Ifn-γ-independent immune markers of mycobacterium tuberculosis exposure

ABSTRACT Exposure to _Mycobacterium tuberculosis_ (_Mtb_) results in heterogeneous clinical outcomes including primary progressive tuberculosis and latent _Mtb_ infection (LTBI). _Mtb_

infection is identified using the tuberculin skin test and interferon-γ (IFN-γ) release assay IGRA, and a positive result may prompt chemoprophylaxis to prevent progression to tuberculosis.

In the present study, we report on a cohort of Ugandan individuals who were household contacts of patients with TB. These individuals were highly exposed to _Mtb_ but tested negative by

IFN-γ release assay and tuberculin skin test, ‘resisting’ development of classic LTBI. We show that ‘resisters’ possess IgM, class-switched IgG antibody responses and non-IFN-γ T cell

responses to the _Mtb_-specific proteins ESAT6 and CFP10, immunologic evidence of exposure to _Mtb_. Compared to subjects with classic LTBI, ‘resisters’ display enhanced antibody avidity and

distinct _Mtb_-specific IgG Fc profiles. These data reveal a distinctive adaptive immune profile among _Mtb_-exposed subjects, supporting an expanded definition of the host response to

_Mtb_ exposure, with implications for public health and the design of clinical trials. SIMILAR CONTENT BEING VIEWED BY OTHERS IMMUNE CORRELATES OF EARLY CLEARANCE OF _MYCOBACTERIUM

TUBERCULOSIS_ AMONG TUBERCULOSIS HOUSEHOLD CONTACTS IN INDONESIA Article Open access 02 January 2025 SPECIFIC CD4+ T CELL PHENOTYPES ASSOCIATE WITH BACTERIAL CONTROL IN PEOPLE WHO ‘RESIST’

INFECTION WITH _MYCOBACTERIUM TUBERCULOSIS_ Article Open access 12 July 2024 _MYCOBACTERIUM TUBERCULOSIS_ INFECTION IS ASSOCIATED WITH INCREASED B CELL RESPONSES TO UNRELATED PATHOGENS

Article Open access 31 August 2020 MAIN _Mycobacterium tuberculosis_ (_Mtb_) is the leading infectious cause of death worldwide1. Exposure to _Mtb_ leads to a spectrum of outcomes, including

primary progressive disease and latent _Mtb_ infection (LTBI). A diagnosis of LTBI is based on evidence of immune sensitization to _Mtb_ antigens and the absence of clinical symptoms of

tuberculosis (TB) or direct microbiologic evidence of disease2. The clinical standards that establish evidence of _Mtb_ exposure and infection include the tuberculin skin test (TST) and

interferon-γ (IFN-γ) release assay (IGRA). TST measures a delayed-type hypersensitivity reaction to purified protein derivative (PPD) from _Mtb_2,3. The IGRA was developed to distinguish

between bacille Calmette–Guèrin (BCG) vaccination and _Mtb_ infection via the ex vivo measurement of T cell-produced IFN-γ to peptides from the _Mtb_ proteins ESAT6 and CFP10 (ref. 2,3). A

subset of healthy, immunocompetent individuals remain TST and IGRA negative despite persistent, high levels of exposure to _Mtb_4,5. Highly _Mtb_-exposed but persistently TST and IGRA

negative individuals have been described among healthcare workers6,7, household contacts of patients with TB8,9,10,11 and gold miners living and working in close quarters with individuals

with active disease12,13. These individuals have been dubbed ‘resisters’ related to their persistent ability to remain TST and IGRA negative4,5. Initial studies seeking to define why these

individuals continue to remain TST/IGRA negative despite high Mtb exposure identified two associated chromosomal loci14. In addition, differences in transcriptional responses to _Mtb_

infection were found in blood monocytes from these individuals compared with individuals who develop a positive TST after similar mycobacterial exposure15. These innate signatures point to

potentially unique, first-response immunity to _Mtb_. From the adaptive immune perspective, the persistent lack of TST and IGRA reactivity has been interpreted as suggesting that these

individuals are uninfected despite long-term close-contact exposure. Another explanation could, however, be that the ‘resister’ phenotype reflects an alternative immune response to _Mtb_

exposure and/or infection. In the present study, we sought to explore the immunologic basis of persistent TST and IGRA negativity. We leveraged a longitudinal cohort study in Uganda11 to

identify ‘resisters’, a population of household contacts who were highly exposed to _Mtb_ yet remained persistently IGRA and TST negative over an average of 9.5 years of follow-up for each

individual. ‘Resisters’ did not possess a natural or generic anti-pathogen-specific antibody profile that could account for a unique ability to handle _Mtb_. Instead, they possessed IgM and

also class-switched IgG and IgA to several _Mtb_ antigens, suggestive of extended exposure and T cell help. Moreover, T cell responses to _Mtb_ antigens were detected, marked by

antigen-specific upregulation of CD40L/CD154, a co-stimulatory molecule facilitating antigen-specific B cell maturation. _Mtb_-specific humoral immunity among ‘resisters’ exhibited enhanced

avidity, skewing toward the IgG1 subclass selection, and distinct IgG Fc-glycosylation profiles compared with matched household contacts who converted their TST and IGRA, indicative of

classic LTBI. These data reveal a durable and unique adaptive immune profile after _Mtb_ exposure not captured within the current clinical spectrum of disease and expand the range of TB

responses, informing future immune correlate-guided interventions. RESULTS A SUBSET OF HIGHLY _MTB_-EXPOSED ADULTS ‘RESIST’ DEVELOPING TRADITIONAL TST- AND IGRA-POSITIVE LTBI _Mtb_ infection

is acquired primarily via aerosol transmission through close contact with an individual with pulmonary TB. Nevertheless, in household contact studies not all individuals with high levels of

_Mtb_ exposure become infected, as measured by TST and IGRA9. In the present study we aimed to more fully characterize the immune responses _to Mtb_ in these individuals to determine

whether they are truly non-reactive to _Mtb_ or, alternatively, have non-canonical responses after exposure. A longitudinal cohort in Uganda was established to identify and follow

individuals prospectively between 2002 and 2012 who remained persistently TST negative (PTST–) and IGRA negative despite high exposure to _Mtb_ in household contacts of pulmonary TB9. High

exposure in this area1 and within the households was determined using an epidemiologic risk score16 built on proximity and clinical characteristics of the index case. This score was used to

ensure all subjects were highly and equally exposed across subject groups. Among 2,585 household contacts of 872 individuals with pulmonary TB, 173 (7.3%) were diagnosed with active TB and

1,954 (82.1%) with LTBI by TST on initial enrollment. Of these household contacts, 198 (8.3%) were PTST– upon repeated testing over 2 years of follow-up despite equivalent epidemiologic risk

profiles to contacts diagnosed with LTBI. Although most conversions in the cohort occurred rapidly, we aimed to determine the durability, stability and long-term outcomes across the 144

contacts who remained PTST– and 303 contacts with traditional LTBI who had equivalent baseline clinical and epidemiologic risk scores. Specifically, a re-tracing study was performed in

2014–2017 at an average of 9.5 years after initial _Mtb_ exposure9,16. Three sequential IGRAs, measured by QuantiFERON-TB Gold, were performed on blood samples and one additional TST was

performed at the end of the re-tracing study. Of the original TST population, 82.7% remained PTST– and IGRA negative. Although there were small groups of individuals with conversions and

reversions of TST and IGRAs, only human immunodeficiency virus (HIV)-negative subjects who remained concordantly negative for all tests (_n_ = 82) were defined as ‘resisters’ and used in

this analysis (see Supplementary Table 1)11. By extension, HIV-negative control subjects with LTBI were defined by consistently positive results at all time points by both IGRA (Extended

Data Fig. 1a) and TST (Extended Data Fig. 1b,c), with no evidence of clinical disease. To balance for confounding factors, a representative subset (see Supplementary Table 2) of ‘resisters’

and LTBI controls were matched by age (≥15 years), gender and epidemiologic risk score (see Supplementary Table 1), representing, to our knowledge, the longest followed cohort of

‘resisters’. To assess immune responses, peripheral blood samples obtained during the re-tracing study, reflecting cumulative experience of _Mtb_ exposure during the initial TB household

contact study and subsequent years in a TB-endemic urban environment, were used for further analysis. LIMITED EVIDENCE FOR DIFFERENTIAL NATURAL AND NON-_MTB_ ANTIBODIES AMONG ‘RESISTERS’

Given the emerging appreciation of a role for antibodies in TB17,18,19,20,21, we first hypothesized that ‘resisters’ may have high levels of natural antibodies that might provide protection

from infection. Plasma collected at the time of enrollment into the re-tracing study was used to profile natural IgG and IgM levels against classic natural antibody targets, such as

cardiolipin, phosphatidylserine and β2-glycoprotein. However, no differences were observed in antibody titers between 39 ‘resisters’ and 40 matched LTBI controls (Fig. 1a). Given the

complexity of glycosylated lipids and proteins in _Mtb_, we next hypothesized that ‘resisters’ might have a propensity to target carbohydrate antigens more readily than control subjects. The

reactivity of antibodies to more than 600 distinct glycans was assessed using two arrays: the National Center for Functional Genomics (nCFG) array, composed of 100 mammalian, microbial and

plant-derived glycans, and the larger Consortium for Functional Glycomics (CFG) array, composed of 609 mammalian, microbial, milk and arthropod glycans22,23. No differences were observed in

overall glycan reactivity between ‘resisters’ and LTBI controls across either IgG or IgM (Fig. 1b,c). We also hypothesized that ‘resisters’ may respond to vaccination or infection

differentially, mounting a unique response to respiratory pathogens including _Mtb_. Thus, we profiled the humoral immune response to a number of pathogen and vaccine antigens. No

statistically significant differences were observed in the humoral responses to antigens from respiratory pathogens (_S. pneumoniae_ and influenza) (Fig. 1d) and non-respiratory pathogens

(varicella-zoster virus (VZV), cytomegalovirus (CMV), rubella and tetanus), across IgG and IgM. Multivariate analysis of the antibody reactivity across the two groups showed complete overlap

(Fig. 1e), providing no evidence of differences in general immunologic humoral reactivity between ‘resisters’ and LTBI controls. ROBUST _MTB_-SPECIFIC HUMORAL IMMUNE RESPONSES AMONG

‘RESISTERS’ We then assessed humoral immune responses to _Mtb_-associated protein and glycan antigens. As a result of the negative TST and IGRA results, we hypothesized that these responses

would be absent among ‘resisters’ but detectable among LTBI control subjects. Surprisingly, IgM (Fig. 2a), IgG (Fig. 2b) and IgA (Fig. 2c) reactivity was observed to all _Mtb_ antigens

tested (purified protein derivative (PPD), antigen 85 (Ag85), ESAT6/CFP10, the latency-associated protein HspX, the chaperone protein GroES and _Mtb_ cell-wall lipoarabinomannan or LAM) in

both ‘resisters’ and matched LTBI individuals. Importantly, ‘resisters’ had antibody responses of all isotypes against ESAT6 and CFP10, which are used to distinguish _Mtb_ exposure from BCG

vaccination in the IGRA. In both ‘resisters’ and matched LTBI controls, antibody responses were higher than those detected in healthy individuals from a non-endemic region, which serve as a

technical benchmark for the assay. Thus, although ‘resisters’ are defined by the lack of IFN-γ-dependent T cell immunity to ESAT6 and CFP10 by IGRA, these individuals possess persistent

antibody responses to these same antigens, providing immunologic evidence of exposure to _Mtb_. Furthermore, these antibody responses have undergone class switching, arguing for concomitant

T cell responses which may be distinct from those identified by IGRA. These data are consistent with the anti-_Mtb_ humoral responses reported in a study of Chinese healthcare workers who

were highly exposed but TST and IGRA negative24. ‘RESISTERS’ POSSESS _MTB_-SPECIFIC IFN-Γ-NEGATIVE T CELL RESPONSES Given our emerging appreciation for the complexity of T cell functions in

different infections25, we tested for _Mtb_-specific, IFN-γ-independent, CD4+ T cell immunity. Peripheral blood mononuclear cells (PBMCs) from 25 ‘resisters’ and 21 LTBI control subjects,

matched for age, sex and epidemiologic risk score (see Supplementary Table 1), were analyzed. PBMCs were stimulated with overlapping peptide pools targeting ESAT6/CFP10, and assessed for

seven T cell functions using a previously validated intracellular cytokine staining (ICS) assay, capturing distinct T cell functional subsets producing interleukin (IL)-2, IL-4, IL-17a,

IFN-γ, tumor necrosis factor (TNF) and CD107a, and expressing CD40L/CD154 (ref. 26,27.). A theoretical 128 possible combinations of T cell functions were captured, 64 of which included

IFN-γ. To ensure the detection of IFN-γ-negative T cells that might be present at extremely low frequencies in this high-dimensional analysis, combinatorial polyfunctionality analysis of

antigen-specific T cell subsets (COMPASS) was employed28,29. As expected, we detected polyfunctional CD4 T cell responses to ESAT6/CFP10, which included IFN-γ among almost all LTBI subjects.

Two subjects with LTBI did not show IFN-γ responses. This was attributed to decreased sensitivity from a short incubation time (6 h compared with overnight in standard IGRA testing). In

contrast, no IFN-γ responses were observed among ‘resisters’, accounting for the reduced polyfunctionality score compared with LTBI subjects (Fig. 3a,b). The absolute magnitude of responding

CD4 T cells showed the same profile observed in the COMPASS analysis (Fig. 3c and Extended Data Fig. 2). However, ‘resisters’ did exhibit detectable ESAT6/CFP10-specific CD4+ T cell

responses characterized by the absence of IFN-γ and the presence of TNF+IL-2+CD40L/CD154+, IL-2+CD40L/CD154+, CD40L/CD154 alone or CD107a alone (Fig. 3a,c). The absolute magnitudes of

IFN-γ-independent T cell responses among ‘resisters’ were less than those among LTBI subjects but consistently above the background level (Fig. 3c,d). IFN-γ-independent T cell responses were

also detected among household contacts who developed LTBI but were not universally present in TB-endemic populations, as we have shown previously28. Thus, even though ‘resisters’ do not

meet clinical diagnostic criteria for _Mtb_ infection or disease, they possess IFN-γ-independent CD4 T cell responses to ESAT6/CFP10, consistent with the presence of class-switched humoral

immunity to _Mtb_ antigens. ‘RESISTERS’ DISPLAY REDUCED CD4-MEDIATED IFN-Γ RESPONSES ACROSS _MTB_ ANTIGENS Next, we sought to more broadly characterize CD4 T cell immunity to mycobacteria

among ‘resisters’. PBMCs were stimulated with overlapping peptide pools targeting Ag85A, Ag85B, TB10.4 and _Mtb_ lysate. These antigens are expressed across a larger array of mycobacterial

species compared with the restricted expression of ESAT6 and CFP10, reflecting exposure to non-tuberculous mycobacteria or BCG vaccination. COMPASS analysis following CD4 T cell stimulation

with Ag85/TB10.4 overlapping peptides (Fig. 4a,b) showed detectable but overall reduced absolute magnitudes of both IFN-γ-containing and IFN-γ-independent T cell populations (Fig. 4c,d and

Extended Data Figs. 2 and 3) in ‘resisters’ compared with LTBI individuals. Results obtained after stimulation with _Mtb_ lysate were also consistent with this pattern (Fig. 4e,h, Extended

data Fig. 3). As these data were similar to stimulation with ESAT6/CFP10, the possibility that ‘resisters’ may be globally deficient in IFN-γ production by T cells was raised. However,

stimulation with staphylococcal enterotoxin B (SEB) induced comparable levels of IFN-γ production among CD4 T cells in both ‘resisters’ and LTBI subjects (Extended Data Fig. 4a–c). Also,

stimulation with peptides specific for CMV, Epstein–Barr virus and influenza demonstrated comparable levels of IFN-γ production from CD8 T cells in both groups (Extended Data Fig. 4d–f).

Thus, overall, ‘resisters’ generate reduced IFN-γ-producing CD4 T cells to mycobacterial antigens in the absence of any evidence of compromised overall IFN-γ/T-helper 1 (Th1) immunity.

‘RESISTERS’ GENERATE QUALITATIVELY DISTINCT, _MTB_-SPECIFIC, HUMORAL IMMUNE RESPONSES Given the distinct Th profile observed among ‘resisters’, we next probed for potential differences in

the humoral immune profiles in ‘resisters’ compared with LTBI subjects. IgG from individuals with LTBI and active _Mtb_ disease mediates differential intracellular bacterial restriction

coupled with _Mtb_–phagolysosomal co-localization and inflammasome activation in the absence of differential opsinophagocytosis17. As such, we interrogated the antimicrobial potential of IgG

from ‘resisters’ in an in vitro macrophage model of _Mtb_ infection. No statistically significant differences were observed between the effects of ‘resister’ and LTBI IgG on macrophage

intracellular bacterial burden (Fig. 5a), pointing to equivalent antimicrobial function across both groups. Similarly, IL-1β release, a marker of inflammasome activation previously linked to

antimicrobial antibody _Mtb_ restriction30, was equivalent in the presence of ‘resister’ and LTBI IgGs, both of which trended to higher levels than those induced by IgG from individuals

with active pulmonary TB17 (Fig. 5a). These data suggest equivalent restrictive activity across ‘resisters’ and LTBI controls, previously observed to diverge from active _Mtb_ disease,

pointing to the generation of antimicrobial humoral immune responses in ‘resisters’ in the absence of classic Th1 immunity. For better identification of antibody features that may diverge in

‘resisters’, the strength of binding to the complex array of proteins and peptides represented by PPD was interrogated. Notably higher PPD-specific IgG avidity was observed among the

polyclonal responses from ‘resisters’ compared with LTBI control subjects (Fig. 5b). Given the bivalent nature of IgG, these data suggest that ‘resisters’ possess PPD-specific antibodies

that may be more affinity matured than those found in LTBI controls. To further probe whether changes in the Fab were accompanied by changes in the Fc of _Mtb_-specific antibodies, we

compared the Fc-effector functions and isotype distribution between ‘resisters’ and LTBI controls. Similar PPD-specific, Fc-effector functional profiles were observed between ‘resisters’ and

LTBI controls in monocyte phagocytosis, neutrophil phagocytosis and natural killer (NK) cell degranulation, but higher levels of PPD-specific, NK cell IFN-γ-inducing antibodies were

detected in ‘resisters’ (Fig. 5c–e). Consistent with these findings, similar binding to low-affinity Fc-receptor variants (FcγR2a and FcγR3a) was observed across the two groups, with an

expected trend toward higher FcγR3a binding in ‘resisters’ (Fig. 5f). In addition, similar isotype ratios were observed across the two groups (Fig. 5g). In contrast, subclass selection

differences were observed between the ‘resisters’ and the LTBI controls (Fig. 5h). Specifically, statistically significant skewing toward IgG1 was observed in subclass ratios in ‘resisters’

compared with LTBI controls (Fig. 5h). These data suggest that additional IgG subclasses evolve in individuals who develop LTBI whereas ‘resisters’ maintain a focused IgG1 response to _Mtb_

antigens. Beyond subclass differences, recent data suggest that differences in Fc glycosylation at a single conserved _N_-glycan residue (Asn297) can discriminate between LTBI and active

_Mtb_ disease17. Thus, Fc-glycan profiles were assessed across non-antigen-specific, bulk IgG, influenza hemagglutinin (HA)-specific IgG and PPD-specific IgG. No differences were observed in

glycosylation patterns between ‘resisters’ and LTBI control subjects in bulk non-antigen-specific and influenza HA-specific antibodies (Fig. 5i and Extended data Fig. 5). In contrast,

PPD-specific, Fc-glycan profiles diverged substantially across the groups, with elevated levels of singly galactosylated (G1), highly fucosylated, bisected and decreased sialylation in

‘resisters’ (Fig. 5i,j). The glycan structures that are selectively enriched in ‘resisters’ are distinct from those commonly analyzed by the monoclonal therapeutics community involved in

antibody-dependent cellular phagocytosis or cytotoxicity. Thus, these Fc-glycan profiles point to potential non-canonical effector functions that may be produced in polyclonal humoral

responses among ‘resisters’. To ultimately identify the minimal humoral signature that was uniquely enriched among ‘resisters’, we used a stringent multivariate model to quantitatively rank

all antibody features. Collected humoral immune data were normalized and subjected to a penalty-based, least absolute shrinkage and selection operator (LASSO) to reduce highly correlated

features and select the minimal number of individual antibody features capturing the overall variation among the two groups. Partial least squares discriminant analysis (PLSDA) was then used

to display the data and identify the specific relationships between individual features among the groups (‘resisters’ and LTBI controls) (Fig. 6a). As few as 16 of the original 216 antibody

features were required to completely separate PPD-specific antibody profiles between the groups, after taking body mass index, age and sex into account (Fig. 6b and Extended data Fig. 6).

Striking separation was observed in PPD-specific Fc profiles across the two groups, resulting in 100% classification accuracy between ‘resisters’ and LTBI controls (Fig. 6a) (nominal _P_

value < 0.0005 in both permutation tests, Extended data Fig. 6). The loadings plot depicts the minimal 16-feature distribution in the same multivariate space, highlighting the population

of individuals in which each antibody profile feature was enriched (Fig. 6a). Consistent with analyses at an individual feature level, ESAT6/CFP10 IgG1 levels, PPD IgG1:IgG2 ratio and

PPD-specific IgG-glycan features were among the top features that were enriched among ‘resisters’ (Fig. 6b). Together, these data highlight the differences in Fc profiles between the groups,

marked by class-switched antibody responses with unique glycan profiles among the ‘resisters’ in the presence of a non-canonical T cell response to _Mtb_ antigens. DISCUSSION Despite

epidemiologic evidence of persistent exposure to _Mtb_, individuals who remain persistently TST and IGRA negative have been thought to have escaped _Mtb_ infection using existing clinical

tools. Using a longitudinal Ugandan study of household contacts of individuals with TB to identify the most highly exposed individuals who remained persistently TST and IGRA negative after

long-term follow-up, the data presented here demonstrate that these individuals—‘resisters’—harbor humoral and non-canonical cellular immunity to _Mtb_. Specifically, we demonstrate that

‘resisters’ maintain high-titer, class-switched, affinity-matured, _Mtb_-specific antibodies with a unique Fc profile compared with matched controls. Moreover, although ‘resisters’ have the

capacity to make IFN-γ in response to control antigens, they generate a non-IFN-γ-centric, _Mtb_-specific, CD4 T cell response, marked by high levels of CD40L/CD154 upregulation, which may

be key to the induction of _Mtb_-specific humoral immunity. Importantly, we find that these responses to multiple _Mtb_ antigens, including the antigens ESAT6 and CFP10, suggest that these

responses were not generated by BCG vaccination. In some immunocompromised states such as HIV2,31 and some cases of advanced disseminated TB, a persistently negative TST or IGRA is

associated with loss of _Mtb_ control. In the present study, ‘resisters’ are clinically well, with no signs or symptoms of clinical or subclinical immune dysfunction (Fig. 1d and Extended

data Fig. 4). Moreover, TB incidence rates calculated using the last visit date of the original study and the date of re-tracing show no evidence for increased risk of progression to TB in

the PTST– compared with their matched LTBI controls (see Supplementary Table 3). Based on their antibody and T cell profiles, ‘resisters’ have clearly been exposed to _Mtb_ and probably have

been (and may still be) infected. A larger cohort of ‘resisters’, who represent less than 10% of heavily _Mtb_-exposed individuals, is required to accurately determine whether their

non-canonical immune response to _Mtb_ is associated with a different risk of progression to TB compared with that of people with traditional LTBI. Mendelian defects in IFN-γ production or

signaling are associated with increased susceptibility to mycobacterial infections32, and studies in mice demonstrate the importance of IFN-γ in controlling _Mtb_ infection33,34,35,36,37,38.

However, several examples reveal IFN-γ-independent control of _Mtb_ infection or even an antagonistic role for IFN-γ39,40,41. Moreover, in BCG-vaccinated children, low-level IFN-γ-producing

T cells do not represent an immunologic correlate of risk for the development of TB42 and IFN-γ T cell immunity failed to predict protection against progression to _Mtb_ disease after

MVA85A vaccination, known to induce strong IFN-γ responses43. Indeed, ESAT6-specific T cells have been shown to control _Mtb_ infection in the absence of IFN-γ and TNF39. Thus immune factors

beyond IFN-γ and classic Th1 immunity may provide protection against _Mtb_ disease. The data presented here suggest that ‘resisters’ may represent an overlooked clinical outcome after _Mtb_

exposure. The presence of class-switched, _Mtb_-specific immunity, in the setting of IFN-γ-independent T cells targeting ESAT6/CFP10, demonstrates that these individuals have not escaped

_Mtb_ exposure4,5 while living with an adult with pulmonary TB16 and residing in a TB-endemic, urban African environment1. Instead ‘resisters’ harbor B and T cell immunity specific for the

tubercle bacillus with CD4 Th responses linked to quantitative and qualitative differences in IgG profiles to ESAT6/CFP10, LAM and PPD, compared with their matched LTBI counterparts (see

Fig. 2). Persistent antibody titers equivalent to those observed in LTBI controls argue for prolonged antigenic exposure, and thus very likely _Mtb_ infection. Similarly, higher-avidity IgG

antibodies, observed in ‘resisters’, argue for enhanced affinity maturation and long-lasting antigen exposure (see Fig. 5). Yet, although LTBI individuals diversify their IgG subclass

response, ‘resisters’ maintain an IgG1-centric state. Compared with equivalent levels of antibody-dependent phagocytosis, higher NK-cell IFN-γ secretion, linked to trending higher FcγR3a

binding (see Fig. 5), recently implicated in enhanced _Mtb_ control17,44, is observed in ‘resisters’. Finally, ‘resisters’ generate a unique, polyclonal Fc-glycan profile (see Fig. 5) marked

by high levels of single galactosylated glycans. Given that antibodies bathe pulmonary tissues45, _Mtb_-specific antibodies may form immune complexes able to rapidly interact, regulate and

direct innate and adaptive immune cell functions. Thus, further in vitro and in vivo dissection of ‘resister’-derived, antigen-specific antibody mechanism(s) of action may point to

additional canonical (that is, opsinophagocytosis, complement activation and so on) and non-canonical (that is, antibody-dependent cellular toxicity, adaptive immune priming and so on)

mechanisms in functional antibody responses, which track with different clinical phenotypes across the spectrum of TB. Similar to the observed _Mtb_-specific humoral immune responses,

non-IFN-γ T cell responses were detected in nearly all ‘resisters’ after ESAT6/CFP10 stimulation (see Figs. 3, 4 and Supplementary Fig. 2). These data suggest that, although ‘resisters’ do

not have a defect in IFN-γ production overall, these individuals selectively develop a non-IFN-γ-producing, T cell response to _Mtb_, marked by high levels of CD40L/CD154 upregulation that

is critical for T-follicular B cell help, CD107a that may drive cytotoxicity, and a variety of non-Th subset-specific cytokines that may be critical for B cell and innate activation. Whether

this lack of IFN-γ reflects the generation of a distinct Th pathway (T-follicular, Th2, Th17, Th1) in response to differential exposure, major histocompatibility complex-mediated antigen

processing and presentation or control of _Mtb_, or related to a blunted differentiation pathway in Th1 maturity, is unclear. There are several models that could explain the emergence of

‘resisters’. It is possible that they become sensitized to mycobacterial antigens through BCG vaccination or exposure to environmental mycobacteria before they are exposed to _Mtb_. BCG

experience appears to skew PPD immunity toward statistically significant, higher PPD-specific IgG titers (see Supplementary Fig. 1d), but, as expected, it has a limited impact on ESAT6/CFP10

profiles (Extended data Fig. 1e). Similarly, although the structure of this study was not focused on answering the question of BCG influence on _Mtb_ immunity, the observation that IFN-γ

production in response to cross-reactive antigens was decreased, but not completely absent, as it was with ESAT6/CFP10, suggests a potential influence of BCG on shaping immunity to shared

antigens. Thus, pre-existing immunity to BCG or environmental mycobacteria could facilitate early clearance of _Mtb_ after infection. Furthermore, as acquisition of IFN-γ occurs later in the

differentiation of effector T cells46, it is possible that early clearance of antigen may arrest T cell differentiation after acquisition of IL-2 and TNF, but before IFN-γ. Future studies

will be required to determine the role of vaccination, the time frame of evolution of these responses, whether these peripheral responses are reflective of site-specific immunity in the lung

and how age at exposure impacts outcome. Importantly, our data do not rule in or out persistent paucibacillary infection with _Mtb_ among ‘resisters’. There is no microbiologic standard for

persistent _Mtb_ infection without disease. Both the IGRA and the TST, which are used currently, are informative only with respect to immune sensitization after exposure. Collectively, the

discovery of _Mtb_-specific adaptive immunity among ‘resisters’ represents a potential opportunity to explore unexpected immune correlates by expanding the spectrum of human _Mtb_ infection

and disease beyond that classically associated with TST and IGRA, with implications for the design of vaccine trials and public health interventions47,48. Future comprehensive immunologic

investigative efforts of various high-exposure cohorts could provide unique insights into non-canonical immune responses44,49. Moreover, the discovery of validated immune correlates could

significantly advance the design and testing of new therapeutics, including monoclonal antibodies and vaccines. METHODS STUDY SUBJECTS A total of 79 Ugandans (see Supplementary Tables 1 and

2), who were recruited from the Kawempe Community Health Study, were included in this analysis9,51. Index individuals with pulmonary TB were identified by culture for confirmed pulmonary TB

at the Uganda National Referral Tuberculosis Treatment Center at Upper Mulago Hospital in Kampala, Uganda, between 2002 and 2012. A total of 2,585 household contacts of these index cases

were enrolled and followed prospectively for up to 2 years, aimed at identifying development of LTBI based on serial TST at 0, 3, 6, 12, 18 and 24 months, or active TB based on clinical

signs and symptoms of disease and culture evaluation9. Among all household contacts, 29.8% (_n_ = 764) were TST negative at the initial visit and 10.7% of this group (_n_ = 198) remained TST

negative over 2 years of follow-up, that is persistently TST negative. Isoniazid preventive therapy was offered to all TST-positive contacts, and all children aged ≤ 5 years and HIV+

contacts irrespective of TST. Persistent TST– HIV– contacts aged ≥5 years were not offered isoniazid. None of the ‘resisters’ and only two LTBI individuals received chemoprophylaxis to

prevent progression to TB per Ugandan national policy. From 2014 to 2017, a subset of the original cohort, specifically 162 TST-negative and matched 486 TST-positive LTBI individuals, who

were 15 years of age or older at the time of this follow-up study, were eligible for re-tracing11; 441 (63.8%) were successfully re-contacted and willing to be re-evaluated11. Individuals

within these two groups were matched by age, and household or epidemiological risk score11,16,52 (see Supplementary Tables 1 and 2). Re-traced subjects underwent a clinical evaluation

including HIV testing and completed a questionnaire concerning _Mtb_ exposure. HIV-uninfected individuals were selected for this study of immune responses. No isoniazid preventive therapy

was provided during the re-tracing study to LTBI or ‘resister’ subjects. Among re-traced subjects, six individuals developed TB based on self-reporting (see Supplementary Table 3). These

cases were used to calculate incidence rates in IGRA-positive and IGRA-negative individuals but were excluded for the immunologic analyses of this study (see Supplementary Table 2). The

re-tracing study’s evaluation for _Mtb_ infection status consisted of three QuantiFERON-TB Gold (QFT) assays with the first at enrollment in the re-tracing study, the next two over the next

2 years, and a TST following the last QFT. QuantiFERON-Gold-In-Tube (QFT-GIT) was used in the present study, given that this was the version of the IGRA available at the time of the

re-tracing study (2014–2017), the QFT-GIT was appropriate for high-altitude settings (Kampala is at 1,200 m altitude) and, in a setting of BCG vaccination, an assay to measure _Mtb-_specific

responses, was important. TST was performed using the Mantoux method (0.1 ml of 5 tuberculin units of PPD, Tubersol; Connaught Laboratories). A positive TST was defined as an induration of

≥10 mm. QFT assays were performed according to the manufacturer’s instructions and analyzed with the manufacturer’s software-generated standard curves, pass–fail criteria and definitions. In

the re-tracing study 195 individuals were found to be completely concordant by two TSTs (the original from the TB contact study and one at the end of the re-tracing study) and three QFTs,

and categorized as definite LTBI controls (no reversions). Eighty-two re-traced individuals were concordantly negative for the same five assays and defined as definite ‘resisters’ (Extended

data Fig. 1a–c). Cryopreserved PBMCs and plasma from a subset of these definite LTBI controls and ‘resisters’ were used for the experiments in this manuscript. Sample size for antibody

studies were based on our previous published study of individuals with LTBI and pulmonary TB17. Sample sizes for T cell studies were motivated by balancing for confounders, as well as our

recently published study of South African adolescents29. These individuals are representative of the overall cohort (Supplementary Table 2). All study participants gave written, informed

consent, approved by the institutional review boards of the participating institutions. IGG PURIFICATION AND POOLS Total IgG was purified from plasma via negative selection using Melon Gel

resin (Thermo Scientific) following the manufacturer’s instructions and filtered through 0.2 mM (Fisher) and 300-kDa filters (Amicon) before use. Pools of ‘resister’ and LTBI IgG were

generated by mixing equivalent total IgG from each group: _n_ = 40 for ‘resisters’ and _n_ = 39 for TST-/IGRA-positive LTBI control individuals. The resulting pools were passed through a

300-kDa centrifugal filter (Amicon) to remove immunoglobulin complexes. IgG quantifications were determined by ELISA (eBioscience) following the manufacturer’s instructions, with each sample

run in duplicate. ANTIGENS _Mtb_ antigens used were: PPD (Statens Serum Institute), recombinant Ag85A and -B in a 1:1 ratio (BEI Resources, NR-14871 and NR 14870), recombinant ESAT6 (BEI

Resources, NR-14868) and CFP10 in a 1:1 ratio (BEI Resources, NR-49425), HspX (provided by T. Ottenhoff), GroES (provided by T. Ottenhoff) and LAM (BEI Resources, NR-14848). A mixture of

seven recombinant influenza envelope HA antigens, representative of the dominant strains in the past 10 years, was used: H1N1-A/Brisbane/59/2007, B/Florida/4/2006, B/Malaysia/2506/2004,

H1N1-A/Solomon Island/3/2006, H3N2-A/Wisconsin/67/X-161/2005, H3N2-A/Brisbane/10/2007 and H1N1-A/New Caledonia/20/99 (all from Immune Technology). Whole virions (BioRad, PIP044) were used

for rubella virus, purified tetanus toxoid Lp1099p (University of Massachusetts MassBiologics) for tetanus, gE(Orf68) for VZV (provided by D. Lingwood), capsular carbohydrates from the

PPSV23 pneumococcal vaccine for _S. pneumoniae_ and recombinant pp65 for CMV (Abcam, 43041). Cardiolipin (Sigma-Aldrich, C0563), phosphatidylserine (Sigma-Aldrich, P7769) and recombinant

human apolipoprotein H/b2GP1 (R&D, P7769) were used as self-antigens. For T cell assays, _Mtb_ whole cell lysate from H37Rv (BEI Resources), SEB (List Biological Laboratories, Inc.), and

a cocktail of CMV, Epstein–Barr virus and influenza virus peptides (Mabtech) were used. Peptide Pool 1 consisted of ESAT6 and CFP10 (BEI Resources). Peptide Pool 2 consisted of Ag85A, Ag85B

and TB10.4 (BEI Resources). CUSTOMIZED MULTIPLEX LUMINEX A Luminex isotype assay was used to quantify the relative levels of antigen-specific antibody isotypes and subclasses. Luminex

Magplex carboxylated beads (Luminex) were coupled to proteins via covalent NHS-ester linkages with 1-ethyl-3-(3-dimethylaminopropyl)carbodiimide hydrochloride and NHS (Thermo Scientific)

following the manufacturer’s recommendations. Glycan antigens (LAM and pneumococcal polysaccharides) were modified by 4-(4,6-dimethoxy[1,3,5]triazin-2-yl)-4-methyl-morpholinium and

conjugated to Luminex Magplex carboxylated beads53. Lipid antigens were dissolved in ethanol and incubated with Luminex Magplex carboxylated beads54. Antigen-coupled beads (50 µl of a 100

microspheres µl–1 solution in 0.1% BSA in PBS) were added to each well of a 96-well plate (Greinier). Plasma at 1:40, 1:200 and 1:1,000 dilutions in PBS were added to beads and incubated at

48 °C for 18 h of shaking. Beads were washed three times with 200 µl of PBS-Tween. Individual isotype and subclass detection reagents (bulk IgM, bulk IgG, IgG1, IgG2, IgG3, IgG4, IgA1 and

IgA2) conjugated to phycoerythrin (SouthernBiotech) or Fc-receptor (FcR) variants (Duke Human Vaccine Institute), biotinylated by BirA (Avidity) and conjugated to streptavidin phycoerythrin

(Prozyme) following the manufacturer’s instructions, were added and incubated at room temperature for 2 h of shaking. Beads were washed three times with 200 µl PBS-Tween, resuspended in 100 

µl Bio-Plex sheath fluid, and read on Bio-Plex 200. Each plasma sample was tested in duplicate (Extended data Fig. 7) across all dilutions as indicated with median fluorescence intensities

(MFIs) from three dilutions used to calculate area under the curve (AUC) by GraphPad Prism v.7.0. GLYCAN ARRAYS The NCFG glycan v.1 glycan microarray (NCFGv1) consists of 99 different

glycans that were conjugated to the bifunctional fluorescent linker AEAB prepared according to Song et al.55. The AEAB-labeled glycans were printed on NHS-functionalized microarray slides

and assays were performed as previously described56. More details on the individual glycans can be found at https://ncfg.hms.harvard.edu. Briefly, plasma samples were diluted 1:50 in TSM

buffer containing 0.05% Tween-20 and 1% BSA and incubated on the slides for 1 h. Slides were washed in TSM wash buffer (TSM-0.05%, Tween-20), and incubated simultaneously with secondary

antibodies to IgG and IgM (Invitrogen, 5 μg ml–1 each) for 1 h to detect the presence of anti-glycan antibodies in the plasma. Slides were then washed, dried, imaged and analyzed. A subset

of individual plasma samples at the same dilution was also run on the CFG mammalian glycan array v.5.2, which contains over 600 unique carbohydrate structures. More details on the individual

glycans, methods and analysis can be found at www.functionalglycomics.org. AVIDITY ELISA The calculated avidity of plasma anti-PPD IgG was determined as the molar concentration of urea

required to reduce the initial absorbance by 50%57. Plasma from ‘resisters’ (_n_ = 40), LTBI controls (_n_= 39) and healthy, HIV-uninfected North Americans (_n_ = 10) was pooled for

evaluation of IgG reactivity to PPD by ELISA in a dilution series of urea 0–7 M for 15 min before the addition of the secondary antibody. Each plasma group had evaluations performed in

triplicate. The statistical significance was calculated using the Student’s _t_-test. IGG GLYCANS PPD (Statens Serum Institute) was biotinylated with Sulfo-NHS-LC-LC Biotin (Thermo

Scientific) and excess biotin was removed with a 3-kDa molecular mass cutoff column (Amicon/EMD, UFC500396) following manufacturers’ instructions. Biotinylated PPD (20 μg per individual

sample) was coupled to streptavidin magnetic beads (New England BioLabs, S1420S) (50 μl per individual sample) rotating for 1 h at room temperature following the manufacturer’s instructions.

PPD-coupled streptavidin magnetic beads were washed with 0.5 M NaCl, 20 mM Tris-HCl (pH 7.5) and 1 mM ethylenediaminetetraacetic acid five times. Plasma (200 μl) from individuals was

blocked with non-coated streptavidin magnetic beads (50 μl per individual sample) for 2 h at room temperature. PPD-adsorbed streptavidin magnetic beads and blocked plasma were incubated

subsequently for 2 h at room temperature while rotating. Antibodies bound to PPD-coupled streptavidin beads were pelleted with a magnet and any supernatant removed. Non-antigen-specific bulk

IgG was purified from 5 μl of plasma per individual with protein G beads (Millipore PureProteome, LSKMAGG10) following the manufacturer’s instructions and washed in PBS-Tween three times.

Fc from antigen-specific antibody bound to PPD-coupled streptavidin beads or bulk IgG bound to protein G beads was cleaved via IdeZ (New England Biolabs, P0770S) following the manufacturer’s

instructions. The subsequent supernatant containing antibody Fc was removed and glycans isolated and labeled with Glycan Assure APTS kit (Life Technologies, A28676) following the

manufacturer’s instructions. PPD-specific IgG glycans were run with a LIZ 600 DNA ladder in Hi-Di formamide (ThermoFisher) on an ABI 3130XLl DNA sequencer. Data were analyzed using

GeneMapper v.5.0. Bulk IgG glycans were run on Applied Biosystems 3500/3500xL Genetic Analyzer and analyzed with GlycanAssure Data Acquisition Software v.1.1. INTRACELLULAR CYTOKINE STAINING

ICS staining was performed on 25 ‘resisters’ and 25 LTBI controls, and samples were processed in two batches in which the number of ‘resisters’ and controls was matched. PBMCs were thawed

and washed in warm, sterile-filtered RPMI 1640 (Gibco) supplemented with 10% fetal bovine serum (FBS) (HyClone) and 2 μl ml–1 Benzonase (Millipore) and enumerated using the Guava easyCyte

(Millipore) with guavaSoft v.2.6 software. PBMCs were then resuspended in a 50 ml conical flask at a density of 2 × 106 cells ml–1 in RPMI/10% FBS and allowed to rest overnight at 37 °C in

humidified incubators supplemented with 5% CO2. The following day, the PBMCs were enumerated using the Guava easyCyte and resuspended at a density of 5 × 106 cells ml–1. To observe ICS after

antigen stimulation, 1 × 106 cells per well were plated into a 96-well U-bottomed plate and stimulated in the presence of peptide pools, 100 μg ml–1 _Mtb_ Whole Cell Lysate, H37Rv (BEI

Resources), 0.25 μg ml–1 SEB (List Biological Laboratories, Inc.) or 0.5% DMSO (Sigma). Peptide Pool 1 consisted of ESAT6 and CFP10 (BEI Resources), and Peptide Pool 2 consisted of Ag85A,

Ag85B and TB10.4 (BEI Resources), with final concentrations of each peptide at 1 μg ml–1. In addition to antigen, each stimulation cocktail consisted of 1 μg ml–1 anti-CD28/49d (BD

Biosciences), 10 μg ml–1 Brefeldin A (Sigma), GolgiStop (BD Biosciences), prepared according to manufacturer’s instructions, and anti-CD107a phycoerythrin Cy7 (BD Biosciences). Stimulation

and all remaining steps were performed in the dark. The cell mixture was allowed to incubate for 6 h at 37 °C/5% CO2 after which ethylenediaminetetraacetic acid (ThermoFisher Scientific), at

a final concentration of 2 mM, was added to disaggregate cells. Samples were stored overnight at 4 °C and then stained and acquired by flow cytometry the following day. We used a previously

published optimized and validated 12-color panel26,27 to examine cells (see Supplementary Table 4). Briefly, cells were first washed twice in PBS (Gibco) and then stained for 20 min at room

temperature with AViD Live/Dead viability dye (Life Technologies), prepared according to the manufacturer’s instructions. After washing twice with PBS, the cells were incubated with 1× FACS

Lyse (BD Biosciences) at room temperature for 10 min, washed once with FACS buffer (1× PBS supplemented with 0.2% BSA (Sigma)), and then incubated again at room temperature for 10 min with

1× FACS Perm II (BD Biosciences). The cells were washed twice with FACS buffer and then stained for the remaining markers: CD3 ECD, CD4 APC Ax750 (Beckman Coulter), CD8 PerCP Cy5.5, IFN-γ

V450, TNF FITC, IL-2 phycoerythrin, IL-4 APC, CD40L phycoerythrin Cy5 (BD Biosciences) and IL-17a Ax700 (BioLegend). The choice of T cell and functional markers was determined by those

included in a formally validated endpoint assay for vaccine studies26,27. After two final washes in FACS buffer, the cells were fixed in 1% paraformaldehyde (Electron Microscopy Sciences) in

PBS and acquired on a BD LSRFortessa (BD Biosciences), equipped with a high-throughput sampler and configured with blue (488 nm), green (532 nm), red (628 nm), violet (405 nm) and

ultraviolet (355 nm) lasers using standardized good clinical laboratory practice procedures to minimize the variability of data generated. IN VITRO MACROPHAGE _MTB_ SURVIVAL CD14-positive

cells were isolated from whole blood from HIV-seronegative donors using the EasySep CD14 Selection Kit II following the manufacturer’s instructions (Stem Cell Technologies) and matured for 7

days in RPMI (Invitrogen) and 10% FBS (Life Technologies) in low-adherent flasks (Corning). Monocyte-derived macrophages (5 × 104 per well) were plated in glass-bottomed, 96-well plates

(Greiner) 24 h before _Mtb_ infection. Live dead reporter bacteria constitutively expressing mCherry and a tetracycline-inducible green fluorescent protein (GFP)58 were cultured in 0.5 mg 

ml–1 Hygromycin 7H9 media (BD Biosciences) at 37 °C in log phase, washed, sonicated and passed through a 5-mm filter (Milliplex) to obtain a single cell suspension before infection at

multiplicity of infection 1 for 14 h at 37 °C. Extracellular bacteria were washed off and purified IgG at 0.1 mg ml–1, 0.01 mg ml–1 and 0.001 mg ml–1 was added. After 3 days of treatment,

anhydrotetracycline (Sigma) (200 ng ml–1) was added for 16 h to induce GFP expression in live but not dead bacteria. The cells were washed, fixed and stained with DAPI. Images were obtained

via an Operetta High-Content Imaging Fluorescence Microscope (Perkin-Elmer) outfitted with a 20× NA objective. The total _Mtb_ bacterial burden was determined based on mCherry+ pixels.

Transcriptionally active _Mtb_ bacterial burden was determined based on GFP+ pixels. Data from technical triplicates per donor were analyzed using CellProfiler v.3.1.8 (ref. 17,59).

Bacterial survival was calculated as a ratio of live to total bacteria (the number of GFP+ pixels (live) divided by the number of mCherry+ pixels (total burden)). IL-1Β ELISA Human IL-1β

levels in the culture supernatants from the in vitro macrophage assays were determined using a Human IL-1β High sensitivity ELISA (eBioscience). The ratio of the level of IL-1β in the

presence of ‘resister’ or LTBI IgG to the absence of antibodies was used to calculate the relative IL-1β level (‘resister’ or LTBI/no IgG). FC FUNCTIONAL ASSAYS ANTIBODY-DEPENDENT CELLULAR

PHAGOCYTOSIS THP-1 cell phagocytosis of antigen-coated beads was conducted as previously described17,60. _Mtb_ antigens were biotinylated with Sulfo-NHS-LC Biotin (ThermoFisher) following

the manufacturer’s instructions and incubated with 1-μm fluorescent neutravidin beads (Invitrogen) at 4 °C for 16 h. Excess antigen was washed away. Antigen-coated beads were incubated with

plasma (at 1:100, 1:1,000, 1:10,000 dilutions in PBS) for 2 h at 37 °C. THP-1 cells (1 × 105 per well) were added and incubated at 37 °C for 16 h. Bead uptake was measured in fixed cells

using flow cytometry on a BD LSRII (BD Biosciences) equipped with a high-throughput sampler. Phagocytic scores are presented as the integrated MFI (percentage bead-positive frequency × MFI

per 10,000) (Extended data Fig. 8a)50. Antibody-dependent cellular phagocytosis experiments for individual plasma samples were performed in duplicate in two independent experiments.

ANTIBODY-DEPENDENT NEUTROPHIL PHAGOCYTOSIS Whole healthy donor blood was mixed with an equal volume of 3% Dextran-500 (ThermoFisher) and incubated for 25 min at room temperature to lyse and

pellet the red blood cells. Leukocytes were removed and washed in Hanks’ balanced salt solution without calcium and magnesium (ThermoFisher), separated using Ficoll-Histopaque

(Sigma-Aldrich) centrifugation and washed with PBS. PPD-conjugated beads, as described above, were incubated with plasma (at 1:30, 1:100, 1:1,000, 1:10,000 dilutions in PBS) for 2 h at 37 

°C. Isolated neutrophils (1 × 105 per well) were added and incubated for 16 h at 37 °C. Bead uptake was measured as described above. The purity of the neutrophils was confirmed by staining

with CD66b (BioLegend). Phagocytic scores are presented as the integrated MFI (percentage bead-positive frequency × MFI per 10,000) (Extended data Fig. 8b). Antibody-dependent neutrophil

phagocytosis experiments for individual plasma samples were performed in duplicate across dilutions using cells from five healthy HIV-negative donors. NK CELL ACTIVATION ELISA-based,

antibody-dependent, NK-cell activation assays were performed17,61. ELISA plates (ThermoFisher NUNC MaxiSorp flat bottom) were coated with PPD (300 ng per well) or BSA as a negative control

at 4 °C for 16 h. Plasma (at 1:100, 1:1,000, 1:10,000 dilutions in PBS) was added to each well. NK cells were isolated from whole blood from healthy HIV-negative donors with RosetteSep (Stem

Cell Technologies). NK cells (5 × 104 per well), anti-CD107a-phycoerythrin-Cy5 (BD Biosciences), Brefeldin A (10 mg ml–1) (Sigma) and GolgiStop (BD Biosciences) were added and incubated for

5 h at 37 °C. Cells were stained for surface markers using anti-CD16–allophycocyanin-Cy7 (BD), anti-CD56-phycoerythrin-Cy7 (BD) and anti-CD3-AlexaFluor 700 (BD Biosciences), and

intracellularly with anti-IFN-γ-APC (BD Biosciences) and anti-macrophage inflammatory protein-1β-phycoerythrin (BD Biosciences) using Fix and Perm A and B solutions (ThermoFisher). NK cells

were defined as CD3– and CD16/56+ (Extended data Fig. 8c). NK-cell activation assays were performed across the dilutions stated above using cells from four healthy HIV-negative donors.

COMPUTATIONAL/STATISTICS To estimate the incidence rate of TB, we calculated the person-years of follow-up using the last visit date during the phase 1 study9, and the date when we re-traced

them during the re-tracing study. Among the 144 PTST– and 303 TST-positive individuals, there were 6 who developed TB from the end of the phase 1 study; these events and their person-years

were used to calculate incidence. LASSO was used initially to reduce highly correlated features, with the goal of selecting the minimal number of individual antibody features that captured

the overall variation among the ‘resisters’ and control subjects. PLSDA was then used to visualize antibody profiles, using these minimal LASSO-selected features, in multivariate space. To

estimate the minimal correlates that best explain group differences without overfitting, 5,000 repeated, 10-fold nested, cross-validation was designed. In each repetition, the dataset was

randomly divided into groups of 10 arbitrarily assorted individuals, where 90% of the dataset was used to build the model and the remaining holdout set was used to test the model prediction,

and the goodness of fit of the model was measured by classification accuracy between ‘resisters’ and LTBI controls. Ultimately, this approach resulted in the generation of a model with the

minimal set of features that generates the best classification prediction in a cross-validation test. In addition, variable importance in projection, using a weighted sum of squares of the

PLSDA weights to summarize the importance of individual selected features from the PLSDA model, was also computed. To estimate the statistical significance of the optimized model with the

defined correlates, we employed two types of permutation tests—(1) shuffling the outcome label and (2) selecting the randomized correlates—to test the likelihood of obtaining a model

prediction accuracy (displaying in a receiver operating characteristic curve) by chance. Each permutation test was performed 1,000 times to generate an empirical null distribution and an

exact _P_ value of the correct model was computed. All data used in this analysis are available in the accompanying dataset. The raw ICS data were compensated for and manually gated using

FlowJo (TreeStar Inc.). A representative gating tree is shown in Extended data Fig. 9. The data were then processed using the OpenCyto framework in the R programming environment62. Although

we began with 25 subjects for each group, samples with poor viability defined on the basis of low CD3 counts (<10,000 cells) or low CD4 counts (<3,000 cells) were excluded from further

analysis. The final data analysis included the following: Peptide Pools 1 and 2 consisted of 22 ‘resisters’ and 19 LTBI controls, _Mtb_ lysate consisted of 21 ‘resisters’ and 20 LTBI

controls, and SEB consisted of 22 ‘resisters’ and 20 LTBI controls. Total event counts ranged from 49,252 events to 584,133 events per sample, and from 15,183 events to 143,933 events per

sample for CD3. To analyze which T cell subsets were being activated by the various stimulations, we used COMPASS28. COMPASS uses a Bayesian computational framework to identify T cell

subsets for which there is a high probability of an antigen-specific response. For each combination of subset and patient, COMPASS compared the proportion of gated events in the

antigen-stimulated sample with the proportion of gated events in the control sample. Notably, COMPASS reported only the probability of detecting T cell responses with a particular functional

profile, rather than the frequency, which was calculated separately. For a given subject, COMPASS was also used to compute a functionality score that summarized the entire functionality

profile into a single number. For the data presented here, COMPASS was applied to each of the five stimulations of CD4+ T cells. Each one of the analyses was unbiased and considered all of

the 128 possible cytokine functions (defined as a Boolean combination). Individuals with a high probability of response across many subsets were accordingly assigned a high functionality

score. Magnitudes of T cell responses were calculated independent of COMPASS as the maximum of zero, or the proportion of gated events in the stimulated condition minus the proportion of

gated events in the unstimulated condition. Note that two subjects can have equally high probabilities of response for a given subset, even if one patient’s background-corrected proportion

of gated events is higher than the other’s. All the flow cytometry data are available for download from ImmPort (www.immport.org) under study accessoin SDY1385, ‘Flow cytometry of T cells

for TB Resistance Study’. The code to complete COMPASS analyses can be found at https://github.com/seshadrilab/ResisterCOMPASSAnalysis. REPORTING SUMMARY Further information on research

design is available in the Nature Research Reporting Summary linked to this article. DATA AVAILABILITY The data supporting the findings of this study are available in the accompanying

Supplmentary Information, from ImmPort (www.immport.org) under study accessoin SDY1385 ‘Flow cytometry of T cells for TB Resistance Study’, and from the corresponding author upon reasonable

request. CHANGE HISTORY * _ 20 JUNE 2019 In the version of this article originally published, there was an error in the abstract. The word disease should not have been included in the

sentence “These individuals were highly exposed to Mtb but tested negative disease by IFN-γ release assay and tuberculin skin test, ‘resisting’ development of classic LTBI”. The sentence

should have been “These individuals were highly exposed to Mtb but tested negative by IFN-γ release assay and tuberculin skin test, ‘resisting’ development of classic LTBI.” The error has

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reproducible, and automated, end-to-end flow cytometry data analysis. _PLoS Comput. Biol._ 10, e1003806 (2014). Article  Google Scholar  Download references ACKNOWLEDGMENTS We would like to

thank the Gates Foundation for their support under the supplement no. OPP1109001 and grant nos. OPP1151840 and OPP1156795. We would also like to acknowledge the ongoing support from the

Ragon Institute (to G.A. and S.M.F.) and the Samana Cay MGH scholar program to G.A. This work was supported by the following grants (grant no. K08-AI130357 to L.L.L., grant no. U01-AI115642

to W.H.B. and H.M.-K., grant no. R01-AI124348 to W.H.B., and C.M.S. and T.R.H. as multi-PI, and grant no. P41GM103694 to R.D.C.). We thank T. Ottenhoff and D. Lingwood for antigens and P.

Sorger for access to the Operetta High-Content Imaging Fluorescence Microscope. We gratefully acknowledge the invaluable contribution made by the Kawempe study team’s medical officers,

health visitors, laboratory and data personnel in Uganda and the United States. The present study would not have been possible without the generous participation of the Ugandan patients with

TB and their families. Finally, we would also like to sincerely thank the initial catalysts of this project, G. Kaplan and W. Hannekom, and K. Makar and the Gates Foundation Discovery Team

for all their support. AUTHOR INFORMATION Author notes * These authors contributed equally: Chetan Seshadri, Galit Alter. AUTHORS AND AFFILIATIONS * Department of Immunology and Infectious

Diseases, Harvard TH Chan School of Public Health, Boston, MA, USA Lenette L. Lu & Sarah M. Fortune * Ragon Institute of MGH, MIT and Harvard, Cambridge, MA, USA Lenette L. Lu, Corinne

Luedemann, Todd J. Suscovich, Patricia S. Grace, Adam Cain, Wen Han Yu, Sarah M. Fortune & Galit Alter * Department of Medicine, University of Washington, Seattle, WA, USA Malisa T.

Smith, Krystle K. Q. Yu, Thomas R. Hawn & Chetan Seshadri * Department of Biological Engineering, MIT, Cambridge, MA, USA Wen Han Yu & Douglas Lauffenburger * Department of Surgery,

Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA Tanya R. McKitrick & Richard D. Cummings * Department of Medicine, Makerere University, Kampala, Uganda

Harriet Mayanja-Kizza * Department of Medicine, Case Western Reserve University and Univ. Hospitals Cleveland Medical Center, Cleveland, OH, USA W. Henry Boom & Catherine M. Stein *

Department of Population & Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH, USA Catherine M. Stein Authors * Lenette L. Lu View author publications You can

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inPubMed Google Scholar * Tanya R. McKitrick View author publications You can also search for this author inPubMed Google Scholar * Douglas Lauffenburger View author publications You can

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author publications You can also search for this author inPubMed Google Scholar * Thomas R. Hawn View author publications You can also search for this author inPubMed Google Scholar * W.

Henry Boom View author publications You can also search for this author inPubMed Google Scholar * Catherine M. Stein View author publications You can also search for this author inPubMed 

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author inPubMed Google Scholar * Galit Alter View author publications You can also search for this author inPubMed Google Scholar CONTRIBUTIONS L.L.L., C.S. and G.A. conceived and planned

experiments. L.L.L., K.K.Q.Y., P.S.G., A.C. and T.M. performed the experiments and analyzed the data. M.T.S., W.H.Y. and D.L. facilitated computational analyses. C.M.S., H.M.-K., T.R.H. and

W.H.B. contributed epidemiologic analysis and established the clinical cohorts. L.L.L., C.S., S.M.F. and G.A. wrote the manuscript, with contributions from M.T.S., K.K.Q.Y., C.L., T.J.S.,

P.S.G., A.C., W.H.Y., T.M., R.D.C., D.L., H.M.-K., T.R.H., W.H.B. and C.M.S. CORRESPONDING AUTHORS Correspondence to Chetan Seshadri or Galit Alter. ETHICS DECLARATIONS COMPETING INTERESTS

The authors declare no competing interests. ADDITIONAL INFORMATION PUBLISHER’S NOTE: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional

affiliations. EXTENDED DATA EXTENDED DATA FIG. 1 STRATIFICATION OF ‘RESISTERS’ AND LTBI CONTROLS BY IGRA, TST AND BCG SCAR. A–C, IGRA results (A) are shown by the average of three sequential

QFT-Gold readings minus the background (nil) stratified across RSTR (_n_ = 40) or LTBI (_n_ = 39). TST results, stratified across RSTR or LTBI, are reported in mM of induration measured in

phase 1 (B) and phase 2 (C) of the clinical trial. Medians are depicted by lines with interquartile ranges. D,E, Plasma levels of IgG reactive to PPD (D) and ESAT6 and CFP10 (E) were

quantified in RSTR (_n_ = 40) and LTBI (_n_ = 39) individuals using a customized multiplex Luminex in serial dilutions. AUCs were determined from MFIs generated with each dilution and

plotted for each individual. Data points are stratified by BCG scar status. Statistical significance was calculated by Mann–Whitney U test and two-tailed _P_ values are indicated. EXTENDED

DATA FIG. 2 ANALYSIS OF TOTAL IFN-Γ PRODUCTION BY CD4 T CELLS AFTER STIMULATION WITH PEPTIDE POOLS. A,B, Aggregate IFN-γ-positive events, irrespective of the production of other cytokines,

in response to stimulation with ESAT6/CFP10 (A) or Ag85/TB10.4 (B) are plotted. Individual data points for _n_ = 41 are displayed after background correction, stratified by cohort assignment

(RSTR or LTBI) with medians represented by lines. To facilitate visualization, we have not displayed a single LTBI outlier with value 3.41 and 4.25% in A and B, respectively. Statistical

testing was performed on all the data points using Mann–Whitney U test and unadjusted two-tailed _P_ values are shown. EXTENDED DATA FIG. 3 FREQUENCIES OF CD4 T CELL FUNCTIONAL SUBSETS

IDENTIFIED BY COMPASS AFTER STIMULATION WITH AG85/TB10.4 AND _MTB_ LYSATE. A, Absolute magnitude after background correction of CD4 T cell functional subsets identified by COMPASS in Fig. 4a

upon stimulation with Ag85/TB10.4 are shown for RSTRs (_n_ = 22) and LTBI (_n_ = 19). B,C, For CD4 T cell subsets identified by COMPASS after _Mtb_ lysate stimulation in Fig. 4e, absolute

magnitude after background correction is shown for IFN-γ-containing (B) or IFN-γ-independent (C) T cell subsets. Boxplots show median, 25th and 75th percentile of the distribution and

whiskers depict the range without outliers. IFN-γ-containing subsets are noted in red. Statistical testing was performed on all the data points using Mann–Whitney U test with correction for

multiple hypothesis testing using the Bonferroni method and two-tailed _P_ values are shown. EXTENDED DATA FIG. 4 ‘RESISTERS’ ARE NOT GLOBALLY DEFICIENT IN IFN-Γ PRODUCTION BY T CELLS. A,

The COMPASS heatmap shows 49 informative CD4 T cell subset responses to staphylococcus enterotoxin B (SEB) for _n_ = 42 individuals. Rows represent study subjects and columns represent CD4 T

cell functional subsets. The depth of shading within the heatmap represents the probability of detecting a response to a given subset in a given subject above background. IFN-γ-containing

subsets are noted in red. B, Subject-specific COMPASS results in response to SEB stimulation were summarized using a polyfunctionality score, which weights T cell subsets that include more

than one function. Boxplots show median and interquartile range. Statistical significance was calculated by Mann–Whitney U test and the two-tailed _P_ value is shown. C, Representative flow

cytometry plots from a ‘resister’ and LTBI subject show frequencies of CD154+IFN-γ+IL-2+TNF+ T cells (red dots) in response to stimulation with SEB or DMSO, with each experiment performed

once. D, The COMPASS heatmap shows 10 informative CD8 T cell subset responses to CMV, Epstein Barr virus (EBV) and influenza (CEF) combined peptide pool. IFN-γ containing subsets are noted

in red. E, Polyfunctionality scores are depicted for _n_ = 21 RSTRs and _n_ = 21 LTBI subjects with boxplots show median and interquartile ranges. Statistical significance was calculated by

Mann–Whitney U test and the two-tailed _P_ value is shown. F, Representative flow cytometry plots from a ‘resister’ and LTBI subject display nearly equivalent frequencies of

CD107a+IFN-γ+IL-2+TNF+ T cells (red dots) in response to stimulation with CEF or DMSO, with each experiment performed once. EXTENDED DATA FIG. 5 OVERLAPPING INFLUENZA HA-SPECIFIC, IGG GLYCAN

DISTRIBUTIONS BETWEEN ‘RESISTERS’ AND LTBI CONTROLS. Principal component analysis demonstrates the overlapping profiles of ‘resisters’ (purple, _n_ = 22) and TST/IGRA-positive LTBI (green,

_n_ = 19) individuals in the glycoform substructures isolated from influenza HA-specific IgG. The glycoform substructures of individuals are represented in the loadings plot (right), a

mirror image of the dot plot (left), where the location of the glycoform substructures reflects the distribution of the individuals in the dot plot. EXTENDED DATA FIG. 6 THE STATISTICAL

PERFORMANCE OF THE LASSO–PLSDA MODEL. To estimate the statistical significance of the model prediction by LASSO–PLSDA, two types of permutation tests were used: (1) shuffling the outcome

label and (2) selecting randomized data sets. Each permutation test was performed 1,000 times and the prediction accuracy was calculated based using a receiver operating characteristic curve

(shown in the dots). The empirical null distributions for each permutation test were generated and the nominal _P_ values were calculated comparing the true model to the null distributions.

EXTENDED DATA FIG. 7 REPRODUCIBILITY IN ANTIBODY ASSAYS. A, Variability between technical replicates in customized Luminex are shown by a representative dataset of ESAT6/CFP10 specific IgG

MFI readings. B, Variability between technical replicates in Fc-effector functional assays are shown by a representative dataset of ESAT6/CFP10 specific antibody-dependent cellular

phagocytosis scores. C, Variability between two different donors in NK cell activation is shown by percentage Mip1b positive from Donor C and Donor D. Correlations are determined by Spearman

rank with _P_ values as indicated. EXTENDED DATA FIG. 8 GATING STRATEGIES FOR ANTIBODY-DEPENDENT PHAGOCYTOSIS, ANTIBODY-DEPENDENT NEUTROPHIL PHAGOCYTOSIS AND NK CELL ACTIVATION. A,

Antibody-dependent cellular phagocytosis of PPD and or ESAT6/CFP10 adsorbed fluorescent FITC beads was measured in THP-1 monocytes. After gating on size, granularity and singlets, the

frequency and mean fluorescence intensity of FITC beads was measured. The phagocytic score was calculated as the integrated MFI (percentage frequency × MFI/10,000)50. B, Antibody-dependent

neutrophil phagocytosis of PPD adsorbed fluorescent FITC beads was measured. Neutrophils were identified by CD66b staining after gating on size, granularity and singlets. The frequency and

mean fluorescence intensity of FITC beads was measured, and phagocytic score was calculated as the integrated MFI (percentage frequency × MFI/10,000). C, For antibody-dependent NK-cell

activation, cells were first captured after gating on size, granularity and singlets. CD3+ T lymphocytes were gated out and CD16 was used to identify NK cells for which MIP-1β expression,

and CD107a and IFN-γ production were measured. EXTENDED DATA FIG. 9 GATING STRATEGY FOR ICS. A representative gating tree for flow analysis of cells following stimulation with antigen.

Gating (top row) began with singlets, followed by viable cells. Lymphocytes were then identified by size, and CD3 expression was used to focus on T cells. The T cells were then separated

into CD4 versus CD8 co-receptor subsets. For each subset (CD4 middle row, CD8 bottom row), cytokines were visualized by gating against IFN-γ. Pink boxes demonstrated positive staining.

Positivity of cytokines was determined by DMSO negative and SEB positive controls as well as by gating on CD3 negative populations (not shown). Gating for CD4 and CD8 cytokines was

determined separately. SUPPLEMENTARY INFORMATION SUPPLEMENTARY INFORMATION Supplementary Tables 1–4 REPORTING SUMMARY SUPPLEMENTARY DATA Supplementary data including demographics, clinical

characteristics, antibody, and T cell data. RIGHTS AND PERMISSIONS OPEN ACCESS This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use,

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permissions ABOUT THIS ARTICLE CITE THIS ARTICLE Lu, L.L., Smith, M.T., Yu, K.K.Q. _et al._ IFN-γ-independent immune markers of _Mycobacterium tuberculosis_ exposure. _Nat Med_ 25, 977–987

(2019). https://doi.org/10.1038/s41591-019-0441-3 Download citation * Received: 08 November 2018 * Accepted: 01 April 2019 * Published: 20 May 2019 * Issue Date: June 2019 * DOI:

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