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The function of a protein is mediated by its ability to form precise three-dimensional structures or specific protein-protein interaction (PPI) interfaces. However, it has been challenging to study these aspects of the proteome at scale, in sufficient detail, and in a generalisable way. Cross-linking mass spectrometry (XL-MS) performed on high complexity samples (such as entire organelles or cells) theoretically enables the large scale mapping and monitoring of protein structural conformations and PPI interfaces in native proteoforms. However, as the large scale XL-MS field is young and historically driven by the reporting of technological innovations, assessment of the biological accuracy (and overall utility) of large scale XL-MS studies is still largely underexplored. This thesis applies large scale XL-MS to two eukaryotic systems (Saccharomyces cerevisiae and cultured human cells) and is presented as three independent studies. Firstly, it reports the first budding yeast XL-MS interactome, generated by cross-linking intact nuclei isolated from wild-type cells with DSSO. The wealth of yeast interactome data enabled identification of an inflated false discovery rate for cross-links representing PPIs, and development of a novel quality control approach. Surprisingly, the high confidence PPIs were substantially orthogonal to historical binary interactome mapping efforts. Subsequently, it reports the largest XL-MS dataset currently available for any species, generated by diversifying analyses (cross-linkers, mass spectrometry analyses, software) performed on organelles isolated from human HEK293 cells. Here, we show how the ~30,000 low-resolution distance constraints generated in near-native proteoforms can be used to uniquely (1) contextualise regions within existing experimental protein structures, (2) annotate interfaces in PPIs and multi-protein complexes, and (3) validate structures predicted by computational modellers like AlphaFold. Finally, this thesis reports the use of quantitative XL-MS to explore links between gene function and cellular phenotype, comparing wild-type yeast with a highly pleiotropic deletion strain (Δhpm1) using SILAC multiplexing and PIR cross-linking of intact cells. The untargeted comparison of structural conformations and PPIs uniquely enabled insights into phenotypes entirely invisible to investigation of protein abundance alone. This thesis will therefore argue that XL-MS is the missing link in the systems biology toolbox.

Cross-linking mass spectrometry (XL-MS) is a powerful tool for studying protein-protein interactions and elucidating architectures of protein complexes. However, one of the inherent challenges in MS analysis of cross-linked peptides is their unambiguous identification. To facilitate this process, we have previously developed a series of amine-reactive sulfoxide-containing MS-cleavable cross-linkers. These MS-cleavable reagents have allowed us to establish a common robust XL-MS workflow that enables fast and accurate identification of cross-linked peptides using multistage tandem mass spectrometry (MSn). Although amine reactive reagents targeting lysine residues have been successful, it remains difficult to characterize protein interaction interfaces with little or no lysine residues. To expand the coverage of protein interaction regions, we present here the development of a series novel sulfoxide-containing cross-linker that target acidic residues (dihydrazide sulfoxide (DHSO)), cystine residues (bismaleimidesulfoxide (BMSO)), and finally a heterobifunctional cross-linker that targets lysine on one end and a non-specifically targets residues (Succinimidyl diazirine sulfoxide (SDASO)) on the other. We demonstrate that cross-linkers create cross-linked peptides that display the same predictable and characteristic fragmentation pattern during collision induced dissociation as amine-reactive sulfoxide-containing MS-cleavable cross-linked peptides, thus permitting their simplified analysis and unambiguous identification by MSn. Furthermore, we applied these linkers to either characterize the yeast 26S proteasome (SDASO) or the Cop9 signalosome (DSSO, DHSO and BMSO) demonstrating both the feasibility of SDASO’s photocross-linking of large protein complexes for the first time and the ability of multi-chemistry data for the integrative structure modeling of protein complexes to determine the interaction and structural dynamics of CSN, respectively. Moreover, our platform targeting various chemistries with cross-linking is robust and captures interactions complementary to residue-specific reagents, providing the foundation for future applications of multi-chemistry targeting approach to studying protein complexes.