The freshwater planarian Schmidtea mediterranea has been used in research for over 100 years, and is an emerging stem cell model. Exteriorly, planarians are covered in mucous secretions of unknown composition. While the planarian genome has been sequenced, it remains mostly unannotated. The goal my master’s research was to annotate the planarian proteome and mucous sub-proteome. Using a proteogenomics approach, I elucidated the proteome and mucous subproteome via mass spectrometry together with an in silico translated transcript database. I identified 1604 proteins, which were annotated using the Swiss-Prot BLAST algorithm and Gene Ontology analysis. The S. mediterranea proteome is highly similar to that predicted for the trematode Schistosoma mansoni associated with schistosomiasis. Remarkably, orthologs of 119 planarian mucous proteins are present in human mucosal secretions and tear fluid. I suggest planarians have potential to be a model system for parasitic worms and diseases underlined by mucous aberrancies.

The freshwater planarian Schmidtea mediterranea has been used in research for over 100 years, and is an emerging stem cell model. Exteriorly, planarians are covered in mucous secretions of unknown composition. While the planarian genome has been sequenced, it remains mostly unannotated. The goal my master’s research was to annotate the planarian proteome and mucous sub-proteome. Using a proteogenomics approach, I elucidated the proteome and mucous subproteome via mass spectrometry together with an in silico translated transcript database. I identified 1604 proteins, which were annotated using the Swiss-Prot BLAST algorithm and Gene Ontology analysis. The S. mediterranea proteome is highly similar to that predicted for the trematode Schistosoma mansoni associated with schistosomiasis. Remarkably, orthologs of 119 planarian mucous proteins are present in human mucosal secretions and tear fluid. I suggest planarians have potential to be a model system for parasitic worms and diseases underlined by mucous aberrancies.

L'extrême complexité des échantillons biologiques, la variabilité technique et la dépendance de la protéomique envers les banques protéiques empêchent l'analyse complète d'un protéome. Ce travail de thèse s'est focalisé sur le développement de méthodes pour la protéomique quantitative et la protéogénomique afin d'améliorer la caractérisation du protéome. Premièrement mon travail s'est centré sur le développement de méthodes quantitatives globales et ciblées. La mise en place de standards pour évaluer les performances de tous les niveaux de la stratégie analytique est aussi décrite. Ces méthodes ont été optimisées pour répondre à diverses questions biologiques. Mon doctorat s'est focalisé aussi autour de la protéogénomique. Une méthode d'analyse N-terminomique à haut débit a été développée et appliquée à l'étude de la mitochondrie humaine. Enfin, ce manuscrit présente une approche multi-omique visant à améliorer l'analyse du protéome avec la création de banques de données personnalisées . / The high intrinsic complexity of biological samples, the technical variability and the dependency of Bottom-up Proteomics to consensus protein sequence databases handicap the comprehensive analysis of an entire Proteome. My doctoral work was focused on method development in quantitative Proteomics and Proteogenomics in order to achieve a better proteome characterization. First, I focused on the development of global and targeted quantitative methods. The introduction and development of standard samples to assess the performances at any level of the analytical workflow is also described. These methods were applied to answer different biological questions. My PhD also focused on Proteogenomic method development. A high throughput N-terminomic analysis approach was developed and applied to the analysis of the human mitochondria. Finally, this manuscript presents a personalized multi-omics profiling strategy to improve the proteome analysis with the use of personalized databases.

Breast cancer is the second most common type of cancer among women in the US and the second leading cause of cancer death. HER2+ breast cancers represent ~20% of all cancer types, are highly invasive, and can be treated by using targeted therapies against the HER2 receptor. However, these therapies are challenged by the development of drug resistance, often induced by the presence of mutations in the cell-membrane proteins and receptors and/or by alternative signaling pathways that cross-talk with- or transactivate HER2+ triggered signaling. This study was aimed at investigating the cell membrane proteome of SKBR3 cells, representative of HER2+ breast cancers, and the signaling landscape and cellular responses elicited by the cell membrane receptors when the cells are stimulated with either growth factors or therapeutic drugs. It was hypothesized that the identification of a broad range of cell membrane proteins with roles in cancer progression and signaling crosstalk will lead to a more comprehensive understanding of the biological processes that sustain the proliferation of cancer cells, and will guide the selection of more efficient drug targets. The project was conceptualized in three stages: (1) profiling the cell membrane proteins of SKBR3 cells, (2) determining the functional role of the detected cell membrane proteins in the context of cancer hallmarks and exploring their mutational profile, and (3) analyzing the cellular events that occur in response to treatment with a single therapeutic agent or a combination of drugs. Mass spectrometry technologies were used for performing proteomic and phosphoproteomic profiling of SKBR3 cells, detecting changes in the abundance of the detected proteins, and identifying the presence of mutations in the cell membrane proteins. Orthogonal enrichment methods were developed for profiling the low-abundance cell membrane proteins, for generating a rich landscape of cell membrane receptors with various functional roles and relevance to the cancer hallmarks, and for enabling the detection of potentially new drivers of aberrant proliferation. The analysis of serum-starved, stimulated (with growth factors), or inhibited (with kinase inhibitors) cells revealed alternative protein players and crosstalk activities that determine the fate of cells, and that may fuel the development of resistance to treatment with drugs. The proteome profiles that were generated in this project expand the opportunities for targeting cancer-relevant processes beyond proliferation, which is commonly attempted, broadening the landscape to also include apoptosis, invasion, and metastasis. Altogether, the findings that emerged from this work will lay the ground for future studies that aim at developing more complex and effective targeted cancer treatment approaches. / Doctor of Philosophy / Breast cancer is one of the most common cancers among women in the US and the second major contributor to cancer-related deaths. Several therapies that have been developed for the treatment of cancer target the HER2 receptor, which is overexpressed in ~20% of breast cancers and results in a highly invasive cancer phenotype. However, most patients receiving these therapies observe cancer reoccurrence within a year due to the development of resistance to the therapeutic drug. The current challenge stands in identifying novel protein targets, and in developing new therapies that can be used in combination with the existing approaches to eradicate cancer. Research has indicated that proteins located at the cell membrane play crucial roles in cancer progression and invasion due to their involvement in cell response to stimuli and in initiating signaling cascades within the cell. Knowledge about the cell membrane proteins of HER2+ breast cancer cells is limited due to the challenges associated with their isolation. Therefore, this project was aimed at profiling the cell membrane proteins of HER2+ breast cancer cells, and their intra-cellular signaling activity, to provide insights into the behavior of these cells and to support the identification of potentially novel drug targets. The three objectives of the work were to (1) isolate the cell membrane proteins through various approaches using cell culture conditions that would encourage or discourage cancer cell growth, (2) identify the cancer-relevant signaling pathways and processes represented by the detected cell membrane proteins, and (3) investigate the behavior of cancer cells when treated with drugs. To approach these objectives, a powerful analytical technology, called mass spectrometry, was utilized. Mass spectrometry can accurately and simultaneously detect the presence of the proteins in a biological sample. Our study identified cell membrane proteins that are involved in cancer progression through various signaling pathways, and how these proteins interact with each other to drive the behavior of cells. The study also provided insights into how cancer cells respond when they are treated with various drugs, uncovering to the scientific community a variety of proteins with potential therapeutic value. Lastly, this study sheds light on the complex biology of breast cancer and highlights the importance of continued research to develop more effective treatments.

L’objectif de cette thèse était de développer et d’optimiser de nouvelles méthodologies et approches analytiques afin d’améliorer le potentiel de l’analyse protéomique pour les études biologiques.La première partie de ce travail est consacrée à la détermination massive et exacte de la position N-Terminale des protéines (N-Terminome). Pour cela, nous avons utilisé et développé une approche basée sur une dérivation N-Terminale au TMPP. Cette méthodologie de marquage de la position N-Terminale a permis d’aborder l’étude des clivages protéolytiques des protéines exportées par le parasite P. falciparum (pathogène de la malaria) dans le globule rouge.Afin de permettre une exploitation automatique à haut débit des données de MS/MS, nous avons élaboré une nouvelle méthodologie (dénommée dN-TOP). Celle-Ci repose sur l’utilisation de TMPP portant des isotopes stables et permet ainsi d’accéder à la détermination des positions N-Terminales pour des études de N-Terminome à large échelle.La seconde partie est dédiée aux développements de différentes stratégies analytiques de quantification, aussi bien au niveau peptidique qu’au niveau protéique, appliquées à une série de problématiques biologiques. Ces optimisations ont été réalisées dans le contexte de l’étude des complexes protéiques, du dosage de prion par SRM, de quantification des glycations d’anticorps monoclonaux thérapeutiques et de l’hémoglobine HbA2 pour la standardisation des méthodes de référence. / The objective of this Ph.D. thesis was to develop and optimize new methodologies and analytical approaches to improve the potential of the mass spectrometry based proteomics.The first part of this work focused on the development of the N-Termini proteomics. This topic was addressed with a specific N-Termini chemical derivatization based on TMPP. We have shown that our method allowed both specific N-Terminomics and classical proteomics studies in the same experiment.This N-Terminus methodology was applied to study the proteolytic cleavages of the exported proteins in P. falciparum, a parasite responsible for the malaria.In order to automatize the complex and tedious informatics processsing of the MS/SM data of ourTMPP based N-Terminomics method, we have introduced a new approach (named dN-TOP), based on the use of a stable isotope labeled TMPP which made now N-Terminome proteomics compatible with high throughput studies.The second part addresses quantitative aspects of proteomics. It describes the optimization of quantitative methods at the peptide level or at the protein level for five different proteomic studies in the context of protein complex subunits, targeted SRM based prion, quantification of monoclonal antibodies glycation and hemoglobin HbA2 for reference measurement methods standardization.

The scope and application of high throughput techniques has expanded from studying a single genome, transcriptome or proteome to understanding complex environments at a greater resolution with the help of novel computational frameworks. Comprehensive structural annotation i.e. description of all functional elements in the genome, is required for measuring genome response accurately, using high throughput methods. Annotation of genome sequences using high throughput data from RNA-seq and proteomics experiments complement computational methods for identifying functional elements and can help validate existing in silico annotation, correct annotation errors, and could potentially identify novel functional elements. Re-annotation studies in recent times have revealed shortcomings of automated methods and the necessity to validate existing annotations using experimental data. This dissertation elucidates re-annotation of Mannheimia haemolytica, Pasteurella multocida and Histophilus somni, bacterial pathogens associated with bovine respiratory disease in cattle. Experimental re-annotation of these bacterial genomes using RNA-seq and proteomics enabled the validation of existing annotation and discovery of novel functional elements that can be utilized in future functional genomics studies. We also addressed the need for developing an automated bioinformatics workflow that is broadly applicable for bacterial genome re-annotation, by developing open source Perl pipeline that can use RNA-seq and proteomics data as input. Simultaneous analysis of host and pathogen gene expression profiling using metatranscriptomics approaches is necessary to improve our understanding of infectious diseases. Traditional methods for analysis of RNA-seq data do not address the impact of cross-mapping of reads to multiple genomes for data originating from a metatranscriptomic study. Analysis of sequence conservation between species can help determine a metric for cross mapping to correct for signal vs. noise. We generated artificial RNA-seq data and evaluated the impact of read length and sequence conservation on cross-mapping. Comparative genomics was used to identify a core and pan-genome for quantifying gene expression. Our results show that cross mapping between genomes can directly be related to evolutionary distance between these genomes and that an increase in RNA-seq read length tends to negate cross mapping.

Technological advancements in mass spectrometry allowing quantification of almost complete proteomes make proteomics a key platform for generating unique functional molecular data. Furthermore, the integrative analysis of genomic and proteomic data, termed proteogenomics, has emerged as a new field revealing insights into gene expression regulation, cell signalling, and disease processes. However, the lack of software tools for high-throughput integration and unbiased modification and variant detection hinder efforts for large-scale proteogenomics studies. The main objectives of this work are to address these issues by developing and applying new software tools and data analysis methods. Firstly, I address mapping of peptide sequences to reference genomes. I introduce a novel tool for high-throughput mapping and highlight its unique features facilitating quantitative and post-translational modification mapping alongside accounting for amino acid substitutions. The performance is benchmarked. Furthermore, I offer an additional tool that permits generation of web accessible hubs of genome wide mappings. To enable unbiased identification of post-translational modifications and amino acid substitutions for high resolution mass spectrometry data, I present algorithmic updates the mass tolerant blind spectrum comparison tool ’MS SMiV’. I demonstrate the applicability of the changes by benchmarking against a published mass tolerant database search of a high resolution tandem mass spectrometry dataset. I then present the application of ‘MS SMiV’ on a panel of 50 colorectal cancer cell lines. I show that the adaption of ‘MS SMiV’ outperforms traditional sequence database based identification of single amino acid variants. Furthermore, I highlight the utility of mass tolerant spectrum matching in combination with isobaric labelled quantitative proteomics in distinguishing between post-translational modifications and amino acid variants of similar mass. In the last part of this work I integrate both tools with a high-throughput proteogenomic identification pipeline and apply it to a pilot study of chondrocytes derived from 12 osteoarthritic individuals. I show the value of this approach in identifying variation between individuals and molecular levels and highlight them with individual examples. I show that multi-plexed proteogenomics can be used to infer genotypes of individuals.

La 5-azacytidine (AZA) est un médicament approuvé pour le traitement des leucémies myéloïdes aiguës des patients qui ne sont pas éligibles à une greffe de cellules souches hématopoïétiques. Bien que l’AZA est augmenté significativement le pronostic des patients, le mécanisme d’action précis de l’AZA demeure nébuleux. En plus de son activité d’hypométhylation, il a été montré que l’AZA a aussi des effets immunologiques. Des études précédentes suggèrent que ces réponses immunitaires sont causées par des modifications du répertoire de peptides présentés par le CMH-I (MAPs), dont l’expression de MAPs dérivés de rétroéléments endogènes (EREs) et des cancer-testis antigens (CTAs). Ces gènes sont généralement réprimés par la méthylation de l’ADN. Dans cette thèse, nous avons testé cette hypothèse à l’aide de séquençage à haut débit et de spectrométrie de masse appliqués à quatre lignées cellulaires d’AML différentes. Notre approche protéogénomique d’avant-garde a révélé que l’AZA induit la présentation de MAPs dérivés de CTAs, mais pas d’EREs, malgré le fait que ces deux groupes de séquences soient surexprimés au niveau transcriptomique. Ces résultats indiquent que les réponses des lymphocytes T observées chez les patients suite au traitement à l’AZA dépendent probablement des MAPs dérivés des CTAs, et non pas des EREs. Les EREs stimulés par l’AZA ont tout de même un impact sur la réponse immunitaire en formant des ARN double-brins menant à une activation de l’immunité innée. L’incorporation de l’AZA et l’inhibition subséquente de la DNMT2 mène cependant à des agrégats protéiques et à l’autophagie, qui dégrade les transcrits EREs et limite leur surexpression. Nous avons démontré que les effets immunologiques de l’AZA peuvent être amplifiés par un traitement combiné de l’AZA et d’inhibiteurs de l’autophagie. De plus, le travail contenu dans cette thèse a montré que bien qu’elles soient un modèle expérimental pratique, les lignées cellulaires ont des limitations et doivent être utilisés avec prudence. Des différences majeures ont été observées entre des lignées cellulaires supposément identiques provenant de fournisseurs établis. Nos analyses ont permis de démontrer quelle lignée cellulaire était la plus similaire à la lignée parentale. Ainsi, ce travail fourni des recommandations pour améliorer les lignes directrices d’utilisation des lignées cellulaires en recherche. / 5-azacytidine (AZA) is approved for the treatment of acute myeloid leukemia (AML) patients ineligible for hematopoietic cell transplantation. Although AZA treatment has substantially improved patient outcomes, there remains a lack of clear understanding of the mechanisms driving these responses. In addition to its hypomethylating activity, AZA has been shown to have immunological effects. Previous reports suggest that these immune responses occur due to alterations in the repertoire of MHC-I-associated peptides (MAPs), including the expression of MAPs deriving from endogenous retroelements (EREs) and cancer-testis antigens (CTAs). These genes are typically silenced by methylation. With this thesis, we aimed to test this hypothesis using high-coverage RNA sequencing and mass spectrometry in four different AML cell lines. Our state-of-the-art proteogenomic approach uncovered that AZA treatment induced MAPs deriving from CTAs, but not EREs, despite both being upregulated at the RNA level. This indicates that T-cell responses post-AZA treatment are more likely to be dependent on CTA- than ERE-derived MAP presentation. AZA-induced EREs produced at the RNA level still contributed to immune responses by forming double-stranded RNA leading to a state of viral mimicry. However, AZA incorporation into RNA and subsequent DNMT2-inhibition led to protein aggregation and autophagy responses. These responses were responsible for degrading EREs, which limited their upregulation. We further demonstrate that the immune effects of AZA can be enhanced by the combination of AZA with autophagy inhibitors. Additionally, the work in this thesis has shown that although a practical model, cell lines have their caveats and must be used with caution. This work has highlighted the grave discrepancies between supposedly identical cell lines supplied by established repositories. Moreover, our analyses determine which of the two is closer to the parental cell line. Finally, this work provides recommendations for improving the current guidelines for cell line-based research.

Increasing evidence of non-canonical protein translation has sparked interest in their identification and characterization for use in immunotherapy. In addition, recent studies on the repertoire of major histocompatibility complex class I (MHC-I) associated peptides (MAPs or immunopeptidome), have suggested that MAPs derived from these translations are potential targets for cancer immunotherapy. Therefore, the aim of this study was to assess the impact of these MAPs in cancer by developing methods to facilitate their identification and their validation as potential targets for immunotherapy. To facilitate the identification of non-canonical proteins, we developed Ribo-db, a proteogenomic approach that combines RNA sequencing, ribosome profiling and mass spectrometry. This approach enables the generation of specific databases aimed at including protein diversity. The use of Ribo-db to analyze diffuse large B-cell lymphoma (DLBCL) samples revealed that approximately 10% of MAPs were derived from non-canonical proteins. These proteins had distinct properties compared to those derived from canonical proteins. They had shorter lengths and lower stability, but greater efficiency in generating MAPs. Importantly, we found limited overlap between the non-canonical proteins detected in the immunopeptidome and those detected in the whole proteome suggesting the existence of two distinct non-canonical protein repertoires. Knowing that non-canonical MAPs can be effective targets for cancer immunotherapy, we developed BamQuery, a tool to assess their expression in tissues to determine whether they can be used in a vaccine. BamQuery aims to predict the probability of MHC-I presentation of each peptide in different tissues based on its RNA expression. Using BamQuery, we found that previously identified tumor antigens (TA) would be highly expressed in healthy tissues, making them poor candidates for immunotherapy. In addition, we also identified highly potential immunotherapeutic targets in DLBCL that were derived from non-canonical translations. These targets showed promising as they were poorly expressed in normal tissues but highly expressed and shared in tumor samples. Thus, BamQuery proved to be a useful tool for identifying and prioritizing potential immunotherapeutic targets. Overall, our research indicated that non-canonical regions of the genome increase the diversity of MAPs that can be recognized by T cells. Furthermore, the expression of MAPs in tissues can be used as a predictor of their presentation to MHC I to identify reliable targets for immunotherapy, for which BamQuery is an effective tool. / Les preuves de plus en plus nombreuses de la traduction des protéines non canonique ont suscité l'intérêt pour leur identification et leur caractérisation en vue de leur utilisation dans les immunothérapies. En outre, des études récentes sur le répertoire des peptides associés au complexe majeur d'histocompatibilité de classe I (CMH-I, connus sous le nom de MAPs ou immunopeptidome), ont suggéré que les MAPs dérivés de ces traductions sont des cibles potentielles pour l'immunothérapie du cancer. L'objectif de cette étude était donc d'évaluer l'impact de ces MAP dans le cancer en développant des méthodes pour faciliter leur identification et leur validation en tant que cibles potentielles pour l'immunothérapie. Afin de faciliter l'identification des protéines non canoniques, nous avons développé Ribodb, une approche protéogénomique qui combine le séquençage de l'ARN, le profilage ribosomal et la spectrométrie de masse. Cette approche permet de générer des bases de données spécifiques visant à inclure la diversité des protéines. Notre analyse avec Ribo-db d'échantillons de lymphome diffus à grandes cellules B (DLBCL) a révélé qu'environ 10% des MAP étaient dérivés de protéines non canoniques. Ces protéines avaient des propriétés distinctes par rapport à celles dérivées de protéines canoniques. Elles étaient plus courtes et avaient une stabilité plus faible, mais une plus grande efficacité dans la génération de MAPs. Fait important, nous avons constaté un chevauchement limité entre les protéines non canoniques détectées dans l'immunopeptidome et celles détectées dans le proteome entier, ce qui suggère l'existence de deux répertoires distincts de protéines non canoniques. Sachant que les MAP non canoniques peuvent être des cibles efficaces pour l'immunothérapie du cancer, nous avons développé BamQuery, un outil permettant d'évaluer leur expression dans les tissus afin de déterminer s'ils peuvent être utilisés dans un vaccin. BamQuery vise à prédire la probabilité de présentation au CMH-I de chaque MAP dans différents tissus sur la base de son expression ARN. En utilisant BamQuery, nous avons découvert que des antigènes tumoraux (TA) précédemment identifiés seraient fortement exprimés dans les tissus sains, ce qui en fait de mauvais candidats pour l'immunothérapie. En outre, nous avons également ii identifié des cibles immunothérapeutiques très potentielles dans DLBCL qui étaient dérivées de traductions non canoniques. Ces cibles se sont révélées prometteuses car elles étaient peu exprimées dans les tissus normaux mais fortement exprimées et partagées dans les échantillons tumoraux. Ainsi, BamQuery s'est avéré être un outil utile pour identifier et hiérarchiser les cibles immunothérapeutiques potentielles. Dans l'ensemble, nos recherches ont indiqué que les régions non canonique du génome augmentent la diversité des MAPs qui peuvent être reconnues par les cellules T. De plus, l'expression des MAPs dans les tissus peut être utilisée comme un prédicteur de leur présentation au CMH I afin d'identifier des cibles fiables pour l'immunothérapie, ce pour quoi BamQuery est un outil efficace.

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