Distinguishing Latent from Active Mycobacterium tuberculosis Infection Using Elispot Assays: Looking Beyond Interferon-gamma

The Applications of ELISpot in the Identification and Treatment of Various Forms of Tuberculosis and in the Cancer Immunotherapies

ELISpot (enzyme-linked immunospot) is a powerful immunological tool for the detection of cytokine-secreting cells at a single-cell resolution. It is widely used for the diagnosis of various infectious diseases, e.g., tuberculosis and sarcoidosis, and it is also widely used in cancer immunotherapy research. Its ability to distinguish between active and latent forms of tuberculosis makes it an extremely powerful tool for epidemiological studies and contact tracing. In addition to that, it is a very useful tool for the research and development of cancer immunotherapies. ELISpot can be employed to assess the immune responses against various tumor-associated antigens, which could provide valuable insights for the development of effective therapies against cancers. Furthermore, it plays a crucial role to the evaluation of immune responses against specific antigens that not only could aid in vaccine development but also assist in treatment monitoring and development of therapeutic and diagnostic strategies. This chapter briefly describes some of the applications of ELISpot in tuberculosis and cancer research.

Sticholysin II shows similar immunostimulatory properties to LLO stimulating dendritic cells and MHC-I restricted T cell responses of heterologous antigen

Induction of CD8⁺ T cell responses against tumor cells and intracellular pathogens is an important goal of modern vaccinology. One approach of translational interest is the use of liposomes encapsulating pore-forming proteins (PFPs), such as Listeriolysin O (LLO), which has shown efficacy at priming strong and sustained CD8⁺ T cell responses. Recently, we have demonstrated that Sticholysin II (StII), a PFP from the sea anemone Stichodactyla helianthus, co-encapsulated into liposomes with ovalbumin (OVA) was able to stimulate, antigen presenting cells, antigen-specific CD8⁺ T cells and anti-tumor activity in mice. In the present study, we aimed to compare StII and LLO in terms of their abilities to stimulate dendritic cells and to induce major histocompatibility complex (MHC) class I restricted T cell responses against OVA. Interestingly, StII exhibited similar abilities to LLO in vitro of inducing dendritic cells maturation, as measured by increased expression of CD40, CD80, CD86 and MHC-class II molecules, and of stimulating OVA cross-presentation to a CD8⁺ T cell line. Remarkably, using an ex vivo Enzyme-Linked ImmunoSpot Assay (ELISPOT) to monitor gamma interferon (INF-γ) producing effector memory CD8⁺ T cells, liposomal formulations containing either StII or LLO induced comparable frequencies of OVA-specific INF-γ producing CD8⁺ T cells in mice that were sustained in time. However, StII-containing liposomes stimulated antigen-specific memory CD8⁺ T cells with a higher potential to secrete IFN-γ than liposomes encapsulating LLO. This StII immunostimulatory property further supports its use for the rational design of T cell vaccines against cancers and intracellular pathogens. In summary, this study indicates that StII has immunostimulatory properties similar to LLO, despite being evolutionarily distant PFPs.

Evaluation of cytokines as a biomarker to distinguish active tuberculosis from latent tuberculosis infection: a diagnostic meta-analysis

OBJECTIVES

With a marginally effective vaccine and no significant breakthroughs in new treatments, a sensitive and specific method to distinguish active tuberculosis from latent tuberculosis infection (LTBI) would allow for early diagnosis and limit the spread of the pathogen. The analysis of multiple cytokine profiles provides the possibility to differentiate the two diseases.

DESIGN

Systematic review and meta-analysis.

DATA SOURCES

PubMed, Cochrane Library, Clinical Key and EMBASE databases were searched on 31 December 2019.

ELIGIBILITY CRITERIA

We included case-control studies, cohort studies and randomised controlled trials considering IFN-γ, TNF-α, IP-10, IL-2, IL-10, IL-12 and VEGF as biomarkers to distinguish active tuberculosis and LTBI.

DATA EXTRACTION AND SYNTHESIS

Two students independently extracted data and assessed the risk of bias. Diagnostic OR, sensitivity, specificity, positive and negative likelihood ratios and area under the curve (AUC) together with 95% CI were used to estimate the diagnostic value.

RESULTS

Of 1315 records identified, 14 studies were considered eligible. IL-2 had the highest sensitivity (0.84, 95% CI: 0.72 to 0.92), while VEGF had the highest specificity (0.87, 95% CI: 0.73 to 0.94). The highest AUC was observed for VEGF (0.85, 95% CI: 0.81 to 0.88), followed by IFN-γ (0.84, 95% CI: 0.80 to 0.87) and IL-2 (0.84, 95% CI: 0.81 to 0.87).

CONCLUSION

Cytokines, such as IL-2, IFN-γ and VEGF, can be utilised as promising biomarkers to distinguish active tuberculosis from LTBI.

PROSPERO REGISTRATION NUMBER

CRD42020170725.

A Systematic Review of Methodological Variation in Healthcare Provider Perspective Tuberculosis Costing Papers Conducted in Low- and Middle-Income Settings, Using An Intervention-Standardised Unit Cost Typology

BACKGROUND

There is a need for easily accessible tuberculosis unit cost data, as well as an understanding of the variability of methods used and reporting standards of that data.

OBJECTIVE

The aim of this systematic review was to descriptively review papers reporting tuberculosis unit costs from a healthcare provider perspective looking at methodological variation; to assess quality using a study quality rating system and machine learning to investigate the indicators of reporting quality; and to identify the data gaps to inform standardised tuberculosis unit cost collection and consistent principles for reporting going forward.

METHODS

We searched grey and published literature in five sources and eight databases, respectively, using search terms linked to cost, tuberculosis and tuberculosis health services including tuberculosis treatment and prevention. For inclusion, the papers needed to contain empirical unit cost estimates for tuberculosis interventions from low- and middle-income countries, with reference years between 1990 and 2018. A total of 21,691 papers were found and screened in a phased manner. Data were extracted from the eligible papers into a detailed Microsoft Excel tool, extensively cleaned and analysed with R software (R Project, Vienna, Austria) using the user interface of RStudio. A study quality rating was applied to the reviewed papers based on the inclusion or omission of a selection of variables and their relative importance. Following this, machine learning using a recursive partitioning method was utilised to construct a classification tree to assess the reporting quality.

RESULTS

This systematic review included 103 provider perspective papers with 627 unit costs (costs not presented here) for tuberculosis interventions among a total of 140 variables. The interventions covered were active, passive and intensified case finding; tuberculosis treatment; above-service costs; and tuberculosis prevention. Passive case finding is the detection of tuberculosis cases where individuals self-identify at health facilities; active case finding is detection of cases of those not in health facilities, such as through outreach; and intensified case finding is detection of cases in high-risk populations. There was heterogeneity in some of the reported methods used such cost allocation, amortisation and the use of top-down, bottom-up or mixed approaches to the costing. Uncertainty checking through sensitivity analysis was only reported on by half of the papers (54%), while purposive and convenience sampling was reported by 72% of papers. Machine learning indicated that reporting on 'Intervention' (in particular), 'Urbanicity' and 'Site Sampling', were the most likely indicators of quality of reporting. The largest data gap identified was for tuberculosis vaccination cost data, the Bacillus Calmette-Guérin (BCG) vaccine in particular. There is a gap in available unit costs for 12 of 30 high tuberculosis burden countries, as well as for the interventions of above-service costs, tuberculosis prevention, and active and intensified case finding.

CONCLUSION

Variability in the methods and reporting used makes comparison difficult and makes it hard for decision makers to know which unit costs they can trust. The study quality rating system used in this review as well as the classification tree enable focus on specific reporting aspects that should improve variability and increase confidence in unit costs. Researchers should endeavour to be explicit and transparent in how they cost interventions following the principles as laid out in the Global Health Cost Consortium's Reference Case for Estimating the Costs of Global Health Services and Interventions, which in turn will lead to repeatability, comparability and enhanced learning from others.

Diagnostic performance of culture filtered protein 10-specific perforin in pediatric patients with active tuberculosis

Background

Mycobacterium tuberculosis (Mtb)‐specific perforin were significantly increased in patients with tuberculosis. This study aims to evaluate the diagnosis value of Mtb‐specific perforin in pediatric patients with tuberculosis.

Methods

Diagnostic performance of perforin levels induced by 6‐kDa early secreted antigen target (ESAT6) or culture filtered protein 10 (CFP10) were evaluated in eighty‐six samples from children participants by receiver operating characteristic curve analysis. Flow cytometry was used to detect the expression of perforin and INF‐γ of CD4⁺, CD8⁺ T cells in response to CFP10 stimulation.

Results

After ex vivo stimulation, levels of ESAT6/CFP10‐specific perforin in LTBI patients were significantly higher than active TB (ATB) patients, non‐tuberculosis infection (non‐TB), and health control (HC) individuals. The diagnostic efficacy of CFP10‐specific perforin for TB diagnosis was significantly higher than ESAT6‐specific perforin and T‐SPOT assay, and when 0.74 ng/mL was taken as the cutoff value, the sensitivity, specificity, and accuracy were 97.83%, 87.5%, and 93.02%. CFP10‐specific perforin in both CD4⁺ and CD8⁺ T cells were significantly higher in ATB patients compared to HCs and further increased in LTBI patients. However, INF‐γ was mainly secreted by CD4⁺ T cells and showed no significant difference between LTBI and ATB patients. In addition, CFP10‐specific perforin can effectively distinguish between ATB and LTBI with the cutoff value of 1.80 ng/mL. Sensitivity and specificity were 88.46% and 85.62%, respectively.

Conclusions

CFP10‐specific perforin may be used as a novel cellular immunity‐based diagnostic marker of pediatric patients with tuberculosis, and with the potential for discriminating ATB from LTBI.

Combination of mean spot sizes of ESAT-6 spot-forming cells and modified tuberculosis-specific antigen/phytohemagglutinin ratio of T-SPOT.TB assay in distinguishing between active tuberculosis and latent tuberculosis infection

OBJECTIVES

Distinguishing between active tuberculosis (ATB) and latent tuberculosis infection (LTBI) remains challenging.

METHODS

The modified T-SPOT.TB assay was performed in 499 participants (243 ATB and 256 LTBI) and another 322 participants (162 ATB and 160 LTBI) who were diagnosed in Qiaokou (training) and Caidian (validation) cohort respectively.

RESULTS

The mean spot sizes (MSS) of early secreted antigenic target 6 (ESAT-6) spot-forming cells (SFC) of T-SPOT.TB assay in ATB patients was significantly higher than that in LTBI individuals. 1.0 × 10⁵ was the optimal number of cells added to phytohaemagglutinin (PHA) well for obtaining more accurate TB-specific antigen to phytohaemagglutinin (TBAg/PHA) ratio. The area under the curve of the diagnostic model by combination of ESAT-6 SFC MSS and modified TBAg/PHA ratio in distinguishing ATB from LTBI was 0.959 in training cohort, with a sensitivity of 90.12% and a specificity of 91.02% when a cutoff value of 0.46 was used. This diagnostic model showed similar performance in the validation cohort. The area under the curve, sensitivity, and specificity were 0.962, 93.21%, and 90.00%, respectively. Further flow cytometry analysis showed that ESAT-6 stimulation induced a significantly higher mean fluorescence intensity of IFN-γ⁺ cells in lymphocytes compared with culture filtrate protein 10 (CFP-10) stimulation. In contrast, CFP-10 stimulation induced a significantly higher percentage of IFN-γ⁺ cells in lymphocytes compared with ESAT-6 stimulation.

CONCLUSIONS

The combination of the MSS of ESAT-6 SFC and the modified TBAg/PHA ratio of T-SPOT.TB assay showed great value in discriminating ATB from LTBI.

Tissue inhibitor of metalloproteinases 1, a novel biomarker of tuberculosis

Tuberculosis (TB) is an important infectious disease of humans and other animals. Conventional diagnostic methods, including the tuberculin skin test, chest X‑rays and bacterial culture, have certain innate disadvantages for the early, rapid and specific diagnosis of tuberculosis. The present study aimed to identify a novel diagnostic biomarker to overcome these disadvantages. The potential target identified in the present study was tissue inhibitor of metalloproteinases 1 (TIMP‑1), which has previously been demonstrated to be critical in the immune response to TB. The concentration of TIMP‑1 in the blood was determined using a commercial ELISA kit, and the relative mRNA expression levels following bacterial infection were detected by reverse transcription‑quantitative polymerase chain reaction. Based on a clinical and microbiological diagnosis, the ELISA for plasma TIMP‑1 had a sensitivity of 91.80% [95% confidence interval (CI): 85.44, 96.00] and a specificity of 91.41% (95% CI: 85.14, 95.63). In a THP‑1 cell model, Bacillus Calmette‑Guérin and Mycobacterium bovis significantly upregulated the mRNA expression levels of TIMP‑1 post infection in a time‑dependent manner (P=0.006 for BCG 24 h PI, P=3.2x10‑7 for M. bovis 24 PI). The results of the present study indicate that plasma TIMP‑1 may be a potential biomarker for the diagnosis of TB.

Use of lateral flow assays to determine IP-10 and CCL4 levels in pleural effusions and whole blood for TB diagnosis

One of the key problems in combating TB is the lack of fast and accurate diagnostic tests that are affordable and easy to use in resource-limited settings. We have used a field-friendly up-converting phosphor (UCP) reporter technology in a lateral flow (LF) based test for the diagnosis of respiratory infections. In this study we analysed samples obtained from patients presenting with symptoms suggestive of TB but prior to confirmation by microbiology in The Gambia. Following clinical and microbiological evaluation they were classified as either having TB or other respiratory disorder (ORD). Analysis of blood was performed for those with pulmonary TB and pleural fluid for those with pleural TB. UCP-LF test for detection and quantitation of IP-10 and CCL4 were used being the two chemokine markers that have been shown to increase in active TB disease. UCP-LF test accurately determined concentrations of both markers as compared to ELISA and multiplex cytokine array. However, only IP-10 could discriminate between TB and ORD, and this was significantly enhanced by analysing the site of infection (pleural fluid), which showed 92% correct classification. Future work will assess the use of multiple markers to increase diagnostic accuracy.

Application of Long-term cultured Interferon-γ Enzyme-linked Immunospot Assay for Assessing Effector and Memory T Cell Responses in Cattle

Effector and memory T cells are generated through developmental programing of naïve cells following antigen recognition. If the infection is controlled up to 95 % of the T cells generated during the expansion phase are eliminated (i.e., contraction phase) and memory T cells remain, sometimes for a lifetime. In humans, two functionally distinct subsets of memory T cells have been described based on the expression of lymph node homing receptors. Central memory T cells express C-C chemokine receptor 7 and CD45RO and are mainly located in T-cell areas of secondary lymphoid organs. Effector memory T cells express CD45RO, lack CCR7 and display receptors associated with lymphocyte homing to peripheral or inflamed tissues. Effector T cells do not express either CCR7 or CD45RO but upon encounter with antigen produce effector cytokines, such as interferon-γ. Interferon-γ release assays are used for the diagnosis of bovine and human tuberculosis and detect primarily effector and effector memory T cell responses. Central memory T cell responses by CD4(+) T cells to vaccination, on the other hand, may be used to predict vaccine efficacy, as demonstrated with simian immunodeficiency virus infection of non-human primates, tuberculosis in mice, and malaria in humans. Several studies with mice and humans as well as unpublished data on cattle, have demonstrated that interferon-γ ELISPOT assays measure central memory T cell responses. With this assay, peripheral blood mononuclear cells are cultured in decreasing concentration of antigen for 10 to 14 days (long-term culture), allowing effector responses to peak and wane; facilitating central memory T cells to differentiate and expand within the culture.

Mycobacterium tuberculosis-specific TNF-α is a potential biomarker for the rapid diagnosis of active tuberculosis disease in Chinese population

Interferon-gamma release assays (IGRAs) have proven to be useful to accurately detect Mycobacterium tuberculosis (Mtb) infection, but they cannot reliably discriminate between active tuberculosis (TB) and latent tuberculosis infection (LTBI). This study aims to test whether Mtb-specific tumor necrosis factor-alpha (TNF-α) could be used as a new tool for the rapid diagnosis of active TB disease. The secretion of TNF-α by Mtb-specific antigen-stimulated peripheral blood mononuclear cells (PBMCs) of sixty seven participants was investigated in the study. Our results showed that the total measurement of TNF-α secretion by Mtb-specific antigen-stimulated PBMCs is not a good biomarker for active TB diagnosis. However, we found that calculation of Mtb-specific TNF-α not only distinguish between active and latent TB infection, but also can differentiate active TB from non-TB patients. Using the cutoff value of 136.9 pg/ml for Mtb-specific TNF-α, we were able to differentiate active TB from LTBI. Sensitivity and specificity were 72% and 90.91%. These data suggest that Mtb-specific TNF-α could be a potential biomarker for the diagnosis of active TB disease.