Alexandra Vujkovic

T cell receptor (TCR) sequencing is an emerging tool in immunovirology with the potential to improve how we detect and interpret virus induced immune responses. This thesis investigates the diagnostic biomarker potential of high-throughput TCR repertoire analysis in two distinct viral contexts: acute SARS-CoV-2 infection and chronic HIV. By using subset-specific TCR sequencing, this work explores how different CD8+ T cell populations could capture temporal dynamics of immune exposure. We demonstrate that activated CD8+ T cells (HLA-DR+/CD38+) are enriched for virus-specific clonotypes during acute infection, enabling discrimination between active COVID-19 and the absence of active infection, including individuals with prior SARS-CoV-2 exposure. In contrast, memory subsets, particularly effector memory cells, retain persistent HIV-specific TCR signatures in people living with HIV (PLWH). These subset-specific profiles reveal a dichotomous model wherein different compartments of the T cell repertoire could serve as indicators of acute or past viral exposure, laying the foundation for a "dual-diagnostic" approach. While promising, the translation of TCR sequencing into clinical diagnostics faces several challenges, including the need for robust, virus-specific TCR signatures, and standardization across genetically diverse populations. Addressing these issues through large-scale, functionally validated, and ethnically diverse cohorts is essential. Ultimately, this thesis establishes that subset-resolved TCR repertoire profiling not only enhances our understanding of viral immunity but could also serve as inspiration for the development of next-generation diagnostics capable of distinguishing between infection stages.

Proteins encoded by the ESX-1 genes of interest are essential for full virulence in all Mycobacterium tuberculosis complex (Mtbc) lineages, the pathogens causing the highest mortality worldwide. Identifying critical regions in these ESX-1-related proteins could provide preventive or therapeutic targets for Mtb infection, the game changer needed for tuberculosis control. We analyzed a compendium of whole genome sequences of clinical Mtb isolates from all lineages from >32,000 patients and identified single nucleotide polymorphisms. When mutations corresponding to all non-synonymous single nucleotide polymorphisms were mapped on structural models of the ESX-1 proteins, fully conserved regions emerged. Some could be assigned to known quaternary structures, whereas others could be predicted to be involved in yet-to-be-discovered interactions. Some mutants had clonally expanded (found in >1% of the isolates); these mutants were mostly located at the surface of globular domains, remote from known intra- and inter-molecular protein–protein interactions. Fully conserved intrinsically disordered regions of proteins were found, suggesting that these regions are crucial for the pathogenicity of the Mtbc. Altogether, our findings highlight fully conserved regions of proteins as attractive vaccine antigens and drug targets to control Mtb virulence. Extending this approach to the whole Mtb genome as well as other microorganisms will enhance vaccine development for various pathogens. IMPORTANCE: We mapped all non-synonymous single nucleotide polymorphisms onto each of the experimental and predicted ESX-1 proteins’ structural models and inspected their placement. Varying sizes of conserved regions were found. Next, we analyzed predicted intrinsically disordered regions within our set of proteins, finding two putative long stretches that are fully conserved, and discussed their potential essential role in immunological recognition. Combined, our findings highlight new targets for interfering with Mycobacterium tuberculosis complex virulence.

T-cell–based diagnostic tools identify pathogen exposure but lack differentiation between recent and historical exposures in acute infectious diseases. Here, T-cell receptor (TCR) RNA sequencing was performed on HLA-DR⁺/CD38⁺CD8⁺ T-cell subsets of hospitalized coronavirus disease 2019 (COVID-19) patients (n = 30) and healthy controls (n = 30; 10 of whom had previously been exposed to severe acute respiratory syndrome coronavirus 2 [SARS-CoV-2]). CDR3α and CDR3β TCR regions were clustered separately before epitope specificity annotation using a database of SARS-CoV-2–associated CDR3α and CDR3β sequences corresponding to >1000 SARS-CoV-2 epitopes. The depth of the SARS-CoV-2–associated CDR3α/β sequences differentiated COVID-19 patients from the healthy controls with a receiver operating characteristic area under the curve of 0.84 ± 0.10. Hence, annotating TCR sequences of activated CD8⁺ T cells can be used to diagnose an acute viral infection and discriminate it from historical exposure. In essence, this work presents a new paradigm for applying the T-cell repertoire to accomplish TCR-based diagnostics.

Coronavirus disease 2019 (COVID-19) is a viral lower respiratory tract infection caused by the highly transmissible and pathogenic SARS-CoV-2 (severe acute respiratory-syndrome coronavirus-2). Besides respiratory failure, systemic thromboembolic complications are frequent in COVID-19 patients and suggested to be the result of a dysregulation of the hemostatic balance. Although several markers of coagulation and fibrinolysis have been studied extensively, little is known about the effect of SARS-CoV-2 infection on the potent antifibrinolytic enzyme carboxypeptidase U (CPU). Blood was collected longitudinally from 56 hospitalized COVID-19 patients and 32 healthy controls. Procarboxypeptidase U (proCPU) levels and total active and inactivated CPU (CPU+CPUi) antigen levels were measured. At study inclusion (shortly after hospital admission), proCPU levels were significantly lower and CPU+CPUi antigen levels significantly higher in COVID-19 patients compared to controls. Both proCPU and CPU+CPUi antigen levels showed a subsequent progressive increase in these patients. Hereafter, proCPU levels decreased and patients were, at discharge, comparable to the controls. CPU+CPUi antigen levels at discharge were still higher compared to controls. Baseline CPU+CPUi antigen levels (shortly after hospital admission) correlated with disease severity and the duration of hospitalization. In conclusion, CPU generation with concomitant proCPU consumption during early SARS-CoV-2 infection will (at least partly) contribute to the hypofibrinolytic state observed in COVID-19 patients, thus enlarging their risk for thrombosis. Moreover, given the association between CPU+CPUi antigen levels and both disease severity and duration of hospitalization, this parameter may be a potential biomarker with prognostic value in SARS-CoV-2 infection.