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Exosomes are extracellular vesicles of endosomal origin released by virtually all cell types across metazoans. Exosomes are active vehicles of intercellular communication and can transfer lipids, RNAs and proteins between different cells, tissues or organs. However, the mechanisms that regulate the selective loading of cytosolic proteins into these vesicles are still largely unknow. Here we describe a mechanism whereby proteins containing a pentapeptide sequence, biochemically related to the KFERQ-motif, are loaded into a subpopulation of exosomes in a process that is dependent on the membrane protein LAMP2A. Moreover, this mechanism is independent of the ESCRT machinery components TSG101 and VPS4b and dependent on HSC70, CD63, Alix, Syntenin-1, Rab31 and ceramides. The transcription factor and master regulator of hypoxia HIF1A is loaded into exosomes by this mechanism to transport hypoxia signaling to normoxic cells. Additionally, by tagging fluorescent proteins with KFERQ-like sequences we were able to follow inter-organ transfer of exosomes in zebrafish larvae. Our findings identify LAMP2A as a key component in exosome biogenesis while opening new avenues for exosome engineering by allowing the loading of bioactive proteins by tagging them with KFERQ-like motifs.

Molecular diagnostics based on discovery research holds the promise of improving screening methods for prostate cancer (PCa). Furthermore, the congregated information prompts the question whether the urinary extracellular vesicles (uEV) proteome has been thoroughly explored, especially at the proteome level. In fact, most extracellular vesicles (EV) based biomarker studies have mainly targeted plasma or serum. Therefore, in this study, we aim to inquire about possible strategies for urinary biomarker discovery particularly focused on the proteome of urine EVs. Proteomics data deposited in the PRIDE archive were reanalyzed to target identifications of potential PCa markers. Network analysis of the markers proposed by different prostate cancer studies revealed moderate overlap. The recent throughput improvements in mass spectrometry together with the network analysis performed in this study, suggest that a larger standardized cohort may provide potential biomarkers that are able to fully characterize the heterogeneity of PCa. According to our analysis PCa studies based on urinary EV proteome presents higher protein coverage compared to plasma, plasma EV, and voided urine proteome. This together with a direct interaction of the prostate gland and urethra makes uEVs an attractive option for protein biomarker studies. In addition, urinary proteome based PCa studies must also evaluate samples from bladder and renal cancers to assess specificity for PCa. info:eu-repo/semantics/publishedVersion

The role of extracellular vesicles (EVs) proteome in diffuse large B-cell lymphoma (DLBCL) pathology, subclassification, and patient screening is unexplored. We analyzed by state-of-the-art mass spectrometry the whole cell and secreted extracellular vesicles (EVs) proteomes of different molecular subtypes of DLBCL, germinal center B cell (GCB subtype), and activated B cell (ABC subtype). After quality control assessment, we compared whole-cell and secreted EVs proteomes of the two cell-of-origin (COO) categories, GCB and ABC subtypes, resulting in 288/1115 significantly differential expressed proteins from the whole-cell proteome and 228/608 proteins from EVs (adjust p-value &lt, 0.05/p-value &lt, 0.05). In our preclinical model system, we demonstrated that the EV proteome and the whole-cell proteome possess the capacity to separate cell lines into ABC and GCB subtypes. KEGG functional analysis and GO enrichment analysis for cellular component, molecular function, and biological process of differential expressed proteins (DEP) between ABC and GCB EVs showed a significant enrichment of pathways involved in immune response function. Other enriched functional categories for DEPs constitute cellular signaling and intracellular trafficking such as B-cell receptor (BCR), Fc_gamma R-mediated phagocytosis, ErbB signaling, and endocytosis. Our results suggest EVs can be explored as a tool for patient diagnosis, follow-up, and disease monitoring. Finally, this study proposes novel drug targets based on highly expressed proteins, for which antitumor drugs are available suggesting potential combinatorial therapies for aggressive forms of DLBCL. Data are available via ProteomeXchange with identifier PXD028267.

Pancreatic cancers (PC) are highly metastatic with poor prognosis, mainly due to delayed detection. We previously showed that PC-derived extracellular vesicles (EVs) act on macrophages residing in the liver, eliciting extracellular matrix remodeling in this organ and marked hepatic accumulation of CD11b+ bone marrow (BM) cells, which support PC liver metastasis. We here show that PC-EVs also bind to CD11b+ BM cells and induce the expansion of this cell population. Transcriptomic characterization of these cells shows that PC-EVs upregulate IgG and IgA genes, which have been linked to the presence of monocytes/macrophages in tumor microenvironments. We also report here the transcriptional downregulation of genes linked to monocyte/macrophage activation, trafficking, and expression of inflammatory molecules. Together, these results show for the first time the existence of a PC–BM communication axis mediated by EVs with a potential role in PC tumor microenvironments. JM was supported by “Fundação para a Ciência e a Tecnologia” (PD/BD/105866/2014). This work was supported by the Champalimaud Foundation; grant 751547 from H2020-MSCA-IF-2016; EMBO Installation Grant 3921; grant 2017NovPCC1058 from Breast Cancer Now’s Catalyst Programme, which is supported by funding from Pfizer; grant 765492 from H2020-MSCA-ITN-2017; and grant LCF/PR/HR19/52160014 from “La Caixa” Foundation. This work was also funded by FEDER funds through the Operational Programme for Competitiveness Factors-COMPETE and National Funds through the Foundation for Science and Technology (FCT), under the project: PTDC/MED-ONC/28489/2017 (to AM). JP acknowledges the FCT grant SFRH/BD/137319/2018.

Funding Information: Funding: This research was partly funded by a “Center of Clinical Excellence” research grant from the Health Region of Southern Denmark to Odense Amyloidosis Center (AmyC). Publisher Copyright: © 2021 by the authors. Li-censee MDPI, Basel, Switzerland. Amyloidosis is a rare disease caused by the misfolding and extracellular aggregation of proteins as insoluble fibrillary deposits localized either in specific organs or systemically through-out the body. The organ targeted and the disease progression and outcome is highly dependent on the specific fibril‐forming protein, and its accurate identification is essential to the choice of treat-ment. Mass spectrometry‐based proteomics has become the method of choice for the identification of the amyloidogenic protein. Regrettably, this identification relies on manual and subjective inter-pretation of mass spectrometry data by an expert, which is undesirable and may bias diagnosis. To circumvent this, we developed a statistical model‐assisted method for the unbiased identification of amyloid‐containing biopsies and amyloidosis subtyping. Based on data from mass spectrometric analysis of amyloid‐containing biopsies and corresponding controls. A Boruta method applied on a random forest classifier was applied to proteomics data obtained from the mass spectrometric analysis of 75 laser dissected Congo Red positive amyloid‐containing biopsies and 78 Congo Red negative biopsies to identify novel “amyloid signature” proteins that included clusterin, fibulin‐1, vitronectin complement component C9 and also three collagen proteins, as well as the well‐known amyloid signature proteins apolipoprotein E, apolipoprotein A4, and serum amyloid P. A SVM learning algorithm were trained on the mass spectrometry data from the analysis of the 75 amyloid-containing biopsies and 78 amyloid‐negative control biopsies. The trained algorithm performed su-perior in the discrimination of amyloid‐containing biopsies from controls, with an accuracy of 1.0 when applied to a blinded mass spectrometry validation data set of 103 prospectively collected am-yloid‐containing biopsies. Moreover, our method successfully classified amyloidosis patients ac-cording to the subtype in 102 out of 103 blinded cases. Collectively, our model‐assisted approach identified novel amyloid‐associated proteins and demonstrated the use of mass spectrometry‐based data in clinical diagnostics of disease by the unbiased and reliable model‐assisted classification of amyloid deposits and of the specific amyloid subtype. publishersversion published

Mass spectrometry is extremely efficient for sequencing small peptides generated by, for example, a trypsin digestion of a complex mixture. Current instruments have the capacity to generate 50-100 K MSMS spectra from a single run. Of these ~30-50% is typically assigned to peptide matches on a 1% FDR threshold. The remaining spectra need more research to explain. We address here whether the 30-50% matched spectra provide consensus matches when using different database-dependent search pipelines. Although the majority of the spectra peptide assignments concur across search engines, our conclusion is that database-dependent search engines still require improvements.

Protein quantitation by mass spectrometry has always been a resourceful technique in protein discovery, and more recently it has leveraged the advent of clinical proteomics. A single mass spectrometry analysis experiment provides identification and quantitation of proteins as well as information on posttranslational modifications landscape. By contrast, protein array technologies are restricted to quantitation of targeted proteins and their modifications. Currently, there are an overwhelming number of quantitative mass spectrometry methods for protein and peptide quantitation. The aim here is to provide an overview of the most common mass spectrometry methods and algorithms used in quantitative proteomics and discuss the computational aspects to obtain reliable quantitative measures of proteins, peptides and their posttranslational modifications. The development of a pipeline using commercial or freely available software is one of the main challenges in data analysis of many experimental projects. Recent developments of R statistical programming language make it attractive to fully develop pipelines for quantitative proteomics. We discuss concepts of quantitative proteomics that together with current R packages can be used to build highly customizable pipelines.

Mass spectrometry has been widely applied to study biomolecules and one rapidly developing field is the global analysis of proteins, proteomics. Understanding and handling mass spectrometry data is a multifaceted task that requires many decisions to be made to get the most comprehensive information from an experiment. Later chapters in this book deal in-depth with various aspects of the process and how different tools can be applied to the many analytical challenges. This introductory chapter is intended as a basic introduction to mass spectrometry (MS)-based proteomics to set the scene for newcomers and give pointers to reference material. There are many applications of mass spectrometry in proteomics and each application is associated with some analytical choices, instrumental limitations and data processing steps that depend on the aim of the study and means of conducting it. Different aspects of the proteome can be explored by choosing the right combination of sample preparation, MS instrumentation and data processing. This chapter gives an outline for some of these commonly used setups and some of the key concepts, many of which are explored in greater depth in later chapters.

Glucose uptake by mammalian cells is a key mechanism to maintain cell and tissue homeostasis and relies mostly on plasma membrane-localized glucose transporter proteins (GLUTs). Two main cellular mechanisms regulate GLUT proteins in the cell: first, expression of GLUT genes is under dynamic transcriptional control and is used by cancer cells to increase glucose availability. Second, GLUT proteins are regulated by membrane traffic from storage vesicles to the plasma membrane (PM). This latter process is triggered by signaling mechanisms and well-studied in the case of insulin-responsive cells, which activate protein kinase AKT to phosphorylate TBC1D4, a RAB-GTPase activating protein involved in membrane traffic regulation. Previously, we identified protein kinase WNK1 as another kinase able to phosphorylate TBC1D4 and regulate the surface expression of the constitutive glucose transporter GLUT1. Here we describe that downregulation of WNK1 through RNA interference in HEK293 cells led to a 2-fold decrease in PM GLUT1 expression, concomitant with a 60% decrease in glucose uptake. By mass spectrometry, we identified serine (S) 704 in TBC1D4 as a WNK1-regulated phosphorylation site, and also S565 in the paralogue TBC1D1. Transfection of the respective phosphomimetic or unphosphorylatable TBC1D mutants into cells revealed that both affected the cell surface abundance of GLUT1. The results reinforce a regulatory role for WNK1 in cell metabolism and have potential impact for the understanding of cancer cell metabolism and therapeutic options in type 2 diabetes. Highlights: Expression levels of protein kinase WNK1 modulate cellular glucose uptake; WNK1 phosphorylates the RAB-GAP proteins TBC1D4 and TBC1D1 in vitro; WNK1-specific phosphorylation sites were identified in TBC1D4 and TBC1D1; Phosphomimetic TBC1D mutants modulate plasma membrane expression of GLUT1 in cells. This work was supported by Fundação para a Ciência e Tecnologia(FCT) [grants PTDC/SAU-MET/117236/2010 to PJ, grant UID/MULTI/04046/2019 to the research unit BioISI, and fellowship SFRH/BD/106080/2015 from the BioSYS PhD programme PD65-2012 to AFAH].The authors acknowledge José Ferrão for regular mycoplasma testing incultured cells and Patrícia Barros for critical reading of the manuscript.Anthony Albiston (Melbourne, Australia) and Florian Lang (Universityof Tubingen, Germany) kindly provided constucts pCR3.1/AS160-2mycor pIRES2-EGFP-SGK1, respectively, for this study info:eu-repo/semantics/publishedVersion

The ribosomal protein L11 (RPL11) integrates different types of stress into a p53-mediated response. Here, we analyzed the impact of the ubiquitin-like protein SUMO on the RPL11-mouse double-minute 2 homolog-p53 signaling. We show that small ubiquitin-related modifier (SUMO)1 and SUMO2 covalently modify RPL11. We find that SUMO negatively modulates the conjugation of the ubiquitin-like protein neural precursor cell-expressed developmentally downregulated 8 (NEDD8) to RPL11 and promotes the translocation of the RP outside of the nucleoli. Moreover, the SUMO-conjugating enzyme, Ubc9, is required for RPL11-mediated activation of p53. SUMOylation of RPL11 is triggered by ribosomal stress, as well as by alternate reading frame protein upregulation. Collectively, our data identify SUMO protein conjugation to RPL11 as a new regulator of the p53-mediated cellular response to different types of stress and reveal a previously unknown SUMO-NEDD8 interplay.-El Motiam, A, Vidal, S., de la Cruz-Herrera, C. F., Da Silva-Álvarez, S., Baz-Martínez, M., Seoane, R., Vidal, A., Rodríguez, M. S., Xirodimas, D. P., Carvalho, A. S., Beck, H. C., Matthiesen, R., Collado, M., Rivas, C. Interplay between SUMOylation and NEDDylation regulates RPL11 localization and function.

The search for novel anticancer small molecules and strategies remains a challenge. Our previous studies have identified TXA1 (1-{[2-(diethylamino)ethyl]amino}-4-propoxy-9H-thioxanthen-9-one) as a hit compound, with in vitro antitumor potential by modulating autophagy and apoptosis in human tumor cell lines. In the present study, the mechanism of action and antitumor potential of the soluble salt of this molecule (TXA1.HCl) was further investigated using in vitro and mouse xenograft tumor models of NSCLC. Our results showed that TXA1.HCl affected steroid biosynthesis, increased RagD expression, and caused abnormal cellular cholesterol localization. In addition, TXA1.HCl treatment presented no toxicity to nude mice and significantly reduced the growth of human NSCLC cells xenografts in mice. Overall, this work provides new insights into the mechanism of action of TXA1, which may be relevant for the development of anticancer therapeutic strategies, which target cholesterol transport. © 2018 by the authors. Acknowledgments: FCT for D.S. and R.T.L. grants (PTDC/SAU-FCT/100930/2008 and SFRH/BPD/68787/2010, respectively) and FCT PhD Programme BiotechHealth grant of A.S.G. (PD/BD/114046/2015); QREN for D. Sousa grant (NORTE-07-0124-FEDER-000023); P. Castro, R. Barros, L. Pereira and S. Ricardo, who provided technical assistance. Funding: IPATIMUP integrates the i3S Research Unit, which is partially supported by FCT, the Portuguese Foundation for Science and Technology. This work is funded by FEDER funds through the Operational Programme for Competitiveness Factors-COMPETE and National Funds through the FCT-Foundation for Science and Technology, under the projects “PEst-C/SAU/LA0003/2013”, ERDF, programme PT2020—Contributos para o reforço da capacidade do IPATIMUP enquanto actor do sistema regional de inovação” and NORTE-07-0162-FEDER-000067—Reforço e consolidação da capacidade infraestrutural do IPATIMUP para o sistema regional de inovação”, both supported by Programa Operacional Regional do Norte (ON.2—O Novo Norte), through FEDER funds under the Quadro de Referência Estratégico Nacional (QREN). This work was also financed by FEDER—Fundo Europeu de Desenvolvimento Regional funds through the COMPETE 2020—Operacional Programme for Competitiveness and Internationalisation (POCI), Portugal 2020, and by Portuguese funds through FCT—Fundação para a Ciência e a Tecnologia/ Ministério da Ciência, Tecnologia e Inovação in the framework of the project “Institute for Research and Innovation in Health Sciences” (POCI-01-0145-FEDER-007274). This work was also supported through national funds provided by FCT/MCTES—Foundation for Science and Technology from the Minister of Science, Technology and Higher Education (PIDDAC) and European Regional Development Fund (ERDF) through the COMPETE—Programa Operacional Factores de Competitividade (POFC) programme, under the Strategic Funding UID/Multi/04423/2013, in the framework of the programme PT2020.

Tetracyclines are among the most commonly used antibiotics administrated to farm animals for disease treatment and prevention, contributing to the worldwide increase in antibiotic resistance in animal and human pathogens. Although tetracycline mechanisms of resistance are well known, the role of metabolism in bacterial reaction to antibiotic stress is still an important assignment and could contribute to the understanding of tetracycline related stress response. In this study, spectral counts-based label free quantitative proteomics has been applied to study the response to tetracycline of the environmental-borne Escherichia coli EcAmb278 isolate soluble proteome. A total of 1484 proteins were identified by high resolution mass spectrometry at a false discovery rate threshold of 1%, of which 108 were uniquely identified under absence of tetracycline whereas 126 were uniquely identified in presence of tetracycline. These proteins revealed interesting difference in e.g. proteins involved in peptidoglycan-based cell wall proteins and energy metabolism. Upon treatment, 12 proteins were differentially regulated showing more than 2-fold change and p0.05 (p value corrected for multiple testing). This integrated study using high resolution mass spectrometry based label-free quantitative proteomics to study tetracycline antibiotic response in the soluble proteome of resistant E. coli provides novel insight into tetracycline related stress.The lack of new antibiotics to fight infections caused by multidrug resistant microorganisms has motivated the use of old antibiotics, and the search for new drug targets. The evolution of antibiotic resistance is complex, but it is known that agroecosystems play an important part in the selection of antibiotic resistance bacteria. Tetracyclines are still used as phytopharmaceutical agents in crops, selecting resistant bacteria and changing the ecology of farm soil. Little is known about the metabolic response of genetically resistant populations to antibiotic exposure. Indeed, to date there are no quantitative tetracycline resistance studies performed with the latest generation of high resolution mass spectrometers allowing high mass accuracy in both MS and MS/MS scans. Here, we report the proteome profiling of a soil-borne Escherichia coli upon tetracycline stress, so that this new perspective could provide a broaden understanding of the metabolic responses of E. coli to a widely used antibiotic.

Bronchoalveolar lavage fluid (BALF) is a lung fluid. BALF is extracted from the lungs by a bronchoscope. The first step is to instill saline liquid into the lungs followed by extraction. The extracted liquid is depleted from cells by low spin centrifugation. The biochemical content of BALF is mainly composed of phospholipids and proteins and to less extent nucleic acids (DNA, miRNA, mRNA). The proteins, mRNAs, miRNAs, and lipids mirror the pathophysiological state of the patient and are consequently regarded as a rich source of biomarkers with already some examples of established clinical applications. Recently, in Proteomics Clin. Appl. 2019, 13, 1900028, Sim et al. established a novel MS-based proteomics protocol for BALF lung cancer sample analysis by combining antibody-based depletion of high abundant BALF proteins, high pH peptide fractionation, and label free quantitation on a high resolution Orbitrap Fusion instrument. They demonstrate an improvement in BALF sample coverage compared with some previous published methodologies. Notably, the result from the study supports the hypothesis that BALF more than serum reflects the lung cancer proteome and for this reason is a promising source for lung cancer biomarkers.

Cells either in response to stimulus or in homeostasis require dynamic signaling through alterations in protein composition. Identification and temporospatial profiling of post translational modifications constitutes one of the most challenging tasks in biology. These challenges comprise both experimental and computational aspects. From the computational point of view identification of post translational modifications by mass spectrometry analysis frequently leads to algorithms with exponential complexity which in practice is approached by algorithms with lower complexity. Regulation of post translational modifications has been implicated in a number of diseases such as cancer, neurodegenerative diseases and metabolic diseases. Furthermore, some post translational modifications are considered as biomarkers and surrogate markers. Consequently, there is a high interest in methodologies that can identify and quantify post translational modifications. We found few papers addressing the issue of which modifications should be considered in a standard database dependent search of MS data for protein analysis. Furthermore, the few papers on the topic are from a time where MS instruments with high precision in both MS and MS/MS were not available. Therefore, based on literature search and extensive analysis we provide recommendations on post translational modifications to be included in mass spectrometry database searches of MS data with high precision in both MS and MS/MS (e.g.

Mass spectrometry (MS) has become the method of choice for the large-scale analysis of protein ubiquitylation. There exist a number of proposed methods for mapping ubiquitin sites, each with different pros and cons. We present here a protocol for the MS analysis of the ubiquitin-proteome captured by TUBEs and subsequent data analysis. Using dedicated software and algorithms, specific information on the presence of ubiquitylated peptides can be obtained from the MS search results. In addition, a quantitative and functional analysis of the ubiquitylated proteins and their interacting partners helps to unravel the biological and molecular processes they are involved in.

Genes that encode glycosylphosphatidylinositol anchored proteins (GPI-APs) constitute an estimated 1-2% of eukaryote genomes. Current computational methods for the prediction of GPI-APs are sensitive and specific; however, the analysis of the processing site (omega- or omega-site) of GPI-APs is still challenging. Only 10% of the proteins that are annotated as GPI-APs have the omega-site experimentally verified. We describe an integrated computational and experimental proteomics approach for the identification and characterization of GPI-APs that provides the means to identify GPI-APs and the derived GPI-anchored peptides in LC-MS/MS data sets. The method takes advantage of sequence features of GPI-APs and the known core structure of the GPI-anchor. The first stage of the analysis encompasses LC-MS/MS based protein identification. The second stage involves prediction of the processing sites of the identified GPI-APs and prediction of the corresponding terminal tryptic peptides. The third stage calculates possible GPI structures on the peptides from stage two. The fourth stage calculates the scores by comparing the theoretical spectra of the predicted GPI-peptides against the observed MS/MS spectra. Automated identification of C-terminal GPI-peptides from porcine membrane dipeptidase, folate receptor and CD59 in complex LC-MS/MS data sets demonstrates the sensitivity and specificity of this integrated computational and experimental approach.

Proteomic screening of strawberry (Fragaria ananassa) yielded a 58% success rate in protein identification in spite of the fact that no genomic sequence is available for this species. This was achieved by a combination of MALDI-MS/MS de novo sequencing of double-derivatized peptides and indel-tolerant searching against local protein databases built on both EST and full-length nucleotide sequences. The amino acid sequence of a strawberry allergen, homologous to the well-known major birch pollen allergen Bet v 1, was partially determined. This strawberry allergen, named Fra a 1 according to the nomenclature for allergen proteins, showed sequence identity of 54 and 77%, respectively, with corresponding allergens from birch and apple. Differential expression, as evaluated by 2-D DIGE, occurred in 10% of protein spots when red strawberries were compared to a colorless (white) strawberry mutant. White strawberries, known to be tolerated by individuals affected by allergy, were found to be virtually free from the strawberry allergen. Also several enzymes in the pathway for biosynthesis of flavonoids, to which the red color pelargonidin belongs, were down-regulated. This approach to assess differential protein expression without access to genomic sequence information can also be applied to other crop plants and phenotypic traits.

Protein and peptide mass analysis and amino acid sequencing by mass spectrometry is widely used for identification and annotation of post-translational modifications (PTMs) in proteins. Modification-specific mass increments, neutral losses or diagnostic fragment ions in peptide mass spectra provide direct evidence for the presence of post-translational modifications, such as phosphorylation, acetylation, methylation or glycosylation. However, the commonly used database search engines are not always practical for exhaustive searches for multiple modifications and concomitant missed proteolytic cleavage sites in large-scale proteomic datasets, since the search space is dramatically expanded. We present a formal definition of the problem of searching databases with tandem mass spectra of peptides that are partially (sub-stoichiometrically) modified. In addition, an improved search algorithm and peptide scoring scheme that includes modification specific ion information from MS/MS spectra was implemented and tested using the Virtual Expert Mass Spectrometrist (VEMS) software. A set of 2825 peptide MS/MS spectra were searched with 16 variable modifications and 6 missed cleavages. The scoring scheme returned a large set of post-translationally modified peptides including precise information on modification type and position. The scoring scheme was able to extract and distinguish the near-isobaric modifications of trimethylation and acetylation of lysine residues based on the presence and absence of diagnostic neutral losses and immonium ions. In addition, the VEMS software contains a range of new features for analysis of mass spectrometry data obtained in large-scale proteomic experiments. Windows binaries are available at http://www.yass.sdu.dk/.

Sucrose laurate esters were synthesized from sucrose and vinyl laurate in organic solvents using an alkaline protease from a new alkalophilic strain, Bacillus pseudofirmus AL-89. Maximum synthetic activity was observed in the presence of 7.5% v/v water and in the pH range of 7–10. With protease AL-89 esterification occurred predominantly at the 2-O-position while subtilisin A-catalyzed monoester formation predominantly at the 1′-O position. In the absence of enzyme, buffer salts catalyzed non-specific reactions, resulting in the formation of a number of esters. Non-specific catalysis was also observed upon inhibition of the enzyme using a serine protease inhibitor or upon deactivation of the enzyme at pH above 10.

We investigated the molecular effects of glucosamine supplements, a popular and safe alternative to nonsteroidal anti-inflammatory drugs, for decreasing pain, inflammation, and maintaining healthy joints. Numerous studies have reported an array of molecular effects after glucosamine treatment. We questioned whether the differences in the effects observed in previous studies were associated with the focus on a specific subproteome or with the use of specific cell lines or tissues. To address this question, global mass spectrometry- and transcription array-based glucosamine drug profiling was performed on malignant cell lines from different stages of lymphocyte development. We combined global label-free MS-based protein quantitation with an open search for modifications to obtain the best possible proteome coverage. Our data were largely consistent with previous studies in a variety of cellular models. We mainly observed glucosamine induced O-GlcNAcylation/O-GalNAcylation (O-HexNAcylation); however, we also observed global and local changes in acetylation, methylation, and phosphorylation. For example, our data provides two additional examples of "yin-yang" between phosphorylation and O-HexNAcylation. Furthermore, we mapped novel O-HexNAc sites on GLU2B and calnexin. GLU2B and calnexin are known to be located in the endoplasmic reticulum (ER) and involved in protein folding and quality control. The O-HexNAc sites were regulated by glucosamine treatment and correlated with the up-regulation of the ER stress marker GRP78. The occupancy of O-HexNAc on GLU2B and calnexin sites differed between the cytosolic and nuclear fractions with a higher occupancy in the cytosolic fraction. Based on our data we propose the hypothesis that O-HexNAc either inactivates calnexin and/or targets it to the cytosolic fraction. Further, we hypothesize that O-HexNAcylation induced by glucosamine treatment enhances protein trafficking.

Recent advances in mass spectrometry have resulted in an exponential increase in annotation of posttranslational modifications (PTMs). Just in the Swiss-Prot Knowledgebase, there are 89,931 of a total of 27 characterized PTM types reported experimentally. A single protein can be dynamically modified during its lifetime for regulation of its function. Considering a PTM can occur at different levels and the number of different PTMs described, the number of possibilities for a single protein is unthinkable. Narrowing the study to a single PTM can be rather unmerited considering that most proteins are heavily modified. Currently crosstalk between PTMs is plentifully reported in the literature. The example of amino acids serine and threonine on one hand and lysine on the other hand, as targets of different modifications, demand a more global analysis approach of a protein. Besides the direct competition for the same amino acid, a PTM can directly or indirectly influence other PTMs in the same protein molecule by for example steric hindrance due to close proximity between the modifications or creation of a binding site such as an SH2 binding domain for protein recruitment and further modifications. Given the complexity of PTMs a number of tools have been developed to archive, analyze, and visualize modifications. VISUALPROT is presented here to demonstrate the usefulness of visualizing all annotated protein features such as amino acid content, domains, amino acid modification sites and single amino acid polymorphisms in a single image. VISUALPROT application is demonstrated for the protein focal adhesion kinase (FAK) as an example. FAK is a highly phosphorylated cytoplasmatic tyrosine kinase comprising different domains and regions. FAK is crucial for integrating signals from integrins and receptor tyrosine kinases in processes such as cell survival, proliferation, and motility.

Tandem mass spectrometry provides a sensitive means of analyzing the amino acid sequence of peptides and modified peptides by providing accurate mass measurements of precursor and fragment ions. Modern mass spectrometry instrumentation is capable of rapidly generating many thousands of tandem mass spectra and protein database search engines have been developed to match the experimental data to peptide candidates. In most studies there is a schism between discarding perfectly valid data and including nonsensical peptide identifications-this is currently managed by establishing a false discovery rate (FDR) but for modified peptides it calls for an understanding of tandem mass spectrometry data. Manual evaluation of the data and perhaps experimental cross-checking of the MS data can save many months of experimental work trying to do biological follow-ups based on erroneous identifications. Especially for posttranslationally modified peptides there is a need for careful consideration of the data because search algorithms seldom have been optimized for the identification of modified peptides and because there are many pitfalls for the unwary. This chapter describes some of the issues that should be considered when interpreting and validating tandem mass spectra and gives some useful tables to aid in this process.

1. Introduction to Mass Spectrometry-based Proteomics Rune Matthiesen and Jakob Bunkenborg 2. LC-MS Spectra Processing Rune Matthiesen 3. Isotopic Distributions Alan L. Rockwood and Magnus Palmblad 4. Retention Time Prediction and Protein Identification Alex Henneman and Magnus Palmblad 5. Comparing Peptide Spectra Matches Across Search Engines Rune Matthiesen, Gorka Prieto and Hans Christian Beck 6. Calculation of False Discovery Rate for Peptide and Protein Identification Gorka Prieto and Jesus Vazquez 7. Methods and Algorithms for Quantitative Proteomics by Mass Spectrometry Rune Matthiesen and Ana Sofia Carvalho 8. Interpretation of Tandem Mass Spectra of Posttranslationally Modified Peptides Jakob Bunkenborg, and Rune Matthiesen 9. Solution to Dark Matter Identified by Mass-tolerant Database Search Rune Matthiesen 10. Phosphoproteomics Profiling to Identify Altered Signaling Pathways and Kinase-targeted Cancer Therapies Barnali Deb, Irene A. George, Jyoti Sharma, and Prashant Kumar 11. Mass Spectrometry Based Characterization of Ub- and UbL-modified Proteins Nagore Elu, Benoit Lectez, Juanma Ramirez, Nerea Osinalde, and Ugo Mayor 12. Targeted Proteomics as a Tool for Quantifying Urine-based Biomarkers Sonali V Mohan, David S Nayakanti, Gajanan Sathe, Irene A Geroge, Harsha Gowda, PrashantKumar 13. Data Imputation in Merged Isobaric Labelling-based Relative Quantification Datasets Nicolai Bjodstrup Palstrom, Rune Matthiesen, and Hans Christian Beck 14. Clustering Clinical Data in R Ana Pina, Maria Paula Macedo, and Roberto Henriques 15. Review of Issues and Solutions to Data Analysis Reproducibility and Data Quality in Clinical Proteomics Mathias Walzer and Juan Antonio Vizcaino 16. Review of Batch Effects Prevention, Diagnostics, and Correction Approaches Jelena Cuklina, Patrick G. A. Pedrioli, and Ruedi Aebersold 17. Using the Object-oriented PowerShell for Simple Proteomics Data Analysis Yassene Mohammed and Magnus Palmblad 18. Considerations in the Analysis of Hydrogen Exchange Mass Spectrometry Data Michael J. Eggertson, Keith Fadgen,John R. Engen, and Thomas E. Wales

The frequent used bottom-up strategy for identification of proteins and their associated modifications generate nowadays typically thousands of MS/MS spectra that normally are matched automatically against a protein sequence database. Search engines that take as input MS/MS spectra and a protein sequence database are referred as database-dependent search engines. Many programs both commercial and freely available exist for database-dependent search of MS/MS spectra and most of the programs have excellent user documentation. The aim here is therefore to outline the algorithm strategy behind different search engines rather than providing software user manuals. The process of database-dependent search can be divided into search strategy, peptide scoring, protein scoring, and finally protein inference. Most efforts in the literature have been put in to comparing results from different software rather than discussing the underlining algorithms. Such practical comparisons can be cluttered by suboptimal implementation and the observed differences are frequently caused by software parameters settings which have not been set proper to allow even comparison. In other words an algorithmic idea can still be worth considering even if the software implementation has been demonstrated to be suboptimal. The aim in this chapter is therefore to split the algorithms for database-dependent searching of MS/MS data into the above steps so that the different algorithmic ideas become more transparent and comparable. Most search engines provide good implementations of the first three data analysis steps mentioned above, whereas the final step of protein inference are much less developed for most search engines and is in many cases performed by an external software. The final part of this chapter illustrates how protein inference is built into the VEMS search engine and discusses a stand-alone program SIR for protein inference that can import a Mascot search result.

Background Protein inference from peptide identifications in shotgun proteomics must deal with ambiguities that arise due to the presence of peptides shared between different proteins, which is common in higher eukaryotes. Recently data independent acquisition (DIA) approaches have emerged as an alternative to the traditional data dependent acquisition (DDA) in shotgun proteomics experiments. MSE is the term used to name one of the DIA approaches used in QTOF instruments. MSE data require specialized software to process acquired spectra and to perform peptide and protein identifications. However the software available at the moment does not group the identified proteins in a transparent way by taking into account peptide evidence categories. Furthermore the inspection, comparison and report of the obtained results require tedious manual intervention. Here we report a software tool to address these limitations for MSE data. Results In this paper we present PAnalyzer, a software tool focused on the protein inference process of shotgun proteomics. Our approach considers all the identified proteins and groups them when necessary indicating their confidence using different evidence categories. PAnalyzer can read protein identification files in the XML output format of the ProteinLynx Global Server (PLGS) software provided by Waters Corporation for their MSE data, and also in the mzIdentML format recently standardized by HUPO-PSI. Multiple files can also be read simultaneously and are considered as technical replicates. Results are saved to CSV, HTML and mzIdentML (in the case of a single mzIdentML input file) files. An MSE analysis of a real sample is presented to compare the results of PAnalyzer and ProteinLynx Global Server. Conclusions We present a software tool to deal with the ambiguities that arise in the protein inference process. Key contributions are support for MSE data analysis by ProteinLynx Global Server and technical replicates integration. PAnalyzer is an easy to use multiplatform and free software tool. Proteomics Core Facility-SGIKER is member of ProteoRed-ISCIII and is supported by UPV/EHU, MCINN, GV/EJ, ERDF and ESF. JMA is supported by the Department of Industry of the Basque Government (ETORTEK grant IE09-256).RM is supported by Fundação para a Ciência e a Tecnologia (FCT) Ciência 2007 and by European Social Fund. IPATIMUP is an Associate Laboratory of the Portuguese Ministry of Science, Technology and Higher Education and is partially supported by FCT. RM is further supported by FCT grants (PTDC/QUI-BIQ/099457/2008 and PTDC/EIA-EIA/099458/2008).

Two-dimensional gel electrophoresis (2D gels) is an essential quantitative proteomics technique that is frequently used to study differences between samples of clinical relevance. Although considered to have a low throughput, 2D gels can separate thousands of proteins in one gel, making it a good complementary method to MS-based protein quantification. The main drawback of the technique is the tendency of large and hydrophobic proteins such as membrane proteins to precipitate in the isoelectric focusing step. Furthermore, tests using different programs with distinct algorithms for 2D-gel analysis have shown inconsistent ratio values. The aim here is therefore to provide a discussion of algorithms described for the analysis of 2D gels.

Protein quantitation by mass spectrometry (MS) is attractive since it is possible to obtain both the identification and quantitative values of novel proteins and their posttranslational modifications in one experiment. In contrast, protein arrays only provide quantitative values of targeted proteins and their modifications. There are an overwhelming number of quantitative mass spectrometry (MS) methods for protein and peptide quantitation. The aim here is to provide an overview of the most common MS-based quantitative methods used in the proteomics field and discuss the computational algorithms needed for the robust quantitation of proteins, peptides, and their posttranslational modifications.

A large number of scoring functions for ranking peptide matches to observed MS/MS spectra have been discussed in the literature. In contrast to scoring functions, search strategies have received less attention, and an accurate description of search algorithms is limited. Proteomics is becoming more and more commonly used in potential clinical applications; for such approaches to be successful, the combinatorial problems from amino acid modifications and somatic and heredity SAPs (single amino acid substitutions) need to be seriously considered. The modifications and SAPs are problematic since MS and MS/MS search algorithms are optimization processes, which means that if the correct match is not iterated through during the search, then the data will be matched incorrectly, resulting in serious downstream flaws. This chapter discusses several search algorithm strategies in more detail.

Udgivelsesdato: 2007-Aug Global proteome analysis of protein glycosylation is a major challenge due to the inherent heterogeneous and diverse nature of this post-translational modification. It is therefore common to enzymatically remove glycans attached to protein or peptide chains prior to mass spectrometric analysis, thereby reducing the complexity and facilitating glycosylation site determinations. Here, we have used two different enzymatic deglycosylation strategies for N-glycosylation site analysis. (1) Removal of entire N-glycan chains by peptide-N-glycosidase (PNGase) digestion, with concomitant deamidation of the released asparagine residue. The reaction is carried out in H218O to facilitate identification of the formerly glycosylated peptide by incorporatation of 18O into the formed aspartic acid residue. (2) Digestion with two endo-beta-N-acetylglucosaminidases (Endo D and Endo H) that cleave the glycosidic bond between the two N-acetylglucosamine (GlcNAc) residues in the conserved N-glycan core structure, leaving single GlcNAc residues with putative fucosyl side chains attached to the peptide. To enable digestion of complex and hybrid type N-glycans, a number of exoglycosidases (beta-galactosidase, neuraminidase and N-acetyl-beta-glucosaminidase) are also included. The two strategies were here applied to identify 103 N-glycosylation sites in the Cohn IV fraction of human plasma. In addition, Endo D/H digestion uniquely enabled identification of 23 fucosylated N-glycosylation sites. Several O-glycosylated peptides were also identified with a single N-acetylhexosamine attached, arguably due to partial deglycosylation of O-glycan structures by the exoglycosidases used together with Endo D/H.

Udgivelsesdato: 2007-Jul Using stable isotope labeling and mass spectrometry, we performed a sensitive, quantitative analysis of multiple phosphorylation sites of the epidermal growth factor (EGF) receptor. Phosphopeptide detection efficiency was significantly improved by using the tyrosine phosphatase inhibitor sodium pervanadate to boost the abundance of phosphorylation of the EGF receptor. Nine phosphorylation sites (pT669, pS967, pS1002, pY845, pY974, pY1045, pY1086, pY1148, and pY1173) of EGF receptor were quantified from EGF-stimulated cells in suspension and adherent conditions. Our data sets revealed that EGF stimulation of adherent cells induced higher levels of tyrosine phosphorylation relative to EGF stimulation of suspended cells. In contrast, EGF stimulation of adherent cells induced lower levels of serine and threonine phosphorylation relative to EGF stimulation of suspended cells. These findings are consistent with the hypothesis that cellular adhesion modulates phosphorylation of plasma membrane receptor tyrosine kinases relevant for EGF-induced signal transduction processes. Furthermore, our results suggest that strong phosphatase inhibitors should be used to generate reference datasets in comparative phosphoproteomics experiments.

Udgivelsesdato: 2007-Apr Oligogalacturonides of different degrees of polymerization (DP) and methyl esterification (DE) were structurally analyzed by nanoESI quadrupole ion-trap mass spectrometry. The fragmentation patterns of the oligogalacturonides were compared using the program 'Virtual Expert Mass Spectrometrist' (VEMS) for structural annotation. In the analyzed oligogalacturonides of lower DP, the generation of C/Y ions, i.e. ions retaining the glycosidic oxygen, was higher than that of B/Z ions. In general, with oligogalacturonides of higher DP, the B/Z ions were generated more abundantly. Oligogalacturonides with free carboxylic acid groups underwent higher water loss compared to fully methyl-esterified oligogalacturonides under the same fragmentation conditions. Cross-ring cleavage, in which fragmentation occurs across the ring system of the galacturonate residue and signified by unique mass losses, was observed to be higher in fully methyl-esterified oligogalacturonides than in non-methyl-esterified ones. This study demonstrates the different fragmentation patterns of oligogalacturonides as influenced by the presence or absence of methyl ester groups. For a detailed analysis of unknown oligogalacturonides, cross-ring fragmentation gives more structural information than glycosidic bond cleavage. One implication of this is that more structural information is obtained when analyzing methyl-esterified oligogalacturonides than non-methyl-esterified ones in an ion-trap instrument. This is of particular importance in pectin chemistry, where mass spectrometry has become the technique of choice for structural determination. Although this study was not designed to explain the mechanisms of oligogalacturonide fragmentation, possible explanations for why non-methyl-esterified oligogalacturonides undergo more water loss than methyl-esterified ones will be postulated. In addition, the VEMS program was extended to automatically interpret and assign the fragment ions peaks generated in this study.

Quantitative analysis of proteins and peptides by mass spectrometry has been greatly advanced by the development of proteomic technologies within recent years. Particularly, labeling of peptides and proteins with stable isotopes such as 2H, 15N, and 13C facilitated the unbiased comparison of protein amounts in distinct samples in a single mass spectrometric experiment. These methods can be applied to detect quantitative changes in protein amounts and posttranslational modifications such as phosphorylation. Quantitation of mass spectra requires accurate and efficient bioinformatics tools, which can match corresponding peptides, determine peak intensities, and calculate relative amounts. In this chapter, we describe the use of virtual expert mass spectrometrist for the quantitation of mass spectra from samples with peptides and proteins encoded with stable isotopes.

Tandem collision-induced dissociation (CID) mass spectrometry (MS) provides a sensitive means of analyzing the amino acid sequence of peptides. Modern MS instrumentation is capable of rapidly generating many thousands of tandem mass spectra, and protein database search engines have been developed to cope with this avalanche of data. In most studies, there is a schism between discarding perfectly valid data and including nonsensical peptide identifications--this is currently a major bottleneck in data analysis and it calls for manual evaluation of the data. Especially for posttranslationally modified peptides, there is a need for manual validation of the data because search algorithms seldom have been optimized for the identification of modified peptides and because there are many pitfalls for the unwary. This chapter describes some of the issues that should be considered when interpreting and validating low-energy CID tandem mass spectra and gives some useful tables to aid this process.

Histone proteins are subject to a range of post-transcriptional modifications in living cells. The combinatorial nature of these modifications constitutes the "histone code" that dictates chromatin structure and function during development, growth, differentiation, and homeostasis of cells. Deciphering of the histone code is hampered by the lack of analytical methods for monitoring the combinatorial complexity of reversible multisite modifications of histones, including acetylation and methylation. To address this problem, we used LC-MSMS technology and Virtual Expert Mass Spectrometrist software for qualitative and quantitative proteomic analysis of histones extracted from human small cell lung cancer cells. A total of 32 acetylations, methylations, and ubiquitinations were located in the human histones H2A, H2B, H3, and H4, including seven novel modifications. An LC-MSMS-based method was applied in a quantitative proteomic study of the dose-response effect of the histone deacetylase inhibitor (HDACi) PXD101 on histone acetylation in human cell cultures. Triplicate LC-MSMS runs at six different HDACi concentrations demonstrated that PXD101 affects acetylation of histones H2A, H2B, H3, and H4 in a site-specific and dose-dependent manner. This unbiased analysis revealed that a relative increase in acetylated peptide from the histone variants H2A, H2B, and H4 was accompanied by a relative decrease of dimethylated Lys(57) from histone H2B. The dose-response results obtained by quantitative proteomics of histones from HDACi-treated cells were consistent with Western blot analysis of histone acetylation, cytotoxicity, and dose-dependent expression profiles of p21 and cyclin A2. This demonstrates that mass spectrometry-based quantitative proteomic analysis of post-translational modifications is a viable approach for functional analysis of candidate drugs, such as HDAC inhibitors.

Protein complexes are dynamic entities; identification and quantitation of their components is critical in elucidating functional roles under specific cellular conditions. We report the first quantitative proteomic analysis of the human cap-binding protein complex. Components and proteins associated with the translation initiation eIF4F complex that may affect complex formation were identified and quantitated under distinct growth conditions. Site-specific phosphorylation of eIF4E and eIF4G and elevated levels of eIF4G:eIF4E complexes in phorbol ester treated HEK293 cells, and in serum-starved tumorigenic human mesenchymal stromal cells, attested to their activated translational states. The WD-repeat, scaffolding-protein Gemin5 was identified as a novel eIF4E binding partner, which interacted directly with eIF4E through a motif (YXXXXLPhi) present in a number of eIF4E-interacting partners. Elevated levels of Gemin5:eIF4E complexes were found in phorbol ester treated HEK293 cells. Gemin5 and eIF4E co-localized to cytoplasmic P-bodies in human osteosarcoma U2OS cells. Interaction between eIF4E and Gemin5 and their co-localization to the P-bodies, may serve to recruit capped mRNAs to these RNP complexes, for functions related to RNP assembly, remodeling and/or transition from active translation to mRNA degradation. Our results demonstrate that our quantitative proteomic strategy can be applied to the identification and quantitation of protein complex components in human cells grown under different conditions.

Quantitative analysis of protein expression is an important tool for the examination of complex biological systems. Albeit its importance, quantitative proteomics is still a challenging task because of the high dynamic range of protein amounts in the cell and the variation in the physical properties of proteins. Stable isotope labeling by amino acids in cell culture (SILAC) has been successfully used in yeast and mammalian cells to measure relative protein abundance by mass spectrometry. Here we show for the first time that proteins from Arabidopsis thaliana cell cultures can be selectively isotope-labeled in vivo by growing cells in the presence of a single stable isotope-labeled amino acid. Among the tested amino acids ([2H3]-leucine, [13C6]arginine, and [2H4]lysine), [13C6]arginine proved to be the most suitable. Incorporation of [13C6]arginine into the proteome was homogeneous and reached efficiencies of about 80%. [13C6]Arginine-labeled A. thaliana suspension cells were used to study the regulation of glutathione S-transferase expression in response to abiotic stress caused by salicylic acid and to identify proteins that bind specifically to phosphorylated 14-3-3 binding motifs on synthesized bait peptides in affinity purification experiments. In conclusion, the combination of stable isotope labeling of plant cells and mass spectrometry is a powerful technology that can be applied to study complex biological processes that involve changes in protein expression such as cellular responses to various kinds of stress or activation of cell signaling.

Significant identification of proteins by mass fingerprinting and partial sequencing of tryptic peptides is central to proteomics. However, peptide masses cluster with distances of approximately 1 Da. Expanding these clusters will give more peptides of unique masses, thereby identifying proteins with a higher significance. The mass clusters can be expanded downward by including more oxygen atoms in the peptides. Classic performic acid oxidation modifies three residues, Cys to CysO(3), Met to MetO(2), and Trp to TrpO(2). In this study, we compare the mass distributions of tryptic peptides computed from the predicted proteomes of Bacillus subtilis, Drosophila melanogaster, Arabidopsis thaliana, and Homo sapiens modified by oxidation, reduction, and reduction followed by carboxymethylation, carboxamidomethylation, or pyridylethylation. Forty to 46% of the eukaryotic tryptic peptides contain Cys, Met, or Trp. Additionally, the importance of mass accuracy of differentially modified tryptic peptides for significant protein identification by database searches was analyzed. The results show that performic acid oxidation gives markedly extended mass distributions at mass accuracies from +/-0.002 to +/-0.25 Da for the eukaryotes. The effect of the expanded mass distribution on significant protein identification was illustrated by searching simulated mass peak lists against the databases containing oxidized and reduced tryptic peptides. The specificity of formic acid oxidation was tested experimentally, and no general adverse effects were detected. Tryptic peptides provided a 100% sequence coverage of oxidized barley grain peroxidase by LC-MS, and the sequence coverages of oxidized and carboxymethylated bovine serum albumin were similar by MALDI-TOF MS analyses.

Thermolysin catalyses the formation of sucrose esters from sucrose and vinyl laurate in dimethylsulfoxide, with a specific activity of 53 nmol/min/mg and 2-O-lauroyl-sucrose as the main product. Such transesterification reactions are normally observed only when the mechanism involves an acyl enzyme intermediate, as with lipases or serine proteases, and not with metalloproteases like thermolysin. A possible reason is the affinity of the active site of thermolysin for sugar moieties, as for the potent inhibitor phosphoramidon. The reaction is not catalysed by other proteins under the same conditions, and is inhibited by removal of the active site zinc.

Background The Conserved Oligomeric Golgi (COG) complex is an eight-subunit assembly that localizes peripherally to Golgi membranes and is involved in retrograde vesicular trafficking. COG subunits are organized in two heterotrimeric groups, Cog2, -3, -4 and Cog5, -6, -7, linked by a dimeric group formed by Cog1 and Cog8. Dysfunction of COG complex in humans has been associated with new forms of Congenital Disorders of Glycosylation (CDG), therefore highlighting its essential role. In the present study, we intended to gain further insights into the evolution of COG subunits in vertebrates, using comparative analyses of all eight COG proteins. Results We used protein distances and dN/dS ratios as a measure of the rate of proteins evolution. The results showed that all COG subunits are evolving under strong purifying selection, although COG1 seems to evolve faster than the remaining proteins. In addition, we also tested the expression of COG genes in 20 human tissues, and demonstrate their ubiquitous nature. Conclusions COG complex has a critical role in Golgi structure and function, which, in turn, is involved in protein sorting and glycosylation. The results of this study suggest that COG subunits are evolutionary constrained to maintain the interactions between each other, as well with other partners involved in vesicular trafficking, in order to preserve both the integrity and function of the complex.

OBJECTIVEA key event in atherogenesis is the formation of lipid-loaded macrophages, lipidotic cells, which exhibit irreversible accumulation of undigested modified low-density lipoproteins in lysosomes. This event culminates with the loss of cell homeostasis, inflammation and cell death. In this study we propose to identify the chemical etiological factors and understanding the molecular and cellular mechanisms responsible for the impairment of lysosome function in macrophages.APPROACH AND RESULTSUsing shotgun lipidomics we have discovered that a family of oxidized lipids (cholesteryl hemiesters, ChE), end products of oxidation of polyunsaturated cholesteryl esters, occurs at higher concentrations in the plasma of two cohorts of cardiovascular disease patients than in the plasma of a control cohort. Macrophages exposed to the most prevalent ChE, cholesteryl hemiazelate (ChA) exhibit lysosome enlargement, peripheral lysosomal positioning, lysosome dysfunction and lipidosis which are irreversible. The transcriptomic profile of macrophages exposed to ChA indicates that the lysosome pathway is deeply affected and is well correlated with lysosome phenotypic and functional changes. Interestingly, the dysfunctional peripheral lysosomes are more prone to fuse with the plasma membrane, secreting their undigested luminal content into the extracellular milieu with potential consequences to the pathology.CONCLUSIONWe identify ChA not only as one of the molecules involved in the etiology of irreversible lysosome dysfunction culminating with lipidosis but also as a promoter of exocytosis of the dysfunctional lysosomes. The latter event is a new mechanism that may be important in the pathogenesis of atherosclerosis.