TYPE Original Research PUBLISHED 22 July 2022 DOI 10.3389/fmicb.2022.885312 Study of CD27, CD38, HLA-DR OPEN ACCESS and Ki-67 immune profiles for the characterization of active EDITED BY Xiao-Yong Fan, Fudan University, China REVIEWED BY Damien Portevin, tuberculosis, latent infection and end of treatment Swiss Tropical and Public Health Institute (Swiss TPH), Switzerland Margarida Correia-Neves, University of Minho, Portugal Sergio Díaz-Fernández 1,2,3†, Raquel Villar-Hernández 1,2,3†, Santhi Devasundaram, National Cancer Institute at Frederick (NIH), Zoran Stojanovic 2,3,4†, Marco Fernández 5, United States Elisa Petruccioli, Maria Luiza De Souza Galvão 6, Guillermo Tolosa 7, National Institute for Infectious Diseases Adrián Sánchez-Montalva 8,9, Jorge Abad 2,4, Lazzaro Spallanzani (IRCCS), Italy Christopher Sundling, María Ángeles Jiménez-Fuentes 6, Guillem Safont 1,2,3, Karolinska Institutet (KI), Sweden Delia Goletti, Iris Romero 3, Josefina Sabrià 10, Cristina Prat 1,2,3,11, National Institute for Infectious Diseases Jose Domínguez 1,2,3‡ and Irene Latorre 1,2,3*‡ Lazzaro Spallanzani (IRCCS), Italy *CORRESPONDENCE 1 Institut d’Investigació Germans Trias i Pujol, Barcelona, Spain, 2 CIBER Enfermedades Respiratorias, Irene Latorre CIBERES, Instituto de Salud Carlos III, Madrid, Spain, 3 Departament de Genètica i Microbiologia, ilatorre@igtp.cat Universitat Autònoma de Barcelona, Barcelona, Spain, 4 Servei de Pneumologia, Hospital Universitari Germans Trias i Pujol, Barcelona, Spain, 5 Plataforma de Citometría, Institut d’Investigació Germans † These authors have contributed equally to Trias i Pujol, Barcelona, Spain, 6 Unitat de Tuberculosi de Drassanes, Hospital Universitari Vall this work and share first authorship d’Hebron, Barcelona, Spain, 7 Universidad de la Frontera (UFRO), Temuco, Chile, 8 Infectious Diseases Department, Vall d’Hebron University Hospital, PROSICS Barcelona, Universitat Autònoma ‡ These authors have contributed equally to de Barcelona, Barcelona, Spain, 9 Grupo de Estudio de micobacterias (GEIM), Sociedad Española de this work and share senior authorship Enfermedades Infecciosas y Microbiología Clínica (SEIMC), Madrid, Spain, 10 Hospital de Sant Joan SPECIALTY SECTION Despí Moisès Broggi, Barcelona, Spain, 11 Julius Center for Health Sciences and Primary Care, This article was submitted to University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands Infectious Agents and Disease, a section of the journal Frontiers in Microbiology RECEIVED 27February 2022 Background: Current blood-based diagnostic tools for TB are insufficient ACCEPTED 28 June 2022 PUBLISHED 22 July 2022 to properly characterize the distinct stages of TB, from the latent infection CITATION (LTBI) to its active form (aTB); nor can they assess treatment efficacy. Several Díaz-Fernández S, Villar-Hernández R, immune cell biomarkers have been proposed as potential candidates for the Stojanovic Z, Fernández M, Galvão MLDS, development of improved diagnostic tools. Tolosa G, Sánchez-Montalva A, Abad J, Jiménez-Fuentes MÁ, Safont G, Romero I, Objective: To compare the capacity of CD27, HLA-DR, CD38 and Ki-67 Sabrià J, Prat C, Domínguez J and markers to characterize LTBI, active TB and patients who ended treatment and Latorre I (2022) Study of CD27, CD38, HLA-DR and Ki-67 immune profiles for the resolved TB. characterization of active tuberculosis, latent infection and end of treatment. Methods: Blood was collected from 45 patients defined according to clinical Front. Microbiol. 13:885312. and microbiological criteria as: LTBI, aTB with less than 1 month of treatment doi: 10.3389/fmicb.2022.885312 and aTB after completing treatment. Peripheral blood mononuclear cells were stimulated with ESAT-6/CFP-10 or PPD antigens and acquired for flow cytometry after labelling with conjugated antibodies against CD3, CD4, CD8, CD27, IFN-γ, TNF-α, CD38, HLA-DR, and Ki-67. Conventional and multiparametric analyses were done with FlowJo and OMIQ, respectively. Results: The expression of CD27, CD38, HLA-DR and Ki-67 markers was analyzed in CD4+ T-cells producing IFN-γ and/or TNF-α cytokines after ESAT-6/CFP-10 or PPD stimulation. Within antigen-responsive CD4+ T-cells, Frontiers in Microbiology 01 frontiersin.org Díaz-Fernández et al. 10.3389/fmicb.2022.885312 CD27− and CD38+ (ESAT-6/CFP-10-specific), and HLA-DR+ and Ki-67+ (PPD- and ESAT-6/CFP-10-specific) populations were significantly increased in aTB compared to LTBI. Ki-67 demonstrated the best discriminative performance as evaluated by ROC analyses (AUC>0.9 after PPD stimulation). Data also points to a significant change in the expression of CD38 (ESAT-6/CFP-10-specific) and Ki-67 (PPD- and ESAT-6/CFP-10-specific) after ending the anti-TB treatment regimen. Furthermore, ratio based on the CD27 median fluorescence intensity in CD4+ T-cells over Mtb-specific CD4+ T-cells showed a positive association with aTB over LTBI (ESAT-6/CFP-10-specific). Additionally, multiparametric FlowSOM analyses revealed an increase in CD27 cell clusters and a decrease in HLA-DR cell clusters within Mtb-specific populations after the end of treatment. Conclusion: Our study independently confirms that CD27−, CD38+, HLA-DR+ and Ki-67+ populations on Mtb-specific CD4+ T-cells are increased during active TB disease. Multiparametric analyses unbiasedly identify clusters based on CD27 or HLA-DR whose abundance can be related to treatment efficacy. Further studies are necessary to pinpoint the convergence between conventional and multiparametric approaches. KEYWORDS Mycobacterium tuberculosis, T-cells, immune response, activation markers, treatment, flow cytometry, multiparametric analysis, cluster Introduction The immune response to Mtb infection is still not fully understood, but CD4+ T-cells arguably play a pivotal role (Gallegos To date, tuberculosis (TB) is still a major global health et al., 2011; O’Garra et al., 2013). Depletion of this T-cell subset threat, with approximately 10 million new Mycobacterium and/or Th1 responses (Filipe-Santos et al., 2006) result in extreme tuberculosis (Mtb) infections and 1.5 million deaths reported susceptibility to the disease. In fact, immune response to Mtb is so only in 2020. Moreover, the COVID-19 pandemic has set back connected to T-cell activity that its measurement is the basis for several years of progress in TB control, and the target of ending the main culture-free diagnostic assays (Lalvani and Pareek, the epidemic by 2030 set by the WHO’s End TB Strategy seems 2010), such as the Tuberculin Skin Test (TST) and the interferon even more implausible now (Global Tuberculosis Report, 2021). (IFN)-gamma (γ) release assays (IGRAs). The TST consists in the From a pathophysiological setting, TB represents a dynamic intradermal injection of a mixture of mycobacterial antigens, the spectrum from infection to clinical disease (Furin et al., 2019); Purified Protein Derivative (PPD), that causes a skin reaction if however, for pragmatic reasons, patients are usually categorized there is an immunological memory to Mycobacterium spp. as having either active TB (aTB) or latent TB infection (LTBI). (Seddon et al., 2016). Despite being widely used, the TST has a Defining the latent TB condition has been a matter of discussion rather low specificity, and false positives are common. This is over the last decades, since it encompasses a wide array of mainly due to the fact that the PPD antigens are not unique to Mtb situations, from individuals with quiescent Mtb to individuals and are detected by T-cells from patients with the Bacille with controlled bacterial growth for months (Pai et al., 2016). Calmette-Guérin vaccine and/or infected with nontuberculous Updated definitions of LTBI added the concept of host immunity mycobacteria (Domínguez et al., 2008; Latorre et al., 2010). These to the clinical picture, and now it is considered as “a state of limitations were partly overcome thanks to the introduction of the persistent immunoreactivity to Mtb antigenic stimulation with IGRAs. These assays are based on the detection of specific T-cell no evidence of clinically manifest active TB” (Drain et al., 2018). responses against Mtb, represented by the release of IFN-γ after Around a quarter of the world’s population is estimated to stimulation with Mtb-specific antigens (ESAT-6 and CFP-10; be infected with Mtb, from which 5%–10% will develop aTB Andersen et al., 2000). The IGRAs have demonstrated better (Houben and Dodd, 2016). Individuals with LTBI constitute the performance than the TST for the diagnosis of Mtb infection principal reservoir for the bacilli, which is the reason why (Metcalfe et al., 2013); nevertheless, both tests fail to discriminate accurate diagnosis is essential for halting TB worldwide. Correct active disease from latent infection and other status associated to characterization of the TB spectrum is, therefore, a priority in higher risks of developing the disease (Goletti et al., 2022). the development of novel diagnostic tools. Moreover, neither of the assays can be used to monitor therapy Frontiers in Microbiology 02 frontiersin.org Díaz-Fernández et al. 10.3389/fmicb.2022.885312 efficacy, which would be of great value to shorten treatment confirmed with a positive culture and/or PCR, with less than regimen and to accelerate the drug evaluation in the clinical trials. 1 month of anti-TB treatment; (ii) twenty-two individuals Given the fact that T-cells change their activation status and (n = 22) with LTBI based on positive TST and/or IGRAs and cytokine expression after Mtb challenge, the evaluation of their absence of clinical symptoms and radiological signs, detected immune profile is an attractive option for the improvement of by contact-tracing or screening studies, and with less than TB diagnostics. 1 month of chemoprophylaxis; and (iii) nine (n = 9) former aTB The study of immunological biomarkers via flow cytometry patients from group (i) after successfully completing the has already been demonstrated to be a useful tool to evaluate standard treatment regimen with anti-TB drugs and being host response in TB infection and aTB disease (Pollock et al., considered as cured (eTrt). Overall, 37% were women, and the 2013; Coppola et al., 2020). Most studies focus the analysis of mean age (years) ± standard deviation (SD) was 42.7 ± 13.5. these disease markers in specific subsets of cells defined by the Clinical and study information is detailed in Table 1. expression of pro-inflammatory cytokines following antigen stimulation, linking production of TNF-α (Harari et al., 2011; Halliday et al., 2017) and IFN-γ (Petruccioli et al., 2015; Ahmed PBMCs isolation, preservation, and et al., 2019) with infection. Among these cells, several surface thawing and intracellular proteins have been described as potential biomarkers for aTB (Walzl et al., 2018). The present research Approximately 16 ml of whole blood were collected from explores the role of four of them; namely, CD27, CD38, each patient in cell preparation tubes (CPT tubes; BD Biosciences, HLA-DR and Ki-67. CD27 is a maturation marker and its San Jose, CA, United States) containing Sodium Citrate and Ficoll downregulation has already been associated with active disease for peripheral blood mononuclear cells (PBMCs) isolation. and tissue destruction in TB (Portevin et al., 2014; Latorre et al., Briefly, following a centrifugation of 1,600 g for 30 min, PBMCs 2019). CD38 is a transmembrane receptor expressed in many were harvested from the interface and washed with RPMI immune cell types (Hartman et al., 2010), more recently linked medium (ThermoFisher, Waltham, MA, United States) to TB studies because of its strong expression in activated supplemented with 10% FBS (BioWest, Miami, Fla., T-cells. HLA-DR is an MHC cell receptor highly present on United States). Cells were counted with Trypan Blue staining and APCs (Saraiva et al., 2018), but also with robust expression on were resuspended in heat-inactivated FBS supplemented with activated T-cells (Tippalagama et al., 2021). Ki-67, the only 10% Dimethyl Sulfoxide (DMSO) for cryopreservation in liquid intracellular marker from the group, is a nuclear protein nitrogen (Cossarizza et al., 2019). To perform our immunological commonly associated with cell proliferation (Soares et al., studies, frozen PBMCs were thawed and incubated for 2 h at 37°C 2010). The latter three proteins are associated with antigenic with 5% CO2 in AIM-V medium (Thermo Fisher) with stimulation; therefore, their expression is likely to be increased benzonase (Sigma, St. Louis, MO, United States; final in active forms of the disease, where mycobacterial load is concentration 10 U/ml) to avoid cell clumping. higher (Mpande et al., 2021). In this paper, we aim to study the expression of the CD27, CD38, HLA-DR and Ki-67 markers in Mtb-specific CD4+ T-cells by performing a side by side PBMCs stimulation with mycobacterial comparison of their performance on characterizing active antigen disease and latent infection. Furthermore, we intend to evaluate the capacity of these biomarkers to assess treatment efficacy Samples included in the study were stimulated for 16 h after its completion. Deeper knowledge on such immune separately with two mycobacterial antigen mixes: (i) recombinant biomarkers could allow the development of new strategies for proteins ESAT-6/CFP-10 (Lionex Diagnostics and Therapeutics, diagnosis and management of LTBI individuals and Braunschweig, Germany; final concentration 2 μg/ml each) aTB patients. and (ii) PPD (AJVaccines, Copenhagen, Denmark; final concentration 10 μg/ml). A positive control consisting of staphylococcal enterotoxin B (SEB, Sigma, final concentration of Materials and methods 2 μg/ml) and a negative control without stimulation were also included for each sample. One million (106) PBMCs were used Study population and inclusion criteria in each stimulation condition, adding as co-stimulators anti- CD28 and anti-CD49d monoclonal antibodies (BD Bioscience; The patients included in this study (n = 45) attended one of final concentration 1 μg/ml each). After a 2 h incubation at 37°C the following centers in Barcelona, Spain: Hospital Germans in a 5% CO2 atmosphere, Brefeldin A (BFA; Sigma; final Trias i Pujol, Unitat de Tuberculosi Vall d’Hebron-Drassanes, concentration 3 μg/ml) and Monensin (BioLegend, San Diego, Sant Joan Despí Moisés Broggi, and Hospital Universitari Vall USA, final concentration 1X) were added to inhibit intracellular d’Hebrón. They were classified as follows: (i) twenty-three vesicular transport. Cells were then incubated overnight before patients (n = 23) with pulmonary aTB, microbiologically starting the staining procedure. Frontiers in Microbiology 03 frontiersin.org Díaz-Fernández et al. 10.3389/fmicb.2022.885312 TABLE 1 Demographic and clinical characteristics of the participants in each study group. Variables aTB LTBI eTrt Participants, n 23 22 9 Mean age1, years ± SD 43.91 ± 15.47 42.59 ± 12.17 50 ± 14.02 Male gender, n(%) 18 (78.3) 16 (72.7) 9 (100) Disease form, N(%) Pulmonary 22 (95.7) – 9 (100) Pleural 1 (4.3) – – Reported LTBI enrolment, N(%) Contact-tracing – 14 (63.6) LTBI screening – 7 (31.8) Not reported – 1 (4.5) Chemoprofilaxis, N(%) Before starting chemoprophylaxis - 1 (4.5) - After starting chemoprophylaxis (<1 month) 22 (95.7) 21 (95.5) 9 (100) Not prescribed - - - Mean time of chemoprophylaxis2, days ± SD - 20.90 ± 6.32 - Regimen 3RH - 19 (86.4) - Regimen 6H - 3 (13.6) Anti-TB treatment, N(%) Before starting treatment3 2 (8.7) – – After starting treatment (<1 month) 21 (91.3) – – Ended treatment4 - 9 (100) Not prescribed - 22 (100) – Mean time of treatment2, days ± SD 12.95 ± 9.94 – 229.55 ± 91.48 Regimen 2HRZE/4RH 21 (91.3) – 8 (88.9) Others 5 2 (8.7) – 1 (11.1) Comorbidities, N(%) Other respiratory disorders (asthma, PCD, 2 (8.7) 2 (9.1) 2 (22.2) COPD) Neoplasies (lung, prostate) 2 (8.7) – 1 (11.1) Autoimmune diseases (diabetes, psoriasis, 2 (8.7) 2 (9.1) – Löfgren Syndrome) Cardiovascular diseases (AHT, cardiomyopathy) 1 (4.3) – 1 (11.1) Hepatitis C 1 (4.3) 2 (9.1) – Bacille Calmette-Guérin vaccine, N(%) BCG-vaccinated 12 (52.2) 12 (54.5) 3 (33.3) Not BCG-vaccinated 9 (39.1) 10 (45.5) 5 (55.5) Not reported 2 (8.7) – 1 (11.1) Other information, N(%) Reported smokers 9 (39.1) 5 (22.7) 4 (44.44) Reported drug abuse 5 (21.7) 0 (0) 0 (0) aTB, active tuberculosis; LTBI, latent tuberculosis infection; eTrt, aTB patients after anti-TB treatment; SD, standard deviation; PCD, primary ciliary dyskinesia; COPD, chronic obstructive pulmonary disease; AHT, arterial hypertension; SEB, staphylococcal enterotoxin B. 1 Patients in the study are aged 20–73. 2 Range of time between starting chemoprophylaxis and anti-TB treatment and sample collection was from 0 to 30 days in all participants in both groups. 3 Both patients were prescribed with RIMSTAR on the day of sample collection. 4 One of the participants was recruited after 5 months of anti-TB treatment, six of the participants between 6 and 7.5 months and one of the participants after 16 months. 5 One patient was prescribed with HRZ regimen, and one patient was prescribed with Lzd/Mfx/Cfz/Z/E regimen. Extracellular and intracellular staining for 30 min and subsequently stained for 20 min with the following and acquisition in flow cytometer surface markers: anti-CD3-PerCP (BioLegend), anti-CD4-BV786, anti-CD8-BV510, anti-CD27-BV605, anti-CD38-PE, and anti- After stimulation, PBMCs were labeled with viability marker HLA-DR-BV421 (BD Bioscience). Cells were then fixed and LIVE/DEAD Near-IR fluorescent reactive dye (Thermo Fisher) permeabilized with the Foxp3 Transcription Factor Staining Frontiers in Microbiology 04 frontiersin.org Díaz-Fernández et al. 10.3389/fmicb.2022.885312 Buffer Set (Thermo Fisher) and stained for 30 min with Statistics intracellular markers: anti-IFNγ-APC, anti-TNFα-PE-Cy7 and anti-Ki-67-FITC (BD Bioscience). The complete list of antibodies, Results comparing variables between LTBI and aTB conjugated proteins and dilutions can be found in participants were analyzed using the two-tailed Mann– Supplementary Table 1. All incubation processes were performed Whitney test for unpaired comparisons. Paired data from at room temperature in darkness. Fluorescence Minus One patients followed over time was analyzed using the Wilcoxon- (FMO) controls of the four analyzed cell markers (CD27, CD38, matched pairs test. Comparisons between before and after HLA-DR, and Ki-67) were included in each run to accurately treatment groups where data was partially paired (combining distinguish negative from positive populations. Samples were paired and unpaired observations) were analyzed using a resuspended in 100 μl of PBS-0.1%BSA (Bovine Serum Albumin, mixed statistical model controlling repeated measures on Sigma Aldrich) and acquired in a BD LSRFortessa flow cytometer logit-transformed data. Correlation between variables was (BD Bioscience) using FACSDiva software (BD Biosciences) with calculated using the two-tailed non-parametric Spearman test. compensated parameters. Diagnostic accuracy was evaluated via the Receiver operating characteristic (ROC) and Area Under the Curve (AUC) analyses. Differences were regarded as statistically significant Flow cytometry data analysis when the value of p or the False Discovery Rate (FDR) value were below 0.05. For gate-driven analyses, flow cytometry data was analyzed using FlowJo™ (Tree Star, Ashland, OR, United States) and plotted with GraphPad Prism (GraphPad Software, La Jolla, Results CA). Lymphocytes were gated based on their size (FSC) and complexity (SSC). After exclusion of doublet events, CD4+ T Expression of CD27, CD38, HLA-DR and cells were selected from CD3+ alive events. TNF-α+ and/or Ki-67 markers on Mtb-specific CD4+ IFN-γ+ populations were selected for the study of Mtb-specific T-cells differs in LTBI individuals and responses. To avoid inadequate assessment of population anti-TB treated patients compared to aTB percentages, Mtb-specific populations under 100 events were patients not considered valid for analysis (this meant that out of 54 samples, six PPD-stimulated and eight ESAT-6/CFP-10- To specifically study the T-cell response against Mtb, stimulated were excluded). CD27 Median Fluorescence TNF-α and/or IFN-γ cytokines were analyzed on CD4+ T-cells Intensity (MFI) ratio after stimulation with ESAT-6/CFP-10 or PPD antigens (complete gating strategy can be found in  CD 27 MFI on total CD 4+ T − cells  Supplementary Figure 1). From this Mtb-specific population,  +  the percentage of CD27−, CD38+, HLA-DR+ and Ki-67+  CD 27 MFI on Mtb − specific CD 4 T − cells  populations were compared between LTBI individuals and aTB  HLADR MFI on IFNy +   HLADR MFI on  patients at the beginning and end of the treatment. To control and ΔHLA-DR MFI  + +  −  +  that the length of the treatment within the 1-month range of  TNF CD3 cells   total CD3 cells  the aTB group did not interfere with the marker’s expression, were calculated according to published reports led by Portevin we performed a Spearman Correlation Test that showed no et al. (2014) and Mpande et al. (2021), respectively. correlation between the days of treatment in month 1 and our For multiparametric analyses, dimensional reduction and variables (Supplementary Figure 2). clustering were done using OMIQ data analysis software As shown in Figures 1A–D, the percentage of all (OMIQ, Inc. Santa Clara, CA) after preliminary cleaning of populations studied (CD27−, CD38+, HLA-DR+ and Ki-67+) data with FlowJo of aggregates, dead cells and debris. All within Mtb-specific CD4+ T-cells was increased in aTB CD3 positive events from all samples were selected for compared to LTBI in response to ESAT-6/CFP-10 recombinant subsequent analysis on the OMIQ platform. flowCut proteins (p = 0.0092 for CD27−, p = 0.0162 for CD38+, p = 0.001 algorithm was run to check and exclude for any aberrant for HLA-DR+ and p < 0.0001 for Ki-67+). Additionally, the regions of all files analyzed. Subsequently, a UMAP analysis HLA-DR+ and Ki-67+ populations were also associated with was performed to visualize the different CD3 subsets in aTB patients after stimulation with PPD (p = 0.0008 and groups. FlowSOM was run to cluster the data using p < 0.0001, respectively). The trends observed in individuals metaclustering with k = 50. After the FlowSOM analysis, the who finished the anti-TB regimen were comparable to those in metaclusters were grouped into commonly recognized LTBI individuals. As seen again in Figure 1, following biological populations. All clusters were plotted on treatment, a decrease in the percentages of all the phenotypes traditional dot plots for phenotype confirmation as for the was observed, with significance for the CD38 (p = 0.0384 for standard manual gating analysis. ESAT-6/CFP-10) and Ki-67 (p = 0.0293 for ESAT-6/CFP-10, Frontiers in Microbiology 05 frontiersin.org Díaz-Fernández et al. 10.3389/fmicb.2022.885312 A B C D FIGURE 1 CD27−, CD38+, HLA-DR+, and Ki67+ phenotype from Mtb-specific CD4+ T-cells of each patient group. Percentage of CD27−(A), CD38+ (B), HLA- DR+ (C), and Ki67+ (D) within TNF-α+ and/or IFN-γ+ CD4+ T-cells after stimulation with ESAT-6/CFP-10 or PPD (left and right half of graph, respectively) in patients with active TB in the beginning and end of treatment, as well as LTBI individuals. Data plotted with median and interquartile range. Differences between aTB and LTBI conditions were calculated using the two-tailed Mann–Whitney U-test. Differences between aTB and eTrt groups were calculated using a mixed statistical model controlling repeated measures on logit-transformed data. *p<0.05, **p<0.01, ***p<0.001, ****p<0.0001. No indication of p value implies non significance. aTB, active TB; LTBI, latent tuberculosis infection; eTrt, aTB patients after anti-TB treatment. p = 0.022 for PPD) markers. Reduction of CD27− and HLA-DR+ CD27 MFI ratio provides a useful tool to populations in activated CD4+ T-cells was statistically characterize aTB significant only when performing a Mann–Whitney unpaired analysis excluding the matched samples (for CD27−, p = 0.0016 We also evaluated an alternative approach based on the ratio and p = 0.0001 and for HLA-DR+, p = 0.0482 and p = 0.0649 between the CD27 MFI in total CD4+ T-cells and the MFI of after stimulation with ESAT-6/CFP-10 and PPD, respectively). CD27 in Mtb-specific CD4+ T-cells. An increase of this ratio is a No differences were detected on any of the markers’ direct consequence of a decrease of the CD27+ Mtb-specific CD4+ expression regarding BCG-status after PPD stimulation T-cells phenotype associated with active disease. Overall, our data (Supplementary Figure 3). When analyzing only the patients shows a reverse trend of the CD27 MFI ratio with aTB to that monitored at the beginning and at the end of treatment, inter- observed in the percentage of CD27− cells among the Mtb-specific individual variation of the marker’s expression was observed CD4+ cells. As seen in Figure 2A, the ratio of CD27 MFI was (Supplementary Figure 4). increased in aTB patients compared to LTBI individuals after Frontiers in Microbiology 06 frontiersin.org Díaz-Fernández et al. 10.3389/fmicb.2022.885312 TABLE 2 ROC curve analysis of each marker used in the study. A B Marker AUC (95% CI), p ESAT-6/CFP-10 PPD CD27 Mtb-specific CD4 − + 0.7386 (0.5805-0.8968), 0.5714 (0.3841-0.7588), T-cells 0.0120 0.4402 CD38+ Mtb-specific CD4+ 0.7222 (0.5563-0.8881), 0.6078 (0.4268-0.7888), T-cells 0.0167 0.2442 HLA-DR+ Mtb-specific 0.7967 (0.6514-0.9421), 0.8020 (0.6679-0.9361), CD4+ T-cells 0.0140 0.0011 Ki67+ Mtb-specific CD4+ 0.8699 (0.7533-0.9866), 0.9198 (0.8380-1.0000), T-cells <0.0001 <0.0001 CD27 ratio MFI 0.7222 (0.5473-0.8972), 0.6015 (0.4199-0.7831), FIGURE 2 0.0167 0.2727 CD27 MFI ratio is increased in aTB patients over LTBI individuals (ESAT-6/CFP-10-specific) and patients after anti-TB treatment AUC, area under the curve; CI, confidence interval. (PPD-specific). A ratio of CD27 MFI was calculated as suggested by Portevin et al. The numbers result from the division of the MFI of CD27 in CD4+ T-cells over MFI of CD27 in TNF-α+ and/or their diagnostic accuracy of aTB patients over the LTBI condition IFN-γ+ CD4+ T-cells. (A) CD27 MFI ratio after ESAT-6/CFP-10 or (Table 2). As expected, highest AUC values (95% confidence (B) PPD stimulation in patients with active TB in the beginning and end of treatment, as well as LTBI individuals. Data plotted interval, CI) corresponded to the marker which provided the with median and interquartile range. Differences between aTB highest significant discrimination between aTB and LTBI, Ki-67 and LTBI conditions were calculated using the two-tailed Mann– Whitney U-test. Differences between aTB and eTrt groups were [for ESAT-6/CFP-10, AUC 0.87 (0.75–0.99), p < 0.0001; for PPD, calculated using a mixed statistical model controlling repeated AUC 0.92 (0.83–1.00), p < 0.0001]. Albeit lower, good AUC values measures on logit-transformed data. *p<0.05. aTB, active TB; were also obtained for HLA-DR marker with strong significance LTBI, latent tuberculosis infection; eTrt, aTB patients after anti-TB treatment. [for ESAT-6/CFP-10, AUC 0.80 (0.65-0.94), p = 0.0014; for PPD, AUC 0.80 (0.67–0.94), p = 0.0007]. All ROC Curves, as well as sensitivity and specificity cut-off values, can be found in Supplementary Figure 7. ESAT-6/CFP-10 stimulation of T-cells (p = 0.0162) (Figure 2B). A difference was found when comparing aTB and eTrt groups after PPD stimulation when performing a Mann–Whitney unpaired Multiparametric analyses reveal the analysis excluding the matched samples (p = 0.0044). In order to presence of cell subsets with significant demonstrate the association between the proportion of CD27− differences in abundance in aTB patients Mtb-specific CD4+ T-cells and the CD27 MFI ratio, we performed before and after treatment a Spearman’s correlation test (Supplementary Figure 5). A positive interdependence between the two variables was detected in T-cells To avoid the analytical bottleneck produced by manual gating, responding to both ESAT-6/CFP-10 and PPD, supported by a we aimed to explore the same cytometry data in an unbiased strong correlation coefficient (for ESAT-6/CFP-10: Spearman’s manner using a multiparametric analysis. This approach offered rho = 0.8143, p < 0.0001; for PPD: Spearman’s rho = 0.8766, the possibility of defining complex cell phenotypes that cannot p < 0.0001). be revealed using traditional biaxial data presentation. Additionally, we calculated the ΔHLA-DR MFI (difference in We imported the data on CD3+ populations after ESAT-6/CFP-10 MFI of HLA-DR between total T-cells and Mtb-specific T-cells) to or PPD stimulations into OMIQ and analyzed the data using assess its performance in discriminating the three study groups. Uniform Manifold Approximation and Projection for Dimension An increase of this value was observed on aTB patients over LTBI Reduction (UMAP) and FlowSOM for clustering populations. In individuals after stimulation with ESAT-6/CFP-10 (p = 0.0341; total, 50 different cell clusters were defined, being 11 of them Supplementary Figure 6). MFI ratios of CD38 and Ki-67 were also positive for TNF-α and/or IFN-γ. Within this subset, at least seven analyzed but showed no difference between study groups (data clusters displayed significant changes in expression between the not shown). three study groups (Figure 3A). Some of these clusters presented similar features and could broadly be classified into a “maturation phenotype” [CD4+ CD27+ cells with expression of TNF-α (cluster Ki-67+ and HLA-DR+ populations yield #15_16) or IFN-γ (cluster #20)] or an “activation phenotype” the highest discriminative performance [CD4+ HLA-DRint cells with expression of TNF-α (cluster #11) or both TNF-α and IFN-γ (clusters #8, #12)]. One of the clusters did ROC curve analyses were performed for both ESAT-6/ not show our markers of interest and just presented low expression CFP-10 and PPD stimulations for each marker in order to explore of cytokines TNF-α and IFN-γ (cluster #13). Frontiers in Microbiology 07 frontiersin.org Díaz-Fernández et al. 10.3389/fmicb.2022.885312 A B C D E FIGURE 3 Results from multiparametric analyses of the samples. (A) UMAP based on the expression of CD4, CD8, TNF-α, IFN-γ, CD27, CD38, HLA-DR and Ki-67 markers in CD3+ cells from our dataset containing LTBI individuals and aTB patients before and after treatment, after stimulation with ESAT-6/CFP-10 or PPD. Colored clusters indicate populations with difference in abundance depending on disease status, obtained with FlowSOM and analyzed within TNF-α+ and/or IFN-γ+ subsets. In background, all 50 cell clusters defined. (B,D) Box and dot plots showing percentage (Y axis) of each cluster of interest in each respective group [(B) for samples after PPD stimulation, (D) for samples after ESAT-6/CFP-10 stimulation. Data plotted with median and interquartile range. (C,E) Volcano plot displaying logarithm scale of fold-change of percentage ratio of sample from aTB patients over LTBI individuals (left) and patients who completed treatment (right; C) for samples after PPD stimulation, (E) for samples after ESAT-6/CFP-10 stimulation]. Positive values (logFC>1) show clusters whose proportion is increased in aTB, while negative values (logFC<−1) show clusters whose proportion is decreased in aTB. Significant samples are represented above the threshold (q<0.05). Volcano plots were automatically produced by the OMIQ software. aTB, active TB; LTBI, latent tuberculosis infection; eTrt, aTB patients after anti-TB treatment, UMAP: uniform manifold approximation; FDR: false discovery rate. Frontiers in Microbiology 08 frontiersin.org Díaz-Fernández et al. 10.3389/fmicb.2022.885312 Figures 3B,C show the results obtained for samples infections. Our data gathered on these also confirms what has stimulated with PPD. As it can be seen, the percentage of been published on the topic: CD38 expression on activated population of each cluster was compared between the aTB, CD4+ T-cells was increased in aTB patients after ESAT-6/ LTBI and eTrt groups (Figure 3B). No differences were found CFP-10 stimulation (Luo et al., 2021), but HLA-DR+ and Ki-67+ between the aTB and LTBI groups for any cluster. However, as populations showed the most significant association with evidenced by median log2 fold-changes [log2FC(aTB/eTrt) > 1 active disease in all conditions. These findings are consistent or < −1 when increased or decreased in aTB samples, with most of the previous research in the field (Adekambi et al., respectively] and confirmed by FDR analyses (q < 0.05), 2015; Silveira-Mattos et al., 2020). AUC values obtained for the clusters #8, #11, and #13 were significantly increased in aTB discriminating performance of these two proteins, especially patients, whereas cluster #20 was significantly increased in Ki-67, greatly surpass those from CD27, indicating that patients who completed treatment (Figure 3C). An additional activation markers might have more potential than maturation cluster of CD8+IFN-γ+CD27+ cells (cluster #49) was also markers on conventional analyses. identified with a positive association with cured patients In this paper we also evaluated the ratio of CD27 MFI as an (q = 0.059). The same analysis was performed for samples alternative way to measure the expression of the biomarkers. This stimulated with ESAT-6/CFP-10 antigens, showing that cluster method, proposed by Portevin et al. (2014), added a technique #13 was more prominent in active TB patients than in LTBI to discriminate aTB from LTBI similar to measuring CD27− individuals (Figures 3D,E). Together, data from populations but allowing normalization of results, thus multiparametric analyses show a potential role of CD27 and preventing discrepancies raised by positive or negative gating. HLA-DR clusters in differentiating aTB patients before and Here, we show that CD27 MFI quantification mirrors the data after treatment, and warrant more research using obtained by the analysis of percentage of CD27−. This was further unbiased analyses. supported using Spearman’s Correlation test, which shows positive interdependence between both variables. We also performed an analysis on the ΔHLA-DR median fluorescence Discussion intensity biomarker following recent work in South Africa (Mpande et al., 2021), and it provided an even additional Recently, the field of TB diagnosis and management has seen technique for distinguishing latent from active infection. These a rise in the development of tools based on the evaluation of the findings warrant further studies on this approach, either for host immune features. In this study, we have analyzed the validation with the same biomarkers or implementation on expression profile of different biomarkers in specific T-cell subsets other ones. stimulated with Mtb antigens. We have reported modulations on Another objective of this research was to study the efficacy the expression of the four cell markers in Mtb-specific CD4+ of the markers in evaluating anti-TB treatment efficacy. The T-cells, dependent on the presence of clinical disease or infection hypothesis followed was that participants with a successful alone, and that also reflect therapy efficacy. Additionally, we have response to treatment developed similar immunophenotypes provided data from unbiased multiparametric analyses showing to individuals without clinical manifestations. Despite the fact the presence of several cell clusters with potential to characterize that data on treatment monitoring is sparse, some studies have different disease status. shown that T cell activation markers are reduced after The results of our conventional analyses show the treatment (Vickers et al., 2020), and that the same markers can performance of CD27, CD38, HLA-DR and Ki-67 to be used to identify both LTBI and cured individuals (Ahmed discriminate active disease from latent infection. Regarding et al., 2018) or predict relapse (Goletti et al., 2018). In our CD27 receptor, our data suggests that its expression on Mtb- study, a small cohort of patients who completed treatment specific CD4+ T-cells is down-regulated during active disease. showed a significant decrease on the expression CD38+, and These results are in line with most of the published data; in fact, Ki-67+ phenotypes, compared to those at the beginning of CD27 is, out of the four proteins of our study, the one with treatment. Despite the size difference between the groups, our more extensive literature, both in mice (Lyadova et al., 2004) results agree with what has been published on the matter (Hiza and human (Petruccioli et al., 2016; Riou et al., 2017; Acharya et al., 2022). We did not find statistical significance differences et al., 2021; Xu et al., 2021). CD27 is a maturation marker in our mixed model for the HLA-DR and CD27 expression expressed by lymphocytes associated with lack of after anti-TB treatment; however, this can be explained by the responsiveness toward different antigens (Schiött et al., 2004), relatively small sample size of the group of patients who and downregulated in effector differentiated T-cells (Nikitina completed therapy. This limitation was also present when et al., 2012). Therefore, it can be expected that CD27− analyzing each patient monitored individually. We expect to populations are increased in aTB patients. The rationale behind carry out future studies with the necessary population size to the discriminative power of the other three markers is simple: state robust conclusions. they are related to the activation and/or enhancement of The unbiased, multiparametric analysis provides an immune responses, which commonly follow pathogenic additional approach that is in line with literature on the Frontiers in Microbiology 09 frontiersin.org Díaz-Fernández et al. 10.3389/fmicb.2022.885312 evaluation of therapy efficacy via manually gated analyses. The Data availability statement abundance of clusters expressing CD27 was increased after treatment, as commonly do the CD27+ populations in The raw data supporting the conclusions of this article will conventional analysis; and so occurred with HLA-DR+ clusters be made available by the authors, without undue reservation. and populations in the case of patients with aTB. It should be noted that Ki-67, the most discriminative marker, was not defined in any of our 50 clusters. However, given that most Ethics statement clustering techniques are more accurate when the number of data points is high, it might be possible that the low cell count in Ki67+ The studies involving human participants were reviewed and populations posed a difficulty in the identification of such approved by the Hospital Germans Trias i Pujol (reference number subsets. It seems that the multiparametric analyses might open PI-19-149). The patients/participants provided their written the door for investigating unique combinations of biomarkers, informed consent to participate in this study. but much further work is required to establish and standardize this technique. There are limitations in this study that should be addressed. Author contributions First, the strategy chosen for the definition of Mtb-specific cells relies on the measurement of IFN-γ and TNF-α, since we already IL and RV-H designed the study. IL, MF, RV-H, and SD-F showed that CD27 profile was similar in populations positive for designed the experiments. GT, GS, IR, IL, RV-H, and SD-F one or both cytokines (Latorre et al., 2019). However, not all performed the experiments. AS-M, CP, MG, MJ-F, JS, JA, and ZS Mtb-specific CD4+ T-cells express these cytokines (Morgan et al., contributed with resources. IL, MF, and SD-F analyzed the data. 2021). Other approaches for the characterization of this subset IL and JD supervised the study. SD-F wrote the paper. All authors (e.g., measurement of other cytokines or multimeric tetramer contributed to the article and approved the submitted version. staining) should be considered. And second, the immune status of each patient depends on multiple parameters, involving not only host and pathogen genetics but also the age of the host (Veneri Funding et al., 2009), the length and type of antibiotic treatment and the recency of infection (Amiano et al., 2020), among others. This research was supported by a grant from the Instituto de Therefore, it is necessary to take into account the inherent Salud Carlos III (PI18/00411, PI19/01408 and CP20/00070), heterogeneity of the patients when translating potential integrated in the Plan Nacional de I + D + I and cofunded by the biomarkers into clinical applications. The use of healthy controls ISCIII Subdirección General de Evaluación and the Fondo Europeo in future work could help establish the baseline expression of these de Desarrollo Regional (FEDER); a grant from the Sociedad Española markers and highlight their diagnostic potential. Another issue to de Neumología y Cirugía Torácica (project 25/2016; SEPAR; address in future studies is the miniaturization of the assay for its Barcelona, Spain); and from the European Union’s Horizon 2020 implementation as point of care testing. Although flow cytometry Research and Innovation Programme under the Marie Skłodowska- studies are generally unwieldy, they can be simplified as evidenced Curie grant agreement no. 823854 (INNOVA4TB). JD and IL are by recent work on HLA-DR-based (Musvosvi et al., 2018) and researchers from the Miguel Servet programme. AS-M is supported CD38-based (Hiza et al., 2021) rapid assays. Reducing diagnostic by a Juan Rodés (JR18/00022) postdoctoral fellowship from ISCIII. waiting times, test difficulty and costs, among others, is of utmost importance to make the test deployable in areas with high LTBI burden. Acknowledgments In conclusion, our findings on maturation and activation markers CD27, CD38, HLA-DR and Ki-67 on Mtb-specific CD4+ The authors thank Ester Boixadera and Ana Vázquez from the T-cells confirm their promising role as potential TB biomarkers Servei d’Estadística Aplicada de la UAB for their help through the for the characterization of LTBI and aTB. Moreover, we provide data analysis process. The authors also thank all the participants data showing that after finishing therapy, the immune profile of of the study and the clinicians and nurses from the Pneumology these markers resembles that of LTBI individuals. It is crucial to Department of Hospital Germans Trias i Pujol for their evaluate these results in larger cohorts of patients to validate its implication especially to Alan Jhunior Solis Solis for his performance and to study the possibilities of implementation with involvement in patient recruitment and classification. other clinical signs and microbiology tests. We also show how multiparametric profiling of Mtb-specific cell subsets can lead to the discovery of unique cell clusters with different expression Conflict of interest across study groups of aTB, LTBI and cured patients. More research on the topic is necessary in order to pinpoint the link The authors declare that the research was conducted in the between the immune phenotype and the different stages of absence of any commercial or financial relationships that could the disease. be construed as a potential conflict of interest. Frontiers in Microbiology 10 frontiersin.org Díaz-Fernández et al. 10.3389/fmicb.2022.885312 BCG vaccination had no effect in the outcome measures of the analysis Publisher’s note in PPD-stimulated samples. Percentage of CD27−, CD38+, HLA-DR+, and Ki67+ within TNF-α+ and/or IFN-γ+ CD4+ T-cells after stimulation with PPD. aTB patients (up) and LTBI individuals (down) are separated by their All claims expressed in this article are solely those of the vaccination status of BCG. Differences between conditions were authors and do not necessarily represent those of their affiliated calculated using the Mann–Whitney U test. No indication of p value organizations, or those of the publisher, the editors and the implies no significance. reviewers. Any product that may be evaluated in this article, or SUPPLEMENTARY FIGURE 4 Changes in CD27−, CD38+, HLA-DR+, and Ki67+ phenotypes of each claim that may be made by its manufacturer, is not guaranteed or monitored individual before and after treatment. Percentage of CD27−, endorsed by the publisher. CD38+, HLA-DR+, and Ki67+ within TNF-α+ and/or IFN-γ+ CD4+ T-cells after stimulation with ESAT-6/CFP-10 (left) or PPD (right) exclusively for the aTB patients that were monitored before (≤1month) and after (≥6months) anti-TB therapy. Because of exclusion from one of the Supplementary material points from both ends due to analysis restrictions, only patients with both samples positive for the stimulants are shown. Differences between conditions were calculated using the Wilcoxon signed rank The Supplementary material for this article can be found paired test. *p<0.05. No indication of p value implies non significance. online at: https://www.frontiersin.org/articles/10.3389/fmicb. SUPPLEMENTARY FIGURE 5 Strong correlation between the percentage of CD27− in TNF-α+ and/or 2022.885312/full#supplementary-material IFN-γ+ CD4+T-cells and the CD27 MFI ratio after ESAT-6/CFP-10 (left) SUPPLEMENTARY FIGURE 1 and PPD (right) stimulation. Correlation was calculated using the two- Gating strategy used for CD4+ T-cells cytokine secretion and markers tailed non-parametric Spearman test. *p<0.05, **p<0.01, ****p<0.0001. analysis. (A) After rough selection of lymphocytes, aggregated cells aTB, active TB; LTBI, latent tuberculosis infection; eTrt, aTB patients after were taken off by gating on the diagonal that appears with Forward- anti-TB treatment. Scatter (height; FSC-H) vs. Forward-Scatter (area; FSC-A) dot plot. CD4+ SUPPLEMENTARY FIGURE 6 T-cells were gated from a parent population of alive CD3+ T-cells. ΔHLA-DR MFI of each respective group. ΔHLA-DR median fluorescent (B) Mtb-specific population were selected from parent population CD4+ intensity (MFI) was calculated as suggested by Mpande et al. The numbers T-cells and gated based on the expression of TNF-α+ and/or IFN-γ+, result from subtracting the HLA-DR MFI on IFN-γ+ and/or TNF+ CD3+ from which CD27/CD38/HLA-DR/Ki67 expression was studied. The cells to the HLA-DR MFI on total CD3+ cells. (A) ΔHLA-DR MFI after panels are representative of populations found without stimulation (left) ESAT-6/CFP10 or (B) PPD stimulation in patients with active TB in the and after PPD (middle) and ESAT-6/CFP-10 (right) stimulation. beginning and end of treatment as well as LTBI individuals. Data plotted (C) Panels showing representative examples of cell distribution with median and interquartile range. Differences between aTB and LTBI according to each marker of the study (sample shown is from an LTBI conditions were calculated using the two-tailed Mann–Whitney U-test. individual after PPD stimulation). The gates were decided according to Differences between aTB and eTrt groups were calculated using a mixed FMO (Fluorescence Minus One) controls. statistical model controlling repeated measures on logit-transformed SUPPLEMENTARY FIGURE 2 data. *p<0.05. 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