DEqMS : A Method for Accurate Variance Estimation in Differential Protein Expression Analysis

Quantitative proteomics by mass spectrometry is widely used in biomarker research and basic biology research for investigation of phenotype level cellular events. Despite the wide application, the methodology for statistical analysis of differentially expressed proteins has not been unified. Various methods such as t test, linear model and mixed effect models are used to define changes in proteomics experiments. However, none of these methods consider the specific structure of MS-data. Choices between methods, often originally developed for other types of data, are based on compromises between features such as statistical power, general applicability and user friendliness. Furthermore, whether to include proteins identified with one peptide in statistical analysis of differential protein expression varies between studies. Here we present DEqMS, a robust statistical method developed specifically for differential protein expression analysis in mass spectrometry data. In all data sets investigated there is a clear dependence of variance on the number of PSMs or peptides used for protein quantification. DEqMS takes this feature into account when assessing differential protein expression. This allows for a more accurate data-dependent estimation of protein variance and inclusion of single peptide identifications without increasing false discoveries. The method was tested in several data sets including E. coli proteome spike-in data, using both label-free and TMT-labeled quantification. Compared with previous statistical methods used in quantitative proteomics, DEqMS showed consistently better accuracy in detecting altered protein levels compared with other statistical methods in both label-free and labeled quantitative proteomics data. DEqMS is available as an R package in Bioconductor.Peer reviewe

Therapeutic Cancer Vaccination with Immunopeptidomics-Discovered Antigens Confers Protective Antitumor Efficacy

Simple Summary Immunotherapy has revolutionized cancer treatment, yet many tumors remain resistant to current immuno-oncology therapies. Here we explore a novel, customized oncolytic adenovirus vaccine platform as immunotherapy in a resistant tumor model. We present a workflow for customizing the oncolytic vaccine for improved tumor targeting. This targeting is based on experimentally discovered tumor antigens, which are incorporated as active components of the vaccine formulation. The pipeline may be further applied for designing personalized therapeutic cancer vaccines. Knowledge of clinically targetable tumor antigens is becoming vital for broader design and utility of therapeutic cancer vaccines. This information is obtained reliably by directly interrogating the MHC-I presented peptide ligands, the immunopeptidome, with state-of-the-art mass spectrometry. Our manuscript describes direct identification of novel tumor antigens for an aggressive triple-negative breast cancer model. Immunopeptidome profiling revealed 2481 unique antigens, among them a novel ERV antigen originating from an endogenous retrovirus element. The clinical benefit and tumor control potential of the identified tumor antigens and ERV antigen were studied in a preclinical model using two vaccine platforms and therapeutic settings. Prominent control of established tumors was achieved using an oncolytic adenovirus platform designed for flexible and specific tumor targeting, namely PeptiCRAd. Our study presents a pipeline integrating immunopeptidome analysis-driven antigen discovery with a therapeutic cancer vaccine platform for improved personalized oncolytic immunotherapy.Peer reviewe

Overexpression - purification and structure - function relationships of NAT transporters in a model bacterial system

Our lab has recently cloned and functionally characterized YgfO, a specific, high-affinity xanthine:Η+ symporter from Escherichia coli Κ-12, a member of the nucleobase-ascorbate transporter (NAT/NCS2) family. With introduction of appropriate epitope tags at the C terminus (biotin-acceptor domain or His10-tail) and application of the Cys-scanning mutagenesis technology, a model bacterial system was developed for the study of structure-function relationships of the NAT transporters, based on the YgfO permease (Karatza P.). Despite considerable progress, today, important aspects of the topology, active site mapping and the mechanism of YgfO remain unanswered and there are no high-resolution structures available for any member of this family. The aims of this thesis was to develop a protocol for the overexpression, purification and a first structural characterization of YgfO, with biophysical methods, to apply a first experimental study of the topology of YgfO with substituted-cysteine accessibility method (SCAM), and to further study the role of the NAT signature motif, 324QNXGXXXXTG333, which had been indicated to contain important determinats for the mechanism. We developed a protocol for the large-scale overexpression and purification of YgfO in detergent solution (n-dodecyl- β,D-maltoside, DDM) with a yield of 0.7 mg of purified protein per L of cell culture. It was found that the purified YgfO retains a high alpha-helical content (with circular dichoism spectroscopy), recognizes specifically the substrate (xanthine) but not 7- methylxanthine which is not a ligand for YgfO (with tryptophan fluorescence spectroscopy) and retains local secondary structure elements at the NAT motif region (with site-directed spin labeling of mutants Q324C and R337C and EPR spectroscopy). While searching for other homologs to be used as alternative sources for purification, from thermophilic microorganisms, we cloned and characterized functionally a close YgfO homolog from the Gram-positive thermophilic bacterium Moorella thermoacetica, which was found to transport xanthine at 37 °C, pH 6.6-6.8, in the heterologous expression system of E. coli. We analyzed general feautures of the topology of YgfO with substituted-cysteine accessibility method (SCAM) which is based on the Cys-scanning technology. We engineered single-Cys mutants at the tips of the predicted hydrophilic loops (A48C, R78C, S109C, L142C, A176C, S206C, T243C, S295C, L319C, A366C, R394C, I419C) and assayed for their reactivity with the hydrophilic, membrane-impermeable reagent MTSES-, in right-side out membrane vesicles (RSOs). Our data show that there is a clear alternation of solvent accessibility for the region between transmembrane helices (TMs) 1 and 8, as expected from the in silico prediction algorithms, while, at the C-terminal third of the molecule (TMs 9-12), all the single-Cys residue positions were found to be accessible, contraty to the predictions of the models. This discrepancy is possibly due to the presence of amphipathic helical segments that cross the membrane only partially and/or reentrant loops, giving a perturbed topology at the C-terminal part of the molecule. Using gene fusion with the green fluorescent protein (GFP), we confirmed that the Ctail of YgfO is cytoplasmic, consistent with previous proteomic analyses from the group of Dr. Gunnar von Heijne (Stockholm).Πρόσφατα, κλωνοποιήθηκε και χαρακτηρίσθηκε λειτουργικά από την ερευνητική μας ομάδα ο μεταφορέας YgfO του εντεροβακτηρίου E. coli Κ-12, μέλος της οικογένειας NAT/NCS2, o οποίος εδείχθη ότι λειτουργεί ως ειδικός, υψηλής συγγένειας συμμεταφορέας ξανθίνης: Η+. Με την εισαγωγή κατάλληλων αλληλουχιών-επιτόπων στο C-τελικό άκρο της πρωτεΐνης [περιοχή δέσμευσης βιοτίνης (BAD), αλληλουχία 10 συνεχόμενων καταλοίπων His (His10)] και εφαρμογή των μεθοδολογιών της μεταλλαξιγένεσης κυστεϊνικής σάρωσης (Cysscanning mutagenesis) αναπτύχθηκε ένα πρότυπο βακτηριακό σύστημα μελέτης των σχέσεων δομής-λειτουργίας για τους μεταφορείς NAT, με βάση το μόριο του YgfO (Καρατζά Π.). Παρά τα σημαντικά ευρήματα, παραμένουν αρκετά αναπάντητα ερωτήματα για την τοπολογία, για το ενεργό κέντρο του μορίου, για άλλες σημαντικές περιοχές καθώς και τον μηχανισμό λειτουργίας του YgfO. Επίσης, δεν υπάρχουν έως τώρα δεδομένα δομικών κρυσταλλογραφικών αναλύσεων για καμιά πρωτεϊνη της οικογένειας NAT. Με βάση τα παραπάνω, στόχοι της παρούσας διατριβής ήταν η ανάπτυξη ενός πρωτοκόλλου απομόνωσης και αρχικού δομικού χαρακτηρισμού του YgfO, η εξέταση της γενικής τοπολογικής του οργάνωσης με εργαστηριακές μεθόδους και μια εμβάθυνση στο ρόλο του μοτίβου-υπογραφή ΝΑΤ, 324QNXGXXXXTG333, που είχε δειχθεί από προηγούμενες μελέτες μεταλλαξιγένεσης ότι περιλαμβάνει σημαντικούς καθοριστές για τον μηχανισμό λειτουργίας του YgfO. Αναπτύχθηκε καταρχήν ένα πρωτόκολλο για την υπερέκφραση και καθαρισμό του YgfO σε μεγάλη κλίμακα σε διάλυμα απορρυπαντικού (n-δωδεκυλο-β,D-μαλτοπυρανοσιδίου, DDM), με τελική απόδοση απομονωμένης πρωτεΐνης ~0.7 mg/L καλλιέργειας. Η μελέτη αυτή οδήγησε στην απομόνωση και έναν αρχικό δομικό χαρακτηρισμό της πρωτεΐνης YgfO σε διάλυμα DDM (0.008% w/v), που έδειξε ότι η απομονωμένη πρωτεΐνη διατηρεί υψηλό ποσοστό περιοχών α- έλικας (φασματοσκοπία CD) και μπορεί να αναγνωρίζει ειδικά το υπόστρωμά της (ξανθίνη) αλλά όχι ένα ανάλογο ξανθίνης που δεν δεσμεύεται (7-μεθυλοξανθίνη) (φθορισμομετρία τρυπτοφανών), ενώ φαίνεται να διατηρεί και επιμέρους στοιχεία της δευτεροταγούς δομής της στην περιοχή του μοτίβου-υπογραφή ΝΑΤ (φασματοσκοπία EPR και SDSL). Τα παραπάνω αποτελέσματα αποδεικνύουν ότι η απομονωμένη πρωτεΐνη διατηρεί λειτουργικά και δομικά στοιχεία της και ότι το πρωτόκολλο απομόνωσης μπορεί να χρησιμοποιηθεί στο μέλλον για περαιτέρω δομικές μελέτες. Εξάλλου, στα πλαίσια των προσπαθειών μας για την υπερέκφραση και απομόνωση ομολόγων μεταφορέων από θερμόφιλους μικροοργανισμούς, ως εναλλακτικών επιλογών, κλωνοποιήθηκε και χαρακτηρίσθηκε λειτουργικά ένα συγγενές ομόλογο του μεταφορέα YgfO από το θερμόφιλο Gram-θετικό βακτήριο Moorella thermoacetica, το οποίο εδείχθη ότι λειτουργεί ως μεταφορέας ξανθίνης στους 37 °C, pH 6.6-6.8, στο ετερόλογο σύστημα έκφρασης της E. coli

Comprehensive proteomics and meta-analysis of COVID-19 host response

Abstract COVID-19 is characterised by systemic immunological perturbations in the human body, which can lead to multi-organ damage. Many of these processes are considered to be mediated by the blood. Therefore, to better understand the systemic host response to SARS-CoV-2 infection, we performed systematic analyses of the circulating, soluble proteins in the blood through global proteomics by mass-spectrometry (MS) proteomics. Here, we show that a large part of the soluble blood proteome is altered in COVID-19, among them elevated levels of interferon-induced and proteasomal proteins. Some proteins that have alternating levels in human cells after a SARS-CoV-2 infection in vitro and in different organs of COVID-19 patients are deregulated in the blood, suggesting shared infection-related changes.The availability of different public proteomic resources on soluble blood proteome alterations leaves uncertainty about the change of a given protein during COVID-19. Hence, we performed a systematic review and meta-analysis of MS global proteomics studies of soluble blood proteomes, including up to 1706 individuals (1039 COVID-19 patients), to provide concluding estimates for the alteration of 1517 soluble blood proteins in COVID-19. Finally, based on the meta-analysis we developed CoViMAPP, an open-access resource for effect sizes of alterations and diagnostic potential of soluble blood proteins in COVID-19, which is publicly available for the research, clinical, and academic community

Proteome Analysis of Pancreatic Tumors Implicates Extracellular Matrix in Patient Outcome

Pancreatic cancer remains a disease with unmet clinical needs and inadequate diagnostic, prognostic, and predictive biomarkers. In-depth characterization of the disease proteome is limited. This study thus aims to define and describe protein networks underlying pancreatic cancer and identify protein centric subtypes with clinical relevance. Mass spectrometry–based proteomics was used to identify and quantify the proteome in tumor tissue, tumor-adjacent tissue, and patient-derived xenografts (PDX)-derived cell lines from patients with pancreatic cancer, and tissues from patients with chronic pancreatitis. We identified, quantified, and characterized 11,634 proteins from 72 pancreatic tissue samples. Network focused analysis of the proteomics data led to identification of a tumor epithelium–specific module and an extracellular matrix (ECM)-associated module that discriminated pancreatic tumor tissue from both tumor adjacent tissue and pancreatitis tissue. On the basis of the ECM module, we defined an ECM-high and an ECM-low subgroup, where the ECM-high subgroup was associated with poor prognosis (median survival months: 15.3 vs. 22.9 months; log-rank test, P = 0.02). The ECM-high tumors were characterized by elevated epithelial–mesenchymal transition and glycolytic activities, and low oxidative phosphorylation, E2F, and DNA repair pathway activities. This study offers novel insights into the protein network underlying pancreatic cancer opening up for proteome precision medicine development. Significance: Pancreatic cancer lacks reliable biomarkers for prognostication and treatment of patients. We analyzed the proteome of pancreatic tumors, nonmalignant tissues of the pancreas and PDX-derived cell lines, and identified proteins that discriminate between patients with good and poor survival. The proteomics data also unraveled potential novel drug targets

Proteome Analysis of Pancreatic Tumors Implicates Extracellular Matrix in Patient Outcome

Pancreatic cancer remains a disease with unmet clinical needs and inadequate diagnostic, prognostic, and predictive biomarkers. In-depth characterization of the disease proteome is limited. This study thus aims to define and describe protein networks underlying pancreatic cancer and identify protein centric subtypes with clinical relevance. Mass spectrometry–based proteomics was used to identify and quantify the proteome in tumor tissue, tumor-adjacent tissue, and patient-derived xenografts (PDX)-derived cell lines from patients with pancreatic cancer, and tissues from patients with chronic pancreatitis. We identified, quantified, and characterized 11,634 proteins from 72 pancreatic tissue samples. Network focused analysis of the proteomics data led to identification of a tumor epithelium–specific module and an extracellular matrix (ECM)-associated module that discriminated pancreatic tumor tissue from both tumor adjacent tissue and pancreatitis tissue. On the basis of the ECM module, we defined an ECM-high and an ECM-low subgroup, where the ECM-high subgroup was associated with poor prognosis (median survival months: 15.3 vs. 22.9 months; log-rank test, P = 0.02). The ECM-high tumors were characterized by elevated epithelial–mesenchymal transition and glycolytic activities, and low oxidative phosphorylation, E2F, and DNA repair pathway activities. This study offers novel insights into the protein network underlying pancreatic cancer opening up for proteome precision medicine development. Significance: Pancreatic cancer lacks reliable biomarkers for prognostication and treatment of patients. We analyzed the proteome of pancreatic tumors, nonmalignant tissues of the pancreas and PDX-derived cell lines, and identified proteins that discriminate between patients with good and poor survival. The proteomics data also unraveled potential novel drug targets