Surfaceome Architecture Maps of Primary Human T Cell Subsets Reveal Distinct T Cell Receptor Protein Communities

The cell surface proteome (surfaceome) is the primary interface for cellular communication and environmental sensing. The identity, abundance, and spatial organization of surface proteins (surfaceome architecture) reflect cellular state and functional potential. Determining how proteins are organized at the cell surface could identify disorganized protein communities in diseased cells and guide the development of precision therapies. While highly relevant for clinical translation, the comprehensive surfaceome architecture interrogation of rare primary human cell systems is constrained by sensitivity limitations of current methods. To overcome these limitations, in my thesis I redesigned strategies for cell surface capture (CSC) and receptor-proximity labeling (LUX-MS) technologies, now enabling robust spatial proteotyping of the surfaceome and contained receptor communities for rare primary human cell populations (Chapter 2). Key improvements comprise automated cell washing, SP2-based cleanup and the development of specialized data integration pipelines for prior knowledge annotation. Further improvements involved adoption of a specialized tag for CSC enrichment, a customized lysis buffer for enhanced membrane protein extraction, streptavidin bead washing in 96-well plates, improved PNGaseF deglycosylation efficiency, shortened liquid chromatography gradients, enhanced signature motif detection and expansion of the N-glycosylation motif. These technical improvements allowed the creation of receptor community and global surfaceome maps of primary human T cells from limited input material (5 x 105 - 5 x 106 primary T cells). This is anticipated to enable receptor community mapping for sub-subsets of central interest, such as Treg cells, and highly multiplexed protein community mapping on primary human panT cells for one single donor. Next, I asked whether the refined technologies can be applied to test whether pre-formed, subset-specific αβ-T cell receptor (αβTCR) proximity architectures could underlie second-scale TCR signaling kinetics and subset-specific stimulus responses (Chapter 3). To this end, the optimized CSC and LUX-MS strategies were applied to compare surfaceome identity, abundance and organisation between primary human naive and memory CD4+ and CD8+ T cell subsets. Using CSC technology, 282 high-confidence surface proteins were quantified, showing strong conservation across sorted T cell subsets. While naive subsets showed high quantitative similarity, memory subsets differed in abundance, reflecting their known activation-induced functional specialization, reflected in the enrichment of memory CD4+ T cells in immune modulatory functions. LUX-MS technology enabled the identification of 355 αβTCR-proximal candidates across T cell subsets, revealing both shared and subset-specific proximity proteins which were visualized in a subset-resolved αβTCR proximity map. Annotating the interactors of apical TCR signaling, curated protein-protein interactions, and signaling contexts suggested conserved and subset-specific signaling regulators. Analysis of αβTCR protein communities for protein complex subunits as well as protein family- and domain-level enrichment analyses supported functional specialization within subset-specific αβTCR neighborhoods aligning with the known function of these subsets. Further, we evaluated and demonstrated that protein-protein interaction network propagation of the highest-confidence pan-T αβTCR neighborhood can be leveraged to predict adjacent protein modules located in the plasma membrane or within the cell cortex. Lastly, LUX-MS technology was adapted to map interactions between adeno-associated viruses and host cells, identifying molecular determinants of tissue tropism and informing the design of viral gene therapy vehicles. The resulting pipeline overcomes challenges associated with adeno-associated viruses and enables the time-resolved discovery of adeno-associated virus receptors (Chapter 4). To summarize, in my thesis I developed CSC and LUX-MS strategy based systems biology framework for multilayered surfaceome analysis. The framework enabled the generation of molecular reference maps of αβTCR protein communities across primary human T cell subsets, revealing that quantitative global surfaceome similarity does not translate into local receptor-proximity networks. Together, those findings support the hypothesis of pre-formed, subset-specific receptor community neighborhoods, and emphasize the need to extend receptor community mapping to decipher signaling responsiveness. Finally, primary human T cells are presented as a valuable system for translational studies that could, in the future, facilitate the development of T‑cell subset-specific engagement anchors, assessment of patient immune responsiveness, and mapping of disease‑driving receptor protein communities in clinical samples.