Session 4

4.1 Cancer proteomics — connecting genotype with molecular phenotype Janne Lehtiö(1) (1)Karolinska Institutet, Science for Life Laboratory, Stockholm, Sweden The explosion of genomics data has improved our understanding of cancer greatly in recent years. However, the knowledge of how genomic aberrations affect the functional proteome at the systems level is still very limited. Proteome data represents the combined effect of epigenetic, transcriptional and translational regulation and will therefore provide an important molecular phenotype data layer for multi-omics analysis. To allow effective systems biology analysis including proteomics, we have generated tools that take advantage of massive genomics data by incorporating sequence information to the proteomics data-analysis pipeline. This will allow protein level analysis of gene variants as well as detection of novel protein coding regions. To control error rate in variant detection, we have a combined experimental isoelectric point data from peptide fractions (HiRIEF LC-MS/MS) and bioinformatics approaches into the proteogenomics workflow (IPAW). A proteogenomics analysis of histologically human tissues using the IPAW pipeline reveals novel coding regions. When applied on breast cancer tumor sample, we could demonstrate in-depth quantitative analysis revealing drug target interesting correlations as well as discovers putative cancer neoantigens. Further, to narrow down on proteins involved in immediate cellular response to drug treatment, we have analyzed cell subcellular relocation of protein post drug treatment using SubCellBarcode based proteome wide location analysis. 4.2 The relation between infection, autoimmune mechanisms and Parkinson's disease Michel Desjardins(1) (1)Département de pathologie et biologie cellulaire, Université de Montréal Parkinson's disease (PD) is a neurodegenerative disorder caused by the progressive loss of dopaminergic neurons (DNs). While it affects close to 3% of the population over 75 years of age, a significant proportion of PD patients, possibly as high as 10%, develops the disease due to familial, transmitted mutations, at a much earlier age. Two of the genes mutated in early-onset PD, PINK1 and Parkin, are involved in mitophagy, the process by which damaged mitochondria are captured for recycling within autophagosomes. Hence, it is assumed that in the absence of PINK1 or Parkin, failure to eliminate non-functional mitochondria in DNs results in the accumulation of toxic organelles, excessive oxidative stress and cell death. Although compelling, this model has proven difficult to validate in vivoas there is, so far, little evidence for a deregulation of mitophagy within DNs in PD. Furthermore, Parkin- and PINK1-independent pathways of mitophagy exist, suggesting the involvement of these proteins in PD through different mechanisms. Importantly, PINK1 and Parkin KO mice are generally healthy and display no signs of the disease. We have shown recently that PINK1 and Parkin play a role in the immune system by inhibiting the formation of mitochondria-derived vesicles (MDVs) and mitochondrial antigenpresentation, a process we refer to as MitAP. In the absence of PINK1/Parkin, stress conditions such as inflammation induced by LPS treatment activate MitAP in antigen presenting cells (macrophages and dendritic cells) in vivo, a process leading to the establishment of autoreactive CD8+ T cells. LPS being the major component of the outer membrane of Gram-negative bacteria, we went on to show that gut infection with enteropathogenic E. coli (EPEC) induces MitAP and the elicitation of anti-mirochondrial CD8+ T cells in PINK1 KO mice. Remarkably, these animals display severe motor impairment as early as 3 months after infection, reversible by L-DOPA treatment. The link between infection, autoimmune mechanisms and the emergence of parkinsonism in PD-susceptible mice opens novel avenues for the development of therapeutics. 4.3 Identification of mechanisms of activity and resistance to thalidomide analogs with a targeted quantitative immuno-mass spectrometry assay Adam S. Sperling(1,2), Michael Burgess(2), Hasmik Keshishian(2), Jessica A. Gasser(1,2), Max Jan(1,2), Mikolaj Slabicki(1,2), Peter G. Miller(1), Rohan Sharma(1), Dylan N. Adams(1), Mariateresa Fulciniti(1), Namrata D. Udeshi(2), Eric Kuhn(2), Nikhil C. Munshi(1), Steven A. Carr(2), Benjamin L. Ebert(1,2) (1)Dana-Farber Cancer Institute, (2)Broad Institute of MIT and Harvard Pharmacologic agents that modulate ubiquitin ligase activity to induce protein degradation are a major new class of therapeutic agents. We developed a high-throughput, quantitative, targeted mass spectrometry (MS) assay leveraging immune enrichment of specific peptides to measure the levels of proteins that are degraded by the CRL4(CRBN) ubiquitin ligase in the presence of thalidomide analogs. Using this immuno-MS assay to determine the levels of eight protein substrates, we defined key differences in substrate specificity between thalidomide derivatives, characterized distinct kinetics of degradation for different substrates, and identified a novel mechanism of resistance to this class of drugs mediated by competition between substrates for access to the ubiquitin ligase. We demonstrated that increased expression of a non-essential substrate can lead to decreased degradation of other substrates that are critical for anti-neoplastic activity of the drug, resulting in drug resistance. These findings suggest that tissue-specific activity of drugs that induce protein degradation will depend on the levels of the ubiquitin ligase as well as the expression of substrates. The quantitative mass spectrometry assay we describe is a powerful tool to characterize the activity of novel molecules that induce protein degradation, to evaluate the activity of such molecules in vitro and in vivo, and to predict sensitivity and resistance to this class of therapeutic agents. 4.4 Crosslinking mass spectrometry and single particle cryoEM describe the structure of a novel translocon in complex with the ribosome Michael J. Trnka(1), Philip T. McGilvray(2), Robert J. Keenan(2), Alma L. Burlingame(1) (1)University of California San Francisco, CA 94158, (2)University of Chicago, IL 60637 Multi-pass transmembrane proteins play key roles in numerous aspects of cell physiology. These proteins are synthesized at the endoplastic reticulum (ER) and their insertion, folding, and assembly into the membrane is coordinate by the 'translocon', a poorly defined and dynamic assembly comprising the Sec61 translocation channel and a variety of accessory subunits that act cotranslationally with the ribosome. We have isolated a novel eukaryotic, 93-protein ribosome-translocon complex (RTC) that facilitates the biogenesis of ∼20% of all multi-pass membrane proteins. The structure of this RTC was characterized by single particle EM reconstruction supported by crosslinking mass spectrometry (CLMS). Over 1200 unique crosslinked residue pairs were identified at an FDR of 0.5%. A subset of 130 crosslinks localized the translocon at the exit channel of the ribosome and facilitated modeling of electron density corresponding to the lumenal and membrane subunits of the translocon. Crosslinking was performed using the membrane soluble reagent DSS, and analysis was performed using sequential high resolution HCD and ETD product ion scans of the same precursor ion, on an Fusion Lumos mass spectrometer. The decoy distribution was modeled using 930 randomized sequences, corresponding to 10 decoy versions of each target protein. FDR calculations were adjusted for the discrepancy in database sizes using a mathematical approach described here. Additional checks on the validity of the dataset came from agreement of the ribosomal crosslinks with high-resolution structure and by monitoring ribosomal aggregation during reaction optimization with negative stain EM. We discuss the relationship between crosslink violation rate and FDR. Mass spectrometry for this work was supported by the Dr. Miriam and Sheldon G. Adelson Medical Research Foundation, the UCSF Program for Breakthrough Biomedical Research (PBBR) and HHMI. 4.5 Systematic profiling of HLA class I immunopeptidome improves neoantigen binding prediction Susan Klaeger(1) (1)Broad Institute Highly polymorphic class I HLA proteins present short peptides from endogenous or foreign proteins to cytotoxic T cells. Each allele is estimated to present 1,000–10,000 peptides, however the rules of antigen presentation are not fully understood. Mass spectrometry allows for direct identification of endogenously processed and presented peptides. Using a single allele expressing cell line, the underlying criteria for antigen presentation can be systematically studied. This information is of high value for training epitope prediction models used in e.g. personalized vaccine generation. Our strategy improves the performance of current predictive algorithms and provides a rapid and scalable method to generate rules for the substantially diverse set of human HLA alleles. We developed a mono-allelic MS approach to profile endogenously presented HLA-peptides, whereby the HLA class I deficient B721.221 cell line expresses a single allele of interest and eluted HLA peptides are analyzed by LC-MS/MS. Using this approach, we have generated binding data for 95 HLA- A, B, C and G alleles identifying more than 200,000 peptides and covering the most frequent alleles in the population. This extensive dataset enables peptide-binding and proteasomal cleavage motifs to be elucidated on a single allele basis. HLA- A and B alleles present more peptides of length 10–11 than C alleles, while C alleles have a higher propensity for 8-mers. Correlation-based analysis of binding motifs revealed that HLA-A and B motifs are more specific whereas C motifs are less stringent and thus share more overlapping binders. This data is used to train neural network mo

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