Nowadays, ever evolving LC-MS/MS systems have greatly added to our understanding of the endogenous peptide repertoire and binding motifs of many MHC class I and II molecules (108– 111), as well as of class1b MHC molecules (112). For the classical MHC pathways, the notion has emerged that antigen-presenting cells express approximately 100,000 MHC class I and II molecules at their surface, presenting thousands of different endogenous peptides, at widely divergent abundances (113). LC-MS/MS sequencing can unambiguously identify the epitopes as they are eluted from their antigen-presenting molecules in a qualitative and quantitative manner, revealing both primary epitope sequences, as well as any modifications to them (114). LC-MS/MS analyses have shown that processing inside antigen-presenting cells can generate modified or unpredictable MHC epitopes, such as deamidated (115), citullinated (116), or cysteinylated (117) ligands, as well as ligands arising from protein splicing (118–120) or from alternative reading frames or read-throughs of protein-encoding genes (121–123).

Pathogen-encoded immunoproteomes, including PTMs, generated from the proteome inside infected or antigen endocytosing antigen-presenting cells, should be detectable through LC-MS/MS sequencing approaches as well, although pathogen-derived ligands will be needles in the haystack of eluted *self* epitopes. To facilitate the identification of these *non-se*lf pathogen-derived antigens, targeted LC-MS/MS approaches have been developed (124–127). Foreign epitopes that originate from proteins synthesized during infection inside antigen-presenting cells, such as viral MHC class I epitopes during infection, can be traced using algorithms detecting isotopic patterns in the mass chromatograms of MHC immunoproteomes from carefully mixed infected and non-infected cell cultures that were metabolically labeled during growth (128). Alternatively, epitopes that arise from exogenous proteins endocytosed by antigen-presenting cells during infection, such as bacterial MHC class II epitopes, can be traced back in the MHC-bound peptide repertoire after metabolic labeling of antigen during the prokaryotic cell growth (126,129). However, if PTMs are suspected in the foreign MHC immunoproteome, chromatography, ion fragmentation strategy, and even affinity enrichment strategies will have to be considered accordingly. Until now, only a single study has reported the identification of several Mtb epitopes presented by MHC class I via LC-MS (130). More approaches are underway to extend our knowledge on the naturally processed and MHCpresented Mtb epitopes, including those derived from methylated HBHA, using dedicated LC-MS. These studies include large-scale human monocyte or dendritic cell cultures and either *in vitro* Mtb infection or targeted antigen pulsing. Inhibition of MHC class II presentation upon incubation with live Mtb, mycobacterial lysates, or purified antigens may frustrate these attempts (131, 132). Dedicated isolation and analytical discovery procedures should then help to identify the Mtb epitope "needles" in the *self* "haystack," and increase our knowledge on the role of PTM in the Mtb immunoproteome.

#### **CONCLUDING REMARKS**

Fast developments in LC-MS/MS-based proteomics have enabled the detection of many types of PTMs in proteomes of prokaryotes, including Mtb. Elucidating the role of PTMs in the immunoproteome of protective Mtb protein antigens is important for the molecular optimization of vaccine candidates, and will also greatly benefit from technical advancements in LC-MS/MS.

#### **ACKNOWLEDGMENTS**

We thank Ad de Jong for stimulating discussions. Cécile A. C. M. van Els, Véronique Corbière, Kaat Smits, Hugo D. Meiring, Francoise Mascart, and Camille Locht received funding on Mtb epitope discovery by the EU FP7 Collaborative Project NEWTBVAC (grant no. HEALTH-F32009-241745).

#### **REFERENCES**

innate immune system pulmonary C-type lectin surfactant protein A. *J Biol Chem* (2007) **282**:5133–42. doi:10.1074/jbc.M610183200

and affords protection in a guinea pig model. *Infect Immun* (2003) **71**:1929–37. doi:10.1128/IAI.71.4.1929-1937.2003

**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

*Received: 02 April 2014; accepted: 14 July 2014; published online: 11 August 2014. Citation: van Els CACM, Corbière V, Smits K, van Gaans-van den Brink JAM, Poelen MCM, Mascart F, Meiring HD and Locht C (2014) Toward understanding the essence of post-translational modifications for the Mycobacterium tuberculosis immunoproteome. Front. Immunol. 5:361. doi: 10.3389/fimmu.2014.00361*

*This article was submitted to Microbial Immunology, a section of the journal Frontiers in Immunology.*

*Copyright © 2014 van Els, Corbière, Smits, van Gaans-van den Brink, Poelen, Mascart , Meiring and Locht . This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.*

### The PGRS domain from PE\_PGRS33 of Mycobacterium tuberculosis is target of humoral immune response in mice and humans

#### **Ingrid Cohen1 , Cristina Parada1 , Enrique Acosta-Gío2 and Clara Espitia1\***

1 Departamento de Inmunología, Instituto de Investigaciones Biomédicas, Universidad Nacional Autónoma de México, Mexico City, Mexico 2 Facultad de Odontología, Universidad Nacional Autónoma de México, Mexico City, Mexico

#### **Edited by:**

Juraj Ivanyi, Kings College London, UK

**Reviewed by:**

Diego A. Vargas-Inchaustegui, National Cancer Institute, USA Juraj Ivanyi, Kings College London, UK

#### **\*Correspondence:**

Clara Espitia, Departamento de Inmunología, Instituto de Investigaciones Biomédicas, Universidad Nacional Autónoma de México, Apartado Postal 70-228, 04510 D.F. México, México e-mail<EMAIL_ADDRESS>The PE\_PGRS33 protein is a member of the PE family, which encompasses the PE and the PE\_PGRS subfamilies. Among PE\_PGRS's, this protein is one of the most studied antigens and its immunomodulatory properties are influence by both PE and PGRS domains. However, the contribution of these domains to the host immune recognition of the PE\_PGRS33 protein and their potential role in latent tuberculosis infection in humans is still unknown. In this study, the immunogenic properties of the complete PE\_PGRS33 protein and each domain separately were evaluated in BALB/c mice and latent tuberculosis infected (LTBI) humans. In mice, PE\_PGRS33 and its domains induced similar antibody production and secretion of IFN-γ. PE\_PGRS33 and the PE domain stimulated higher CD4+ and CD8+ T-cell proliferation compared to the PGRS domain. This demonstrated that the principal difference in the immune recognition of the domains is the higher activation of T-cell subpopulations involved in the control of tuberculosis. In humans, the secretion of IFN-γ in response to PE\_PGRS33 was detected in both LTBI and in non-infected vaccinated individuals. The same was observed for antibody response, which targets epitopes located in the PGRS domain but not in the PE domain. These observations suggest that T and B cell responses to PE\_PGRS33 are induced by BCG vaccination and can be maintained for many years in non-infected individuals.This also indicates that the IFN-γ response detected might not be associated with latent tuberculosis infection. These results contribute to the elucidation of the role of the PE\_PGRS33 protein and its PE and PGRS domains in the immune response against Mycobacterium tuberculosis.

**Keywords: Mycobacterium tuberculosis, PE\_PGRS33, PE domain, PGRS domain, latent tuberculosis infection**

#### **INTRODUCTION**

*Mycobacterium tuberculosis,* the causative agent of human tuberculosis, is one of the most successful pathogens known. This bacterium is able to elude the host immune system and starts the disease after the infection or remains latent during long time (1). Many factors that could explain these characteristics were elucidated after the genome sequencing of the *M. tuberculosis* H37Rv (2). The genome sequence of these bacteria also revealed the presence of the PE family, which encompasses the PE and PE\_PGRS subfamilies with about 100 genes scattered throughout the genome. Around 61 of these genes encodes for members of the PE\_PGRS subfamily. These proteins are characterized by a highly conserved PE domain of approximately 110 amino acid residues that contains the motif Pro–Glu (PE) near the N-terminus. This domain is followed by the PGRS (polymorphic GC-rich-sequence) domain, which varies in size from 100–1400 amino acid residues and is rich in repetitive Gly–Gly–X motifs (2).

Some PE\_PGRS proteins are exposed at the bacterial surface, where they can interact with the host immune system (3–5). Antibodies against PE\_PGRS51, PE\_PGRS62, PE\_PGRS33, and the PGRS domain of Wag22 (Rv1759cPE\_PGRS) are present in sera from patients with tuberculosis or during experimental tuberculosis in

mice (6–10). Several PE\_PGRS elicit T-cell responses in humans and are recognized by major histocompatibility complex-I (MHC-I)-restricted CD8+ T cells in mice, suggesting that many members of the PE\_PGRS subfamily are highly immunogenic (11, 12).

PE\_PGRS proteins are also involved in latency. Mutations in *pe\_pgrs* genes of other mycobacterial species have shown decreased persistence in granulomas (13). The PE\_PGRS33 protein is a member of the PE\_PGRS subfamily that stimulates tumor necrosis factor-α (TNF-α) production, one of the cytokines involved in the induction and maintenance of latent tuberculosis infection in animal models mimicking human latency (14–16). The Rv1759cPE\_PGRS antigen induces immune response maintaining the latent infection in a murine model of chronic tuberculosis (17). *M. tuberculosis* clinical strains harboring big genetic variations in the *rv1818c* that codifies the PE-PGRS33 have been associated with clustering of tuberculosis cases and absence of cavitations in the lungs. This suggests that this protein plays a role in the establishment or maintenance of latent infection (18). Until now, the immune response against the PE\_PGRS proteins has not been described in *M. tuberculosis* latent-infected individuals.

Additionally, the PE\_PGRS33 protein plays an important and may be non-redundant role in the pathogenesis of *M. tuberculosis* (19). The sequence of the PE domain of this protein is highly conserved among *M. tuberculosis* clinical isolates (18, 20). This domain directs the cell wall localization of PE\_PGRS33 (21). It has been reported that mutations in the PE domain affect the pro-inflammatory properties of the protein (22). On the other hand, the PGRS domain exhibits the major sequence variations in clinical *M. tuberculosis* strains (20). The PGRS fragment mediates the interaction with toll-like receptor 2 (TLR2) triggering host-cell death (14, 22). Deletions inside this domain can modulate the secretion of TNF-α induced by the PE\_PGRS33 (14). The immunogenic properties of the PE domain have been evaluated in a murine model (9). The contribution of the PGRS domain to the immune response generated by PE\_PGRS33 has been inferred from the study of the complete protein and the PE domain. However, the effect of the PGRS single domain has not been reported.

In this work, the immunogenic properties of the PE\_PGRS33 protein and the PE and PGRS domains were studied in mice. This study was extended to humans where the secretion of IFN-γ and antibodies levels in latent tuberculosis-infected (LTBI) and non-infected individuals were evaluated.

#### **MATERIALS AND METHODS**

### **PREPARATION OF ANTIGENS**

#### **Cloning the PE and PGRS domains of PE\_PGRS33**

The full-length *rv1818c* gene, which codifies for the PE\_PGRS33 was cloned into the pET15b vector (Novagen Inc., Madison, WI, USA) fused to a histidine (His) tag was kindly provided by Dr. M. J. Brennan [CBER, FDA, Bethesda, MD, USA (13)]. The *rv1818c* gene from pET15b was inserted into the plasmid pcDNA3 (Invitrogen, Carlsbad, CA, USA). An 1172 bp fragment (from nucleotide 339 to 1494) encoding the PGRS region of the *rv1818c* gene was amplified by PCR from pcDNA3 using the forward primer 5 0 -GGAATTCCATATGGGGCGCCCACTGATCGGT-30 (which includes an NdeI site) and the reverse primer 50 -ATGGATCCCTAC GGTAACCCGTTCATCCCGTTC-30 containing a BamHI site and a stop codon. The NdeI–BamHI fragment was then cloned in pET15b. The PE coding region of the *rv1818c* gene (from nucleotide 1 to 339) was amplified using the forward primer 50 -CGGGATCCATGTCATTTGTGGTCACGATCC-3 0 holding a BamHI site and the reverse primer 50 - CGGAATTCACAACAGCGCCAGGGCG-30 including an EcoRI site and a stop codon. The EcoRI–BamHI fragment was then cloned into the multiple cloning site of the plasmid pGEX-4T-2 (Amersham Pharmacia, Piscataway, NJ, USA) to create a fusion product with the coding sequence for glutathione *S*-transferase (GST).

#### **Expression and production of PE\_PGRS33, PE, and PGRS domains**

PE\_PGRS33 and its PGRS domain were expressed in *Escherichia coli* C41 (DE3). Bacteria were cultivated at 37°C in Luria–Bertani broth with 100µg/ml ampicillin. All the chemicals were obtained from SIGMA Aldrich, St. Louis, MO, USA unless otherwise stated. Protein expression was induced with 0.5 mM isopropyl-βd-thiogalactopyranoside (IPTG) at OD = 0.6. Cells were harvested by centrifugation, resuspended in phosphate-buffered saline (PBS) with 1× complete ethylenediaminetetraacetic acid (EDTA)-free protease inhibitor (Roche Applied Science, Mannheim, Germany), and disrupted by sonication. After centrifugation, the inclusion bodies were washed sequentially with 2% Triton X-100, 1% Triton X-100, and PBS. The inclusion bodies were dissolved in buffer A [50 mM Na2HPO4 (pH 8.0), 8 M urea, 300 mM NaCl, 10 mM Imidazole] at 4°C for 14 h. The PE\_PGRS33 protein was purified by metal affinity chromatography in an Akta-Prime (GE Healthcare Biosciences, Pittsburgh, PA, USA). The solution of proteins was bound to a His–Trap HP column (GE Healthcare Biosciences, Pittsburgh, PA, USA) previously equilibrated with buffer A. The protein elution was performed using 500 mM Imidazole in buffer. The purified protein was dialyzed and buffer was exchanged for 50 mM Tris–HCl (pH 8.0), 150 mM NaCl.

The PE domain fusion to GST was expressed in *E. coli* BL21 (DE3) grown in Luria–Bertani broth with 100µg/ml carbenicillin at 37°C. Protein expression was induced with 0.25 mM IPTG at OD = 0.6. Cells were harvested by centrifugation and disrupted by sonication. Inclusion bodies were dissolved in 50 mM Tris–HCl (pH 8.0), 150 mM NaCl, 8 M urea, 1 mM dithiothreitol (DTT), 1 mM EDTA. The supernatant was dialyzed against 50 mM Tris– HCl (pH 8.0), 100 mM NaCl, and 1 mM DTT (union buffer) containing 4 and 2 M urea in sequential steps. The final dialysis step was performed against union buffer. A final concentration of 1% Triton X-100, 20µg/ml PMSF, and 1 mM EDTA was added to the dialyzed sample. The suspension was bound to glutathione agarose at 0.5 ml resin per 2 ml sample by the batch method with gentle agitation at 4°C for 12 h. The resin was washed with 20 bed volumes of union buffer/1% Triton X-100 and then with 20 bed volumes of union buffer. The PE protein was eluted by incubation with elution buffer [50 mM Tris–HCl (pH 8.0), 100 mM NaCl, and 20 mM reduced glutathione] at 4°C for 90 min. The glutathione was removed by dialysis against 50 mM Tris–HCl (pH 8.0), 100 mM NaCl.

#### **MURINE MODEL**

#### **Preparation of PE\_PGRS33 for the immunization of mice**

A total amount of 100µg of recombinant PE\_PGRS33 was resolved in 12% polyacrylamide gels containing SDS according to the discontinuous buffer system of Laemmli (23). Proteins were transferred to nitrocellulose membranes (Amersham Pharmacia, Piscataway, NJ, USA). The protein band was identified by temporary staining with Ponceau S solution. The portion of the membrane with the identified protein was cut and converted into antigen-bearing particles using a previously described method (24). Briefly, the protein band was excised from the nitrocellulose sheet, cut in small pieces, and dissolved in dimethyl sulfoxide. The PE\_PGRS33-bearing nitrocellulose was precipitated with 0.05 M carbonate/bicarbonate buffer (pH 9.6). After washing three times with PBS, the product was resuspended in 500µl of sterile PBS. Nitrocellulose particles without protein were prepared under same conditions to be used as control. This methodology minimized the presence of undesirable proteins allowing the immunization to be performed only with the protein of interest.

#### **Immunization of mice**

The 6–7 weeks old female BALB/c mice were obtained from Harlan, Mexico. These mice were housed under standard pathogen-free conditions. All animal studies were carried out in strict accordance with the recommendations from the current Institutional Guidelines for the Care and Use of Laboratory Animals. The animal study was previously approved by the Committee for the Care and Use of Laboratory Animals of Instituto de Investigaciones Biomédicas. Two groups of mice (*n* = 4 per group) were used in each of three independent experiments. Mice were immunized by intraperitoneal injection of 20µg of recombinant PE\_PGRS33 on antigen-bearing nitrocellulose (100µl of PBS containing 20µg of protein per mouse). Control mice received 100µl of PBS containing only nitrocellulose particles by the same route. Intraperitoneal booster injections with same amount of antigenbearing nitrocellulose were administered on days 21 and 42 to immunized mice. Control mice were injected with nitrocellulose particles on days 21 and 42.

#### **Carboxyfluorescein diacetate succinimidyl ester proliferation assay**

Spleen cells were obtained from immunized and control mice 2 weeks after the last immunization. Cells were extracted by tissue disruption and suspended in RPMI 1640 medium. All chemicals were obtained from GIBCO, Gran Island, NY, USA, unless otherwise stated. The erythrocytes were lysed by mixing the cells with 0.15 M ammonium chloride (NH4Cl), 1.5 mM buffer HEPES (SIGMA Aldrich, St. Louis, MO, USA), 1 mM sodium bicarbonate (NaHCO3) at room temperature for 5 min. The reaction was stopped by adding 10 volumes of Dulbecco's PBS (DPBS). Later 107 splenocytes were incubated at room temperature in the dark with 0.5µM carboxyfluorescein diacetate succinimidyl ester (CFSE, Invitrogen, Carlsbad, CA, USA) for 5 min. The reaction was stopped by adding nine volumes of RPMI 1640 plus 10% fetal bovine serum (FBS). CFSE-stained cells were centrifuged at 1500 rpm for 5 min, washed twice in DPBS with 10% FBS, and resuspended in RPMI supplemented with 10% FBS, 1.5 mM glutamine, 100 U/ml penicillin, 100µg/ml streptomycin, 1% non-essential amino acids, 20 mM HEPES buffer, and 50µM 2-mercaptoethanol. Viable cells were counted by trypan blue exclusion, and 1.5 million cells were stimulated with 25µg of PE\_PGRS33, PE, PGRS, or GST protein plus 10µg/ml of polymyxin B (Calbiochem, Pacific Center, CA, USA) in 24 well plates at 37°C in 5% CO2 for 96 h. Polymyxin B was added to rule out the possibility of contamination with lipopolysaccharide (LPS). As positive control, 1.5 million CFSE-labeled spleen cells from control and immunized mice were stimulated with 2µg/ml of concanavalin A (SIGMA Aldrich, St. Louis, MO, USA) at 37°C in 5% CO2 for 72 h. The cells were harvested, washed with DPBS with 2% FBS and 0.09% sodium azide (NaN3), and incubated with an anti-mouse FcγR antibody (CD16–CD32, CALTAG, Burlingame, CA, USA) diluted 1:500 to block the non-antigen-specific binding of conjugated antibodies. CFSE-labeled cells were then incubated with phycoerythrinconjugated anti-CD4 antibody (BD Pharmingen, San Diego, CA, USA) diluted 1:200 and allophycocyanin-conjugated anti-CD8 antibody diluted 1:200 (CALTAG, Burlingame, CA, USA) on ice for 15 min. The cells were washed with DPBS with 2% FBS and 0.09% NaN3 and resuspended in 0.5 ml DPBS. Three-color flow cytometry was performed in a fluorescence-activated cell sorting (FACS) Calibur cytometer (BD, Mountain View, CA, USA).

Lymphocytes and blasts were identified by forward scatter (FCS) and side scatter characteristics (SSC) in 10,000 events acquired. The percentage of proliferating cells was determined by gating on CD4+ or CD8+ cells and comparing the proliferating population (CFSEdim) with lineage positive cells that had not divided (CFSEbright). Cellquest™ software was used to acquire and analyze the data. Samples and controls were analyzed under same conditions.

#### **Mouse cytokine assay**

The supernatants from mice cultured spleen cells used in the CFSE proliferation assay were evaluated for IFN-γ production using a Murine IFN-γ ELISA development kit (PEPROTECH, Mexico City, Mexico) following the instructions of manufacturer. Briefly, ELISA plates containing 1µg/ml capture antibody per well were incubated at 4°C overnight. After addition of standards and samples, plates were incubated at room temperature for 2 h. The detection was performed with 0.5µg/ml detection antibody. The plates were incubated at room temperature for 2 h. Avidin peroxidase diluted 1:2000 was added and incubated at room temperature for 30 min. A color reaction was developed using ABTS liquid substrate and absorbance values were measured at 405 nm using an ELISA plate reader.

#### **Antibody detection in mice**

Two weeks after the last immunization blood was collected from the tail veins of the immunized and control mice. The titers of Immunoglobulin G (IgG), IgG1 and IgG2a in sera were determined using the ELISA assay. Briefly, 96-well plates (Maxisorp Nunc Immunoplates) were coated with 5µg/ml of recombinant PE\_PGRS33, PE, PGRS, or GST at 4°C overnight. The plates were blocked with bovine serum albumin (BSA. SIGMA, St. Louis, MO, USA) and incubated with different dilutions of the mouse sera (3 × 102–1 × 105 ). Goat anti-mouse IgG–horseradish peroxidase (HRP) conjugate, IgG1–HRP and IgG2a–HRP antibody (all from ZYMED, San Francisco, CA, USA) were used as secondary antibodies. A color reaction was developed with *o*phenylenediamine tetrahydrochloride (SIGMA, St. Louis, MO, USA), and absorbance values were measured at 492 nm using an ELISA plate reader.

### **STUDY IN HUMANS**

#### **Human donors**

All the 88 volunteers who participated in this study were graduate students from the School of Dentistry, Universidad Nacional Autónoma de México. All participants had been vaccinated with *Mycobacterium bovis* Bacillus Calmette–Guérin (*M. bovis* BCG) when infants. The individuals were between 25 and 32 years old, clinically healthy, and had chest radiography negative for tuberculosis. The study in humans was performed in accordance with the Guidelines for Scientific Research with Humans of the Instituto de Investigaciones Biomédicas. The protocol was previously approved by the Ethics Committee of the same Institute. All participants signed consent forms detailing all relevant information about the nature of the study. All individuals participated voluntarily and their identities will remain undisclosed. No incentives were offered to participants.

#### **IFN-**γ **release assay to detect LTBI and non-infected individuals**

Blood samples were collected in heparinized tubes from each of the 88 participants. Aliquots of 1 ml of heparinized blood were incubated in the presence of the QuantiFERON®-TB Gold Kit (Cellestis Limited, Carnegie, VIC, Australia) antigens ESAT-6, CFP-10, and mitogen in 24-well tissue culture plates at 37°C in 5% CO2 for 16 h. Plasma was obtained by centrifugation and the samples were evaluated for IFN-γ production using the Human IFN-γ ELISA kit provided with the QuantiFERON®- TB Gold Kit following the instructions of manufacturer. Briefly, human IFN-γ standards and plasma samples were added to 96 well microplates coated with murine anti-human IFN-γ. The conjugate murine anti-human IFN-γ HRP was incorporated immediately after samples, standards, and conjugates were thoroughly mixed in a microplate shaker and incubated at room temperature for 2 h. After the addition of the enzyme substrate solution, the plate was incubated at room temperature for 30 min. The reaction was stopped with enzyme stopping solution. The optical density was read after 5 min using a microplate reader. The results were analyzed using the QuantiFERON® Analysis software. The results of this analysis were used to divide the group of participants as LTBI and non-infected individuals.

#### **IFN-**γ **release assay to detect responders to the PE\_PGRS33 complete protein**

An aliquot of 1 ml of heparinized blood obtained from each of the 88 participants was incubated with 25µg/ml of PE\_PGRS33 in 24 well tissue culture plates at 37°C in 5% CO2 for 16 h. Plasma was obtained by centrifugation and the samples were evaluated for IFN-γ production using the Human IFN-γ ELISA kit provided with the QuantiFERON®-TB Gold Kit following the instructions of manufacturer, as above described. The results of this assay identified responders to the complete PE\_PGRS33 protein among the LTBI and non-infected individuals.

#### **IFN-**γ **release assay to study the response to the PE\_PGRS33 protein and its PE and PGRS domains in LTBI and non-infected individuals**

A volume of 5 ml of blood was collected in heparinized tubes and diluted 1:10 with RPMI 1640 medium supplemented with 2 mM glutamine, 100 U/ml penicillin, and 100µg/ml streptomycin (all from GIBCO BRL). An aliquot of 1 ml of diluted blood was incubated in a 24-well plate with 25µg of PE\_PGRS33, PE, PGRS, or GST protein plus 10µg/ml polymyxin B at 37°C in 5% CO2 for 6 days. The concentration of IFN-γ in supernatants was quantified using the Human IFN-γ ELISA kit provided with the QuantiFERON®-TB Gold Kit according to the instructions of manufacturer, as above described.

#### **Antigen-specific antibody detection in LTBI and non-infected humans**

Antibodies against PE\_PGRS33 and their domains were detected in 63 out of 88 sera of the individuals by ELISA assay. This assay was carried out as above described for antibody detection in mice with the following modifications: human sera were diluted 1:100, 1:300, and 1:500. All samples were incubated with anti-human IgG

HRP conjugate. In addition, three samples from LTBI and four from non-infected individuals that produce IFN-γ in response to PE\_PGRS33 were also tested with IgG1 HRP conjugates (Caltag, Burlingame, CA, USA). The color reaction was developed with *o*-phenylenediamine tetrahydrochloride. Absorbance values were measured at 492 nm using an ELISA plate reader.

#### **STATISTICAL ANALYSIS**

Data between groups were compared using the Mann–Whitney *U* test at the 0.05 significance level.

#### **RESULTS**

#### **HUMORAL AND CELLULAR IMMUNE RESPONSE TO PE\_PGRS33, THE PE, AND PGRS DOMAINS IN MICE**

#### **Humoral immune response in mice**

Sera from immunized and control mice were tested using ELISA assay to determine the levels of antigen-specific IgG antibodies against PE\_PGRS33 and its PGRS and PE domains. Similar titers of IgG were observed in both immunized and control mice (**Figure 1A**). Titers of IgG1 and IgG2a were quantified to identify the differences between these IgG subclasses. Similar titers of IgG1 against the complete protein and its domains were detected in all dilutions tested (**Figure 1B**). In contrast, the levels of IgG2a subclass against the PE domain were lower than the levels against the PGRS domain or the complete PE\_PGRS33 protein (**Figure 1C**). This indicated that IgG1 antibodies in sera from the immunized mice targeted the complete PE\_PGRS33 and its domains, whereas the IgG2a antibodies recognized epitopes located exclusively in the PGRS domain.

#### **Antigen-specific T-cell proliferation in mice**

The proliferation of CD4+ and CD8+ T cells was measured in splenocytes of the mice immunized with the PE\_PGRS33 protein to determine the contribution of PE\_PGRS33 and its PE and PGRS domains to the activation of T cells (for flow cytometry histograms, see Figure S1 in Supplementary Material). The PE\_PGRS33 complete protein similarly activated the proliferation of CD4+ and CD8+ T cells (**Figure 2**). Both the PE and PGRS domains stimulated the proliferation of CD4+ and CD8+ T cells. However, the response of the two cell subpopulations against the PE domain was significantly higher than that from the PGRS domain (**Figure 2**). The proliferative responses of lymphocytes from the control and immunized mice were statistically different (**Figure 2**). The GST co-expressed as a fusion product with the PE domain did not impact cell proliferation (**Figure 2**).

#### **INF-**γ **secretion in mice**

The PE\_PGRS33 protein, the PE, and PGRS domains induced significantly higher IFN-γ responses compared with unstimulated cells (**Figure 3**). The concentration of IFN-γ in the immunized mice was also higher than that from the controls (**Figure 3**). The levels of INF-γ secretion after stimulation with PE\_PGRS33 and the domains were similar (**Figure 3**). This indicated that the PE\_PGRS33, the PE, and PGRS domain are inducers of cellular immune response in mice.

**FIGURE 1 | Humoral immune response to PE\_PGRS33, PGRS, and PE in immunized mice.** BALB/c mice were immunized with PE\_PGRS33 and sera were collected 15 days after the last immunization. IgG **(A)**, IgG1 **(B)**, and IgG2a **(C)** responses to PE\_PGRS33 (), PE (N), PGRS ( ), and the control protein GST (), were evaluated by ELISA assay. For total IgG determination, each serum was diluted 1:100 and for IgG1 and IgG2a determination, mice sera were diluted as indicated in the figure. Bars **(A)** and datum points **(B,C)** are the average readings ± SD of data from four mice in the group, and the results showed are representative of three independent experiments.

#### **IMMUNE RESPONSE IN HUMANS**

#### **INF-**γ **responses to the complete PE\_PGRS33 protein in LTBI and non-infected individuals**

From the 88 individuals that participated in the study, 14 were identified as LTBI and 74 as non-infected (**Table 1**). To determine whether PE\_PGRS33 is inducing an immunological response in humans, the secretion of IFN-γ by whole blood cells stimulated with the PE\_PGRS33 protein was measured. The results obtained showed that the blood cells from 28.5% of LTBI secreted IFN-γ in response to the PE\_PGRS33 compared to the 21.6% from the non-infected individuals (**Table 1**). This suggests that the IFN-γ response to the PE\_PGRS33 protein is not associated with latent tuberculosis infection.

**FIGURE 2 | Antigen-specific proliferation of CD4**+ **and CD8**+ **T cells in immunized mice.** Splenocytes from PE\_PGRS33-immunized mice were stained with CFSE and incubated with 25µg of PE\_PGRS33, PGRS, PE, or GST protein plus 10µg of Polymyxin B for 4 days. Spleen cells from mice injected with only nitrocellulose were also cultured with antigens (control). Cells without the antigens were incubated for the same length of time (unstimulated). Splenocytes were then labeled with anti-CD4-phycoerythrin **(A)** or anti-CD8-allophycocyanin **(B)** monoclonal antibodies and the percentage of proliferating cells were determined by CFSE dilution and flow cytometry. Each bar represents the mean ± SD of data from four mice per group, and the results are representative of those obtained from three independent experiments.

**FIGURE 3 | Antigen-specific IFN-**γ **secretion in immunized mice.** Spleen cells from mice immunized with PE\_PGRS33 or from control mice were incubated with 25µg of PE\_PGRS33, PGRS, PE, or GST recombinant purified proteins plus 10µg/ml of polymyxin B for 4 days. The culture supernatants were evaluated for IFN-γ production using ELISA assay. Each bar represents the mean ± SD of data from four mice per group. Representative results of three independent experiments are shown.

#### **Table 1 | IFN-**γ **release assay to detect responders to the PE\_PGRS33 complete protein in LTBI and non-infected individuals**.

#### **INF-**γ **response to PE\_PGRS33 and its PE and PGRS domains in LTBI and non-infected individuals**

From the 20 individuals (4 from LTBI and 16 from non-infected) that showed positive IFN-γ response to the PE\_PGRS33 protein, only 7 were further tested for immune response to the PE and PGRS domains (**Table 1**). This group of participants that agreed to continue participating in the study included three LTBI and four non-infected individuals.

The secretion of IFN-γ in response to the PE\_PGRS33 protein and its PE and PGRS domains was quantified in whole blood cells from the seven participants with positive IFN-γ response to PE\_PGRS33. The results indicated a higher secretion of IFN-γ in response to the PE\_PGRS33 protein in non-infected individuals than in LTBI individuals (**Figure 4**). A tendency for IFN-γ secretion to be higher in response to the PE domain than the PGRS domain was observed (**Figure 4**).

#### **Antigen-specific humoral immune response in LTBI and non-infected humans**

The serum from each of the seven individuals from LTBI and from non-infected individuals that produce IFN-γ in response to PE\_PGRS33 was tested for antibody response using the ELISA assay. Human anti-IgG and IgG1 antibodies were used to detect specific antibodies against the PE\_PGRS33 protein and its PE and PGRS domains. The IgG response against the PE domain was significantly lower compared to that from the PE\_PGRS33 complete protein in the non-infected (*p* < 0.05) and in the LTBI individuals (*p* < 0.05) (**Figure 5A**). The IgG response against the PE was lower than that from the PGRS (*p* < 0.05) in non-infected individuals. On the other hand, the IgG response against the PE was as low as the response against the negative control (GST) in the LTBI individuals (**Figure 5A**). The IgG1 response against the PE domain was significantly lower than that against the PGRS domain and the PE\_PGRS33 protein in non-infected and LTBI individuals (**Figure 5B**).

Furthermore, levels of IgG against PE\_PGRS33 and their PGRS and PE domains were detected by ELISA in 63 sera from LTBI and non-infected individuals. Based in the above assay, only individuals with OD 600 nm over 0.3 were considered to have a significant amount of antibodies. It is worth of note, that 58.4% of non-infected individuals showed antibodies against the complete protein and a higher number of sera 66.6% recognized the PGRS domain. Results are shown in **Table 2**.

Together these results indicated that the humoral immune responses against PE\_PGRS33 targets epitopes mainly located in the PGRS domain.

**FIGURE 4 | INF-**γ **response to the PE\_PGRS33 and its PE and PGRS domains in LTBI and non-infected individuals.** Diluted whole blood cells were stimulated with 25µg of PE\_PGRS33, PE, PGRS, or GST protein plus 10µg/ml of polymyxin B for 6 days. IFN-γ in the supernatants was quantified using the Human IFN-γ ELISA kit provided with the QuantiFERON®-TB Gold Kit. Letters represent each individual tested and symbols correspond to the amount of IFN-γ produced by each of them.

#### **DISCUSSION**

The PE\_PGRS33 protein has been involved in the pathogenesis of *M. tuberculosis* (18) and it is known that the PE domain is required for the protein translocation through the mycobacterial cell wall and the induction of primary necrosis (21, 25). The PGRS domain interacts with the TLR2-inducing apoptosis, targets the mitochondria triggering necrosis, and is responsible of the immunomodulatory properties of the entire protein (14, 22, 25). Even though the mentioned characteristics of the PE and PGRS domains have been elucidated, their contribution to the immunogenicity of the complete PE\_PGRS33 protein has not been described.

In this study, the immunization of mice with the PE\_PGRS33 protein stimulated CD4+ and CD8+ T-cell proliferation as well as IFN-γ secretion. This indicated that PE\_PGRS33 is highly immunogenic. These results agreed with previous reports describing the immunogenic properties of the PE\_PGRS33 (12). The CD4+ and CD8+ T cells are crucial in the protective host response against *M. tuberculosis.* These T-cell subsets migrate to the site of infection to produce the cytokines involved in the control of the disease (26, 27). The proliferation of CD8+ T cells caused by the immunization with the gene *rv1818c*, which codifies for PE\_PGRS33 has been reported (12). The activation of CD4+ T cells in response to PE\_PGRS33 presented in this work contribute to the knowledge of T cells subpopulations involved in the immunological response against this protein. These findings support the potential use of PE\_PGRS33 as a vaccine candidate for tuberculosis (12).

The absence of secretion of IFN-γ in response to the full-length PE\_PGRS33 protein has been reported in C57Bl/6 mice (9). In contrast, high concentrations of IFN-γ secreted using BALB/c

**Table 2 | IgG levels against PE\_PGRS33 and their PGRS and PE domains detected by ELISA in LTBI and non-infected individuals**.

Sera from LTBI and non-infected vaccinated individuals were diluted 1:300.

mice were obtained. These results agreed with those published by Chaitra et al. (12) in same mice strain. The BALB/c mice were immunized with protein in the present study, while DNA and DNA prime-protein boosted were used in published works (12). Therefore, the immunization method does not explain the contrasting results. Such discrepancy is probably due to the dissimilar strains of mice used. This indicates that differences in the MHC might have an impact in the immune recognition of the PE\_PGS33 protein.

The results of the cellular immune response in mice indicated that the PE and PGRS domains triggered the proliferation of CD4+ and CD8+ T cells. In agreement, Chaitra et al. (12) reported epitopes in the PE and PGRS domains presented to MHC-I and inducing effectors functions in CD8+ T cells. A MHC-II-restricted epitope found in the PE\_PGRS53 is capable of stimulating CD4+ T-cell responses in human reactors to PPD (28). A comprehensive analysis of MHC-II epitopes has not been performed in PE\_PGRS33. However, the activation of CD4+ T cells observed in this work suggested that both domains carry peptides inducers of MHC-II-dependent responses. According to the results obtained, both domains stimulated comparable IFN-γ secretion levels while the PE domain was the main inducer of proliferation of CD4+ and CD8+ T cells. This suggested that the PE domain could be stimulating a higher proliferation rate in these subpopulations to perform other functions besides the production of IFN-γ, as described previously (27).

When the PE\_PGRS33 was used as immunogen in mice, the induced IgG levels to the full-length protein and to its domains was very similar. A possible explanation to this observation could be that when the domains are separated, they lose their original conformation and expose cryptic epitopes that are recognized by the antibodies generated in the immunized animal. On the other hand, in the complete protein these antigenic determinants remain hidden. This demonstrated that both domains are as highly antigenic as the entire protein in mice. The levels of IgG subclasses were further analyzed to detect differences in response to the domains studied. The IgG2a antibodies were directed to the complete protein and the PGRS domain whereas the IgG1 targeted all three antigens. The titration of these IgG subclasses revealed higher IgG1 levels than IgG2a. This showed that the IgG2a response is masked by the high IgG1 titer, which is the mayor contributor to the total IgG. These results indicated that PE and PGRS are antigenic in BALB/c mice with differences in the recognition at IgG subclass levels.

The role of some PE\_PGRS proteins in mycobacterial persistence has been described (13, 17, 18). The identification of antigens interacting with the immune system during the latent infection will be essential in the development of immunological markers for this particular condition. One of the hypotheses of the present study was that PE\_PGRS33 could be an important antigen in *M. tuberculosis* latency in humans. For this reason, a cellular immune response to PE\_PGRS was expected in LTBI individuals. The results obtained in humans indicated that the IFN-γ response to the PE\_PGRS33 protein might not be associated with latent tuberculosis infection. The high number of LTBI individuals with negative response to the PE\_PGRS33 might be explained by the possible infection with strains not expressing *rv1818c* gene. Another reason could be the infection by strains containing large variations in the gene sequence. This genetic variation would result in significant changes in the PE\_PGRS33 leading to the nonrecognition by the immune system. Both mechanisms have been described to be a source of polymorphism for PE\_PGRS members in clinical isolates of *M. tuberculosis* (20, 29–32).

The IgG1 subclass has been reported to be the predominant isotype in tuberculosis infection (33). For this reason, the humoral immune response to the PE\_PGRS33 protein and the PE and PGRS domains was evaluated in LTBI and non-infected individuals by determination of total IgG and IgG1. The results showed that the antibody response was directed against the PE\_PGRS33 protein targeting specifically the PGRS domain. The PGRS domain of PE\_PGRS33 is rich in Gly–Gly–Ala–Gly–Gly repeats. These sequences could be the target of the antibody response observed in this study because proteins with repetitive amino acid sequences have been identified as immunodominant in rabbits and humans (7). In agreement, the PE\_PGRS62 protein induced a strong antibody response against the full-length protein and a weak response to its PE domain in LTBI and non-infected humans (8). This supports the pattern of antibody recognition observed in this study for PE\_PGRS33. The antibody response to the PE\_PGRS33 in noninfected individuals can be attributed to *M. bovis* BCG vaccination. This indicates that sera reactivity to this protein in healthy individuals is independent of the infection with *M. tuberculosis*. In the PE\_PGRS33 responders who participated in the second stage of the study, the cellular immune recognition of PE\_PGRS33 showed a tendency to be higher in non-infected individuals compared with LTBI individuals. For the protein domains a clear tendency was not observed. In studies involving large populations a more evident trend might be obtained.

In conclusion, it was demonstrated that the PE and the PGRS domains have a role in the cellular and humoral immune response stimulated by the PE\_PGRS33 protein in BALB/c mice. The PE\_PGRS33 also induced the activation of T-cell subpopulations involved in the control of tuberculosis and secretion of IFN-γ. This confirmed the potential use of the PE\_PGRS33 protein as candidate vaccine for tuberculosis and further increased the understanding of the immunogenicity of this protein. The IFN-γ response in humans to PE\_PGRS33 protein might not be associated with latent tuberculosis infection. In this context, the PE\_PGRS33 will not be suitable as immunological biomarker for this condition. The IFN-γ response and the sera reactivity to the PE\_PGRS33 protein in healthy individuals is independent

of the infection with *M. tuberculosis*. These observations suggest that T and B cell responses to PE\_PGRS33 could be induced by BCG vaccination and can be maintained for many years in noninfected individuals. Additionally, the humoral immune response against PE\_PGRS33 in humans targets epitopes located in the PGRS domain. All the findings reported here contribute to the elucidation of the role of the PE\_PGRS33 protein in the immune response against *M. tuberculosis*.

#### **AUTHOR CONTRIBUTIONS**

Ingrid Cohen carried out the experimental procedures unless otherwise stated, performed statistical analysis, participated in the experiment design, and wrote the manuscript. Cristina Parada carried out ELISA assays in human studies and helped in mice experiments. Enrique Acosta-Gío participated in the design and coordination of the human sampling. Clara Espitia conceived and coordinated the study, participated in the experiment design, and wrote part of the manuscript. All authors read and approved the final manuscript.

#### **ACKNOWLEDGMENTS**

Authors acknowledge Carlos Castellanos for his help in the FACS data acquisition, Erika Segura for technical assistance, and Dr. Alejandro Negrete for critical editorial assistance. Ingrid Cohen was a Ph.D. student in the Programa de Doctorado en Ciencias Biomédicas, Universidad Nacional Autónoma de México and recieved a scholarship from Universidad Nacional Autónoma de México. This work was supported by grants from Consejo Nacional de Ciencia y Tecnología (CONACyT) No. 81214 and Dirección General de Asuntos del Personal Académico (DGPA) IN221107.

#### **SUPPLEMENTARY MATERIAL**

The Supplementary Material for this article can be found online at http://www.frontiersin.org/Journal/10.3389/fimmu.2014.00236/ abstract

#### **REFERENCES**

**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

*Received: 01 February 2014; accepted: 06 May 2014; published online: 27 May 2014. Citation: Cohen I, Parada C, Acosta-Gío E and Espitia C (2014) The PGRS domain from PE\_PGRS33 of Mycobacterium tuberculosis is target of humoral immune response in mice and humans. Front. Immunol. 5:236. doi: 10.3389/fimmu.2014.00236 This article was submitted to Microbial Immunology, a section of the journal Frontiers in Immunology.*

*Copyright © 2014 Cohen, Parada, Acosta-Gío and Espitia. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.*

### Immunogenicity of 60 novel latency-related antigens of *Mycobacterium tuberculosis*

*Madel Mar Serra-Vidal 1,2,3, Irene Latorre1,2,3, Kees L. C. M. Franken4, Jéssica Díaz 1,2,3, Maria Luiza de Souza-Galvão2,5, Irma Casas 2,6, José Maldonado7, Cèlia Milà5, Jordi Solsona5, M. Ángeles Jimenez-Fuentes 5, Neus Altet 5, Alícia Lacoma1,2,3, Juan Ruiz-Manzano2,3,8, Vicente Ausina1,2,3, Cristina Prat 1,2,3, Tom H. M. Ottenhoff 4 and José Domínguez 1,2,3\**

*1 Department of Microbiology, Institut d'Investigació en Ciències de la Salut Germans Trias i Pujol, Hospital Universitari Germans Trias i Pujol, Badalona, Spain*

*2 Department of Genetics and Microbiology, Universitat Autònoma de Barcelona, Bellaterra, Spain*

*4 Department of Immunohematology and Blood Transfusion/Department of Infectious Diseases, Leiden University Medical Center, Leiden, Netherlands*

*5 Unitat de Tuberculosi de Drassanes, Hospital Universitari Vall d'Hebron, Barcelona, Spain*

*6 Department of Preventive Medicine, Institut d'Investigació en Ciències de la Salut Germans Trias i Pujol, Hospital Universitari Germans Trias i Pujol,*

*Badalona, Spain 7 Serveis Clínics de Barcelona, Barcelona, Spain*

*8 Department of Pneumology, Institut d'Investigació en Ciències de la Salut Germans Trias i Pujol, Hospital Universitari Germans Trias i Pujol, Badalona, Spain*

#### *Edited by:*

*Juraj Ivanyi, Kings College London, UK*

#### *Reviewed by:*

*Jieliang Li, Temple University, USA Kris Huygen, Scientific Institute of Public Health, Belgium*

#### *\*Correspondence:*

*José Domínguez, Servei de Microbiologia, Hospital Universitari Germans Trias i Pujol, Carretera del Canyet s/n, Badalona 08916, Barcelona, Spain e-mail<EMAIL_ADDRESS>
The aim of our work here was to evaluate the immunogenicity of 60 mycobacterial antigens, some of which have not been previously assessed, notably a novel series of *in vivo*-expressed *Mycobacterium tuberculosis* (IVE-TB) antigens. We enrolled 505 subjects and separated them in individuals with and without latent tuberculosis infection (LTBI) vs. patients with active tuberculosis (TB). Following an overnight and 7 days stimulation of whole blood with purified recombinant *M. tuberculosis* antigens, interferon-γ (IFN-γ) levels were determined by ELISA. Several antigens could statistically significantly differentiate the groups of individuals. We obtained promising antigens from all studied antigen groups [dormancy survival regulon (DosR regulon) encoded antigens; resuscitation-promoting factors (Rpf) antigens; IVE-TB antigens; reactivation associated antigens]. Rv1733, which is a probable conserved transmembrane protein encoded in DosR regulon, turned out to be very immunogenic and able to discriminate between the three defined TB status, thus considered a candidate biomarker. Rv2389 and Rv2435n, belonging to Rpf family and IVE-TB group of antigens, respectively, also stood out as LTBI biomarkers. Although more studies are needed to support our findings, the combined use of these antigens would be an interesting approach to TB immunodiagnosis candidates.

**Keywords: tuberculosis, latent tuberculosis infection, immune response, antigenic stimulation, interferon-γ**

#### **INTRODUCTION**

Tuberculosis (TB) remains one of the most death-causing microorganism worldwide (World Health Organization, 2013). The increasing numbers of drug-resistant TB cases evidence that there is an urgent need for effective diagnosis, drugs and vaccines (Mwaba et al., 2011; Abubakar et al., 2013). The control of latent TB, a stage in which a person is infected with *Mycobacterium tuberculosis* (*Mtb*) but does not currently have active disease, plays an important role for disease control, since dormant bacilli are an enormous reservoir of potential TB cases (Rustad et al., 2009).

*M.tb* can live in a latent stage without causing any clinical symptom and has a potential of reactivation during all the infected individual lifetime. In fact, about one third of the world population is considered to be latently infected (Corbett et al., 2003). The diagnosis of latent tuberculosis infection (LTBI) through the classic tuberculin skin test (TST) has a lack of specificity, and its sensitivity is low in high-risk groups of progression to active TB. The new interferon (IFN)-γ release assays (IGRAs) are immunodiagnostic methods based on the *in vitro* quantification of the cellular immune response. The detection of IFN-γ released by sensitized T cells stimulated with specific *M.tb* antigens enables the identification of infected individuals. The main antigens used in IGRAs, the 6-kDa *M.tb* earlysecreted antigenic target (ESAT)-6 protein, 10-kDa culture filtrate protein (CFP-10), coded in the region of difference (RD) 1, and TB7.7, coded in RD11, are present in *M.tb* but not in any *Mycobacterium bovis* bacillus Calmette-Guérin (BCG) vaccine strain nor in the majority of non-tuberculous mycobacteria (Andersen et al., 2000). Although their specificity is better than in TST, IGRAs do not discriminate between active disease and LTBI (Latorre et al., 2009) and do not clearly distinguish between a recently acquired infection and remote LTBI (Esmail et al., 2012; Pollock et al., 2013). Moreover, their sensitivity barely exceed 80%, and the response level against the antigens used does not seem to indicate high risk of progression to active TB.

*3 CIBER Enfermedades Respiratorias, Instituto de Salud Carlos III, Badalona, Spain*

There is a need of new TB antigens as biomarkers for LTBI immunodiagnosis.

During LTBI, *M.tb* is contained within granulomas, which are formed by activated macrophages and other host components that isolate the infected cells in an organized structure and create an environment that suppresses *M.tb* replication (Esmail et al., 2012). Bacilli must adapt to a variety of environment stresses including reduced oxygen tension, iron limitation, nutrient deprivation, low pH and production of host factors such as nitric oxide and carbon monoxide. Some *in vitro* models demonstrated that *M.tb* is capable of an extensive repertoire of metabolic realignments to enter a defined non-replicating state. The initial response of *M.tb* is encoded by the dormancy survival regulon (DosR, also called DevR, Rv3133c), which leads to induction of a set of ∼50 genes, many of unknown function. DosR controls the expression of genes that allow the bacteria to use alternative energy sources, especially lipids, and genes encoding factors that are selectively recognized by T cells from humans with LTBI (Ernst, 2012). This initial response is followed by a more extensible and more stable response called Enduring Hypoxic Response (EHR), which is comprised of 230 genes involved in the control of the regulatory factors and enzymatic machines of the long-term bacteriostasis program of non-replicating *M.tb* (Rustad et al., 2008). The antigens expressed by *M.tb* vary during the continued pressure mounted by host immune response in the course of the infection (Honer zu Bentrup and Russell, 2001; Demissie et al., 2006). Using *in vitro* models which mimic the conditions that the tubercle bacillus encounter within the host as infection progresses from latency to active disease, some infection phase-dependent genes have been identified and believed to be candidates for immunodiagnostics or for future vaccines (Mukamolova et al., 1998; Zvi et al., 2008; Ottenhoff and Kaufmann, 2012).

DosR regulon is crucial for rapid resumption of growth by involving resuscitation-promoting factors (Rpf) once *M.tb* exits the hypoxic non-respiring state. *M.tb* contains five Rpf -like proteins that are implicated in resuscitation of this microorganism from dormancy to reactivation via a mechanism involving hydrolysis of the peptidoglycan by Rpfs and partnering proteins (Ernst, 2012).

The *in vitro* models mentioned above supposed to recapitulate relevant environmental stress conditions that *M.tb* encounters upon host infection, which allow to identify differentially regulated *M.tb* genes. However, they present some limitations: many of these environmental stress factors may not be well known yet; there may be additive or synergistic effects between multiple stress factors *in vivo* that may easily be missed when studied in isolation *in vitro*; and certain key features of host response-induced stress cannot readily be recapitulated *in vitro*, including granuloma formation and TB necrosis (Commandeur et al., 2013).

For these reasons, different approaches have been developed to analyze the gene expression profiles of intracellular *M.tb* using infected human or murine macrophages, infected murine tissue or artificial granuloma mouse models (Schnappinger et al., 2003; Karakousis et al., 2004; Talaat et al., 2004; Cappelli et al., 2006). Specifically, several *M.tb* genes have been found to be differentially expressed in the lungs of mice strains with high susceptibility to TB during *in vivo* infection, the so-called *in vivo*-expressed *M.tb* (IVE-TB) genes. Interestingly, some of these IVE-TB genes had been also described as induced for nutrient deprivation in *in vitro* models (Commandeur et al., 2013).

Some *M.tb* infection phase-dependent antigens have already been tested in whole-blood assays or in peripheral blood mononuclear cells and may be differentially recognized in individuals with different TB status, that is, subjects with no risk of *M.tb* infection, LTBI individuals and active TB patients (Leyten et al., 2006; Lin et al., 2007, 2009; Black et al., 2009; Schuck et al., 2009; Goletti et al., 2010; Commandeur et al., 2013). The response is commonly measured through the release of IFN-γ. Additionally, IFN-γ plays a central role in the protection against *M.tb* (Cooper et al., 1993; Flynn et al., 1993; Kaufmann, 2001).

However the studies conducted *in vivo*, mice models of latency, seem to merely recapitulate primary disease and are closer to human HIV-TB co-infection. The infectious forms of TB arise after an adequate immune response, which itself may contribute to tissue destruction and cavitation. Hence, there has been a move away from considering IFN-γ as protective, except in the first encounter with the tubercle bacillus, with a renewed emphasis on polyfunctional T cells to contain TB infection (Ernst, 2012; Kaufmann, 2012). However, the ease of measuring IFN-γ gives it applicability to diagnostic tests.

The study of the immune response to the potential immunogenic *M.tb* antigens described above will enlarge our knowledge and will get us closer to the validation of a diagnostic LTBI candidate antigen. We hypothetized that these antigens expressed in latency conditions and involved in reactivation of the dormant bacterial will mainly induce IFN-γ response in LTBI infected patients, and not in no LTBI individuals.

This prospective study aims to evaluate the whole blood IFN-γ response to 60 *M.tb* recombinant antigens, the immunogenicity of some of them has not yet been assessed: 6 DosR regulonencoded antigens, 12 TB reactivation-associated antigens, 1 Rpf antigen, 1 starvation antigen, 6 other stress response-associated TB antigens and 34 IVE-TB antigens (2 of those were EHR and 3 were EHR/starvation), in order to identify potential candidates for new LTBI diagnostic methods. We enrolled subjects with LTBI, active TB patients and controls not *M.tb* infected.

#### **MATERIALS AND METHODS STUDY POPULATION**

We prospectively recruited 578 patients from contact-tracing studies, LTBI screening (such as immigrants from endemic areas or health-care workers) and active TB patients between October 2010 and May 2013. A detailed questionnaire from each subject was collected, including age, birth country, previous TST, BCG vaccination status, history of prior active TB, chest radiography, and other medical conditions (**Table 1**). A total of 8 mL of whole blood was collected in a heparinized tube from each participant. The study obtained approval of the Hospital Universitari Germans Trias i Pujol Ethics Committees (Ref. 10/00214-28/03/2010). They supervised that all the experiments were performed according to the regulatory standards. All the study participants gave written informed consent before entering the study.

*Number of individuals and percentage (%) are indicated.*

Participants were classified, following Spanish Society of Respiratory Pathology (SEPAR) guidelines (Ruiz-Manzano et al., 2008) and also Centers for Disease Control and Prevention (CDC) recommendations (Centers for Disease Control and Prevention, 2000), in four groups depending on the TB status, as is described in detail below. The method used for diagnosing LTBI was TST (PPD RT23, Statens Serum Institute, Copenhagen, Denmark) and QuantiFERON-TB Gold *In Tube* (QFN; QIAGEN, Düsseldorf, Germany).

The following individuals were included as no LTBI: (a) individuals from LTBI screening studies, who tested QFN negative and TST under 10 or 15 mm (depending on the absence or presence of BCG vaccination, respectively); and (b) individuals who reported contact with a TB patient and with negative QFN, whose TST was under 5 mm. All patients included were HIV negative.

As LTBI were included: (a) individuals who reported a contact with a TB patient or from LTBI screening studies, who tested QFN positive; (b) individuals who reported an intense contact with a TB patient, with negative QFN and TST higher than 5 mm (if the subject is BCG vaccinated, the index case has to be smearpositive; if it is smear-negative, TST has to be higher than 15 mm); (c) individuals from LTBI screening studies, who tested QFN negative and whose TST converted (by definition, from under 10 mm to above 10 mm with a change of 6 mm); and (d) individuals from LTBI screening studies, who tested QFN negative and TST positive (higher than 10 mm in non BCG-vaccinated and recent immigrants; and higher than 15 mm in BCG-vaccinated).

Individuals with pulmonary or extrapulmonary active TB, clinically, radiologically and/or microbiologically diagnosed (World Health Organization, 2013) were included.

#### *MYCOBACTERIUM TUBERCULOSIS* **ANTIGENS**

A total of 60 *M.tb* recombinant latency-related antigens were evaluated (**Table 2**): 6 DosR regulon-encoded antigens, 12 TB reactivation-associated antigens, 1 Rpf antigen, 1 starvation antigen, 6 other stress response-associated TB antigens and 34 IVE-TB antigens (two of them were EHR and three were EHR/starvation). They were previously produced at the Department of Infectious Diseases, Leiden University Medical Center following the methododology previously described (Franken et al., 2000). Briefly, antigens were selected from RNA microarray studies after inducing hypoxic conditions in a *M.tb* liquid culture. The selected genes were cloned in *Escherchia coli* and antigens were overexpressed and purified by immobilized metal chelate affinity chromatography. Some antigens were prepared as two or three recombinant protein fragments owing to their large sizes (C, middle [M], and N termini). For IVE-TB genes, mice were infected with *M.tb* and RNA was isolated from mouse lung tissue (Commandeur et al., 2013). After a RT-PCR, highly or differentially expressed genes were selected and cloned by Gateway technology (Invitrogen, Carlsbad, US) in *E. coli* and antigens were obtained as explained before.

Apart from those *M.tb* recombinant antigens, we used 4 control antigens for which immunogenicity and specificity to *M.tb* is well defined: the fusion protein ESAT-6 [Rv3875]/CFP-10[Rv3874], Ag85A[Rv3804c], TB10.4[Rv0288], and PPD (PPD RT 23, Serum Institute, Copenhagen, Denmark).

Antigens were reconstituted in sterile phosphate buffered saline, to a concentration of 50μg/mL and stored at −20◦C. The 60 latency-related antigens were randomly grouped into 10 batches of 6, and the individuals tested randomly selected. Thus, the whole blood from each patient was stimulated with six antigens, and the four control antigens as well.

#### **WHOLE BLOOD ASSAY**

400μL of whole blood were transferred to a 48 well culture plate (Nunc, St. Louis, US) and control antigens were added at a final concentration of 10μg/mL except for PPD, that was **Table 2 | Description of the 4 control and 60** *M.tb* **recombinant antigens tested, included DosR regulon-encoded (***n* **= 6), TB reactivation-associated (***n* **= 12), Rpf (***n* **= 1), starvation (***n* **= 1), other stress response-associated (***n* **= 6), and IVE-TB antigens (***n* **= 34) (Function information source: http://www***.***ncbi***.***nlm***.***nih***.***gov/ nuccore).**

**Table 2 | Continued**

*M.tb recombinant antigens with Rv designation in bold induced a relevant IFN-*γ *response in this study.*

*\*also EHR.*

=*also starvation*

*(Continued)*

added at 1μg/mL. *M.tb* recombinant antigens were tested at a final concentration of 10μg/mL. A negative (RPMI medium; PAA, Pasching, Austria) and a positive control of immunity (phytohemagglutinn, Invitrogen, Carlsbad, US) were included. This procedure was performed in two different plates: one plate was incubated in a 5% CO2 incubator a 37◦C overnight (18 h, short-term stimulation) and the other for 7 days (long-term stimulation). In the long-term incubation plate, blood was previously diluted 1:5 with RPMI 1640 medium supplemented with L-glutamine, penicillin and streptomycin (Weir et al., 2003). After incubation time, supernatants were then collected and stored at −80◦C until tested.

#### **DETERMINATION OF IFN- γ BY ELISA**

The measurement of the amount of IFN-γ released following the antigenic stimulation was evaluated by the commercial ELISA included in the QFN kit and data are presented as pg/mL after subtraction of the negative control. We considered a valid result when the value of the negative control was under 50 pg/ml. The cut-off value for high level of IFN-γ response was arbitrarily set at 20 pg/ml, taking as reference the QFN cut-off.

#### **STATISTICAL ANALYSIS**

The production level of IFN-γ was compared between the groups included in the study. Median and range of the cytokine production was calculated and Mann Withney test was used for pair-wise comparisons and Kruskall Wallis test was used for multiple comparisons. A *P*-value *<*0.05 was considered significant. Data were analyzed using SPSS statistical software (IBM SPSS Statistics 20; IBM Corporation, NY, USA). Graphical representation is based on GraphPad Prism version 4 (GraphPad Software, Inc., San Diego, CA).

#### **RESULTS**

From the 578 participants, 60 were not tested for the determination of IFN-γ because of insufficient samples, eight subjects did not fulfill the inclusion criteria and five subjects were excluded from the study because the amount of IFN-γ in the negative control was too high. In the patients PHA induced high responses, which ratifies the validity of our methodology.

#### **IMMUNOGENICITY OF CONTROL TB ANTIGENS**

We included four control antigens in our study. Significant differences in the IFN-γ responses elicited by all of them could be observed between the three study groups after short-term and after long-term stimulation (**Tables 3**, **4**). The antigens that elicited a higher response were PPD and the fusion protein ESAT-6/CFP-10, followed by TB10.4 and Ag85A.

#### **IMMUNOGENICITY OF DosR REGULON-ENCODED ANTIGENS**

We evaluated six different DosR regulon-encoded antigens (**Figure 1**). Two of them were the C-ter and N-ter domain of a latency antigen (**Table 2**). There were three antigens which presented a differentiated response depending on the TB status group: Rv1733, Rv2627, and Rv0570c (**Tables 3**, **4**). While Rv1733 discriminated between groups when the stimulation was either short-term or long-term, the discrimination of Rv2627 only was significant after short-term stimulation, and Rv0570c was only after long-term stimulation (although with a low IFN-γ response). The best discriminatory response was elicited when whole blood was stimulated overnight with Rv1733 (*p* = 0*.*001), where the infected individuals response was clearly much higher

**Table 3 | Median levels of IFN-γ (pg/ml), minimum and maximum values (in brackets) elicited in no TB infected individuals, subjects with LTBI and active TB patients by the antigens, when tested after short-term stimulation.**

*N indicates the number of subjects in each group. Data were analyzed by Kruskal Wallis test for the comparison of no TB infection, TB infection, and active TB groups of patients. Only significant differences (p < 0.05) were included.*

**Table 4 | Median levels of IFN-γ (pg/ml), minimum and maximum values (in brackets) elicited in no TB infected individuals, subjects with LTBI and active TB patients by the antigens, when tested after long-term stimulation.**

*N indicates the number of subjects in each group. Data were analyzed by Kruskal Wallis test for the comparison of no TB infection, TB infection, and active TB groups of patients. Only significant differences (p < 0.05) were included.*

than in TB patients and higher than the response produced by non-infected individuals. When incubated for 7 days, Rv1733 also induced a high amount of IFN-γ released in infected individuals, being the response much higher than in TB patients. Rv1733 turned out to be a strong immunoresponse inducer, a promising LTBI biomarker and a promising antigen in discriminating between LTBI individuals, active TB patients and non-infected subjects. The Rv1733, considering the 20 pg/ml as a cut-off, accurately predicted 85% (17/20) of LTBI patients in short-term stimulation; and 95% (19/20) in long-term stimulation.

#### **IMMUNOGENICITY OF TB REACTIVATION-ASSOCIATED ANTIGENS**

A total of 12 TB reactivation-associated antigens were evaluated in the study (**Figure 2**). In general, recognition of these antigens was poor in subjects with LTBI and TB patients. However, there were several antigens which showed different IFN-γ production depending on the group of individuals (**Tables 3**, **4**). While Rv1471, Rv1874, Rv1875, Rv2662, and Rv3862 induced differentiate response in infected individuals in short-term stimulation; Rv1471, Rv2622, and Rv3862 induced differentiate and high response in infected individuals in long-term stimulation.

#### **IMMUNOGENICITY OF Rpf, STARVATION AND OTHER STRESS RESPONSE-ASSOCIATED ANTIGENS**

We tested 1 Rpf, 1 starvation, and 6 other stress responseassociated antigens (**Figure 3**). The response to some of those antigens did present statistical differences when compared among groups (**Tables 3**, **4**). Rv2389, and Rv0244 in short and longterm estimulation, and Rv1909 in long-term stimulation induce high response in infected individuals. However, in some of them relevant production of IFN-γ after the stimulation in noninfected individuals was observed. Rv2389 accurately predicted 81% (13/16) of LTBI patients in long-term stimulation.

#### **IMMUNOGENICITY OF IVE-TB ANTIGENS**

We evaluated the immunogenicity of 34 IVE-TB antigens (**Figure 4**). The LTBI individuals were the group that most recognized IVE-TB antigens, although the response level was not very high (**Tables 3**, **4**). In addition to the antigens that induce a significant IFN-γ response (Rv0967, Rv1806, and Rv1957 after short-term stimulation; and Rv0847, Rv2558, and Rv2642 after long-term stimulation), several antigens obtained IFN-γ response in infected individuals: Rv0847, Rv0990, Rv0991, Rv1363, Rv1955, Rv2034, Rv2035, Rv2435n, Rv2642, Rv2643, Rv2658, Rv3420, and Rv3536 after short-term stimulation; and Rv1363, Rv1806, Rv2435n, Rv2643, Rv25658, and Rv3536 after long-term stimulation. However, in some of them the amount of IFN-γ was not very high, and the regions of response overlapped with the response obtained in non-infected individuals.

#### **COMPARISON BETWEEN QFN-POSITIVE AND QFN-NEGATIVE LTBI INDIVIDUALS**

Given that the lack of specificity of the TST, we evaluated if the response of LTBI individuals to the 60 novel latency-related mycobacterial antigens varied according to the result of their QFN. There were four antigens to which the response was statistically different depending on the QFN result (**Table 5**) when used in short-term stimulation. Latently infected individuals responded to Rv2389 (*p* = 0*.*029) and Rv2435n (*p* = 0*.*050) in higher amounts when the individual presented a positive QFN, thus indicating to be promising LTBI biomarkers. However, the

response to Rv2435n overlapped between the two groups. The other two antigens, Rv2660 and Rv2380M, induced a significant response in individuals with a negative QFN (*p* = 0*.*046 and *p* = 0*.*030, respectively), indicating to be possible candidates for remote infection. The response to Rv2380M barely overlapped in the two groups, whereas the response to Rv2660 clearly overlapped. Some of these antigens could be good candidates to be used in combination with the QFN.

#### **EFFECT OF BCG VACCINATION IN THE RESPONSE TO STUDIED ANTIGENS IN INDIVIDUALS WITH AND WITHOUT LTBI**

Among non-infected individuals, there were five antigens in which the response was different according to the vaccination status. Specifically, Rv717, Rv0570n, Rv2658, and Rv2643 induced a significant response in BCG vaccinated individuals (*p* = 0*.*043, *p* = 0*.*009, *p* = 0*.*041, *p* = 0*.*041, respectively). In contrast, it was the non-BCG vaccinated individuals who most responded to Rv2627 (*p* = 0*.*019). Interestingly, while the higher response to antigens in BCG vaccinated individuals was produced after short-term stimulation, the higher response elicited by non-vaccinated individuals was only produced after long-term stimulation.

Regarding the LTBI subjects, BCG vaccinated individuals elicited a significant response to the following antigens: Rv2035, Rv1471, Rv1957, and Rv2435n (*p* = 0*.*016, *p* = 0*.*020, *p* = 0*.*020, *p* = 0*.*015, respectively) when compared to non-BCG subjects. In all four antigens the significance was after overnight stimulation.

#### **DISCUSSION**

In this study we evaluated whether latency antigens induced a response which varied according to the group of individuals. Each category of antigens, that is, DosR regulon-encoded, TB reactivation-associated, Rpf, starvation, IVE-TB antigens and other stress response-associated TB antigens, contained at least one antigen whose statistical analysis was significative.

Regarding the control antigens we studied, in general, the response they induced was higher after 7 days of incubation. PPD and ESAT-6/CFP-10 were the antigens which induced a highest response, followed by the TB10.4 and finally Ag85A, which is in concordance with what Kassa et al. (2012) found. According to our finding, Chegou et al. (2012) observed that the majority of response to *M.tb* infection is largely driven by ESAT6/CFP-10, not by the other antigens that they used as controls (TB7.7, Ag85A/B, and HSP65), where the recognition was poor. Generally speaking, it was observed that infected individuals provided higher responses than those with the disease. In a study performed by Sutherland et al. (2013)it was found, instead, that PPD and ESAT-6/CFP-10 generated dominant responses but very few differences between active TB and LTBI subjects. In the present study, some antigens induced a lower response in active TB patients when compared with non-TB infected subjects. This fact could be explained by the criteria selection followed for including individuals in the non-infected group. In our study, patients from LTBI screening with negative QFN, but TST results under 10 mm (non BCG-vaccinated) or 15 mm (BCG-vaccinated) were considered non-infected, but in some cases some cross-reactivity with the antigens used as a control (including ESAT-6/CFP-10) and the latency antigens could not be rejected. Indeed, in general, in the group of non-infected individuals the IFN-γ responses against ESAT-6/CFP-10 are lower in patients with TST under 5 mm, than in patients with TST over 5 mm (data not shown). On the other hand, results in the literature regarding IFN-γ responses to the these antigens in active TB patients are inconsistent. Possible differences may reside in variations in host genetic makeup, *M.tb* strains, study methodologies or the extent of TB progression, with diminished IFN-γ production during advanced disease (Weir et al., 2003; Jabado and Gros, 2005; Tsenova et al., 2007; Winek et al., 2008; Day et al., 2011).

Among all *M.tb* recombinant antigens we studied, there is one which stands up significantly: Rv1733, which is a probable conserved transmembrane protein and is part of the DosR regulon. As it can be observed in **Figure 1**, this antigen induces a differentiated response between non-infected subjects, infected individuals and TB patients. Specifically, infected individuals are the ones that generate a highest response, followed by the non-infected, and by the patients with the active disease at the end. Rv1733 immunogenity has been previously analyzed, and a genomic study from Zvi et al. (2008) describes it as an immunodominant T cell antigen. Moreover, many authors agree that there is

significantly higher T cell response in LTBI as compared to TB patients (Vordemeier et al., 1991; Leyten et al., 2006; Black et al., 2009; Schuck et al., 2009; Commandeur et al., 2011; Sutherland et al., 2013), and Rv1733 is one of the DosR antigens that induces a highest response. Interestingly enough, this response pattern against Rv1733 is produced after the stimulation during 24 h, which makes it very appealing to be used for diagnostic purposes. In contrast with our finding, Riaño et al. (2012) observed that LTBI and TB patients did not react to Rv1733. In another study with TB patients, a high response to Rv1733 was also obtained (Kassa et al., 2012).

Even though Rv1733 turned out to be a very immunogenic antigen, Rv2389, which belongs to the Rpf family, induced a high response in most of the individuals as well. Kassa et al. (2012) described that the Rv2389 was able to induce a high IFNγ response in active TB patients. In fact, the immunoresponse to Rpf may play a protective role against bacilli reactivation (Riaño et al., 2012). Rv2389 was able to differentiate between noninfected individuals, individuals with LTBI and active TB patients when incubated with whole blood for 7 days, even though some overlapping is present. As observed by Chegou et al. (2012), active TB patients response was much lower than in non-TB individuals. Commandeur et al. (2011), demonstrated Rv2389 specific T cell response in long-term *M.tb* nonprogressors to active TB patients. Riaño et al. (2012), observed higher levels of IFN-γ in the supernatant of stimulated cells from LTBI compared to active TB patients. Huang et al. (2013) demonstrated that LTBI infected through household contacts possessed higher IFN-γ production to Rv2389c than did the community exposed individuals. In addition, QFN-positive individuals responded in a higher level to Rv2389 when compared to QFN-negative individuals. The Rv2389 ability of discriminate between these two groups of patients have been confirmed by receiver operating characteristics curve (ROC) analysis (area under curve = 0.877). Altogether, these findings indicate that Rv2389 would be a good biomarker of LTBI.

Concerning the recently identified IVE-TB antigens, the only research group that has studied their immunogenicity *in vitro* found that some of them induced high levels of IFN-γ (Commandeur et al., 2013). In our study, some antigens showed a certain difference when comparing the three groups of individuals. While the median value was quite low in all groups, a great number of antigens such as Rv0967, Rv1363, Rv1957, Rv2034, Rv3420, or Rv2642 among others were able to induce outstanding IFN-γ responses in some individuals. In concordance with the study performed by Commandeur and coworkers, it was the active TB patients the group who showed a lowest response. They observed that the individuals who generated a

highest response were those that did it with ESAT-6/CFP-10 as well. They also observed that controls not exposed to *M.tb* and individuals with positive TST and negative response to ESAT-6/CFP-10 did not respond to IVE-TB antigens, which shows that there is a specificity linked to *M.tb* exposure. In our study, although some non-TB infected individuals produced IFN-γ after being stimulated with IVE-TB antigens, individuals with LTBI also responded as well. BCG vaccine was ruled out as the response trigger in subjects without LTBI, as T cells from non-BCG vaccinated individuals generated a response as well. However, due the difficulty of totally rule out the infection in the no LTBI individuals, we cannot reject that, alternatively, those responder non-BCG vaccinated individuals were really *M.tb* infected; and that the responder BCG-vaccinated individuals were, in fact, responding to the shared BCG antigens.

Interestingly, the response to Rv2380M and Rv2660 was higher in individuals with a negative QFN than subjects with a positive QFN, indicating that both antigens could be possible biomarkers for remote infection. In the opposite way, Rv2435n induced a higher response in subjects with positive QFN. It may be, therefore, a possible biomarker for recent infection.

Activated lymphocytes and effector T cells that produce IFN-γ from *M.tb* antigens sensitized individuals, persist for a limited time in the circulation once the antigen is cleared (Pathan et al., 2001). It is thought that central memory T cells, but not effector ones, may take several days (rather than hours) to produce effector cytokines (Kaech et al., 2002; Dheda et al., 2007). This is because, the commercial IGRAs are thought to reflect more recent, rather than remote infections. Therefore, contrary to the findings of the TST, in cases of remote infection, the IFN-γ level did not increase during the short period of exposure to the antigen in the *ex vivo* IFN-γ assay at baseline. For these reasons we chose to stimulate short and long term the blood samples with the different latency-related antigens. Interestingly, the higher IFN-γ responses have been obtained after long-term stimulation instead of short-term stimulation: Rv1733, Rv3862, Rv2662, Rv0244, Rv2389, Rv1909, Rv2435n, Rv0847, Rv0967, Rv1806, and Rv2642.

As far as we know, only Goletti et al. (2010) assessed the comparison between individuals recently and remotely infected to five latency mycobacterial antigens. They found that Rv2628 was able to differentiate recent from remote infection, being the individuals with remote infection the group that showed significantly higher IFN-γ whole blood responses. In a very preliminary results, using well TB status characterized individuals, we have observed that responses to some antigens (Rv2380M, Rv0967,

**Table 5 | Median levels of IFN-γ (pg/ml), minimum, and maximum values (in brackets) elicited in latently infected individuals depending on the QFN result.**

*N indicates the number of subjects in each group. Data were analyzed by Mann Whitney test for the comparison of patients with positive QFN and negative QFN. Only significant differences (p < 0.05) were included.*

Rv2435n, and Rv2913) could differentiate between recent and remote infection (data not shown).

The fact of not obtaining response to an antigen that other studies identify as immunogenic, can be due to different host immune responses, *M.tb* strains and variations in the methodology used (Ottenhoff et al., 1998; Caws et al., 2008; Homolka et al., 2010), and also some factors such as ethnicity (host genetics), nutritional status, and microbial environment (Sutherland et al., 2013). The discordance in results between studies could be also attributed to the lack of gold standard for defining LTBI, and the consequent heterogenicity in the study population included in the different studies. The difficulty of establishing a group of LTBI is demonstrated by the criteria followed by the different authors: Leyten et al. (2006) included both patients from contact-tracing studies and also from screening studies; Chegou et al. (2012) included contact-tracing studies individuals, where neither TST nor QFN results were available; Commandeur et al. (2013) included TST positive patients, with exposure to *M.tb* and or with history of traveling to high TB incidence countries; and Sutherland et al. (2013) included household contacts of TB patients or by random community selection or from HIV care clinics with TST higher than 10 mm in HIV negative, and higher than 5 in HIV positive (independently of the BCG status). According to a recent study (Sutherland et al., 2013), which includes individuals from different sub-Saharan African countries, despite possible differences in the criteria of study subjects, there were variations between sites in regards to antigen reactivity, suggesting that need to be considered.

In order to ensure the validity of the promising antigens, we decided to study if some antigens induced a different response depending on whether the individual had been vaccinated with BCG or not. Among the antigens that distinguished between non-infected individuals, infected individuals and patients with TB disease, three of them were also identified when we analyze the effect of the BCG: Rv2627, Rv1471, and Rv1957. In order to measure the magnitude of the BCG influence, the response of non-vaccinated individuals was assessed. Being *p >* 0*.*05 and the charts showing an overlapping of the response between the three groups it seems that BCG has a considerable influence in the results (data not shown).

The effect of the BCG on the immune response against latency *M.tb* antigens has been studied by other authors. Lin et al. (2007) found that, although the homology between the DosR regulon from the BCG strain and from *M.tb* was very high, BCGvaccinated individuals did not present immune response against DosR. Instead, individuals exposed to *M.tb* did respond to DosR. Thus, it seems that the response to antigens linked to the control of LTBI is only generated when there is an exposure to *M.tb*, and it does not depend on whether the individual has been immunized by the BCG, probably because BCG fails to establish long-lived latent infections, and therefore it may not express (or under express) these antigens *in vivo* following vaccination (Honaker et al., 2008). However, this issue warrants further investigation.

The current study presents certain limitations which are worth mentioning. In the first place, it is worth highlighting the difficulty found in the classification of the individuals according to their TB status, specially among BCG-vaccinated individuals, since there is no gold standard assay for LTBI diagnosis. We therefore cannot rule out in some cases a misclassification. Secondly, it seems that some of the studied antigens could present certain lack of specificity; they could be shared in BCG strain and also in other mycobacteria (Lin et al., 2009), since some non-infected and non BCG-vaccinated individuals responded. Anyway, it is not clear whether the cross-reactivity to latency antigens in *M.tb* naive people contributes to the natural protection developed in 90% of the individuals who are infected but do not progress to active TB (Fine, 1995; Brandt et al., 2002). Thirdly, the sample size we could include was certainly limited for some antigens, including some antigens found as promising. Another limitation of our work lies in the fact that we only evaluated the immunoresponse in terms of IFN-γ production by T cells. Combination of other cytokines with IFN-γ can strengthen the diagnostic potential of *M.tb* antigen (Goldsack and Kirman, 2007). However, despite these limitations, this work obtained strong conclusions identifying potential antigens as candidates for further validation studies.

In conclusion, after screening the potential antigenicity in subjects across the spectrum of TB, we could identify promising antigens in all groups of antigens studied. Rv1733, which is encoded in DosR regulon, turned out to be very immunogenic and able to discriminate between the three defined TB status, thus considered a candidate biomarker. Rv2389 and Rv2435n, belonging to Rpf family and IVE-TB group of antigens, respectively, also stood out as LTBI biomarkers. Further work needs to be done in order to support our hypothesis and to have a pattern of host responses available so that by testing the response to a set of *M.tb* antigens we can define the TB status and make a clinical decision.

#### **AUTHOR CONTRIBUTIONS**

All authors listed contributed substantially in the conception or design of the work (Tom H. M. Ottenhoff, José Domínguez) or the adquisition of data (Irene Latorre, Kees L. C. M. Franken, Jéssica Díaz, Maria Luiza de Souza-Galvão, Irma Casas, José Maldonado, Cèlia Milà, Jordi Solsona, M. Ángeles Jimenez-Fuentes, Neus Altet, Alícia Lacoma, Juan Ruiz-Manzano, Cristina Prat), analysis (Vicente Ausina, Madel Mar Serra-Vidal, José Domínguez, Tom H. M. Ottenhoff), or interpretation of data (Madel Mar Serra-Vidal, José Domínguez, Tom H. M. Ottenhoff); in drafting the work or revising it critically for important intellectual content; in doing final approval of the version to be published; and in agreement to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

#### **ACKNOWLEDGMENTS**

The research was supported by grants from the Instituto de Salud Carlos III and Sociedad Española de Patología Respiratoria (SEPAR). Madel Mar Serra-Vidal is a PhD student funded from Instituto de Salud Carlos III and José Domínguez is a researcher funded from the Miguel Servet programme of the Instituto de Salud Carlos III.

#### **REFERENCES**

after specific antigen stimulation in active and latent tuberculosis infection in adults and children. *Diagn. Microbiol. Infect. Dis.* 65, 236–246. doi: 10.1016/j.diagmicrobio.2009.07.015

**Conflict of Interest Statement:** Tom H. M. Ottenhoff is coinventor of a *M.tb* latency antigen patent, which is owned by Leiden University Medical Center, but receives no financial benefits from this. The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

*Received: 29 April 2014; accepted: 15 September 2014; published online: 08 October 2014.*

*Citation: Serra-Vidal M, Latorre I, Franken KLCM, Díaz J, de Souza-Galvão ML, Casas I, Maldonado J, Milà C, Solsona J, Jimenez-Fuentes MÁ, Altet N, Lacoma A, Ruiz-Manzano J, Ausina V, Prat C, Ottenhoff THM and Domínguez J (2014) Immunogenicity of 60 novel latency-related antigens of Mycobacterium tuberculosis. Front. Microbiol. 5:517. doi: 10.3389/fmicb.2014.00517*

*This article was submitted to Microbial Immunology, a section of the journal Frontiers in Microbiology.*

*Copyright © 2014 Serra-Vidal, Latorre, Franken, Díaz, de Souza-Galvão, Casas, Maldonado, Milà, Solsona, Jimenez-Fuentes, Altet, Lacoma, Ruiz-Manzano, Ausina, Prat, Ottenhoff and Domínguez. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.*


**7. The adaptive migration of a base station**

A static assignment of BS location takes into consideration anticipated (and what is more important static) sensors activity. It is a common knowledge that situation in WSN changes, some areas are more active some even dormant – it is very infrequent unlikely situation that entire WSN area is active. The routing activity entails substantial energy consumption and changes network communication conditions. A new situation requires changes and these involve BS location change – as per analogy to military tactical charts, no one will start repositioning troops on a map from a scratch (deployment of a new map) but using runny movements of existing available units. Similarly with Base Station – smooth transition from one dynamic event to another entails migration of BS to follow resultant changes. WSN adaptation involves migration of the BS towards "hot" area, whereas the remaining region is covered cursorily.

Typically, at early life of WSN - its energy is distributed evenly across entire its area. Gradually with time, this changes. There are some nodes with no energy and WSN operation becomes problematic. Since the dynamic allocation of energy within the network is not (directly) possible, we propose the migration of BS that can greatly influence on energy distribution and consumption across the nodes. Since adaptive migration is a result of smart interaction between BS and its vicinity, now we consider how to determine a migration vector in the BS vicinity. In order to do so, a number of messages received by each node within BS neighborhood must be known. Having these numbers, for each node � � �(��) we calculate node's load quotient within BS neighborhood as

$$L\_n(BS) = \frac{\mathcal{M}\_n}{\Sigma^{\ell}\_{\mathcal{N}(BS)}\mathcal{M}\_\ell} \tag{13}$$

where: ��is a number of messages received by *n-*th node,

108 Wireless Sensor Networks – Technology and Protocols

better than those obtained when the BS was located in the best possible static position (V) and its location was fixed. Periodically migrated BS provides a larger number of neighbors increased the network lifespan but this issue reduce energetic efficiency (an average energy

The number of neighbors (on average four times), we expected a commensurate increase in WSN lifespan. As a result we obtain a prolongation of WSN lifespan, but unfortunately it was not even doubled. Where we have lost so much potential energy resources (12)? Well, there are three reasons for this; firstly we do not know whether other BS migration path would not give better results. Secondly, the migration of the base station does not take into account changes in the WSN topology. Subsequent BS positions were determined before the WSN nodes start to be active. After another round, taking into consideration these nodes, which energy was almost drained, the new BS positions should always take this into account. Thirdly, a migrating base station is not equal to four ones still remaining in their initial locations. Each of these static BS supports only a part of the WSN and thus realizes communication more efficiently. One migrant BS serves the entire WSN and thus being in the **A** spot (see in Fig. 4) must receive packets sent from the vicinity of the nodes located in the **C** spot. So, we really know that BS at each position is working not optimally, generating such a significant loss of energy resources. Only a large number of neighbors make the total balance of such activity positive. In the case depicted in Fig. 4 a lot of energy is being simply

consumption per packet has increased noticeably). That was an obvious trade-off.

wasted, hence far from the best, but yet better than previously had been achieved.

A static assignment of BS location takes into consideration anticipated (and what is more important static) sensors activity. It is a common knowledge that situation in WSN changes, some areas are more active some even dormant – it is very infrequent unlikely situation that entire WSN area is active. The routing activity entails substantial energy consumption and changes network communication conditions. A new situation requires changes and these involve BS location change – as per analogy to military tactical charts, no one will start repositioning troops on a map from a scratch (deployment of a new map) but using runny movements of existing available units. Similarly with Base Station – smooth transition from one dynamic event to another entails migration of BS to follow resultant changes. WSN adaptation involves migration of the BS towards "hot" area, whereas the remaining region

Typically, at early life of WSN - its energy is distributed evenly across entire its area. Gradually with time, this changes. There are some nodes with no energy and WSN operation becomes problematic. Since the dynamic allocation of energy within the network is not (directly) possible, we propose the migration of BS that can greatly influence on energy distribution and consumption across the nodes. Since adaptive migration is a result of smart interaction between BS and its vicinity, now we consider how to determine a migration vector in the BS vicinity. In order to do so, a number of messages received by each

**7. The adaptive migration of a base station**

is covered cursorily.

∑ �� � �(��) - is a total number of all messages received by nodes within �(��) neighborhood.

Once the load quotients of nodes are calculated, we take into account only few of BS neighbor nodes and treat ��(��) values, as magnitude of vectors significant in determination of BS migration vector. Then using simple vectors addition of these significant � �� ����� (�� �������� � � � �) vectors as components (Fig. 5), we shape BS migration vector ���� as follows:

$$
\overline{\mathbf{w}} = \sum\_{\mathcal{N}^\*(BS)}^f \overline{L\_l(BS)} \tag{14}
$$

where �∗(��) � �(��) is a significant neighborhood of BS.

Now, in order to move BS we need to decide, how long this movement should be. It is being decided by value, a movement distance factor that shapes BS movement distance from its original position.

$$k < a \cdot \overline{w} < Range$$

where *Range* is a BS radio link range parameter,

*k* is lower bounds parameter for BS movement distance.

The formula (15) provides some kind of neighborhood �(��) continuity during the BS migration.

**Figure 5.** Shaping the BS migration vector

However there should be one more observation detected. We select only some of all calculated node's load quotients. One may wonder what and why such a criterion choice is? In our simulations, we were able to choose, building a BS migration vector തݓതത, all the neighbors since we knew their locations. So there was no difficulty in defining direction and sense of all vectors. Selection of neighbors taking part in the shaping of the vector (14) allows for smart elimination of unwanted nodes in this process. For example, if a node transmits the parameter *temperature in my environment*, and this temperature is too high (potentially harmful), then BS should not migrate in that direction. Often in the real world, only some nodes locations are known to BS, then it is apparent to include only those nodes in the equation (14).

BS migration shall continue until such location is reached, in which a balanced number of messages reaches BS from all directions in its vicinity. Such a case, in the real world situation may never occur, so in order to stop redundant movements, to prevent further energy drain, we introduce indifference constant *k* (refer to (15)) that decides if any additional movement shall be done or not. If the left part of condition (15) is not fulfilled, BS remains on its previous position.