ORIGINAL RESEARCH published: 22 June 2022 doi: 10.3389/fmicb.2022.907296 Immunogenicity of Mycobacterial Extracellular Vesicles Isolated From Host-Related Conditions Informs About Tuberculosis Disease Status Sebastian Schirmer 1 , Lucas Rauh 1 , Sogol Alebouyeh 2 , Mario Delgado-Velandia 2,3 , Vivian C. Salgueiro 2 , Laura Lerma 2 , José L. Serrano-Mestre 2 , Mikel Azkargorta 4 , Félix Elortza 4 , José L. Lavín 5 , Maria Jesus García 2 , María Teresa Tórtola Fernández 6 , Edited by: Susanne Gola 1* and Rafael Prados-Rosales 2* Mireia Coscolla, University of Valencia, Spain 1 Department of Medical Engineering and Biotechnology, Ernst-Abbe-Hochschule, University of Applied Sciences, Jena, Reviewed by: Germany, 2 Department of Preventive Medicine, Public Health and Microbiology, School of Medicine, Universidad Autónoma Giovanni Delogu, de Madrid, Madrid, Spain, 3 CIBERESP (CIBER of Epidemiology and Public Health), Madrid, Spain, 4 Proteomics Platform, Catholic University of the Sacred CIC bioGUNE, Basque Research and Technology Alliance (BRTA), Derio, Spain, 5 Bioinformatics Unit, Applied Mathematics Heart, Italy Department, NEIKER-Basque Institute for Agricultural Research and Development, Basque Research and Technology Pooja Vir, Alliance (BRTA), Derio, Spain, 6 Department of Genetics and Microbiology, Universitat Autònoma de Barcelona, Barcelona, Uniformed Services University of the Spain Health Sciences, United States Valesca Anschau, Sanford Burnham Prebys Medical Tuberculosis (TB) still represents a major global health problem affecting over 10 million Discovery Institute, United States people worldwide. The gold-standard procedures for TB diagnosis are culture and *Correspondence: nucleic acid amplification techniques. In this context, both lipoarabinomannan (LAM) Rafael Prados-Rosales urine test and rapid molecular tests have been major game changers. However, the low rafael.prados@uam.es Susanne Gola sensitivity of the former and the cost and the prohibitive infrastructure requirements to susanne.gola@eah-jena.de scale-up in endemic regions of the latter, make the improvement of the TB diagnostic landscape a priority. Most forms of life produce extracellular vesicles (EVs), including Specialty section: This article was submitted to bacteria despite differences in bacterial cell envelope architecture. We demonstrated Evolutionary and Genomic that Mycobacterium tuberculosis (Mtb), the causative agent of TB, produces EVs in vitro Microbiology, a section of the journal and in vivo as part of a sophisticated mechanism to manipulate host cellular physiology Frontiers in Microbiology and to evade the host immune system. In a previous serology study, we showed that Received: 29 March 2022 the recognition of several mycobacterial extracellular vesicles (MEV) associated proteins Accepted: 16 May 2022 could have diagnostic properties. In this study, we pursued to expand the capabilities of Published: 22 June 2022 MEVs in the context of TB diagnostics by analyzing the composition of MEVs isolated Citation: Schirmer S, Rauh L, Alebouyeh S, from Mtb cultures submitted to iron starvation and, testing their immunogenicity against Delgado-Velandia M, Salgueiro VC, a new cohort of serum samples derived from TB+ patients, latent TB-infected (LTBI) Lerma L, Serrano-Mestre JL, Azkargorta M, Elortza F, Lavín JL, patients and healthy donors. We found that despite the stringent condition imposed García MJ, Tórtola Fernández MT, by iron starvation, Mtb reduces the number of MEV associated proteins relative to Gola S and Prados-Rosales R (2022) iron sufficient conditions. In addition, TB serology revealed three new MEV antigens Immunogenicity of Mycobacterial Extracellular Vesicles Isolated From with specific biomarker capacity. These results suggest the feasibility of developing a Host-Related Conditions Informs point-of-care (POC) device based on selected MEV-associated proteins. About Tuberculosis Disease Status. Front. Microbiol. 13:907296. Keywords: Mycobacterium tuberculosis, extracellular vesicles, immunogenicity, diagnostic biomarkers, serology, doi: 10.3389/fmicb.2022.907296 iron starvation Frontiers in Microbiology | www.frontiersin.org 1 June 2022 | Volume 13 | Article 907296 Schirmer et al. TB Serology of Mycobacterial Extracellular Vesicles INTRODUCTION into a mode of slow proliferation, stimulates vesiculation in Mtb (Prados-Rosales et al., 2014b). Tuberculosis (TB) is the leading cause of death due to a single In the context of infection, host-derived EVs (HEVs), such bacterial infectious agent worldwide, with approximately 1.4 as exosomes or microparticles, may remotely interfere with the million deceased in 2020 (WHO, 2020b). Thus, TB remains immune system from the primary site of infection (Choi et al., one of the greatest global health threats. At present, there is an 2015). Exosomes from macrophages infected with Mtb activate urgent need for TB biomarkers, which dampens the advance proinflammatory responses, drive dendritic cell maturation, and in highly demanding approaches such as vaccine development regulate antigen presentation, consistent with the exosome- or diagnostics. The gold-standard procedures for TB diagnosis associated bacterial cargo (Bhatnagar and Schorey, 2007). are culture and nucleic acid amplification techniques. However, A major premise for antigen export from infected phagocytes culture-based methods need laboratory infrastructure, trained is that Mtb-related antigens associate with host membranes and personnel, and entail incubation times that considerably delay traffic into exosomes. However, reports exploring the origin the outcome of the diagnosis. Although the World Health of EVs in Mtb-infected macrophages challenged this view by Organization (WHO) endorsed GeneXpert Mtb/RIF, among showing that HEVs and MEVs may represent two independent others, to improve the rapid diagnosis of drug-sensitive and populations of vesicles (Athman et al., 2015), indicating that resistant TB, it is costly and requires technological investment. the examination of just HEVs in the context of infection will Therefore, albeit being limited by reduced sensitivity of around provide only a partial picture of the interplay between Mtb and 50% (Steingart et al., 2006), culture methods remain the standard the host (Palacios et al., 2021). Since most of Mtb’s biology approach for TB diagnosis in resource-limited settings. The occurs inside of immune cells, EVs derived from this interaction rapid diagnosis of the disease is critical to reduce transmission, can provide valuable information about the outcome of such morbidity, and mortality. In this context, the WHO proposed interaction. Therefore, we hypothesize that deciphering the a set of target product profiles (TPPs) (WHO, 2020a) to guide heterogeneity and immunogenicity of vesicles in the context of and encourage the development of point-of-care (POC) devices human Mtb-infection could have the potential to contribute to to enhance TB case detection. Consequently, TB biomarkers that the development of the highly demanded approaches to tackle the can set the bases for the development of novel POC tests are disease. We have previously evaluated the serological responses to urgently needed. One such TPP is a non–sputum biomarker MEVs isolated from Mtb and BCG grown in high iron conditions test to start TB treatment at the time of the initial clinical visit in human TB individuals and controls showing that a set of three (WHO, 2020a). Among these approaches is the detection of the MEV-associated proteins produced a TB-specific serologic profile mycobacterial cell wall-associated lipoglycan lipoarabinomannan (Ziegenbalg et al., 2013). (LAM) in urine. However, due to its moderate sensitivity, it is The goal of the present study was to investigate the only recommended in HIV co-infected individuals with low CD4 compositional changes of MEVs when isolated from Mtb growing cell counts (Shah et al., 2016). Recent versions of this method under the host-related condition of Fe starvation and test whether improved sensitivity, but this parameter is still far below that of immunogenicity changes can improve their biomarker capacity culture- and molecular-based methods (reviewed in Flores et al., in a new cohort of serum samples from 90 individuals, including 2021). 30 TB patients, 30 latent TB infected individuals (LTBI), and 30 Most forms of life produce extracellular vesicles (EVs). healthy volunteers. Since the first detection of bacterial EVs more than 60 years ago in Escherichia coli (Bishop and Work, 1965), subsequent studies have demonstrated their functional commonality despite RESULTS differences in bacterial cell envelope architecture. Bacterial EVs are “spherical, membranous vesicles from microbial cell Mycobacterium tuberculosis Modifies surfaces ranging in size from 20 to 500 nm in diameter” the Magnitude and Composition of (Brown et al., 2015; Schwechheimer and Kuehn, 2015). We demonstrated that Mycobacterium tuberculosis (Mtb), the Mycobacterial Extracellular Vesicle causative agent of TB, produces EVs in vitro and in vivo as Production When Growing Under Iron part of a sophisticated mechanism to manipulate host cellular Starvation physiology and evade the host immune system (Prados-Rosales We have previously shown that Mtb and other mycobacteria et al., 2011). Mtb EVs (MEVs) have immunomodulatory species produce EVs when cultured in minimal medium properties in vitro and when administered to mice (Prados- (MM) supplemented with Fe (Prados-Rosales et al., 2011). Rosales et al., 2011; Athman et al., 2015), they pose promising Compositional analysis of High Fe MEVs indicated enrichment vaccine properties (Prados-Rosales et al., 2014a) and seem in lipoproteins LpqH, LppX, or LprG (Prados-Rosales et al., 2011; to be genetically regulated (Rath et al., 2013; White et al., Lee et al., 2015); and lipid profile analysis suggested that they 2018). Consequently, MEVs have generated considerable originated from the bacterial cell membrane since polar lipids interest for their potential role in TB pathogenesis and their were the most abundant species in High Fe MEVs. Moreover, we implications in the development of new preventive and have also shown that Fe starvation is a condition that makes Mtb therapeutic antitubercular strategies. Moreover, we reported overproduce MEVs (Prados-Rosales et al., 2014b). Importantly, that iron starvation, a host condition that drives the pathogen iron starvation is a state that induces slow proliferation, Frontiers in Microbiology | www.frontiersin.org 2 June 2022 | Volume 13 | Article 907296 Schirmer et al. TB Serology of Mycobacterial Extracellular Vesicles suggesting that vesiculation is not strictly linked to the growth Moreover, most Low Fe MEV-associated proteins were present rate. Overall, those results showed that the magnitude of the in High Fe MEVs and only 12 proteins appeared as unique in vesiculation process and the composition of MEVs can be altered MEVs isolated in Fe starvation condition (Figure 2A). Those 12 when Mtb faces host-related culturing conditions. However, a unique Low Fe-related MEV proteins were mostly low abundant comprehensive differential proteomic analysis between High and hypothetical proteins without known function. Only the ATP Low Fe MEVs has never been performed. binding subunit ClpC1 and the membrane-bound protease FtsH We, therefore, proceeded to grow Mtb in High and Low appear to be well represented in Low Fe MEVs with Normalized Fe conditions and analyzed vesiculation. We confirmed that Fe Spectral Abundance Factor (NSAF) values of 0.22 and 0.09, starvation enhances vesiculogenesis as measured by nanoparticle respectively (Supplementary Table 1). When looking at the most tracking analysis (NTA) (Figure 1A). Although the average abundant proteins in each functional category we could notice mean diameter of MEVs in High and Low Fe was similar, the that they were mostly the same in both conditions (Table 1). concentration of purified MEV from Low Fe condition was Proteins like GlnA1 (NSAF 1.76 High Fe; NSAF 1.57 Low fourfold higher than that of High Fe condition (Figure 1A). Fe) or LpqH (NSAF 1.71 High Fe; NSAF 7.13 Low Fe) were Alternatively, a specific antibody against MEVs (Rath et al., detected as the most abundant ones in High and Low Fe MEVs, 2013; Prados-Rosales et al., 2014b) was used to determine MEV respectively. Of note, LpqH was between 5 to 7-times more production by dot-blot, which indicated Fe starvation induces abundant in Low Fe than in High Fe MEVs. Nevertheless, the a statistically significant fivefold increase in MEV production fact that both LpqH and GlnA1 are present in MEVs linked relative to Fe sufficiency conditions (Figures 1B,C). Further, to such divergent conditions, suggests that they may represent we isolated MEVs from High and Low Fe conditions and bonafide MEV markers. These results indicate that the enhanced determined protein composition by label-free high throughput vesiculation observed in Mtb upon Fe starvation is accompanied liquid chromatography-mass spectrometry analysis (LC-MS) by a reduction in the number of proteins present in MEVs. (Figure 2 and Supplementary Table 1). We could unequivocally In addition, Low Fe MEVs proteins are not unique relative identify 778 proteins in High Fe MEVs and 257 proteins in the to High Fe MEVs. subset of Low Fe MEVs, indicating a dramatic reduction in the An in-depth protein analysis between both datasets indicated number of proteins incorporated in MEVs upon Fe starvation that most proteins were less abundant in Low Fe MEVs relative (Figure 2A). Despite such reduction in MEV proteins in the to the High Fe condition (Figure 2C). Unsupervised clustering Low Fe condition, similarities between both types of MEVs analysis of the identified proteins revealed two groups of proteins were observed. First, identified proteins appeared to be equally with higher abundance in Low Fe MEVs, corresponding to distributed according to functional category between both types lipoproteins, proteins related to the ESX-1 secretion system, and of MEVs (Figure 2B). Furthermore, in both High and Low some highly immunogenic proteins such as Ag85bc (Figure 2C). Fe MEVs we could not identify any protein linked to “stable We also observed some proteins related to mycolic acid synthesis. RNAs” or “insertion sequences and phages” functional categories. In fact, when running gene ontology (GO) analysis of the FIGURE 1 | Fe starvation induces vesicle production in Mtb. (A) MEVs purified from High and Low Fe cultures using sucrose gradient centrifugation and submitted to nanoparticle tracking analysis using ZetaView. Graph shows size distribution (nm) and corresponding to particle concentration (particle cm- 3 ). (B) Dot blot analysis of the indicated MEV preparation from three independent cultures (a, b, c) using a specific antibody against MEVs. (C) The area (pixel2 ) of the spots calculated in ImageJ as previously described (Ziegenbalg et al., 2013). Graph shows mean values and standard deviation. Results are considered to be statistically significant when P < 0.05 according to an unpaired two-tailed t-test. Frontiers in Microbiology | www.frontiersin.org 3 June 2022 | Volume 13 | Article 907296 Schirmer et al. TB Serology of Mycobacterial Extracellular Vesicles FIGURE 2 | Label-free MS analysis of isolated MEVs. (A) Venn diagram showing the total number of proteins identified for both High and Low Fe conditions, distributed between unique and shared proteins for each condition. Analysis was run using Venny 2.0.2 (Oliveros, 2007). (B) Distribution of identified MEV-associated proteins in different functional categories for both High Fe (filled circles) and Low Fe (empty circles) MEVs. Functional categories: Virulence, detoxification, adaption (0), lipid metabolism (1), information pathways (2), cell wall and cell processes (3), stable RNAs (4), insertion seqs and phages (5), PE/PPE (6), intermediary metabolism and respiration (7), unknown (8), regulatory proteins (9), conserved hypotheticals (10). Arrows indicate NSAF values of certain MEV proteins such as LpqH or GlnA1 as bonafide MEV markers. (C) Heat map showing the expression levels of both Low Fe and High Fe MEV proteins. Samples a, b and c represent independent biological replicates. The blue color indicates up-regulation of proteins, whereas down-regulation is marked in red. Several proteins of two clusters of upregulation in the Low Fe MEV dataset are highlighted. Gene Ontology (GO) analysis of upregulated (D) and downregulated (E) Low Fe MEV-associated proteins. Low Fe MEV proteins we could confirm that upregulated stress to superoxide, mycolic acid synthesis, and nucleoside proteins were restricted to biological processes such as protein biosynthesis (Figure 2D). On the other hand, Low Fe MEV secretion and Type VII secretion system, cellular response to downregulated proteins belonged mostly to cellular processes Frontiers in Microbiology | www.frontiersin.org 4 June 2022 | Volume 13 | Article 907296 Schirmer et al. TB Serology of Mycobacterial Extracellular Vesicles such as beta-oxidation of lipids or metabolism of carboxylic acid for latent TB serum samples seems to be conserved between High (Figure 2E). These results indicate that besides carrying less and Low Fe MEVs. Further, no reactivity against low Fe MEVs protein load, Low Fe MEVs incorporate specific proteins related was detected in samples from healthy volunteers. to cell envelope-related processes in higher abundance relative Overall, these results confirm that MEVs are a source of to High Fe MEVs. TB biomarkers with the capacity to discriminate between TB disease status by serology. In addition, evidence was provided for Immunogenicity of High Fe and Low Fe the recognition of additional MEV antigens with the potential Mycobacterial Extracellular Vesicles to discriminate TB from non-TB individuals, as well as active To expand the catalog of TB biomarkers, we moved to test TB from latent TB ones. On the other hand, Low Fe MEVs the immunogenicity of both High and Low Fe MEVs against do not seem to carry additional biomarkers in comparison a different cohort of 90 serum samples, including 30 TB, 30 to High Fe MEVs. LTBI individuals, and 30 healthy controls (Figure 3). To achieve this, we first separated equivalent amounts (based on NTA Performance of Disease Biomarkers measurements) of High Fe and Low Fe MEVs by SDS-PAGE in a Having established the similarities and differences between each range (10–250 kDa) and submitted them to immunoblot against set of MEVs regarding reactivity against serum samples from TB serum samples from different groups. cases and controls, we proceeded to determine the marker which best discriminate between sample type. Analyses were performed Immunogenicity of High Fe Mycobacterial for bands a, b, and c from High Fe MEV blots, while band Extracellular Vesicles d was analyzed from Low Fe MEVs blots. At first glance, the We proceeded to analyze the immunoblot profiles of the different immunogenicity analysis seemed to differentiate between TB+ sets of EVs against three types of serum samples: (a) smear+, (smear+, IGRA+ and smear-, IGRA+) and TB- (smear-, IGRA-) culture+, IGRA+ (TB); (b) smear-, culture-, IGRA+ (LTBI); and samples, since no reactivity was observed in samples from healthy (c) smear-, culture-, IGRA- (healthy volunteers). The results volunteers for most of the selected bands. All selected bands were showed a change in the number of reactive bands according to somewhat correlated [Spearman’s coefficients range from 0.69 (p- the disease status (Figure 4). We observed more reactive bands value < 0.001)] for bands A vs. B to 0.30 (p-value 0.047) for bands in samples from individuals with active TB than in LTBI and c vs. d (Supplementary Table 2). Band areas were consistently healthy individuals, which is consistent with our previous study higher for latent and active TB cases than for healthy volunteers (Ziegenbalg et al., 2013) and other serological studies (Steingart (Supplementary Table 3). Notably, the area for band d, contrary et al., 2009). When looking at the band pattern, we could observe to other bands’ areas, was higher for latent [median (interquartile reactivity against a band > 100 kDa (band a) in 23/30 of TB range) 2441.15 pixel2 (1758.41–3237.36)] rather than for active samples, a smeared band < 37 kDa (band b) in 28/30 TB samples, cases [370.21 pixel2 (150.56–750.02)] (Supplementary Table 3). a band < 10 kDa (band c) in 28/30 TB samples, and a double We next run receiver-operating characteristic (ROC) analyses band < 50–60 kDa (band d) in 10/30 TB samples (Figure 4). (Figures 5A,C,E,G and Table 2) and found that band a, band b Interestingly, no reactivity against band a was observed in any and band d have optimal overall performance for the distinction of the LTBI samples analyzed (0/30). However, we could detect between TB cases and controls. Band a seems to reliably identify reactivity against band d in 28/30 LTBI samples and reactivity smear+ IGRA+ [AUC 0.924, 95% CI (0.82–1)] (Figure 5A against band c was observed in 20/30 LTBI samples. Like band a, and Table 2) latent [0.918 (0.82–1)] and all TB cases (Mtb- reactivity against band b was absent in most of the LTBI samples infected) [0.921 (0.85–1)]. Band b showed a great power to (20/30) (Figure 4). Finally, when looking at samples from healthy identify smear+ TB+ individuals [0.99 (0.97–1)] but poorer volunteers almost no reactivity was detected for bands observed capacity for latent [0.72 (0.52–0.92)] and all TB cases (Mtb- in the other set of samples (Figure 4). These results indicate infected) [0.85 (0.74–0.97)] (Figure 5C and Table 2). Of note, antibody (Ab) reactivity to High Fe MEV antigens in a higher band d showed the strongest capacity to identify latent TB cases proportion of smear-positive (TB) compared to smear-negative [AUC 1.0 (1.0–1.0)] compared to the other bands (Figure 5G (LTBI) patients and identify additional MEV proteins with the and Table 2). Conversely, band c showed lower AUC values capacity to discriminate TB from non-TB individuals by serology. relative to the other bands [AUC 0.86 (0.71–1), 0.74 (0.54– 0.95), 0.80 (0.63–0.97) for TB+, latent and all TB cases (Mtb- Immunogenicity of Low Fe Mycobacterial infected), respectively] (Figure 5E and Table 2). Statistically Extracellular Vesicles significant differences between AUC values were only found We next moved to investigate the immunogenicity of Low Fe for bands b vs. d (DeLong test p-value, 0.009), and bands MEV for the first time. When checking the immunogenicity of c vs. d (p-value, 0.013) when discriminating between latent Low Fe MEVs against smear+, IGRA+ samples, we noticed a TB cases and healthy controls (Supplementary Table 4). We dramatic reduction in the number of bands detected relative to assessed the performance of the different markers at the optimal High Fe MEVs (Figure 4). No reactivity was observed for bands threshold which provided maximal accuracy (Figures 5B,D,F,H a, b, or c. Regarding band d, it could only be detected in 12/30 and Table 2). Unsurprisingly, we found that most bands have TB samples. However, when immunoblots were analyzed using a specific optimal cut-off point according to disease status. For smear-, IGRA+ samples (LTBI), band d could be observed in instance, a cut-off point of 54 pixel2 for band a gives 0.90 (95% CI, 26/30 samples (Figure 4). The preferential recognition of band d 0.8–1) and 0.82 (0.71–0.93) accuracy for the detection of smear+ Frontiers in Microbiology | www.frontiersin.org 5 June 2022 | Volume 13 | Article 907296 Schirmer et al. TB Serology of Mycobacterial Extracellular Vesicles TABLE 1 | Most abundant proteins in High Fe and Low Fe MEVs. Functional category High Fe MEVs Low Fe MEVs # detected most Protein name NSAF # detected most Protein NSAF proteins abundant proteins abundant name proteins proteins Virulence and detoxification 30 Rv1908c KatG 1.11 11 Rv1908c KatG 1.09 Rv0798c Cfp29 0.82 Rv0798c Cfp29 1.07 Rv2031c HspX 0.66 Rv0440 GroEL2 0.96 Rv2740 EphG 0.43 Rv0350 DnaK 0.55 Rv0350 DnaK 0.32 Rv0432 SodC 0.39 Lipid metabolism 110 Rv0242c FabG4 0.83 35 Rv0242c FabG4 1.39 Rv2831 EchA16 0.59 Rv2244 AcpM 1.2 Rv0824c DesA1 0.56 Rv2831 EchA16 1.08 Rv3800c Pks13 0.54 Rv0675 EchA5 1.07 Rv1070c EchA8 0.51 Rv0642c MmaA4 0.72 Information pathways 93 Rv0723 RpIO 1.18 41 Rv0054 Ssb 1.73 Rv0054 Ssb 1.06 Rv0716 RpIE 1.23 Rv2904c RpIS 1 Rv0714 RpIN 1.21 Rv0714 RpIN 0.86 Rv0704 RpIB 0.85 Rv0716 RpIE 0.84 Rv0701 RpIC 0.85 Cell wall and cell processes 89 Rv3763 LpqH 1.71 44 Rv3763 LpqH 7.13 Rv3875 EsxA 0.89 Rv3875 EsxA 2.89 Rv2346c EsxO 0.61 Rv3616c EspA 2.64 Rv1793 EsxN 0.55 Rv3874 EsxB 2.23 Rv1198 EsxL 0.5 Rv0379 SecE2 1.74 PE/PPE 3 Rv3478 PPE60 0.47 3 Rv3478 PPE60 1.09 Rv2430c PPE41 0.37 Rv2430c PPE41 0.37 Rv1196 PPE18 0.1 Rv1196 PPE18 0.1 Intermediary metabolism 301 Rv2220 GlnA1 1.76 90 Rv2220 GlnA1 1.57 Rv2215 DlaT 0.88 Rv1872c LldD2 1.33 Rv1023 Eno 0.81 Rv3841 BfrB 1.32 Rv3841 BfrB 0.75 Rv1327c GlgE 1.16 Rv3248c SahH 0.74 Rv1133c MetE 1.1 Unknown 1 Rv2818c Hypothetical 0.02 0 protein Regulatory proteins 19 Rv1479 MoxR1 0.16 2 Rv1479 MoxR1 0.26 Rv3295 probably 0.11 Rv0144 possibly 0.22 TetR-family TetR-family Rv0144 possibly 0.11 TetR-family Rv1267c EmbR 0.1 Rv3692 MoxR2 0.08 Conserved hypotheticals 132 Rv3127 Conserved 0.62 31 Rv2744c Conserved 1.58 protein 35 kDa alanine rich protein Rv3131 Conserved 0.45 Rv0831c Conserved 1.49 protein protein Rv0831c Conserved 0.44 Rv3127 Conserved 0.58 protein protein Rv2744c Conserved 0.44 Rv3747 Conserved 0.37 35 kDa alanine protein rich protein Rv2030c Conserved 0.44 Rv3205c Conserved 0.35 protein protein Frontiers in Microbiology | www.frontiersin.org 6 June 2022 | Volume 13 | Article 907296 Schirmer et al. TB Serology of Mycobacterial Extracellular Vesicles FIGURE 3 | Schematic representation of the characteristics of the serum samples used in the study. TB, tuberculosis, LTBI, Latent tuberculosis infection, QTF, QuantiFERON-TB Gold Plus. FIGURE 4 | Serological reactivity pattern of High Fe and Low Fe MEVs. Immunoblots of 15–18 representative serum samples from smear+, IGRA+ (TB), smear-, IGRA+ (Latent TB), and smear-, IGRA- (healthy) individuals against High Fe (A) and Low Fe (B) MEVs. MEVs were separated by SDS-PAGE and blotted with the serum samples. Membranes were further probed with an anti-human IgG secondary antibody conjugated with horseradish peroxidase (HRP) and developed with 3,3’,5,5’-Tetramethylbenzidin (TMB). Reactive MEV-associated protein bands a, b, c, and d are indicated next to the blots. For clarity, only a subset of standard marker bands (250–10 kDa, Bio-Rad, Hercules, CA, United States) is indicated. Frontiers in Microbiology | www.frontiersin.org 7 June 2022 | Volume 13 | Article 907296 Schirmer et al. TB Serology of Mycobacterial Extracellular Vesicles FIGURE 5 | Perfomance analysis of each reactive band. (A,C,E,G) Receiver-operating characteristic (ROC) curves for each band (Table 2). (B,D,F,H) Optimal threshold analysis based on accuracy measurements for each band and sample type. Lines and numbers indicate the optimal threshold (pixel2 ) of the indicated band for each sample type. Analyses were performed for bands a, b, and c from High Fe MEV blots, while band d was analyzed from Low Fe MEVs blots. and TB+ cases, respectively, while a cut-off point of 27.4 pixel2 965.4 pixel2 when checking for smear+ TB+ cases [accuracy 0.97 gives 0.86 (95% CI 0.73–0.97) accuracy for the identification of (0.9–1)] (Figure 5D). Importantly, a threshold of 193.9 pixel2 for latent TB cases (Figure 5B). These results suggest that band a band d gives the highest accuracy [1 (1 -1)] for the detection of preferentially detects active TB individuals. This performance latent TB cases, while a cut-off of 74.75 pixel2 have 93% (0.83– was very similar for band b by setting the cut-off point at 1) for active TB ones. Thus, a threshold of 74.75 pixel2 could Frontiers in Microbiology | www.frontiersin.org 8 June 2022 | Volume 13 | Article 907296 Schirmer et al. TB Serology of Mycobacterial Extracellular Vesicles Mtb-infected allow the detection of both smear+ and smear- cases (Figure 5H). 0.91–1 0.89–1 0.63–1 0.89–1 Taken together, these results show that MEVs carry proteins 0.955 0.96 0.93 0.96 with great biomarker potential for the distinction between TB+ individuals and healthy controls, as well as smear+ TB+ from smear- TB+ cases. band d Latent TB 1–1 1–1 1–1 1–1 1 1 1 1 DISCUSSION The lack of correlates of protection, diagnostic or prognosis 0.82–1 0.83–1 0.67–1 0.933 for tuberculosis (TB) represents one of the main hurdles at 0.93 0.87 1–1 TB 1 designing strategies to tackle the disease. In addition, there is also a need for biomarkers to speed up the assessment of TB treatment. TB serology can be an attractive option for resource- Mtb-infected 0.63–0.97 0.75–0.93 0.4–0.87 limiting settings for TB diagnosis in the form of a POC test. In 0.83–1 0.844 0.93 0.67 0.8 fact, researchers have tried to develop serology tests aimed at differentiating TB from LTBI for decades. Those commercialized are variable in sensitivity (10–90%) and specificity (47–100%) and this depends on antigen included, subjects, or site, among band c Latent TB 0.54–0.95 0.33–0.8 0.6–0.9 other factors (Steingart et al., 2007; Achkar et al., 2011). Besides 0.766 0.8–1 0.74 0.93 0.6 the intrinsic heterogeneity of antibody (Ab) responses in TB individuals (Kunnath-Velayudhan et al., 2010), most assays are based on antigens that elicit Ab responses in individuals with advanced TB. In addition, early TB stages are linked to a low 0.47–0.93 0.7–0.97 0.71 –1 0.866 0.86 0.73 1–1 TB bacterial burden with the concomitant reduction in Ab titers. 1 Interestingly, HIV-infected TB patients seem to develop Ab responses to a smaller repertoire of Mtb antigens compared to HIV-uninfected TB patients (Sartain et al., 2006). Although Mtb-infected 0.74–0.97 0.67–0.93 specificity has also been shown to be insufficient in TB serology 0.7–0.9 0.64–1 0.818 0.85 0.86 0.8 tests, mostly due to the potential contribution of responses due to non-tuberculous mycobacteria or BCG vaccination, some antigens have been shown to specifically trigger TB- specific Ab responses (Hendrickson et al., 2000; Achkar et al., band b Latent TB 0.52–0.92 0.47–0.93 2010). 0.59–0.9 0.57–1 0.758 0.72 0.73 0.79 Intending to expand the catalog of TB biomarkers, we have AUC, Area under curve; CI, confidence interval. *Assessed at the highest accuracy. studied protein composition changes in MEVs isolated from Mtb submitted to a host-related condition such as Fe starvation, relative to Fe sufficiency. When residing intracellularly, Mtb 0.97–1 0.965 0.9–1 0.8–1 0.99 0.93 1–1 TB 1 faces Fe starvation, a strategy from many hosts that restrict access to Fe upon infection (Weinberg, 1984). Consequently, Mtb reduces its proliferation rate and activates a Fe starvation- Mtb-infected specific transcriptional program which triggers the synthesis 0.71–0.93 0.6–0.9 0.85–1 0.921 0.8–1 0.82 0.77 0.93 TABLE 2 | Performance metrics of MEV reactive bands. of Fe-binding molecules (mycobactins) (Rodriguez and Smith, 2006). In addition, it is reasonable to assume that Mtb also modifies protein composition to adapt to this very stressful and restrictive environment. Indeed, a previous transcriptional band a Latent TB 0.73–0.97 0.47–0.93 study revealed that Fe deficiency induces the expression of 0.82–1 0.918 0.86 0.73 1–1 genes needed for the subversion of macrophage antimicrobial 1 defense, such as those related to type VII secretion systems, the protein kinase PknG and other virulence-associated factors, including sulfolipid biosynthesis, cholesterol utilization genes, 0.82–1 0.67–1 0.924 0.8–1 0.8–1 0.87 0.93 0.9 TB isocitrate lyase, phosphoenolpyruvate carboxykinase, and WhiB6 (Kurthkoti et al., 2017). We have previously shown that another manifestation of the response of Mtb to Fe deprivation is the Specificity* Sensitivity* Accuracy* enhancement in MEV production (Prados-Rosales et al., 2014b). 95% CI 95% CI 95% CI 95% CI We determined by metabolomics that low Fe MEVs load mature AUC Fe-loaded mycobactins, whereas mostly Fe-free mycobactin Frontiers in Microbiology | www.frontiersin.org 9 June 2022 | Volume 13 | Article 907296 Schirmer et al. TB Serology of Mycobacterial Extracellular Vesicles intermediates are abundant in High Fe MEVs, indicating changes 25 kDa proteins, we could see reactivity in 10/30 samples. in vesicle cargo (Prados-Rosales et al., 2014b). In addition, we We suppose that both the cohort geography and the inherent demonstrated growth rescue of mutants unable to grow in Fe- variability of MEV composition (Prados-Rosales et al., 2014a) deficiency without mycobactins upon supplementation with low could explain such differences. However, regarding the latter, Fe MEVs (Prados-Rosales et al., 2014b), indicating a role for we tried to reproduce the exact conditions to isolate MEVs in MEVs in pathogenesis. the former study (Ziegenbalg et al., 2013). Overall, we identified To fully understand how Mtb modifies the whole MEV cargo four protein bands that could be preferentially recognized in TB upon Fe deprivation, we conducted a high throughput proteomic samples over healthy controls. All bands were present in High analysis and found changes in the cargo and number of Low-Fe Fe MEVs. We could not identify additional proteins in Low Fe MEV associated proteins relative to High Fe MEVs (Figures 1, 2). MEVs relative to High Fe MEVs with biomarker capacity. This Specifically, as previously shown, MEVs are produced in higher was initially unexpected but can be explained by the finding that quantity in Fe deprivation but Mtb seems to load fewer proteins most of the Low Fe MEV proteome is present in High Fe MEVs compared to Fe sufficiency. This is probably reflecting the slow (Figure 2). In fact, we observed a strong reduction in reactivity replicating phenotype imposed by such stressful condition. In for most of the bands detected in High Fe MEVs with band d fact, it is known that growth restriction is concomitant to a being the only Low Fe MEV protein robustly recognized by sera. reduction in protein synthesis (Hu et al., 1998). Interestingly, Such differences can be explained by either a change in antibody Low Fe MEVs do not seem to load different proteins than specificity according to disease status or by changes in protein High Fe MEVs but in different quantities. Notably, differential abundance within MEVs. Further performance analysis indicated proteomic analysis between both types of MEVs showed that that bands a and b have superior capacity to detect individuals Low Fe MEVs incorporated higher amounts of lipoproteins, and with active TB vs. latent TB, while band d was a suitable marker to substrates of the ESX-1 Type VII secretion system, as well as detect latent TB individuals. Therefore, Ab responses to proteins other immunogenic proteins such as Ag85bc. The correlation a, b, and d enriched in MEVs constitute a novel TB Ab biomarker between the increase in abundance of these proteins and the signature with diagnostic information. Moreover, the fact that enhanced vesiculation phenomenon in Fe starvation may suggest reactivity against Low Fe MEVs is restricted to band d and in the that these proteins are important for vesicle production in Mtb. context of LTBI, we can argue that Low Fe MEV could be useful In fact, lipoprotein LpqH has been previously shown to interact to discriminate between both TB from not-TB individuals and TB with VirR (Rv0431) a negative regulator of vesicle production from LTBI individuals. (Rath et al., 2013). In addition, the high degree of conservation In conclusion, this study provides valuable information for in the most abundant MEV proteins between such divergent future developments in TB diagnostic with a focus on MEVs: conditions in term of growth and metabolism such as Fe (i) the identification of bonafide MEV markers which could be sufficiency and Fe deprivation clearly indicates the establishment used for direct diagnosis; (ii) a novel biomarker signature of three of certain MEV proteins such as LpqH or GlnA1 as bonafide MEV-proteins with potential in the indirect diagnostic of the MEV markers. This information has important implications in disease. In any case, future studies are needed to establish the diagnostic settings aimed at detecting and/or immunocapturing feasibility of MEVs as a platform to improve TB diagnostics. MEVs in clinical samples. Having established the compositional changes between High and Low Fe MEVs we continued to test their immunogenicity MATERIALS AND METHODS against serum samples from a cohort of 90 individuals distributed between smear+ TB+, smear- TB+, and healthy controls Bacteria and Culture (Figure 3). We have previously demonstrated that High Fe Mtb H37Rv (ATCC) was initially grown in Middlebrook MEVs are strongly immunogenic in HIV uninfected patients 7H9 medium (7H9) supplemented with 10% (v/v) OADC with pulmonary TB (Ziegenbalg et al., 2013). These results enrichment (Becton Dickinson Microbiology Systems, Spark, indicated that some High Fe MEV-associated proteins elicit MD, United States), 0.5% (v/v) glycerol and with or without serum IgG responses in both smear-positive and smear-negative Tyloxapol 0.05% (v/v; Sigma) prior to inoculation in a MM TB patients but not in TST + BCG vaccinated healthy controls consisting of KH2 PO4 1 g/l, Na2 HPO4 2.5 g/l, asparagine with or without LTBI. A biomarker signature including three 0.5 g/l, ferric ammonium citrate 50 mg/l, CaCl2 0.5 mg/l, ZnSO4 MEV proteins of ∼36, 25, and 23 kDa could simultaneously 0.1 mg/l, with or without Tyloxapol 0.05% (v/v), containing differentiate between TB and not TB states in immunoblots, 0.1% (v/v) glycerol, pH 7.0. Cultures were grown in 7H9 at suggesting great diagnostic potential with high sensitivity and 37◦ C until they reached an OD of 0.6 and then washed in specificity. This study included MEV isolated from Mtb growing in phosphate-buffered saline (PBS) + 0.05% Tyloxapol and under Fe sufficiency, a condition that does not resemble what transferred to MM. Low iron minimal medium (LIMM) was Mtb may face when residing in the intracellular environment. used for culture under iron-controlled conditions. To remove Moreover, the size resolution provided by immunoblots in that metal ions MM was treated with 5% Chelex-100 (Bio-Rad, study was restricted to protein masses between 20 and 250 kDa Hercules, CA, United States) for 24 h, at 4◦ C with gentle agitation. (Ziegenbalg et al., 2013). Our study did partially reproduce Chelex-100 was removed by filtration through 0.22 µm filter the above results, since we saw robust reactivity for band b (Millipore, Burlington, MA, United States) and the medium (> 37 kDa) in smear+ TB+ samples. Regarding band 23 and was supplemented with sterile ZnCl2 0.5 mg/l, of MnSO4 Frontiers in Microbiology | www.frontiersin.org 10 June 2022 | Volume 13 | Article 907296 Schirmer et al. TB Serology of Mycobacterial Extracellular Vesicles 0.1 mg/l, and of MgSO4 400 mg/l. The amount of residual Fe in preparation (FASP) protocol (Meier et al., 2018). Trypsin was this medium, determined by atomic absorption spectroscopy is added to a trypsin:protein ratio of 1:50, and the mixture was ∼1 µM. High iron MM (MM) was prepared by supplementing incubated overnight at 37◦ C, dried out in a RVC2 25 speedvac LIMM with 50 µM FeCl3 . concentrator (Christ), and resuspended in 0.1% FA. Peptides were desalted and resuspended in 0.1% FA using C18 stage tips Isolation of Mycobacterial Extracellular (Millipore). Digested sample (200 ng) was loaded in a 15 cm Bruker nanoelute FIFTEEN C18 analytical column (Bruker) and Vesicles resolved at 400 nL/min with a 30 min gradient (gradient from Mycobacterial extracellular vesicles were prepared and purified 3 to 40% B, where A: water with 0.1% FA and B: acetonitrile as previously described (Prados-Rosales et al., 2011). Briefly, with 0.1% FA). Data was acquired using the standard DDA the culture filtrate of 1 L cultures of Mtb grown in MM PASEF-standard_1.1sec_cycletime method, that scans between and LIMM without detergent for 14 days was processed for 100–1,700 m/z, and 0.60–1.60 v.s/cm2 using a ramp time of vesicle isolation by differential centrifugation. In parallel a 2 ml 100 ms. The column was heated to 50◦ C using an oven. culture in MM supplemented with 0.05% tyloxapol to disperse Protein identification and quantification were carried out using bacterial clumps were used to determine viability by plating Peaks software using default settings (Bioinformatics solutions). culture dilutions onto 7H10 agar plates and enumerating colony- Searches were carried out against a database consisting of Mtb forming unit (CFU) at the time of culture filtrate collection. H37Rv protein entries (NCBI), with precursor and fragment The membranous pellet containing vesicles, protein aggregates tolerances of 20 ppm and 0.05 Da. Only proteins identified with and capsule polysaccharides obtained after ultracentrifugation at least two peptides at FDR < 1% were considered for further of the culture filtrate at 100,000 × g for 2 h at 4◦ C, was analysis. Quantification of protein abundance was performed resuspended in 1 ml sterile PBS and overlaid with a series of by calculating the NSAF (Bubis et al., 2017). The NSAF is the Optiprep gradient layers with concentrations ranging from 45 number of spectral counts (SpC, the total number of MS/MS to 20% (w/v). The gradients were centrifuged at 100,000 × g spectra) detected for a specific protein, k, divided by the protein’s for 16 h. At the end 1 ml fractions were removed from the length (L), divided by the sum of SpC/L for all N proteins in the top, diluted to 20 ml with PBS and purified vesicles recovered experiment (Zybailov et al., 2006). NSAF values were calculated by sedimentation at 100,000 × g for 1 h. Vesicle pellets were from three biological replicates of the indicated conditions. suspended in PBS before analysis. Protein concentration was Alternatively, identified proteins were classified by functional measured by Bradford assay (Bio-Rad, Hercules, CA, United category according to the Mycobrowser database (Kapopoulou States) according to manufacturer instructions. et al., 2011). Heatmaps were plotted via heatmap.2 function from the gplots R package,1 using a regularized log transformation Nanoparticle Tracking Analysis (RLB) on NSAF values to enhance the graphical representation Nanoparticle tracking analysis was conducted using ZetaView of the data. The histogram in the heatmap indicates normalized (Particle Metrix, WInning am Ammersee, Germany). Instrument protein abundance (z-score) represented by a color scale. The calibration was performed prior to EV analysis using 102 nm white color represents a z-score of 0 and gradients of red and polystyrene beads (Thermo Fisher Scientific, Walthman, blue increase toward the z-scores around −2/+2, respectively. MA, United States), according to manufacturer instructions. Enrichment analysis of GO terms was performed using the Measurements were performed using a 405 nm 68 mW laser and ClueGO package (Bindea et al., 2009) using a Benjamini- CMOS camera by scanning 11 cell positions and capturing 60 Hochberg method and p-value less than equals to 0.05, keeping frames per position at 25◦ C with camera sensitivity 85, shutter predefined kappa threshold value. speed 100, autofocus and automatic scattering intensity. Samples were diluted in pre-filtered PBS to approximately 106 –107 Serum Samples particles·ml−1 in Millipore DI water. Analysis was performed A total of 90 sera was obtained from 90 patients at the using ZetaView Software version 8.05.12 SP1 with a minimum Vall d’Hebron Hospital of Barcelona during 2017. The sera brightness of 30, maximum brightness of 255, minimum area were selected based on the results of the smear microscopy, of 5, maximum area of 1,000, and s minimum trace length 15. mycobacterial culture, and QuantiFERON-TB Gold Plus (QTF). Triplicate videos of each sample were taken in light scatter mode. The sera were distributed as follows: 30 sera from TB patients Particle size and concentration were analyzed using the built-in (smear-positive, culture positive for Mycobacterium tuberculosis EMV protocol and plotted using Prism software, version 8.0.1 and QTF positive), 30 sera from LTBI patients (smear negative, (GraphPad Inc., San Diego, CA, United States). culture negative for M. tuberculosis and QTF positive), and 30 sera from healthy people (smear-negative, culture-negative Label-Free Mass Spectrometry Analysis for M. tuberculosis and QTF negative). The current study was Mycobacterial extracellular vesicle-associated proteins were approved by the Ethical Committee of Vall d’Hebron Hospital of submitted to LC-MS label-free analysis using a hybrid trapped Barcelona. The informed consent of the patients was not required ion mobility spectrometry–quadrupole time of flight mass since the sera obtained for the study came from remnants of spectrometer (timsTOF Pro with PASEF, Bruker Daltonics, samples that were used in the routine hospital care and no data Billerica, MA, United States) coupled online to a nanoElute liquid related to them has been used. chromatograph (Bruker, Billerica, MA, United States). Samples were incubated and digested following the filter-aided sample 1 https://CRAN.R-project.org/package=gplots Frontiers in Microbiology | www.frontiersin.org 11 June 2022 | Volume 13 | Article 907296 Schirmer et al. TB Serology of Mycobacterial Extracellular Vesicles Immunoblot DATA AVAILABILITY STATEMENT Antibody response profiles to MEV-associated proteins were analyzed by immunoblotting. A solution with 30 µg of MEVs The datasets presented in this study can be found in online was separated by SDS-PAGE and transferred to a nitrocellulose repositories. Proteomics data have been deposited on the membrane before blocking in 5% skimmed milk in PBS + 0.01% ProteomeXchange Consortium database via the PRIDE partner Tween 20 (PBS-T) for 1 h. Serum samples diluted at 1:100 repository with the dataset identifier PXD033170. in blocking buffer were incubated at 4◦ C overnight using the multi-channel blotting system Surf-Blot 7.5 (Idea Scientific, MN, United States). The membranes were washed in PBS- ETHICS STATEMENT T and incubated for 1 h an HRP-conjugated goat antibody to human immunoglobulin G (Sigma) and the bands were The current study was approved by the Ethical Committee of Vall visualized using 1-stepTM ultra TMB-blotting substrate solution d’Hebron Hospital of Barcelona. The informed consent of the (Thermo). Alternatively, to perform Western dot blot, 2 µl of patients was not required since the sera obtained for the study 1:200 dilutions of purified EVs were spotted onto a nitrocellulose came from remnants of samples that were used in the routine care membrane (GE Healthcare, Marlborough, MA, United States) of the hospital and no data related to them has been used. The and incubated with anti-MEV polyclonal murine serum as patients/participants provided their written informed consent to primary antibody. Antigen-antibody complexes were detected participate in this study. using anti-mouse IgG and the ECL prime Western Blotting Detection chemiluminescent kit (GE Healthcare, Marlborough, MA, United States). The signal was visualized in a Chemidoc MP AUTHOR CONTRIBUTIONS imaging system (Bio-Rad, Hercules, CA, United States). SG and RP-R designed and coordinated the study and wrote the manuscript. SS, LR, SA, MD-V, VS, LL, JS-M, MA, FE, JL, and Image Analysis MG performed experiments and analyzed data. MT coordinated Band and spot intensities were analyzed by densitometry using collection of clinical samples. All authors read the manuscript ImageJ (Schneider et al., 2012). Backgrounds were determined for and concur with the current submission. each lane individually and set as a straight line at the lowest point of the histological profile of the lane. FUNDING Statistics (ROC and Accuracy Analyses) Band areas were summarized using median (interquartile range), RP-R acknowledges the support from NIH RO1AI162821 and and their correlations were evaluated using Spearman’s rank support by MICINN contract PID2019-110240RB-I00. VS holds correlation test. The overall performance of each reactive band a FPI fellowships from MICINN linked to PID2019-110240RB- was assessed by estimating the area under the ROC (AUC) and I00 contract. MG acknowledges the support from FEDER (A way its 95% confidence interval (95% CI). Differences between AUC to construct Europe) PI19/00666. MD-V holds a “Predoctoral values were evaluated using DeLong’s test. The optimal band area Training in Health Research” contract (FI20/00162) from the cut-off for the discrimination between cases [active TB, latent TB, Carlos III Health Institute of Spain. SS, LR, and SG acknowledge and All TB (Mtb-infected)] and healthy controls was determined funds from the EAH Jena for international activities. as the point which maximized the overall classification accuracy (i.e., the total correct classification rate of each TB status). Analyses were performed using the “pROC” package (version SUPPLEMENTARY MATERIAL 1.18.0) (Robin et al., 2011) in R software (version 4.1.2 R Core Team, 2021); statistical significance was set at a p-value < 0.05 The Supplementary Material for this article can be found (two-tailed). 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Bacteriol. 196, 1250–1256. doi: 10. 1128/JB.01090-13 Copyright © 2022 Schirmer, Rauh, Alebouyeh, Delgado-Velandia, Salgueiro, Lerma, Rath, P., Huang, C., Wang, T., Wang, T., Li, H., Prados-Rosales, R., et al. Serrano-Mestre, Azkargorta, Elortza, Lavín, García, Tórtola Fernández, Gola and (2013). Genetic regulation of vesiculogenesis and immunomodulation in Prados-Rosales. This is an open-access article distributed under the terms of Mycobacterium tuberculosis. Proc. Natl. Acad. Sci. U.S.A. 110, E4790–E4797. the Creative Commons Attribution License (CC BY). The use, distribution or doi: 10.1073/pnas.1320118110 reproduction in other forums is permitted, provided the original author(s) and the R Core Team (2021) R: A Language and Environment for Statistical Computing. copyright owner(s) are credited and that the original publication in this journal Vienna: R Foundation for Statistical Computing. Available online at: http:// is cited, in accordance with accepted academic practice. No use, distribution or www.R-project.org reproduction is permitted which does not comply with these terms. Frontiers in Microbiology | www.frontiersin.org 13 June 2022 | Volume 13 | Article 907296