Dissecting patient macrophage responses to Mycobacterium tuberculosis Complex strains from Tanzania and assessing T cell biomarkers for TB diagnosis and treatment monitoring

Tuberculosis (TB) has existed throughout human history, traced back to 9000 years ago to date. TB is transmitted through inhalation of infective air droplets from an infected person to the next susceptible host. This devastating disease has been a major cause of death from a single infectious agent more than HIV/AIDS and malaria combined before the COVID-19 pandemic. Caused by several genetically distinct Mycobacterium tuberculosis complex (MTBC) species, TB causes the death of a person every 22 seconds making MTBC one of the most successful human pathogen. TB is mostly curable with a specific combination of anti-TB drugs. Yet the increase of strains carrying drug-resistance mutations and the gap between people who are not diagnosed contributes to the reported TB related deaths. Ending this ongoing epidemic will require investment in biomedical, public health and socioeconomic interventions to sustain the necessary research and development of the necessary tools. Improvement of current diagnostic tests and development of new diagnostic approaches is necessary to increase case detection rates and close in the 4.2 million gap of people who are currently missed every year. In addition, genetically distinct MTBC lineages are differentially distributed globally; further understanding of the link between this diversity and MTBC pathogenesis is likely to improve management of TB patients in different epidemiological settings.
In the first part of this thesis, we hypothesized that TB disease epidemiology in Tanzania is driven by the human-MTBC genetic interactions resulting in an increased susceptibility of specific hosts to a specific circulating MTBC strain. This hypothesis was investigated in Chapter 3, where I will first give detailed introduction of the human adapted MTBC lineages, their distribution and factors contributing to their global distribution. I will then introduce current concepts of strain adaptation to local host populations driven by genetic interaction between human hosts and the circulating strains in various epidemiological settings. To test our hypothesis, we selected representative MTBC strain endemic to the Temeke District of Dar es Salaam where patients were recruited, and peripheral blood mononuclear cells cryopreserved. Patient-derived macrophages from monocytes isolated from their collected blood were infected either with a genetically related strain that had originally infected the patient (“matched infection”) or with other endemic lineages (“mismatched infection”). MTBC replication within patients’ macrophages as well as cytokine and chemokine production in response to infection were assessed. We observed that lineage-matched ex-vivo infection of macrophages derived from TB patients could not deliver sympatric associations signals. In turn, our results suggest that TB epidemiology in Tanzania is mainly driven by different MTBC strain-specific pathogenesis strategies rather than host-specific genetic traits.
In the second part of this thesis, we explored the hypothesis that bacterial load perception by the host adaptive immune system results in a measurable activation status that can be used to: i) diagnose TB infection and; ii) monitor disease resolution. This work is presented in Chapter 4 in which we investigated the diagnostic potential of two T-cell activation markers (TAM) for TB diagnosis (TAM-TB assay). The TAM-TB assay was assessed using a simplified protocol starting from 1ml of blood to comply with childhood TB diagnosis. In this chapter, I will introduce the current TB diagnostic tools, their limitations and provide reasons supporting the implementation of the TAM-TB assay in the field. I will then detail how we assessed the diagnostic performance of the TAM-TB assay for TB diagnosis starting from 1ml of blood from 479 active TB patients and 108 symptomatic controls. I will present how sample processing was done to measure expression of CD38 or CD27 by CD4 T cells producing IFN-γ and/or TNF-α in response to a synthetic peptide pool covering the sequences MTBC ESAT-6, CFP-10 and TB10.4 antigens using a 4-color FACSCalibur apparatus. The CD38-based TAM-TB assay specificity reached 93.4% for a sensitivity of 82.2% with an area under the receiver operating characteristics curve of 0.87 (95% CI 0.84-0.91). I will demonstrate how TAM-TB routine testing with a 24h turnaround time at district level in a resource-limited setting was successfully implemented. Starting from 1ml of blood and being not affected by HIV status, I will conclude that CD38-based TAM-TB assay performance appears closely compatible with the optimal target product profile accuracy criteria defined by WHO for a non-sputum confirmatory TB test.
In Chapter 5, we explored the use of the TAM-TB assay as proxy of host bacterial load and consequently, a treatment-monitoring tool. In this chapter, I will introduce why treatment monitoring is important not only for patient management but also for clinical trials evaluating new treatment regimens. I will also develop the shortcomings of current tools used to measure bacterial load and disease resolution and the need for alternative measures. In this work, we hypothesized that the phenotype of MTBC-specific T cells may be quantitatively impacted by the load of bacteria present in a given patient. To test this hypothesis, we obtained 1 ml blood from 105 active TB patients, before and after 5 months of antibiotic treatment. We evaluated the relationships between patients’ clinical characteristics of disease severity and microbiological as well as molecular proxies of bacterial load in sputum at the time of diagnosis. Reflecting the difficulty to extrapolate bacterial burden from a single end-point read-out, we observed statistically significant but weak correlations between Xpert MTB/RIF, MBLA and time to culture positivity. We demonstrated that resolution of CD38 expression by antigen-specific T cells was observed readily following 5 months of antibiotic therapy. However, the intensity of CD38-TAM signals measured at diagnosis did not significantly correlate with MTBC 16S rRNA or rpoB DNA detected in patients’ sputa. Altogether, our data support CD38-TAM as an accurate marker of infection resolution independently of sputum bacterial load. The CD38-based TAM-TB assay constitutes a promising assay to monitor treatment response.
In summary, in this thesis I dissected the influence of both human and MTBC genetic variability in the epidemiology of TB in Tanzania to an unprecedented extent matching endemic strains to infect patient’s host cells. Secondly, we addressed key aspects in the END-TB strategy to circumvent the limitations of current TB diagnostic tools showing the potential of CD38-based TAM-TB assay as a promising non-sputum diagnostic test that can be implemented in the field and routinely deliver accurate results with a 24h turnaround time.