Recent technological advances in life sciences have greatly enhanced our ability to address scientific questions at the molecular level with unprecedented depth. Since its introduction, Next Generation Sequencing (NGS) enables high-throughput analysis and over time, has become increasingly accessible and affordable, shaping the future of both research and clinical applications. Spatially resolved transcriptomics (SRT), particularly in situ sequencing (ISS), provides single-cell transcriptomic data while preserving the histopathological context of the surrounding tissue microenvironment. This thesis explores the application of padlock probes in combination with in situ sequencing (ISS) or next-generation sequencing (NGS), to tackle questions related to specific diseases.

In paper I, we examined the spatial interactions between Mycobacterium tuberculosis (Mtb) and immune cells in lungs of tuberculosis-infected mice, mapping immune-related transcripts near bacterial clusters and single bacteria. Our findings indicate macrophage activation close to single bacteria in Mtb-resistant C57BL/6 mice. In contrast, organized granulomas that are dominant in lung tissue of Mtb-susceptible C3HeB/FeJ mice, were not enriched for transcripts of immune activation. This approach provides insights into immune responses to tuberculosis and highlights the power of spatially resolved transcriptomics for studying host-pathogen interactions.

In paper II, we investigated the tumor microenvironment in non-small cell lung cancer (NSCLC), focusing on the impact of T cell clonality. We related TCR clonality to genetic mutations, tumor immune profiles, and responses to immunotherapy. Our data show that high TCR clonality is associated with a high tumor mutational burden, inflamed tumor phenotypes, and, notably, improved responses to checkpoint inhibitors, suggesting its potential as a biomarker for personalized immunotherapy in NSCLC. 

In paper III, we spatially explored TCR patterns and immune cell distributions in selected NSCLC tissues with matching unaffected lymph nodes, as well as HER2+ breast cancer cases during neoadjuvant therapy. We noted lower TCR diversity in cancer tissues compared to matched lymph nodes. Our data further revealed regional dominance of expanded clonotypes, predominantly CD8 T cells, located in close proximity to the cancer compartment. Overall, these results demonstrate the utility of ISS in providing crucial, spatial details of the interplay between clonal T cell expansion within the tumor immune microenvironment in diagnostic tissue samples, particularly in the therapeutic context.

In paper IV, we developed a cost-effective molecular inversion probe (MIP)-based assay for detecting microbial pathogens and antimicrobial resistance markers in blood samples, offering high specificity and sensitivity even in low-resource settings. The MIP approach simplifies pathogen detection without extensive sample preparation or bioinformatics analysis, making it an accessible tool for infectious disease monitoring in under-resourced areas.

Collectively, this work demonstrates the application of padlock probes and advanced technologies to deepen our understanding of diseases and improve diagnostics and personalized therapies.

Background T-cell activation and clonal expansion are essential to effective immunotherapy responses in non-small cell lung cancer (NSCLC). The distribution of T-cell clones may offer insights into immunogenic mechanisms and imply potential prognostic and predictive information. Methods We analyzed α/β T-cell receptor (TCR) clonality using RNA-sequencing of bulk frozen tumor tissue from 182 patients with NSCLC. The data was integrated with molecular and clinical characteristics, extensive in situ imaging, and spatial sequencing of the tumor immune microenvironment. TCR clonality was also determined in an independent cohort of nine patients with immune checkpoint-treated NSCLC. Results TCR clonality (Gini index) patterns ranged from high T-cell clone diversity with high evenness (low Gini index) to clonal dominance with low evenness (high Gini index). Generally, TCR clonality in cancer was lower than in matched normal lung parenchyma distant from the tumor (p=0.021). The TCR clonality distribution between adenocarcinoma and squamous cell carcinoma was similar; however, smokers showed a higher Gini index. While in the operated patient with NSCLC cohort, TCR clonality was not prognostic, in an immune checkpoint inhibitor-treated cohort, high TCR clonality was associated with better therapy response (p=0.016) and prolonged survival (p=0.003, median survival 13.8 vs 2.9 months). On the genomic level, a higher Gini index correlated strongly with a lower frequency of epidermal growth factor receptor (EGFR) and adenomatous polypsis coli (APC) gene mutations, but a higher frequency of P53 mutations, and a higher tumor mutation burden. In-depth characterization of the tumor tissue revealed that high TCR clonality was associated with an activated, inflamed tumor phenotype (PRF1, GZMA, GZMB, INFG) with exhaustion signatures (LAG3, TIGIT, IDO1, PD-1, PD-L1). Correspondingly, PD-1+, CD3+, CD8A+, CD163+, and CD138+immune cells infiltrated cancer tissue with high TCR clonality. In situ sequencing recovered single dominant T-cell clones within the patient tumor tissue, which were predominantly of the CD8 subtype and localized closer to tumor cells.

Background Global efforts to characterize diseases of poverty are hampered by lack of affordable and comprehensive detection platforms, resulting in suboptimal allocation of health care resources and inefficient disease control. Next generation sequencing (NGS) can provide accurate data and high throughput. However, shotgun and metagenome-based NGS approaches are limited by low concentrations of microbial DNA in clinical samples, requirements for tailored sample and library preparations plus extensive bioinformatics analysis. Here, we adapted molecular inversion probes (MIPs) as a cost-effective target enrichment approach to characterize microbial infections from blood samples using short-read sequencing. We designed a probe panel targeting 2 bacterial genera, 21 bacterial and 6 fungi species and 7 antimicrobial resistance markers (AMRs).

Results Our approach proved to be highly specific to detect down to 1 in a 1000 pathogen DNA targets contained in host DNA. Additionally, we were able to accurately survey pathogens and AMRs in 20 out of 24 samples previously profiled with routine blood culture for sepsis.

Conclusions Overall, our targeted assay identifies microbial pathogens and AMRs with high specificity at high throughput, without the need for extensive sample preparation or bioinformatics analysis, simplifying its application for characterization and surveillance of infectious diseases in medium- to low- resource settings.

Elucidating spatiotemporal changes in gene expression has been an essential goal in studies of health, development, and disease. In the emerging field of spatially resolved transcriptomics, gene expression profiles are acquired with the tissue architecture maintained, sometimes at cellular resolution. This has allowed for the development of spatial cell atlases, studies of cell-cell interactions, and in situ cell typing. In this review, we focus on padlock probe-based in situ sequencing, which is a targeted spatially resolved transcriptomic method. We summarize recent methodological and computational tool developments and discuss key applications. We also discuss compatibility with other methods and integration with multiomic platforms for future applications.

Mycobacterium tuberculosis (Mtb) bacilli are the causative agent of tuberculosis (TB), a major killer of mankind. Although it is widely accepted that local interactions between Mtb and the immune system in the tuberculous granuloma determine whether the outcome of infection is controlled or disseminated, these have been poorly studied due to methodological constraints. We have recently used a spatial transcriptomic technique, in situ sequencing (ISS), to define the spatial distribution of immune transcripts in TB mouse lungs. To further contribute to the understanding of the immune microenvironments of Mtb and their local diversity, we here present two complementary automated bacteria-guided analysis pipelines. These position 33 ISS-identified immune transcripts in relation to single bacteria and bacteria clusters. The analysis was applied on new ISS data from lung sections of Mtb-infected C57BL/6 and C3HeB/FeJ mice. In lungs from C57BL/6 mice early and late post infection, transcripts that define inflammatory macrophages were enriched at subcellular distances to bacteria, indicating the activation of infected macrophages. In contrast, expression patterns associated to antigen presentation were enriched in non-infected cells at 12 weeks post infection. T-cell transcripts were evenly distributed in the tissue. In Mtb-infected C3HeB/FeJ mice, transcripts characterizing activated macrophages localized in apposition to small bacteria clusters, but not in organized granulomas. Despite differences in the susceptibility to Mtb, the transcript patterns found around small bacteria clusters of C3HeB/FeJ and C57BL/6 mice were similar. Altogether, the presented tools allow us to characterize in depth the immune cell populations and their activation that interact with Mtb in the infected lung.

The malarial parasite Plasmodium exports its own proteins to the cell surfaces of red blood cells (RBCs) during infection. Examples of exported proteins include members of the repetitive interspersed family (RIFIN) and subtelomeric variable open reading frame (STEVOR) family of proteins from Plasmodium falciparum. The presence of these parasite-derived proteins on surfaces of infected RBCs triggers the adhesion of infected cells to uninfected cells (rosetting) and to the vascular endothelium potentially obstructing blood flow. While there is a fair amount of information on the localization of these proteins on the cell surfaces of RBCs, less is known about how they can be exported to the membrane and the topologies they can adopt during the process. The first step of export is plausibly the cotranslational insertion of proteins into the endoplasmic reticulum (ER) of the parasite, and here, we investigate the insertion of three RIFIN and two STEVOR proteins into the ER membrane. We employ a well-established experimental system that uses N-linked glycosylation of sites within the protein as a measure to assess the extent of membrane insertion and the topology it assumes when inserted into the ER membrane. Our results indicate that for all the proteins tested, transmembranes (TMs) 1 and 3 integrate into the membrane, so that the protein assumes an overall topology of Ncyt-Ccyt. We also show that the segment predicted to be TM2 for each of the proteins likely does not reside in the membrane, but is translocated to the lumen.

XBP1u, a central component of the unfolded protein response (UPR), is a mammalian protein containing a functionally critical translational arrest peptide (AP). Here, we present a 3 angstrom cryo-EM structure of the stalled human XBP1u AP. It forms a unique turn in the ribosomal exit tunnel proximal to the peptidyl transferase center where it causes a subtle distortion, thereby explaining the temporary translational arrest induced by XBP1u. During ribosomal pausing the hydrophobic region 2 (HR2) of XBP1u is recognized by SRP, but fails to efficiently gate the Sec61 translocon. An exhaustive mutagenesis scan of the XBP1u AP revealed that only 8 out of 20 mutagenized positions are optimal; in the remaining 12 positions, we identify 55 different mutations increase the level of translational arrest. Thus, the wildtype XBP1u AP induces only an intermediate level of translational arrest, allowing efficient targeting by SRP without activating the Sec61 channel.

Secretory proteins translocate across the mammalian ER membrane co-translationally via the ribosome-sec61 translocation machinery. Signal sequences within the polypeptide, which guide this event, are diverse in their hydrophobicity, charge, length, and amino acid composition. Despite the known sequence diversity in the ER signals, it is generally assumed that they have a dominant role in determining co-translational targeting and translocation process. We have analyzed co-translational events experienced by secretory proteins carrying efficient versus inefficient signal sequencing, using an assay based on Xbp1 peptide-mediated translational arrest. With this method we were able to measure the functional efficiency of ER signal sequences. We show that an efficient signal sequence experiences a two-phase event whereby the nascent chain is pulled from the ribosome during its translocation, thus resuming translation and yielding full-length products. Conversely, the inefficient signal sequence experiences a single weaker pulling event, suggesting inadequate engagement by the translocation machinery of these marginally hydrophobic signal sequences.

Xbp1, a protein involved in the unfolded protein response, is a rare example of a mammalian protein that contains a well-defined translational arrest peptide (AP). In order to define the critical residues in the Xbp1u AP, and to search for variants with stronger arrest potency than the wildtype Xbp1u AP, we have carried out a full mutagenesis scan where each residue in the AP was replaced by the other 19 natural amino acids. We find that 10 of the 21 mutagenized positions are optimal already in the wildtype Xbp1 AP, while certain mutations in the remaining residues lead to a strong increase in the arrest potency. Xbp1 has thus evolved to induce an intermediate level of translational arrest, and versions with much stronger arrest efficiency exist. We further show Xbp1- induced translational arrest is reduced in response to increased tension in the nascent chain, making it possible to carry out studies in mammalian systems of cotranslational processes such as membrane protein assembly and protein folding by using suitable Xbp1 AP variants as “force sensors”, as has been done previously in E. coli using bacterial APs.