Human Mycobacterium tuberculosis infection was thought to result in either active symptomatic tuberculosis (TB) or latent asymptomatic infection. It is now clear that this binary classification is insufficient to describe the myriad of infection outcomes. In active TB, symptomatic disease can be mild to severe, with a range of lung and thoracic lymph node involvement or extrapulmonary manifestations. Most humans control the infection and develop latent TB infection, with differential risks of reactivation to active TB. However, some frequently exposed persons appear to be resistant to infection, whereas others may initially become infected yet subsequently eliminate all bacilli. The immunologic factors influencing these varied outcomes are still not clear, but likely involve a range of different responses. In this article, we review the data supporting the spectrum of M. tuberculosis infection in humans as well as data in nonhuman primates that allow dissection of the immune responses leading to the varied outcomes of infection.

Tuberculosis (TB) remains a major cause of morbidity and mortality worldwide and is now the most common cause of death from an infectious disease, surpassing HIV/AIDS (1). Even with improved measures to diagnose and treat TB, the disease continues to ravage developing countries, causing 1.5 million deaths in 2016 (2). Standard therapy for TB has not changed in almost 50 years and involves 6 mo of treatment (four drugs for 2 mo, followed by two drugs for an additional 4 mo). This long course of treatment can result in poor compliance and the potential for developing drug resistance. Drug-resistant TB is complicated to manage and requires longer treatment with less effective drugs and greater risk of adverse effects. Although there are newer drugs being used for drug-resistant TB, an effective vaccine that prevents infection or disease is essential for ending the scourge of TB. However, identifying the protective mechanisms necessary for an effective TB vaccine, or even correlates of protective immunity, has proved difficult.

Mycobacterium tuberculosis, the bacterium that causes TB, is an intracellular pathogen transmitted in aerosolized droplets, typically by coughing from a person with active TB disease. In the airways, the bacillus primarily infects alveolar macrophages but can infect other cell types. It then transits to the lung parenchyma where it can infect resident macrophages or other phagocytes, including neutrophils. The ability to replicate in macrophages is critical to the pathogenesis of M. tuberculosis. Immune signals produced by infected macrophages and bacterial products recruit other immune cells, including monocytes, which differentiate into macrophages and provide additional targets for infection. Simultaneously, the bacilli can be taken up by dendritic cells and transported to the thoracic lymph nodes where T cells are primed against a broad range of M. tuberculosis Ags. These T cells return to the site of infection in the lung and organize around infected macrophages to form granulomas, the pathologic structure most closely associated with TB (Fig. 1). Granulomas also form in thoracic lymph nodes where they serve as a reservoir of infection and dissemination for M. tuberculosis.

FIGURE 1.

Caseous granuloma from the lung of an M. tuberculosis–infected macaque. Original magnification ×4.

FIGURE 1.

Caseous granuloma from the lung of an M. tuberculosis–infected macaque. Original magnification ×4.

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The course of M. tuberculosis infection is extremely variable in humans. Once infection is established, most people control but do not eliminate the initial infection. Infected but asymptomatic individuals are classified as having latent M. tuberculosis infection (LTBI). Persons with LTBI are characterized as having evidence of infection by an immunologic test [positive tuberculin skin test (TST) or IFN-γ release assay (IGRA)], with no signs or symptoms of TB and are presumed to be noncontagious. A small percentage (5–15%) of these people progress to active, symptomatic, and transmissible TB within 2 y of infection, likely representing a lack of initial control of infection; this is termed primary TB. Symptoms of disease evolve slowly, possibly due to the slow growth of the M. tuberculosis. Not surprisingly, active TB can present in a variety of ways, most commonly as pulmonary TB, but the bacillus can infect any organ in the body. Pulmonary TB can present with mild, moderate, or severe respiratory and systemic symptoms, with involvement of single or multiple lung lobes. Cavitary TB is seen in some, but not all, individuals with pulmonary TB. Active TB can also occur by reactivation of LTBI, resulting in a similar range of severity as primary TB. It is estimated that there is a 10% lifetime risk of reactivation in those with LTBI (3). However, the more recent paradigm of LTBI (4) as a spectrum of infection suggests that this risk is not the same for each person with LTBI. The factors defining this reactivation risk are unclear and likely involve both microbiologic and immunologic components.

Diagnosis of M. tuberculosis infection is indirect and is based on detecting cellular immune responses against mycobacterial proteins, either by a positive TST or IGRA. The TST measures a delayed-type hypersensitivity reaction to the injection of a poorly defined mixture of mycobacterial Ags, known as purified protein derivative, but can yield false positive results from cross-reactivity with nontuberculous Mycobacterium spp. as well as M. bovis. More recently, IGRA blood tests have been used, which rely on measuring IFN-γ produced by T cells ex vivo in response to the M. tuberculosis–specific Ags ESAT-6 and CFP-10. These Ags are absent from the commonly used TB vaccine bacille Calmette–Guérin (BCG), an attenuated strain of M. bovis, and thus IGRAs can distinguish reactions to M. tuberculosis from those to BCG. However, these Ags are present in certain other mycobacteria, such as M. africanum. Thus, although this is an improvement over purified protein derivative skin testing, IGRAs remain an imperfect test for M. tuberculosis infection. Importantly, neither IGRA or TST differentiates active TB versus LTBI, and active TB must be diagnosed by the presence of clinical signs, radiography, sputum smear for acid-fast bacilli, or culture for M. tuberculosis.

The dogma of the binary nature of M. tuberculosis infection (active TB versus LTBI) is an oversimplified and now outdated concept. M. tuberculosis infection has a spectrum of manifestations (57) that encompass a broad range of outcomes, including resisters (no evidence of infection despite repeated exposure to M. tuberculosis); infected initially but able to eradicate M. tuberculosis; infected but asymptomatic and stable; latently infected but at high risk of reactivation; active TB with chronic symptoms; and fulminant, severe tuberculous disease (Fig. 2). This concept has become better appreciated over the last decade owing to technologic advances in transcriptional profiling, in vivo imaging, and more innovative and comprehensive clinical research that has enabled us to gain more thorough insights into TB pathogenesis.

FIGURE 2.

The outcome of M. tuberculosis infection includes a host of outcomes and clinical manifestations. Those with severe outcomes are often highly symptomatic (e.g., weight loss, chills, night sweats, fevers, cough) with a positive skin test or IGRA, chest x-ray (CXR) with substantial TB disease, and growth of M. tuberculosis on sputum culture. In contrast, some individuals may have been infected in the past (with or without a positive IGRA/skin test) and have cleared the infection resulting in the absence of symptoms, negative sputum culture, and normal chest x-ray. Although the greatest proportion of infected individuals are able to control infection (LTBI), the exact distribution of outcomes depicted in this article is not known. PPD, purified protein derivative TST.

FIGURE 2.

The outcome of M. tuberculosis infection includes a host of outcomes and clinical manifestations. Those with severe outcomes are often highly symptomatic (e.g., weight loss, chills, night sweats, fevers, cough) with a positive skin test or IGRA, chest x-ray (CXR) with substantial TB disease, and growth of M. tuberculosis on sputum culture. In contrast, some individuals may have been infected in the past (with or without a positive IGRA/skin test) and have cleared the infection resulting in the absence of symptoms, negative sputum culture, and normal chest x-ray. Although the greatest proportion of infected individuals are able to control infection (LTBI), the exact distribution of outcomes depicted in this article is not known. PPD, purified protein derivative TST.

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The expanding definition of LTBI: resisters and reverters.

A growing appreciation for the complexities of M. tuberculosis exposure and infection has developed from household contact studies in which certain individuals, despite multiple exposures to an index case, have persistently negative TST or IGRA results and appear to be resistant to M. tuberculosis infection. These individuals are termed “resisters.” This phenomenon is described in some of the older literature and was nicely demonstrated in a detailed and extended contact-tracing study involving a single TB index case aboard a naval vessel (known as the Byrd study) (8). In that study, despite similar and prolonged exposure to the index case, several subjects remained TST-negative, whereas many others became TST-positive (8). Resisters were initially thought to be subjects who were not as frequently or severely exposed to the index case. However, household contact investigation studies have since identified subjects with no evidence of infection (9) as long as 2 y after index case exposure (10, 11). This is a fascinating cohort of people from which clues about resistance to infection can be gleaned; this resister phenotype has been better defined recently (reviewed in Ref. 12). It should be noted that the current diagnostics for M. tuberculosis infection are relatively poor at identifying this resister population. The TST can be cross-reactive to other Mycobacterial spp., and the IGRA depends on detecting only one immune response to M. tuberculosis infection (IFN-γ produced in response to two Ags). Thus, it is possible that some IGRA-negative subjects may, in fact, have been infected but are controlling (or eliminating) the infection by IFN-γ–independent mechanisms or have T cells that recognize Ags other than ESAT-6 and CFP-10. Functional Ab responses have been shown recently to distinguish LTBI from active TB cases (13), but there are no data yet on Abs in resister cohorts. Other immune mechanisms, such as nonclassical T cells (e.g., γδ T cells or mucosal-associated invariant T cells) or innate immune functions of alveolar macrophages, could be responsible for the apparent lack of infection observed in this population (14). In any event, this special group of people provide a unique opportunity for more detailed immunologic and transcriptomic studies to determine the mechanisms of protection against infection or disease.

In addition to resisters, another group of interesting subjects has been recently identified: household contacts of an index case or those who live in a high endemic area who develop a positive IGRA but then revert to negative within 2 y (“reverters”) (1517). Some cases of reversion likely represent the imprecise nature of the cut-off between positive and negative IGRA results, given the marginally positive IFN-γ levels often observed. However, a substantial number of patients with high IFN-γ responses truly reverted to IGRA-negative within 2 y. This unique subset of patients may represent initial infection with subsequent self-cure or eradication. A recent vaccine trial in humans found that revaccination with BCG or with the H4 subunit vaccine of mycobacterial proteins did not significantly reduce initial infection and IGRA conversion but instead reduced the rate of sustained IGRA conversion over the 2-y follow-up (18). BCG revaccination of previously BCG vaccinated subjects resulted in reversion of an initially positive IGRA with an efficacy of 45%, suggesting these vaccines had a robust reduction, or possibly elimination, of an initial M. tuberculosis infection. As with resisters, the biologic mechanisms leading to this outcome are of interest for development of preventive strategies and provide new outcome measures for vaccine trials. Additional studies to identify the true infection status and more detailed analysis of immunologic responses of these reverters are critical to more fully understand the spectrum of LTBI. It is possible that there is a link between resisters and reverters, with common immunologic mechanisms responsible for preventing or eliminating infection, respectively.

Subclinical disease.

Subclinical TB, often described as having detectable M. tuberculosis in sputum but with a normal chest x-ray and no symptoms of TB, has been documented in immune competent individuals. However, it is likely underreported, because sputum examinations are not typically performed on patients without symptoms or with negative chest radiographs (8, 19). In the aforementioned Byrd study (8), one of the exposed subjects was found to be sputum positive with a normal chest radiograph and no overt symptoms. Only after intensive questioning did this individual admit to having 6 wk of cough and weight loss, which resolved (8). Surprisingly, recent studies identified some patients who would have been defined as having LTBI but had a positive sputum sample, performed serendipitously for research purposes (19). Similarly, features of active TB have been historically observed at autopsy of patients who died of other non-TB causes, suggesting that these patients were otherwise asymptomatic of TB (20). With the resurgence of TB during the HIV epidemic, clinicians have recognized that immunodeficiency is often associated with atypical clinical and radiographic manifestations of TB. HIV-infected patients, especially those with low CD4 counts, do not generally have cavity formation and can have atypical or even normal chest radiographs despite having confirmed disease (reviewed in Refs. 21 and 22). Patients on TNF inhibitors, a major risk factor for reactivation of LTBI, also can have atypical manifestations of TB with more disseminated disease (23). The quality of chest x-rays has greatly improved from the time they were first used more than five decades ago and this has led to improved diagnosis of TB. More sophisticated imaging technologies such as computed tomography (CT) have been used in research and specific clinical settings, resulting in even more sensitive detection of disease. Positron emission tomography (PET), using 2-deoxy-2-[18F]-fluoro-D glucose (FDG, a PET probe measuring metabolic activity), combined with CT has enabled researchers and clinicians to find metabolically active granulomas in otherwise asymptomatic or LTBI patients. In fact, a spectrum of image patterns has been observed in subjects with clinically defined LTBI (24) and in patients with symptomatic active disease (reviewed in Ref. 25). Esmail et al. (26) reported on 35 HIV-infected, antiretroviral naive patients without signs or symptoms of active TB and identified 10 patients with PET/CT characteristics of active or subclinical disease (e.g., infiltrates or metabolically active nodules) and who also exhibited a higher risk of progression to active TB. In this same study, there were 195 HIV+ patients who were screened for TB but who were excluded from the study for various reasons. Of these 195 patients, 10 were found to be sputum positive, of whom five were asymptomatic with normal chest x-rays. Clearly, there is discordance between the traditional classification of LTBI and active TB.

Transcriptional studies of human blood have shown overlapping signatures between clinically defined active TB and LBTI (19, 27) as well as between LTBI and uninfected subjects (28). These studies support the existence of a full spectrum of M. tuberculosis infection beyond the dogmatic, clinically defined, binary outcome. Recent blood transcriptional studies identified a signature that could predict active TB as early as 18 mo prior to clinical diagnosis (29). Although these studies do not provide biological mechanisms, the predictive signatures reflect ongoing disease evolution that cannot otherwise be detected by clinical signs or symptoms. To account for this broader classification of M. tuberculosis infection, some have coined the term “incipient TB.” Although this term has been disputed since the early 1900s (30), it is now defined by the World Health Organization as “prolonged asymptomatic phase of early disease during which pathology evolves, prior to clinical presentation as active disease” (31). Tests that can identify this phase of infection will facilitate more strategic treatment of large populations, preferably by identifying and treating those at greatest risk of active TB before they become overtly contagious, thereby reducing transmission. To more fully understand the spectrum of M. tuberculosis infection and the underlying mechanisms that drive outcomes (especially with regard to incipient infection), more in-depth studies of basic TB pathogenesis and biology of the host and pathogen are required.

The human data that support the idea of a spectrum of M. tuberculosis infection outcomes are compelling. However, for practical reasons, much of this data comes from blood, whereas TB is a disease primarily of the lungs. Animal models have contributed greatly to our understanding of the key events during infection that dictate outcome and allow one to control the infection dose and timing, to perform intensive monitoring and serial sampling, and to harvest tissue samples, including granulomas, lung, and lymph nodes, at various timepoints postinfection. Although murine models are generally used to study pathogenesis and immunology of TB, mice do not replicate many key aspects of human M. tuberculosis infection, including granuloma formation and LTBI. For these reasons, the available data on LBTI and individual granulomas are primarily from nonhuman primate models. Macaques are unique models for TB in that they recapitulate the entire human range of infection outcomes and exhibit pathology, including granulomas, that is identical to human M. tuberculosis infection. In particular, cynomolgus macaques infected with a low dose of virulent M. tuberculosis develop the full spectrum of M. tuberculosis infections seen in humans, from LTBI to severe disease, over the course of several months (32, 33). Rhesus macaques are more susceptible, with most developing active TB within 4 mo; however, even in rhesus macaques, there is a spectrum of active TB from mild to severe (34). Thus, these macaque models provide unique opportunities to investigate M. tuberculosis host–pathogen interactions with remarkable similarities to humans.

In humans, it is extremely difficult to study early events of infection, because the time of infection is rarely known and the diagnostics rely on development of an adaptive immune response, which usually takes 6–8 wk to be detected by IGRA or TST. However, the available data indicate that early immune control of M. tuberculosis infection plays a critical role in outcome (35). As an intracellular respiratory pathogen, the bacilli first encounter the immune response in the airways, which includes cellular (e.g., alveolar macrophages, T cells, innate lymphocytes) and noncellular (e.g., antimicrobial peptides) (36) components. Alveolar macrophages are capable of killing M. tuberculosis soon postinfection, but these cells are quite heterogeneous in both humans and macaques, with likely variable bactericidal capacity. Specific subsets of alveolar macrophages observed before M. tuberculosis infection were associated with differences in infection outcome (active versus LTBI) (37). Infected macrophages can induce bronchial epithelial cells to express DEFB4 and other antimicrobial effectors that can kill M. tuberculosis directly (36). These very early events are consistent with our findings in which serial PET/CT imaging was performed during M. tuberculosis infection in macaques to determine whether the pattern of lung granulomas could predict outcome. Animals that would later develop active TB had more granulomas as early as 3 wk postinfection (before the adaptive immune response is established) with significantly more new granulomas developing because of dissemination from existing granulomas between 3–6 wk compared with animals that would later present with LTBI (38). These data suggest that innate and early adaptive responses are critical to outcome.

Bacterial burden within individual granulomas peaks at ∼4 wk postinfection when there is minimal bacterial killing detected (39). Substantial bacterial killing occurs within granulomas by 10–11 wk postinfection, coinciding with the development of an adaptive immune response. RNA transcriptional profiling of granulomas at 4 wk shows a predominantly proinflammatory profile that is later reduced by 12 wk postinfection (40). Transcriptional signatures in blood from macaques after M. tuberculosis infection appear to be similar to human signatures (4143). Interestingly, some of the signatures (e.g., IFN-related signatures) that predicted active TB during the period of clinical stability in humans (so-called incipient TB) (29) were observed prior to M. tuberculosis infection in our macaque model (41). In a rhesus study of a CMV vector-based vaccine, Hansen et al. (42) observed upregulation of a transcriptional module related to neutrophil and innate immune function associated with vaccine-induced protection that was present before infection. These data reinforce the notion that early immune factors are critical determinants of outcome.

The histopathologic hallmark of TB is the granuloma, an organized spherical structure composed of a variety of cell types, primarily macrophages and lymphocytes. The classic granuloma has a necrotic (caseous) core, surrounded by epithelioid macrophages, with an outer cuff of lymphocytes and macrophages. However, there is a range of granuloma types, including nonnecrotic, suppurative (neutrophilic), fibrotic, and mineralized. These diverse granuloma types were recognized early in studies on human TB, and we observe the full range of granuloma types in macaques (44). The granuloma contains and prevents dissemination of the infection, and it provides an immune microenvironment where macrophages are activated to kill or restrain the growth of M. tuberculosis bacilli. However, the bacterium has evolved to persist in some granulomas, often for years or even the lifetime of the host. The actual metabolic state of the bacilli in granulomas over the long term is not known, although there likely is replication occurring, even if quite slowly or intermittently. What is becoming clear is that there is substantial heterogeneity of granulomas, even within the same host, in terms of host response, bacterial growth and killing, dissemination, and reactivation. This is exemplified by serial PET/CT imaging of individual granulomas in which individual granulomas appear dynamic and independent, increasing or decreasing in size (measured by CT) and metabolic activity (as measured by FDG avidity) within the same macaque and even within the same lung lobe (38, 45) (Fig. 3). Even in humans, resolution of some granulomas and progression of others during active TB can be observed by PET/CT imaging over as little as 2 mo (46).

FIGURE 3.

Granulomas are independent and dynamic by PET/CT during M. tuberculosis infection in macaques. Top row; between 6 and 16 wk postinfection, one granuloma increases in size but maintains the same FDG avidity (yellow arrow), whereas the other granuloma increases in size and FDG avidity (orange arrow) in the accessory lobe. Bottom row; this same animal has a granuloma in the right lower lobe that has decreased in size and FDG avidity (blue arrow) at the same timepoints. Black line = 1 cm.

FIGURE 3.

Granulomas are independent and dynamic by PET/CT during M. tuberculosis infection in macaques. Top row; between 6 and 16 wk postinfection, one granuloma increases in size but maintains the same FDG avidity (yellow arrow), whereas the other granuloma increases in size and FDG avidity (orange arrow) in the accessory lobe. Bottom row; this same animal has a granuloma in the right lower lobe that has decreased in size and FDG avidity (blue arrow) at the same timepoints. Black line = 1 cm.

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We have shown that individual bacilli that enter the lung give rise to individual granulomas, but these granulomas can have different trajectories (39). The heterogeneity among individual granulomas within the same host can be observed in terms of bacterial burden and killing, immune responses, risk of dissemination, and granuloma type (39, 44, 47, 48). Using a library of “bar-coded” M. tuberculosis, in which individual bacteria can be distinguished by a DNA tag, in conjunction with serial PET/CT imaging, we demonstrated that only a subset of granulomas within a single host disseminate to form new granulomas and advance disease (48). Thus, despite the global host immune response to the pathogen, it is the local host–pathogen response in each granuloma that determines overall control of the infection. During the first 4 wk of M. tuberculosis infection when adaptive immunity is just being initiated, bacterial burden in granulomas is at its greatest with little to no bacterial killing (39). During the course of infection, granulomas from animals with active or latent disease can sterilize the infection, although the proportion of sterile granulomas is greater in those with LTBI (39). Thus, unlike most infections, the clinical outcome of infection is more accurately represented by the cumulative host–pathogen interactions of all sites of involvement. That is, all granulomas within a host need to either kill or control M. tuberculosis bacilli to prevent development of disease; one poorly functioning granuloma can lead to loss of containment and TB progression.

The success or failure of each granuloma is dependent on the immune response within that granuloma. The granuloma functions to immunologically contain M. tuberculosis. Yet, granulomas are heterogeneous in terms of cell types present (T cells, B cells, macrophages, neutrophils), cellular immune responses, and bacterial burden (47), and this heterogeneity likely contributes to the variable range of infection outcomes (Fig. 4). Surprisingly, <10% of T cells within the granuloma produce Th1 or Th17 cytokines (47). Our recent data suggest that this is not due to exhaustion of T cells (49), as might be expected in a chronic infection. Interestingly, the combination of IL-10–, TNF-, or IL-17–producing T cells, rather than a preponderance of Th1 cytokines, within individual granulomas was best associated with low bacterial burden and sterile granulomas (47). Thus, the “success” (bacterial killing or prevention of dissemination) of an individual granuloma appears to be the result of both pro- and anti-inflammatory processes rather than being depending on any single cytokine, chemokine, or cell type. Although the host–pathogen interaction within an individual granuloma is relatively complex, even greater complexity is observed at the organismal level because of the number of heterogeneous granulomas present within a single host.

FIGURE 4.

The hypothetical spectrum of granuloma types is seen in any infected individual with each granuloma associated with a range of immune control and bacterial burden. A granuloma that has lost its overall structure and function (progressive and disseminating granulomas) is associated with poor immune control and high bacterial burden. In contrast, fibrotic granulomas are often sterile reflecting a robust immune response.

FIGURE 4.

The hypothetical spectrum of granuloma types is seen in any infected individual with each granuloma associated with a range of immune control and bacterial burden. A granuloma that has lost its overall structure and function (progressive and disseminating granulomas) is associated with poor immune control and high bacterial burden. In contrast, fibrotic granulomas are often sterile reflecting a robust immune response.

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This concept is important when examining the impact of systemic immunologic interventions on individual granulomas and on the overall outcome of the host. For example, the granulomas during early infection are more homogeneous with high bacterial burden and later become much more heterogeneous and likely less susceptible to immune suppression. For example, depletion of CD4+ T cells during early M. tuberculosis infection resulted in 80% of animals with worsening TB pathology, greater bacterial burden, and dissemination compared with controls (50). In contrast, CD4+ T cell depletion during LTBI resulted in only 50% of animals reactivating (50). Similar findings have been observed with TNF neutralization, which consistently exacerbates acute infection, but only results in reactivation in ∼50% of LTBI macaques (4, 51). The greater susceptibility to disseminated disease during early infection is likely due to higher bacterial loads that require more of a robust immune response to control within any individual granuloma and the very low frequency of sterile granulomas at early timepoints. For example, depletion of CD20+ B cells during early infection did not result in overt clinical deterioration but did significantly increase variability of bacterial burden and influenced T cell responses within individual granulomas (52). Thus, B cells may be important in stabilizing the granuloma immune responses early in infection.

Outcomes in individual granulomas are likely associated with the TB spectrum of risk.

Given the heterogeneity of lesion types seen among the various outcomes of M. tuberculosis infection, it is not surprising that the PET/CT patterns during treatment would be extremely variable. Malherbe et al. (53) characterized PET/CT patterns of active TB cases treated with the standard four-drug regimen and correlated the findings with clinical and microbiological outcomes. PET/CTs were done at baseline, 1 and 6 mo after the start of treatment. Six months after treatment, PET/CT patterns were classified as resolved (i.e., minimal to no increase in FDG from pretreatment baseline, regardless of CT abnormalities), improved (i.e., decreased FDG intensity of all lesions but with ≥1 lesion with increased FDG uptake), and mixed (i.e., ≥1 lesion with higher FDG intensity compared with baseline). Heterogeneous PET/CT scans were observed during treatment. Patients who failed treatment had exclusively mixed patterns; however, mixed patterns could also be seen among cured and recurrent patients. Moreover, M. tuberculosis mRNA was identified in sputum 6 mo after initiation of drug treatment in cured, failed, and recurrent TB cohorts. The significance of this is yet unclear. The spectrum of patterns seen during treatment likely reflects the heterogeneous effect of drug treatment on individual granulomas due to variable drug penetration into various granuloma types (54, 55) and the efficacy of the individual drugs against bacilli in different metabolic states depending on the microenvironment of each granuloma (56) [reviewed in (57)]. Clearly, more comprehensive studies are required to better understand outcome and the appropriate treatment of disease.

Reactivation risk in LTBI may well depend on a single granuloma that is slightly impaired for bacterial control. In LTBI, it traditionally was assumed that all granulomas are successfully controlling or eliminating the infection. However, the new paradigm states that LTBI exists as a spectrum of infection outcomes. What defines the spectrum immunologically is not clear, but it is unlikely that this will be fully understood simply from blood signatures. Data from our macaque models indicate that immune responses in blood do not reliably reflect immune responses in either individual granulomas or the average of all granulomas (47). We performed a large study of reactivation risk in LTBI cynomolgus macaques, in which TNF was neutralized (a major risk factor for reactivation TB in humans). PET/CT scans were performed on macaques with LTBI over the 8-wk course of TNF neutralization (4). Fifty percent of the macaques experienced reactivated TB during this time. We assessed PET/CT features prior to TNF neutralization that were associated with reactivation and found that the number of granulomas in the lung was not a factor. Instead, lung inflammation (often from a single granuloma) and the presence of an extrapulmonary lesion (spleen or liver) predicted reactivation with 92% sensitivity and specificity. To determine the importance of these metrics, we predicted reactivation risk in a large number of LTBI macaques who did not undergo TNF neutralization and characterized their granulomas by PET/CT. The macaques predicted to be at high risk using our PET/CT metrics had a single granuloma with higher bacterial burden than those predicted to be at low risk, supporting the concept that a single granuloma can put a host at higher risk of reactivation and that successful immune responses in all granulomas are essential for long-term prevention of disease. However, the immunologic microenvironment within granulomas is complex and each granuloma likely takes its own path to success or failure, making it unlikely that a single set of immune responses uniformly leads to success (35). This paradigm has major implications for vaccines and host-directed therapies, as protective responses likely involve a variety of immune mechanisms from different cell types.

Given the heterogeneous nature of bacterial dynamics and host immune responses in individual granulomas, it is no wonder that outcomes cannot be classified by binary outcomes of active or LTBI. Moreover, these factors significantly complicate efforts to improve TB treatment and develop protective vaccines. Perhaps it will be more accurate to classify infection outcomes as an individual’s risk of primary disease or reactivation. This requires more precise diagnostics with greater specificity and sensitivity, especially for immune-compromised hosts, such as those with HIV who have the greatest risk of disease. It is possible that risk assessments may require a series of tests and rely on a battery of immune responses that could be difficult to implement in the field instead of simply relying on TST or IGRA results. Non–culture-based assays to identify M. tuberculosis components, such as the urinary lipoarabinomannan assay (58) or trehalose assay (59), show promise as a point-of-care diagnostic. Host-specific risks, such as immune competence, age, genetic background, and comorbidities, will need to be accounted for, not just once, but over time as the risk can change over the life of the host.

That said, even with improved diagnostic methods and a more thorough understanding of the disease and risk, we need to ask ourselves some key questions. Given the complex spectrum of M. tuberculosis infection, what will the optimal treatment regimen look like? For example, what is the optimal treatment for incipient disease? Is a four-drug therapy necessary for a stage that may have a lower bacterial burden than symptomatically overt, active TB? Will individualized host-directed therapies, in conjunction with antimicrobial treatment, shorten treatment duration? Because the disease progression can change over time and the time of infection is unknown, do patients require repeated testing for incipient and overtly active TB? Will there be an accurate and cost-effective method for identifying those at low-to-no risk of reactivation? Does that risk change over time? Can tests of incipient TB that all currently rely on transcriptional signatures be converted to point-of-care assays that are practical in resource-limited settings? Clearly more research is required to better understand the pathogenesis and immune responses that categorize status of infection and risk of disease on both a microscopic (e.g., within the granuloma) and macroscopic (clinical outcomes) level to drive better diagnostic and therapeutic modalities for the future.

We thank all the members of the Flynn and Lin laboratories and our colleagues Drs. Sarah Fortune, Denise Kirschner, Charles Scanga, Edwin Klein, Hannah Gideon, and Joshua Mattila for helpful discussions that contributed to this review. Special thanks to Elise Y. Chu and Pauline Maiello for artistic and graphic contributions.

This work was supported by the Bill and Melinda Gates Foundation (to J.L.F. and P.L.L.), Aeras (to J.L.F.), and National Institutes of Health Grants AI111871 and AI134195 (to P.L.L.) and HL110811, AI114674, AI123093, and AI094745 (to J.L.F.).

Abbreviations used in this article:

BCG

bacille Calmette–Guérin

CT

computed tomography

FDG

2-deoxy-2-[18F]-fluoro-D glucose

IGRA

IFN-γ release assay

LTBI

latent M. tuberculosis infection

PET

positron emission tomography

TB

tuberculosis

TST

tuberculin skin test.

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The authors have no financial conflicts of interest.