar
22. Cura CI, Ramírez JC, Rodríguez M, Lopez-Albízu C, Irazu L, Scollo K, et al. Comparative study and analytical verification of PCR methods for the diagnosis of congenital chagas disease. J Mol Diagn. 2017;19(5):673–81. pmid:28727985
- View Article
- PubMed/NCBI
- Google Scholar
23. Lopez-Albizu C, Cura CI, Ramirez JC, Peyran P, Benchetrit A, Danesi E, et al. Congenital Chagas disease: a cohort study to assess molecular diagnostic methods at the Chagas disease national reference center of Argentina. PLoS Negl Trop Dis. 2025;19(1):e0012785. pmid:39792926
- View Article
- PubMed/NCBI
- Google Scholar
24. Laucella SA, Postan M, Martin D, Hubby Fralish B, Albareda MC, Alvarez MG, et al. Frequency of interferon- gamma -producing T cells specific for Trypanosoma cruzi inversely correlates with disease severity in chronic human Chagas disease. J Infect Dis. 2004;189(5):909–18. pmid:14976609
- View Article
- PubMed/NCBI
- Google Scholar
25. Feng T, Liao X, Yang X, Yang C, Lin F, Guo Y, et al. A shift toward inhibitory receptors and impaired effector functions on NK cells contribute to immunosuppression during sepsis. J Leukoc Biol. 2020;107(1):57–67. pmid:31385383
- View Article
- PubMed/NCBI
- Google Scholar
26. Castro Eiro MD, Alvarez MG, Cooley G, Viotti RJ, Bertocchi GL, Lococo B, et al. The significance of discordant serology in chagas disease: enhanced T-cell immunity to Trypanosoma cruzi in serodiscordant subjects. Front Immunol. 2017;8:1141. pmid:28966620
- View Article
- PubMed/NCBI
- Google Scholar
27. Abel AM, Yang C, Thakar MS, Malarkannan S. Natural killer cells: development, maturation, and clinical utilization. Front Immunol. 2018;9:1869.
- View Article
- Google Scholar
28. Albareda MC, Laucella SA, Alvarez MG, Armenti AH, Bertochi G, Tarleton RL, et al. Trypanosoma cruzi modulates the profile of memory CD8+ T cells in chronic Chagas’ disease patients. Int Immunol. 2006;18(3):465–71. pmid:16431876
- View Article
- PubMed/NCBI
- Google Scholar
29. Egui A, Thomas MC, Carrilero B, Segovia M, Alonso C, Marañón C, et al. Differential phenotypic and functional profiles of TcCA-2 -specific cytotoxic CD8+ T cells in the asymptomatic versus cardiac phase in Chagasic patients. PLoS One. 2015;10(3):e0122115. pmid:25816096
- View Article
- PubMed/NCBI
- Google Scholar
30. Mariuzza RA, Singh P, Karade SS, Shahid S, Sharma VK. Recognition of self and viral ligands by NK cell receptors. Immunol Rev. 2025;329(1):e13435. pmid:39748148
- View Article
- PubMed/NCBI
- Google Scholar
31. Pallmer K, Oxenius A. Recognition and regulation of T cells by NK cells. Front Immunol. 2016;7:251. pmid:27446081
- View Article
- PubMed/NCBI
- Google Scholar
32. Molfetta R, Zingoni A, Santoni A, Paolini R. Post-translational mechanisms regulating NK cell activating receptors and their ligands in cancer: potential targets for therapeutic intervention. Front Immunol. 2019;10:2557. pmid:31736972
- View Article
- PubMed/NCBI
- Google Scholar
33. Wilk AJ, Lee MJ, Wei B, Parks B, Pi R, Martínez-Colón GJ, et al. Multi-omic profiling reveals widespread dysregulation of innate immunity and hematopoiesis in COVID-19. J Exp Med. 2021;218(8):e20210582. pmid:34128959
- View Article
- PubMed/NCBI
- Google Scholar
34. Castriconi R, Cantoni C, Della Chiesa M, Vitale M, Marcenaro E, Conte R, et al. Transforming growth factor beta 1 inhibits expression of NKp30 and NKG2D receptors: consequences for the NK-mediated killing of dendritic cells. Proc Natl Acad Sci U S A. 2003;100(7):4120–5. pmid:12646700
- View Article
- PubMed/NCBI
- Google Scholar
35. Sun C, Fu B, Gao Y, Liao X, Sun R, Tian Z, et al. TGF-β1 down-regulation of NKG2D/DAP10 and 2B4/SAP expression on human NK cells contributes to HBV persistence. PLoS Pathog. 2012;8(3):e1002594. pmid:22438812
- View Article
- PubMed/NCBI
- Google Scholar
36. Lee G, Schauner R, Burke J, Borocz J, Vasana S, Sobieraj L, et al. NK cells from COVID-19 positive patients exhibit enhanced cytotoxic activity upon NKG2A and KIR2DL1 blockade. Front Immunol. 2023;14:1022890. pmid:37483595
- View Article
- PubMed/NCBI
- Google Scholar
37. Valayer A, Brea D, Lajoie L, Avezard L, Combes-Soia L, Labas V, et al. Neutrophils can disarm NK cell response through cleavage of NKp46. J Leukoc Biol. 2017;101(1):253–9. pmid:27587403
- View Article
- PubMed/NCBI
- Google Scholar
38. Peruzzi G, Femnou L, Gil-Krzewska A, Borrego F, Weck J, Krzewski K, et al. Membrane-type 6 matrix metalloproteinase regulates the activation-induced downmodulation of CD16 in human primary NK cells. J Immunol. 2013;191(4):1883–94. pmid:23851692
- View Article
- PubMed/NCBI
- Google Scholar
39. Park YP, Choi S-C, Kiesler P, Gil-Krzewska A, Borrego F, Weck J, et al. Complex regulation of human NKG2D-DAP10 cell surface expression: opposing roles of the γc cytokines and TGF-β1. Blood. 2011;118(11):3019–27. pmid:21816829
- View Article
- PubMed/NCBI
- Google Scholar
40. Yang H-L, Zhou W-J, Chang K-K, Mei J, Huang L-Q, Wang M-Y, et al. The crosstalk between endometrial stromal cells and macrophages impairs cytotoxicity of NK cells in endometriosis by secreting IL-10 and TGF-β. Reproduction. 2017;154(6):815–25. pmid:28971893
- View Article
- PubMed/NCBI
- Google Scholar
41. Crouse J, Xu HC, Lang PA, Oxenius A. NK cells regulating T cell responses: mechanisms and outcome. Trends Immunol. 2015;36(1):49–58. pmid:25432489
- View Article
- PubMed/NCBI
- Google Scholar
42. Chen S, Zhu H, Jounaidi Y. Comprehensive snapshots of natural killer cells functions, signaling, molecular mechanisms and clinical utilization. Signal Transduct Target Ther. 2024;9(1):302. pmid:39511139
- View Article
- PubMed/NCBI
- Google Scholar
43. D’Avila DA, Guedes PMM, Castro AM, Gontijo ED, Chiari E, Galvão LMC. Immunological imbalance between IFN-gamma and IL-10 levels in the sera of patients with the cardiac form of Chagas disease. Mem Inst Oswaldo Cruz. 2009;104(1):100–5. pmid:19274383
- View Article
- PubMed/NCBI
- Google Scholar
44. Albareda MC, Perez-Mazliah D, Natale MA, Castro-Eiro M, Alvarez MG, Viotti R, et al. Perturbed T cell IL-7 receptor signaling in chronic Chagas disease. J Immunol. 2015;194(8):3883–9. pmid:25769928
- View Article
- PubMed/NCBI
- Google Scholar
45. Natale MA, Cesar G, Alvarez MG, Castro Eiro MD, Lococo B, Bertocchi G, et al. Trypanosoma cruzi-specific IFN-γ-producing cells in chronic Chagas disease associate with a functional IL-7/IL-7R axis. PLoS Negl Trop Dis. 2018;12(12):e0006998. pmid:30517089
- View Article
- PubMed/NCBI
- Google Scholar
46. Batalla EI, Pino Martínez AM, Poncini CV, Duffy T, Schijman AG, González Cappa SM, et al. Impairment in natural killer cells editing of immature dendritic cells by infection with a virulent Trypanosoma cruzi population. J Innate Immun. 2013;5(5):494–504. pmid:23689360
- View Article
- PubMed/NCBI
- Google Scholar
47. Vitelli‐Avelar DM, Sathler‐Avelar R, Dias JCP, Pascoal VPM, Teixeira‐Carvalho A, Lage PS. Chagasic patients with indeterminate clinical form of the disease have high frequencies of circulating CD3 CD16– CD56 natural killer T cells and CD4 CD25High regulatory T lymphocytes. Scand J Immunol. 2005;62:297–308.
- View Article
- Google Scholar
48. Gómez I, López MC, Egui A, Palacios G, Carrilero B, Benítez C, et al. Differential expression profile of genes involved in the immune response associated to progression of chronic Chagas disease. PLoS Negl Trop Dis. 2023;17(7):e0011474. pmid:37440604
- View Article
- PubMed/NCBI
- Google Scholar
49. Ferreira LRP, Ferreira FM, Nakaya HI, Deng X, Cândido D da S, de Oliveira LC, et al. Blood gene signatures of chagas cardiomyopathy with or without ventricular dysfunction. J Infect Dis. 2017;215(3):387–95. pmid:28003350
- View Article
- PubMed/NCBI
- Google Scholar
50. Souza-Silva TG, Figueiredo A, Morais KLP, Apostólico J, Pantaleao A, Mutarelli A, et al. Single-Cell targeted transcriptomics reveals subset-specific immune signatures differentiating asymptomatic and cardiac patients with chronic chagas disease. J Infect Dis. 2025;232(6):1402–12. pmid:40434116
- View Article
- PubMed/NCBI
- Google Scholar
51. He S, Li C, Lu M, Lin F, Hu S, Zhang J, et al. Comprehensive analysis of scRNA-seq and bulk RNA-seq reveals the non-cardiomyocytes heterogeneity and novel cell populations in dilated cardiomyopathy. J Transl Med. 2025;23(1):17. pmid:39762897
- View Article
- PubMed/NCBI
- Google Scholar
52. Ong S, Ligons DL, Barin JG, Wu L, Talor MV, Diny N, et al. Natural killer cells limit cardiac inflammation and fibrosis by halting eosinophil infiltration. Am J Pathol. 2015;185(3):847–61. pmid:25622543
- View Article
- PubMed/NCBI
- Google Scholar
53. Dutra WO, Menezes CAS, Magalhães LMD, Gollob KJ. Immunoregulatory networks in human Chagas disease. Parasite Immunol. 2014;36(8):377–87. pmid:24611805
- View Article
- PubMed/NCBI
- Google Scholar
54. Sathler-Avelar R, Vitelli-Avelar DM, Elói-Santos SM, Gontijo ED, Teixeira-Carvalho A, Martins-Filho OA. Blood leukocytes from benznidazole-treated indeterminate chagas disease patients display an overall type-1-modulated cytokine profile upon short-term in vitro stimulation with Trypanosoma cruzi antigens. BMC Infect Dis. 2012;12:123. pmid:22625224
- View Article
- PubMed/NCBI
- Google Scholar
55. Tognarelli EI, Gutiérrez-Vera C, Palacios PA, Pasten-Ferrada IA, Aguirre-Muñoz F, Cornejo DA. Natural killer T cell diversity and immunotherapy. Cancers. 2023;15:5737.
- View Article
- Google Scholar
56. Castro Eiro MD, Natale MA, Alvarez MG, Shen H, Viotti R, Lococo B, et al. Reduced Trypanosoma cruzi-specific humoral response and enhanced T cell immunity after treatment interruption with benznidazole in chronic Chagas disease. J Antimicrob Chemother. 2021;76(6):1580–92. pmid:33693664
- View Article
- PubMed/NCBI
- Google Scholar
57. Pérez-Antón E, Egui A, Thomas MC, Puerta CJ, González JM, Cuéllar A, et al. Impact of benznidazole treatment on the functional response of Trypanosoma cruzi antigen-specific CD4+CD8+ T cells in chronic Chagas disease patients. PLoS Negl Trop Dis. 2018;12(5):e0006480. pmid:29750791
- View Article
- PubMed/NCBI
- Google Scholar
58. de Padua Mansur A, Cunha-Neto E, Bulgarelli Bestetti R, Brochet P, Chevillard C, Pereira-Barretto AC. Curr Heart Fail Rep. 2025;22:27.
- View Article
- Google Scholar

[ref1] 1. Hochberg NS, Montgomery SP. Chagas disease. Ann Intern Med. 2023;176:ITC17–32.
View Article
Google Scholar

[2] View Article

[3] Google Scholar

[ref2] 2. World Health Organization. Chagas disease (also known as American trypanosomiasis). 2024. Accessed 2025 December 11.

[ref3] 3. Irish A, Whitman JD, Clark EH, Marcus R, Bern C. Updated estimates and mapping for prevalence of chagas disease among adults, United States. Emerg Infect Dis. 2022;28(7):1313–20. pmid:35731040
View Article
PubMed/NCBI
Google Scholar

[6] View Article

[7] PubMed/NCBI

[8] Google Scholar

[ref4] 4. Gonzalez-Sanz M, Crespillo-Andújar C, Chamorro-Tojeiro S, Monge-Maillo B, Perez-Molina JA, Norman FF. Chagas disease in Europe. TropicalMed. 2023;8:513.
View Article
Google Scholar

[10] View Article

[11] Google Scholar

[ref5] 5. Martin D, Tarleton R. Generation, specificity, and function of CD8 T cells in Trypanosoma cruzi infection. Immunological Reviews. 2004;201:304–17.
View Article
Google Scholar

[13] View Article

[14] Google Scholar

[ref6] 6. Alvarez MG, Postan M, Weatherly DB, Albareda MC, Sidney J, Sette A, et al. HLA Class I-T cell epitopes from trans-sialidase proteins reveal functionally distinct subsets of CD8+ T cells in chronic Chagas disease. PLoS Negl Trop Dis. 2008;2(9):e288. pmid:18846233
View Article
PubMed/NCBI
Google Scholar

[16] View Article

[17] PubMed/NCBI

[18] Google Scholar

[ref7] 7. Chen S, Zhu H, Jounaidi Y. Comprehensive snapshots of natural killer cells functions, signaling, molecular mechanisms and clinical utilization. Signal Transduct Target Ther. 2024;9(1):302. pmid:39511139
View Article
PubMed/NCBI
Google Scholar

[20] View Article

[21] PubMed/NCBI

[22] Google Scholar

[ref8] 8. Maucourant C, Filipovic I, Ponzetta A, Aleman S, Cornillet M, Hertwig L, et al. Natural killer cell immunotypes related to COVID-19 disease severity. Sci Immunol. 2020;5(50):eabd6832. pmid:32826343
View Article
PubMed/NCBI
Google Scholar

[24] View Article

[25] PubMed/NCBI

[26] Google Scholar

[ref9] 9. Jain A, Pasare C. Innate control of adaptive immunity: beyond the three-signal paradigm. J Immunol. 2017;198(10):3791–800. pmid:28483987
View Article
PubMed/NCBI
Google Scholar

[28] View Article

[29] PubMed/NCBI

[30] Google Scholar

[ref10] 10. Cimpean M, Cooper MA. Metabolic regulation of NK cell antiviral functions during cytomegalovirus infection. J Leukoc Biol. 2023;113(5):525–34. pmid:36843434
View Article
PubMed/NCBI
Google Scholar

[32] View Article

[33] PubMed/NCBI

[34] Google Scholar

[ref11] 11. Lenart M, Rutkowska-Zapała M, Siedlar M. NK-cell receptor modulation in viral infections. Clin Exp Immunol. 2024;217(2):151–8. pmid:38767592
View Article
PubMed/NCBI
Google Scholar

[36] View Article

[37] PubMed/NCBI

[38] Google Scholar

[ref12] 12. Roe K. NK-cell exhaustion, B-cell exhaustion and T-cell exhaustion-the differences and similarities. Immunology. 2022;166(2):155–68. pmid:35266556
View Article
PubMed/NCBI
Google Scholar

[40] View Article

[41] PubMed/NCBI

[42] Google Scholar

[ref13] 13. Ivanova DL, Krempels R, Denton SL, Fettel KD, Saltz GM, Rach D, et al. NK cells negatively regulate CD8 T cells to promote immune exhaustion and chronic Toxoplasma gondii infection. Front Cell Infect Microbiol. 2020;10:313. pmid:32733814
View Article
PubMed/NCBI
Google Scholar

[44] View Article

[45] PubMed/NCBI

[46] Google Scholar

[ref14] 14. Gigley JP, Bhadra R, Moretto MM, Khan IA. T cell exhaustion in protozoan disease. Trends Parasitol. 2012;28(9):377–84. pmid:22832368
View Article
PubMed/NCBI
Google Scholar

[48] View Article

[49] PubMed/NCBI

[50] Google Scholar

[ref15] 15. Elias MJ, Cesar G, Caputo MB, De Rissio AM, Alvarez MG, Lococo B, et al. Increased Natural Killer (NK)-cell cytotoxicity and Trypanosoma cruzi-specific memory B cells in subjects with discordant serology for Chagas disease. Biochim Biophys Acta Mol Basis Dis. 2024;1870(6):167237. pmid:38750768
View Article
PubMed/NCBI
Google Scholar

[52] View Article

[53] PubMed/NCBI

[54] Google Scholar

[ref16] 16. Kuschnir E, Sgammini H, Castro R, Evequoz C, Ledesma R, Brunetto J. Valoración de la función cardíaca por angiografía radioisotópica, en pacientes con cardiopatía chagásica crónica. Arq Bras Cardiol. 1985;45:249–56.
View Article
Google Scholar

[56] View Article

[57] Google Scholar

[ref17] 17. Viotti R, Vigliano C, Alvarez MG, Lococo B, Petti M, Bertocchi G, et al. Impact of aetiological treatment on conventional and multiplex serology in chronic Chagas disease. PLoS Negl Trop Dis. 2011;5(9):e1314. pmid:21909451
View Article
PubMed/NCBI
Google Scholar

[59] View Article

[60] PubMed/NCBI

[61] Google Scholar

[ref18] 18. Viotti R, Vigliano C, Lococo B, Bertocchi G, Petti M, Alvarez MG, et al. Long-term cardiac outcomes of treating chronic Chagas disease with benznidazole versus no treatment: a nonrandomized trial. Ann Intern Med. 2006;144(10):724–34. pmid:16702588
View Article
PubMed/NCBI
Google Scholar

[63] View Article

[64] PubMed/NCBI

[65] Google Scholar

[ref19] 19. Viotti R, Alarcón de Noya B, Araujo-Jorge T, Grijalva MJ, Guhl F, López MC, et al. Towards a paradigm shift in the treatment of chronic Chagas disease. Antimicrob Agents Chemother. 2014;58(2):635–9. pmid:24247135
View Article
PubMed/NCBI
Google Scholar

[67] View Article

[68] PubMed/NCBI

[69] Google Scholar

[ref20] 20. Laucella SA, Mazliah DP, Bertocchi G, Alvarez MG, Cooley G, Viotti R, et al. Changes in Trypanosoma cruzi-specific immune responses after treatment: surrogate markers of treatment efficacy. Clin Infect Dis. 2009;49(11):1675–84. pmid:19877967
View Article
PubMed/NCBI
Google Scholar

[71] View Article

[72] PubMed/NCBI

[73] Google Scholar

[ref21] 21. Cooley G, Etheridge RD, Boehlke C, Bundy B, Weatherly DB, Minning T, et al. High throughput selection of effective serodiagnostics for Trypanosoma cruzi infection. PLoS Negl Trop Dis. 2008;2(10):e316. pmid:18841200
View Article
PubMed/NCBI
Google Scholar

[75] View Article

[76] PubMed/NCBI

[77] Google Scholar

[ref22] 22. Cura CI, Ramírez JC, Rodríguez M, Lopez-Albízu C, Irazu L, Scollo K, et al. Comparative study and analytical verification of PCR methods for the diagnosis of congenital chagas disease. J Mol Diagn. 2017;19(5):673–81. pmid:28727985
View Article
PubMed/NCBI
Google Scholar

[79] View Article

[80] PubMed/NCBI

[81] Google Scholar

[ref23] 23. Lopez-Albizu C, Cura CI, Ramirez JC, Peyran P, Benchetrit A, Danesi E, et al. Congenital Chagas disease: a cohort study to assess molecular diagnostic methods at the Chagas disease national reference center of Argentina. PLoS Negl Trop Dis. 2025;19(1):e0012785. pmid:39792926
View Article
PubMed/NCBI
Google Scholar

[83] View Article

[84] PubMed/NCBI

[85] Google Scholar

[ref24] 24. Laucella SA, Postan M, Martin D, Hubby Fralish B, Albareda MC, Alvarez MG, et al. Frequency of interferon- gamma -producing T cells specific for Trypanosoma cruzi inversely correlates with disease severity in chronic human Chagas disease. J Infect Dis. 2004;189(5):909–18. pmid:14976609
View Article
PubMed/NCBI
Google Scholar

[87] View Article

[88] PubMed/NCBI

[89] Google Scholar

[ref25] 25. Feng T, Liao X, Yang X, Yang C, Lin F, Guo Y, et al. A shift toward inhibitory receptors and impaired effector functions on NK cells contribute to immunosuppression during sepsis. J Leukoc Biol. 2020;107(1):57–67. pmid:31385383
View Article
PubMed/NCBI
Google Scholar

[91] View Article

[92] PubMed/NCBI

[93] Google Scholar

[ref26] 26. Castro Eiro MD, Alvarez MG, Cooley G, Viotti RJ, Bertocchi GL, Lococo B, et al. The significance of discordant serology in chagas disease: enhanced T-cell immunity to Trypanosoma cruzi in serodiscordant subjects. Front Immunol. 2017;8:1141. pmid:28966620
View Article
PubMed/NCBI
Google Scholar

[95] View Article

[96] PubMed/NCBI

[97] Google Scholar

[ref27] 27. Abel AM, Yang C, Thakar MS, Malarkannan S. Natural killer cells: development, maturation, and clinical utilization. Front Immunol. 2018;9:1869.
View Article
Google Scholar

[99] View Article

[100] Google Scholar

[ref28] 28. Albareda MC, Laucella SA, Alvarez MG, Armenti AH, Bertochi G, Tarleton RL, et al. Trypanosoma cruzi modulates the profile of memory CD8+ T cells in chronic Chagas’ disease patients. Int Immunol. 2006;18(3):465–71. pmid:16431876
View Article
PubMed/NCBI
Google Scholar

[102] View Article

[103] PubMed/NCBI

[104] Google Scholar

[ref29] 29. Egui A, Thomas MC, Carrilero B, Segovia M, Alonso C, Marañón C, et al. Differential phenotypic and functional profiles of TcCA-2 -specific cytotoxic CD8+ T cells in the asymptomatic versus cardiac phase in Chagasic patients. PLoS One. 2015;10(3):e0122115. pmid:25816096
View Article
PubMed/NCBI
Google Scholar

[106] View Article

[107] PubMed/NCBI

[108] Google Scholar

[ref30] 30. Mariuzza RA, Singh P, Karade SS, Shahid S, Sharma VK. Recognition of self and viral ligands by NK cell receptors. Immunol Rev. 2025;329(1):e13435. pmid:39748148
View Article
PubMed/NCBI
Google Scholar

[110] View Article

[111] PubMed/NCBI

[112] Google Scholar

[ref31] 31. Pallmer K, Oxenius A. Recognition and regulation of T cells by NK cells. Front Immunol. 2016;7:251. pmid:27446081
View Article
PubMed/NCBI
Google Scholar

[114] View Article

[115] PubMed/NCBI

[116] Google Scholar

[ref32] 32. Molfetta R, Zingoni A, Santoni A, Paolini R. Post-translational mechanisms regulating NK cell activating receptors and their ligands in cancer: potential targets for therapeutic intervention. Front Immunol. 2019;10:2557. pmid:31736972
View Article
PubMed/NCBI
Google Scholar

[118] View Article

[119] PubMed/NCBI

[120] Google Scholar

[ref33] 33. Wilk AJ, Lee MJ, Wei B, Parks B, Pi R, Martínez-Colón GJ, et al. Multi-omic profiling reveals widespread dysregulation of innate immunity and hematopoiesis in COVID-19. J Exp Med. 2021;218(8):e20210582. pmid:34128959
View Article
PubMed/NCBI
Google Scholar

[122] View Article

[123] PubMed/NCBI

[124] Google Scholar

[ref34] 34. Castriconi R, Cantoni C, Della Chiesa M, Vitale M, Marcenaro E, Conte R, et al. Transforming growth factor beta 1 inhibits expression of NKp30 and NKG2D receptors: consequences for the NK-mediated killing of dendritic cells. Proc Natl Acad Sci U S A. 2003;100(7):4120–5. pmid:12646700
View Article
PubMed/NCBI
Google Scholar

[126] View Article

[127] PubMed/NCBI

[128] Google Scholar

[ref35] 35. Sun C, Fu B, Gao Y, Liao X, Sun R, Tian Z, et al. TGF-β1 down-regulation of NKG2D/DAP10 and 2B4/SAP expression on human NK cells contributes to HBV persistence. PLoS Pathog. 2012;8(3):e1002594. pmid:22438812
View Article
PubMed/NCBI
Google Scholar

[130] View Article

[131] PubMed/NCBI

[132] Google Scholar

[ref36] 36. Lee G, Schauner R, Burke J, Borocz J, Vasana S, Sobieraj L, et al. NK cells from COVID-19 positive patients exhibit enhanced cytotoxic activity upon NKG2A and KIR2DL1 blockade. Front Immunol. 2023;14:1022890. pmid:37483595
View Article
PubMed/NCBI
Google Scholar

[134] View Article

[135] PubMed/NCBI

[136] Google Scholar

[ref37] 37. Valayer A, Brea D, Lajoie L, Avezard L, Combes-Soia L, Labas V, et al. Neutrophils can disarm NK cell response through cleavage of NKp46. J Leukoc Biol. 2017;101(1):253–9. pmid:27587403
View Article
PubMed/NCBI
Google Scholar

[138] View Article

[139] PubMed/NCBI

[140] Google Scholar

[ref38] 38. Peruzzi G, Femnou L, Gil-Krzewska A, Borrego F, Weck J, Krzewski K, et al. Membrane-type 6 matrix metalloproteinase regulates the activation-induced downmodulation of CD16 in human primary NK cells. J Immunol. 2013;191(4):1883–94. pmid:23851692
View Article
PubMed/NCBI
Google Scholar

[142] View Article

[143] PubMed/NCBI

[144] Google Scholar

[ref39] 39. Park YP, Choi S-C, Kiesler P, Gil-Krzewska A, Borrego F, Weck J, et al. Complex regulation of human NKG2D-DAP10 cell surface expression: opposing roles of the γc cytokines and TGF-β1. Blood. 2011;118(11):3019–27. pmid:21816829
View Article
PubMed/NCBI
Google Scholar

[146] View Article

[147] PubMed/NCBI

[148] Google Scholar

[ref40] 40. Yang H-L, Zhou W-J, Chang K-K, Mei J, Huang L-Q, Wang M-Y, et al. The crosstalk between endometrial stromal cells and macrophages impairs cytotoxicity of NK cells in endometriosis by secreting IL-10 and TGF-β. Reproduction. 2017;154(6):815–25. pmid:28971893
View Article
PubMed/NCBI
Google Scholar

[150] View Article

[151] PubMed/NCBI

[152] Google Scholar

[ref41] 41. Crouse J, Xu HC, Lang PA, Oxenius A. NK cells regulating T cell responses: mechanisms and outcome. Trends Immunol. 2015;36(1):49–58. pmid:25432489
View Article
PubMed/NCBI
Google Scholar

[154] View Article

[155] PubMed/NCBI

[156] Google Scholar

[ref42] 42. Chen S, Zhu H, Jounaidi Y. Comprehensive snapshots of natural killer cells functions, signaling, molecular mechanisms and clinical utilization. Signal Transduct Target Ther. 2024;9(1):302. pmid:39511139
View Article
PubMed/NCBI
Google Scholar

[158] View Article

[159] PubMed/NCBI

[160] Google Scholar

[ref43] 43. D’Avila DA, Guedes PMM, Castro AM, Gontijo ED, Chiari E, Galvão LMC. Immunological imbalance between IFN-gamma and IL-10 levels in the sera of patients with the cardiac form of Chagas disease. Mem Inst Oswaldo Cruz. 2009;104(1):100–5. pmid:19274383
View Article
PubMed/NCBI
Google Scholar

[162] View Article

[163] PubMed/NCBI

[164] Google Scholar

[ref44] 44. Albareda MC, Perez-Mazliah D, Natale MA, Castro-Eiro M, Alvarez MG, Viotti R, et al. Perturbed T cell IL-7 receptor signaling in chronic Chagas disease. J Immunol. 2015;194(8):3883–9. pmid:25769928
View Article
PubMed/NCBI
Google Scholar

[166] View Article

[167] PubMed/NCBI

[168] Google Scholar

[ref45] 45. Natale MA, Cesar G, Alvarez MG, Castro Eiro MD, Lococo B, Bertocchi G, et al. Trypanosoma cruzi-specific IFN-γ-producing cells in chronic Chagas disease associate with a functional IL-7/IL-7R axis. PLoS Negl Trop Dis. 2018;12(12):e0006998. pmid:30517089
View Article
PubMed/NCBI
Google Scholar

[170] View Article

[171] PubMed/NCBI

[172] Google Scholar

[ref46] 46. Batalla EI, Pino Martínez AM, Poncini CV, Duffy T, Schijman AG, González Cappa SM, et al. Impairment in natural killer cells editing of immature dendritic cells by infection with a virulent Trypanosoma cruzi population. J Innate Immun. 2013;5(5):494–504. pmid:23689360
View Article
PubMed/NCBI
Google Scholar

[174] View Article

[175] PubMed/NCBI

[176] Google Scholar

[ref47] 47. Vitelli‐Avelar DM, Sathler‐Avelar R, Dias JCP, Pascoal VPM, Teixeira‐Carvalho A, Lage PS. Chagasic patients with indeterminate clinical form of the disease have high frequencies of circulating CD3 CD16– CD56 natural killer T cells and CD4 CD25High regulatory T lymphocytes. Scand J Immunol. 2005;62:297–308.
View Article
Google Scholar

[178] View Article

[179] Google Scholar

[ref48] 48. Gómez I, López MC, Egui A, Palacios G, Carrilero B, Benítez C, et al. Differential expression profile of genes involved in the immune response associated to progression of chronic Chagas disease. PLoS Negl Trop Dis. 2023;17(7):e0011474. pmid:37440604
View Article
PubMed/NCBI
Google Scholar

[181] View Article

[182] PubMed/NCBI

[183] Google Scholar

[ref49] 49. Ferreira LRP, Ferreira FM, Nakaya HI, Deng X, Cândido D da S, de Oliveira LC, et al. Blood gene signatures of chagas cardiomyopathy with or without ventricular dysfunction. J Infect Dis. 2017;215(3):387–95. pmid:28003350
View Article
PubMed/NCBI
Google Scholar

[185] View Article

[186] PubMed/NCBI

[187] Google Scholar

[ref50] 50. Souza-Silva TG, Figueiredo A, Morais KLP, Apostólico J, Pantaleao A, Mutarelli A, et al. Single-Cell targeted transcriptomics reveals subset-specific immune signatures differentiating asymptomatic and cardiac patients with chronic chagas disease. J Infect Dis. 2025;232(6):1402–12. pmid:40434116
View Article
PubMed/NCBI
Google Scholar

[189] View Article

[190] PubMed/NCBI

[191] Google Scholar

[ref51] 51. He S, Li C, Lu M, Lin F, Hu S, Zhang J, et al. Comprehensive analysis of scRNA-seq and bulk RNA-seq reveals the non-cardiomyocytes heterogeneity and novel cell populations in dilated cardiomyopathy. J Transl Med. 2025;23(1):17. pmid:39762897
View Article
PubMed/NCBI
Google Scholar

[193] View Article

[194] PubMed/NCBI

[195] Google Scholar

[ref52] 52. Ong S, Ligons DL, Barin JG, Wu L, Talor MV, Diny N, et al. Natural killer cells limit cardiac inflammation and fibrosis by halting eosinophil infiltration. Am J Pathol. 2015;185(3):847–61. pmid:25622543
View Article
PubMed/NCBI
Google Scholar

[197] View Article

[198] PubMed/NCBI

[199] Google Scholar

[ref53] 53. Dutra WO, Menezes CAS, Magalhães LMD, Gollob KJ. Immunoregulatory networks in human Chagas disease. Parasite Immunol. 2014;36(8):377–87. pmid:24611805
View Article
PubMed/NCBI
Google Scholar

[201] View Article

[202] PubMed/NCBI

[203] Google Scholar

[ref54] 54. Sathler-Avelar R, Vitelli-Avelar DM, Elói-Santos SM, Gontijo ED, Teixeira-Carvalho A, Martins-Filho OA. Blood leukocytes from benznidazole-treated indeterminate chagas disease patients display an overall type-1-modulated cytokine profile upon short-term in vitro stimulation with Trypanosoma cruzi antigens. BMC Infect Dis. 2012;12:123. pmid:22625224
View Article
PubMed/NCBI
Google Scholar

[205] View Article

[206] PubMed/NCBI

[207] Google Scholar

[ref55] 55. Tognarelli EI, Gutiérrez-Vera C, Palacios PA, Pasten-Ferrada IA, Aguirre-Muñoz F, Cornejo DA. Natural killer T cell diversity and immunotherapy. Cancers. 2023;15:5737.
View Article
Google Scholar

[209] View Article

[210] Google Scholar

[ref56] 56. Castro Eiro MD, Natale MA, Alvarez MG, Shen H, Viotti R, Lococo B, et al. Reduced Trypanosoma cruzi-specific humoral response and enhanced T cell immunity after treatment interruption with benznidazole in chronic Chagas disease. J Antimicrob Chemother. 2021;76(6):1580–92. pmid:33693664
View Article
PubMed/NCBI
Google Scholar

[212] View Article

[213] PubMed/NCBI

[214] Google Scholar

[ref57] 57. Pérez-Antón E, Egui A, Thomas MC, Puerta CJ, González JM, Cuéllar A, et al. Impact of benznidazole treatment on the functional response of Trypanosoma cruzi antigen-specific CD4+CD8+ T cells in chronic Chagas disease patients. PLoS Negl Trop Dis. 2018;12(5):e0006480. pmid:29750791
View Article
PubMed/NCBI
Google Scholar

[216] View Article

[217] PubMed/NCBI

[218] Google Scholar

[ref58] 58. de Padua Mansur A, Cunha-Neto E, Bulgarelli Bestetti R, Brochet P, Chevillard C, Pereira-Barretto AC. Curr Heart Fail Rep. 2025;22:27.
View Article
Google Scholar

[220] View Article

[221] Google Scholar

Figures

Abstract

Background

Methods

Results

Conclusions

Author summary

Background

Methods

Ethic statement

Selection of study population

Collection of peripheral blood mononuclear cells (PBMC)

NK-cell phenotype and high dimensional analysis

NK-cell function

ELISPOT assays following CD56 or CD4/CD8 depletion

Statistics

Results

NK-cell phenotype according to the severity of chronic Chagas disease

NK-cell function according to the severity of chronic Chagas disease

NK-cell function after treatment with benznidazole

Contribution of NK cells to the T-cell response specific for T. cruzi,

Discussion

Supporting information

S1 Table. Antibodies used for surface and intracellular staining assays by flow cytometry.

S2 Table. The frequency of NK-cell subsets in subjects with chronic Chagas disease.

S3 Table. The phenotype and function of CD56bright clusters identified by Phenograph and FlowSOM algorithm in subjects with chronic Chagas disease.

S4 Table. The phenotype and function of CD56dim clusters identified by Phenograph and FlowSOM algorithm in subjects with chronic Chagas disease.

S5 Table. Percentages of individual CD56bright and CD56dim clusters identified by unsupervised high-dimensional analysis.

S6 Table. Expression of the mean fluorescence intensity (MFI) for individual surface markers of the indicated cluster identified by unsupervised high-dimensional analysis.

S7 Table. Manual gating strategy for the identification of NK cells with activating and cytotoxic phenotype.

S8 Table. Percentage of the total response contributed by CD56+ NK cells with given co-expression profile in subjects chronically infected with T. cruzi.

S1 Fig. Gating strategy for NK cells in a representative donor.

S2 Fig. Depletion of human CD56+ NK cells from PBMC derived from a T. cruzi infected donor.

S3 Fig. Human CD4+ and CD8+ T cells were depleted from peripheral blood PBMC derived from one T. cruzi-infected donor.

S4 Fig. The frequency of NK-cell subsets in subjects with chronic Chagas disease.

S5 Fig. Representative manual gating strategy for the expression of NK activating receptors in subjects with chronic Chagas disease.

Acknowledgments

References

S3 Table. The phenotype and function of CD56^bright clusters identified by Phenograph and FlowSOM algorithm in subjects with chronic Chagas disease.

S4 Table. The phenotype and function of CD56^dim clusters identified by Phenograph and FlowSOM algorithm in subjects with chronic Chagas disease.

S5 Table. Percentages of individual CD56^bright and CD56^dim clusters identified by unsupervised high-dimensional analysis.

S8 Table. Percentage of the total response contributed by CD56⁺ NK cells with given co-expression profile in subjects chronically infected with T. cruzi.

S2 Fig. Depletion of human CD56⁺ NK cells from PBMC derived from a T. cruzi infected donor.

S3 Fig. Human CD4⁺ and CD8⁺ T cells were depleted from peripheral blood PBMC derived from one T. cruzi-infected donor.