Introduction: The management of periprosthetic infections is a major challenge for the operating surgeon, both diagnostically and therapeutically. In recent years, extracellular vesicles have received increasing attention in musculoskeletal research. Mass spectrometry-based identification of proteins transported by extracellular vesicles is an important step towards understanding their biological functions in the defence process. Objective: The aim of our study was to investigate the protein content of extracellular vesicles isolated from acute and chronic infected samples, to search for identities and differences - instead of finding "the single best biomarker", to investigate the proteins encapsulated in extracellular vesicles present in as many detectable amounts as possible and to integrate them into biological processes. Method: Prospective monocentric study was performed, inclusion criteria were based on the 2018 MSIS criteria. 13 (n = 13) patients were included in the study, all patients underwent surgery for periprosthetic infection. 6 (n = 6) patients were confirmed to have an acute purulent (acute group) process, while 7 (n = 7) patients were confirmed to have a low-grade infection (chronic group). Extracellularis vesicles were isolated from the synovial fluid surrounding the prosthesis in all cases. STRING, KEGG, Gene Ontology databases were used for function-based clustering of proteins identified by mass spectrometry analysis. Final visualization was performed using Cytoscape 3.9.1 software. Results: 222 proteins were identified after extracellular vesicles were detected and were present in more than half of the acute or chronic samples. In more than half of the acute samples alone, 50 proteins were identified; in more than half of the chronic samples alone, 33 proteins were identified; in more than half of both groups simultaneously, 86 proteins were identified. These were used to construct functional clusters. Discussion: There has been a long-standing effort in the diagnostics of prosthetic infection to find "the single best biomarker" that can distinguish with certainty between infected and non-infected prosthetic loosening. Conclusion: The aim of our study was not to select a new biomarker, but to describe the role of proteins transported in extracellularis vesicles in biological processes, which will give us a better insight into the processes involved in periprosthetic infection.

Lung cancer is a severe disease for which better diagnostic and therapeutic approaches are urgently needed. Increasing evidence implies that aberrant protein glycosylation plays a crucial role in the pathogenesis and progression of lung cancer. Differences in glycosylation patterns have been previously observed between healthy and cancerous samples as well as between different lung cancer subtypes, which suggests untapped diagnostic potential. In addition, understanding the changes mediated by glycosylation may shed light on possible novel therapeutic targets and personalized treatment strategies for lung cancer patients. Mass spectrometry based glycomics and glycoproteomics have emerged as powerful tools for in-depth characterization of changes in protein glycosylation, providing valuable insights into the molecular basis of lung cancer. This paper reviews the literature on the analysis of protein glycosylation in lung cancer using mass spectrometry, which is dominated by manuscripts published over the past 5 years. Studies analyzing N-glycosylation, O-glycosylation, and glycosaminoglycan patterns in tissue, serum, plasma, and rare biological samples of lung cancer patients are highlighted. The current knowledge on the potential utility of glycan and glycoprotein biomarkers is also discussed.

Bevezetés: A periprotetikus infekciók ellátása jelentős kihívás elé állítja az operáló orvost, mind diagnosztikai, mind terápiás tekintetben. Az utóbbi években a mozgásszervi kutatások során egyre növekvő figyelmet kaptak az extracellularis vesiculák. Az extracellularis vesiculák által szállított fehérjék tömegspektrometrián alapuló azonosítása fontos lépés, mely segíthet megérteni a védekezési folyamatban betöltött biológiai funkcióikat. Célkitűzés: Vizsgálatunk célja volt az akut és a krónikus fertőzött mintákból izolált extracellularis vesiculák fehérjetartalmának megismerése, azonosságok és különbségek keresése – az „egy legjobb biomarker” megtalálása helyett a lehető legtöbb, detektálható mennyiségben jelen lévő extracellularis vesiculába zárt fehérje vizsgálata és biológiai folyamatokba illesztése. Módszer: Prospektív, monocentrikus vizsgálatot végeztünk, a beválasztási kritériumok a 2018-as MSIS-kritériumokon alapultak. A vizsgálatba 13 (n = 13) beteget vontunk be, minden beteg periprotetikus infekció miatt került műtétre. 6 (n = 6) betegnél akut purulens (akut csoport) folyamatot, míg 7 (n = 7) betegnél ’low-grade’ infekciót (krónikus csoport) igazoltunk. Az extracellularis vesiculák izolálása minden esetben a protézist körülvevő synovialis folyadékból történt. A tömegspektrometriai vizsgálattal azonosított fehérjék funkcionális alapú klaszterezésére a STRING, KEGG, Gene Ontology adatbázisokat használtuk. A végleges vizualizáció Cytoscape 3.9.1. szoftverrel történt. Eredmények: Az extracellularis vesiculák feltárása után 222 db fehérjét azonosítottunk, melyek vagy az akut, vagy a krónikus minták valamelyikének több mint felében fordultak elő. Csak az akut minták több mint felében 50 db fehérjét; csak a krónikus minták több mint felében 33 db fehérjét; egyszerre mindkét csoport több mint felében 86 db fehérjét azonosítottunk. Ezek alapján készültek a funkcionális klaszterek. Megbeszélés: A protézisfertőzések diagnosztikájában régóta megvan a törekvés, hogy megtalálják az „egy legjobb biomarkert”, amely biztosan különbséget tud tenni fertőzött és nem fertőzött protézislazulás között. Következtetés: Vizsgálatunk célja nem egy újabb biomarker kiválasztása volt, hanem az extracellularis vesiculákban szállított fehérjék biológiai folyamatokban betöltött szerepének ábrázolása, leírása, amellyel jobban betekinthetünk a periprotetikus infekció során zajló folyamatokba. Orv Hetil. 2024; 165(3): 98–109.

Aqueous extracts from Posidonia oceanica's green and brown (beached) leaves and rhizomes were prepared, submitted to phenolic compound and proteomic analysis, and examined for their potential cytotoxic effect on HepG2 liver cancer cells in culture. The chosen endpoints related to survival and death were cell viability and locomotory behavior, cell-cycle analysis, apoptosis and autophagy, mitochondrial membrane polarization, and cell redox state. Here, we show that 24 h exposure to both green-leaf- and rhizome-derived extracts decreased tumor cell number in a dose-response manner, with a mean half maximal inhibitory concentration (IC50) estimated at 83 and 11.5 μg of dry extract/mL, respectively. Exposure to the IC50 of the extracts appeared to inhibit cell motility and long-term cell replicating capacity, with a more pronounced effect exerted by the rhizome-derived preparation. The underlying death-promoting mechanisms identified involved the down-regulation of autophagy, the onset of apoptosis, the decrease in the generation of reactive oxygen species, and the dissipation of mitochondrial transmembrane potential, although, at the molecular level, the two extracts appeared to elicit partially differentiating effects, conceivably due to their diverse composition. In conclusion, P. oceanica extracts merit further investigation to develop novel promising prevention and/or treatment agents, as well as beneficial supplements for the formulation of functional foods and food-packaging material with antioxidant and anticancer properties.

Lung cancer is one of the most commonly diagnosed cancer types. Studying the molecular changes that occur in lung cancer is important to understand tumor formation and identify new therapeutic targets and early markers of the disease to decrease mortality. Glycosaminoglycan chains play important roles in various signaling events in the tumor microenvironment. Therefore, we have determined the quantity and sulfation characteristics of chondroitin sulfate and heparan sulfate in formalin-fixed paraffin-embedded human lung tissue samples belonging to different lung cancer types as well as tumor adjacent normal areas. Glycosaminoglycan disaccharide analysis was performed using HPLC-MS following on-surface lyase digestion. Significant changes were identified predominantly in the case of chondroitin sulfate; for example, the total amount was higher in tumor tissue compared to the adjacent normal tissue. We also observed differences in the degree of sulfation and relative proportions of individual chondroitin sulfate disaccharides between lung cancer types and adjacent normal tissue. Furthermore, the differences in the 6-O-/4-O-sulfation ratio of chondroitin sulfate were different between the lung cancer types. Our pilot study revealed that further investigation of the role of chondroitin sulfate chains and enzymes involved in their biosynthesis is an important aspect of lung cancer research.

Quantitative proteomics is one of the most widespread applications of mass spectrometry. We have planned a series of short tutorials to help orient PhD students and young post-docs mostly focused on label-free experiments. This is not designed to be a comprehensive textbook, but an open-ended series discussing diverse issues. In this first tutorial we summarize major aspects of study design. In the second, we will discuss MaxQuant, a widely used software for evaluating LC-MS data in terms of protein abundances. The following two issues will deal with selecting proteins which can be reasonably quantified in an experiment, and how to deal with the often-missing values in protein abundance tables. The first step before designing an experiment is to determine the concept of the project. We must decide very clearly on what the objective is, and subsequently what questions need to be asked and what kind of answers we expect. Only after this can we design the experiments comprehensively. This might seem trivial, but incorrectly formulated experimental questions may lead to erroneous inferences, or to much lower impact and significance than hoped for. After conceptualizing the project, several things must be thoroughly examined regarding the experimental questions before further planning can commence. First, our questions should be testable and the experiments to be performed should be selected accordingly, for example, it must be decided if relative or absolute quantitation is required. Second, they should be defined before doing any experimental work. This is crucial to avoid false positives, for example, to employ FDR control correctly when performing multiple statistical tests. Third, response variables (typically protein abundances) should be reliably measurable, for example, their abundances should be over the limit of quantitation. Finally, it must be assessed whether we are focusing on the correct explanatory variables. This is especially important to avoid mistaking correlation for causality, for example, the age of patients should be considered when risk factors are evaluated. A pilot study is exploratory in nature. It is primarily used to characterize effect sizes (the standardized difference) between group means. Although analyzing more samples improves statistical power (the probability of obtaining true positive results), it also requires more effort (time and cost). In practice there is usually a compromise between these; ideally a pilot study should include 10, 15, or 25 samples per group if effect sizes are large, medium, or small, respectively.3 Because effect sizes are usually not known beforehand, they need to be approximated based on prior knowledge of the sample or species under investigation. Pilot studies are often sufficient to point research in novel directions and to push back frontiers of our knowledge. Most publications using quantitative proteomics are pilot studies and are within the range of the financial power of universities and academia. Their major limitation lies in medical research, primarily due to their inability to account for the heterogeneity of human population. The experimental and technical design of a study involves careful planning of the sample preparation, analysis, data handling, and statistical analysis. First, it has to be decided if mass spectrometry based proteomics is the best experimental approach. For this, the possibilities and limitations of MS-based quantitative proteomics need to be understood. It is most frequently based on the measurement of LC-MS peak intensities or areas; however, this can be affected by several factors apart from analyte concentrations, for example, matrix effects, instrument parameters, and differences in ionization efficiencies. Because of these, there are two fundamental approaches to quantitation: relative and absolute quantitation. In relative quantitation two (or more) samples are compared to each other to determine the ratio of different analytes between them, which can be done with the use of stable isotope labeling (chemical, proteolytic, or metabolic labeling) or without it (label-free quantitation). On the other hand, in absolute quantitation protein concentrations (e.g., the concentration of an antibody species in human plasma) can be determined for individual samples with the help of stable isotope labeled internal standards. Although labeling-based strategies (both for relative and absolute quantitation) are more accurate and reproducible than label-free quantitation, they are more expensive, labor-intensive, and not applicable in every circumstance (e.g., for the analysis of human tissue samples). As for the majority of scientific projects that require quantitative proteomics label-free quantitation is sufficient, it is the method of choice in most cases. There is a multitude of experimental methods used in proteomics (sample preparation, HPLC-MS analysis, and data handling);4, 5 selecting and optimizing these is the main task of the analytical chemist. Discussing, or even listing these is out of the scope of this tutorial. Although the method of choice influences the planning process, there are universal concepts needed to be taken into account. The most important parts are the testing of the suitability of the system6—usually through preliminary studies; the randomization of sample preparation and analysis steps7—helping to reduce batch effects; and the implementation of experimental controls,8 which then can be used to monitor the state of the system during the experiments. The latter is especially important to track and minimize unwanted variations introduced into the data during the different steps of the analysis. For example, one may add standards (exogenous proteins or peptides) to the samples to monitor experimental errors, and use quality control samples to show system integrity. Data analysis and statistical methods used can also be tested for robustness via sensitivity analyses, which can provide information on how much the results are affected by the use of different methods. This is becoming more and more important in light of the large number of emerging data analysis solutions available.9 Designing and thoroughly planning a scientific project is an essential part of any project. Incorrectly formulated experimental questions or inadequately planned experiments can make the conclusions of the study invalid regardless of how well other aspects have been executed. Therefore, we recommend investing considerable time and effort into thoroughly planning every part of a project, and revising it several times before its initiation. This short tutorial is by no means comprehensive, but can serve as a starting point or a sort of guidebook summarizing the most important aspects to be considered before starting any experimental work. Data sharing is not applicable as no new data were generated or the article describes entirely theoretical research.

Lung cancer is one of the most common types of cancer with limited therapeutic options, therefore a detailed understanding of the underlying molecular changes is of utmost importance. In this pilot study, we investigated the proteomic and glycosaminoglycan (GAG) profile of ALK rearranged lung tumor tissue regions based on the morphological classification, mucin and stromal content. Principal component analysis and hierarchical clustering revealed that both the proteomic and GAG-omic profiles are highly dependent on mucin content and to a lesser extent on morphology. We found that differentially expressed proteins between morphologically different tumor types are primarily involved in the regulation of protein synthesis, whereas those between adjacent normal and different tumor regions take part in several other biological processes (e.g. extracellular matrix organization, oxidation-reduction processes, protein folding) as well. The total amount and the sulfation profile of heparan sulfate and chondroitin sulfate showed small differences based on morphology and larger differences based on mucin content of the tumor, while an increase was observed in both the total amount and the average rate of sulfation in tumors compared to adjacent normal regions.

Identification and characterization of N-glycopeptides from complex samples are usually based on tandem mass spectrometric measurements. Experimental settings, especially the collision energy selection method, fundamentally influence the obtained fragmentation pattern and hence the confidence of the database search results ("score"). Using standards of naturally occurring glycoproteins, we mapped the Byonic and pGlyco search engine scores of almost 200 individual N-glycopeptides as a function of collision energy settings on a quadrupole time of flight instrument. The resulting unprecedented amount of peptide-level information on such a large and diverse set of N-glycopeptides revealed that the peptide sequence heavily influences the energy for the highest score on top of an expected general linear trend with m/z. Search engine dependence may also be noteworthy. Based on the trends, we designed an experimental method and tested it on HeLa, blood plasma, and monoclonal antibody samples. As compared to the literature, these notably lower collision energies in our workflow led to 10-50% more identified N-glycopeptides, with higher scores. We recommend a simple approach based on a small set of reference N-glycopeptides easily accessible from glycoprotein standards to ease the precise determination of optimal methods on other instruments. Data sets can be accessed via the MassIVE repository (MSV000089657 and MSV000090218).

Background Extracellular vesicles (EVs) are considered as crucial players in a wide variety of biological processes. Although their importance in joint diseases or infections has been shown by numerous studies, much less is known about their function in periprosthetic joint infection (PJI). Our aim was to investigate activated polymorphonuclear (PMN)-derived synovial EVs in patients with PJI. Questions/Purposes (1) Is there a difference in the number and size of extracellular vesicles between periprosthetic joint aspirates of patients with PJI and aseptic loosening? (2) Are these vesicles morphologically different in the two groups? (3) Are there activated PMN-derived EVs in septic samples evaluated by flow cytometry after CD177 labelling? (4) Is there a difference in the protein composition carried by septic and aseptic vesicles? Methods Thirty-four patients (n = 34) were enrolled into our investigation, 17 with PJI and 17 with aseptic prosthesis loosening. Periprosthetic joint fluid was aspirated and EVs were separated. Samples were analysed by nanoparticle tracking analysis (NTA) and transmission electron microscopy (TEM) and flow cytometry (after Annexin V and CD177 labelling). The protein content of the EVs was studied by mass spectrometry (MS). Results NTA showed particle size distribution in both groups between 150 nm and 450 nm. The concentration of EVs was significantly higher in the septic samples (p = 0.0105) and showed a different size pattern as compared to the aseptic ones. The vesicular nature of the particles was confirmed by TEM and differential detergent lysis. In the septic group, FC analysis showed a significantly increased event number both after single and double labelling with fluorochrome conjugated Annexin V (p = 0.046) and Annexin V and anti-CD177 (p = 0.0105), respectively. MS detected a significant difference in the abundance of lactotransferrin (p = 0.00646), myeloperoxidase (p = 0.01061), lysozyme C (p = 0.04687), annexin A6 (p = 0.03921) and alpha-2-HS-glycoprotein (p = 0.03146) between the studied groups. Conclusions An increased number of activated PMN derived EVs were detected in the synovial fluid of PJI patients with a characteristic size distribution and a specific protein composition. The activated PMNs-derived extracellular vesicles can be potential biomarkers of PJI.

Chronic liver diseases have both high incidence and mortality rates; therefore, a deeper understanding of the underlying molecular mechanisms is essential. We have determined the content and sulfation pattern of chondroitin sulfate (CS) and heparan sulfate (HS) in human hepatocellular carcinoma and cirrhotic liver tissues, considering the etiology of the diseases. A variety of pathological conditions such as alcoholic liver disease, hepatitis B and C virus infections, and primary sclerosing cholangitis were studied. Major differences were observed in the total abundance and sulfation pattern of CS and HS chains. For example, the 6-O-sulfation of CS is fundamentally different regarding etiologies of cirrhosis, and a 2-threefold increase in HS N-sulfation/O-sulfation ratio was observed in hepatocellular carcinoma compared to cirrhotic tissues.

Echinoderms are an acknowledged source of bioactive compounds exerting various beneficial effects on human health. Here, we examined the potential in vitro anti-hepatocarcinoma effects of aqueous extracts of the cell-free coelomic fluid obtained from the sea urchin Arbacia lixula using the HepG2 cell line as a model system. This was accomplished by employing a combination of colorimetric, microscopic and flow cytometric assays to determine cell viability, cell cycle distribution, the possible onset of apoptosis, the accumulation rate of acidic vesicular organelles, mitochondrial polarization, cell redox state and cell locomotory ability. The obtained data show that exposed HepG2 cells underwent inhibition of cell viability with impairment of cell cycle progress coupled to the onset of apoptotic death, the induction of mitochondrial depolarization, the inhibition of reactive oxygen species production and acidic vesicular organelle accumulation, and the block of cell motile attitude. We also performed a proteomic analysis of the coelomic fluid extract identifying a number of proteins that are plausibly responsible for anti-cancer effects. Therefore, the anti-hepatocarcinoma potentiality of A. lixula’s preparation can be taken into consideration for further studies aimed at the characterization of the molecular mechanism of cytotoxicity and the development of novel prevention and/or treatment agents.

The optimization of solid-phase extraction (SPE) purification and chromatographic separation is usually neglected during proteomics studies. However, the effects on detection performance are not negligible, especially when working with highly glycosylated samples. We performed a comparative study of different SPE setups, including an in-house optimized method and reversed-phase chromatographic gradients for the analysis of highly glycosylated plasma fractions as a model sample for glycopeptide analysis. The in-house-developed SPE method outperformed the graphite-based and hydrophilic interaction liquid chromatography (HILIC) purification methods in detection performance, recovery, and repeatability. During optimization of the chromatography, peak distribution was maximized to increase the peptide detection rate. As a result, we present sample purification and chromatographic separation methods optimized for the analysis of hydrophilic samples, the most important of which is heavily N-glycosylated protein mixtures.

Identifying molecular alterations occurring during cancer progression is essential for a deeper understanding of the underlying biological processes. Here we have analyzed cancerous and healthy prostate biopsies using nanoLC-MS(MS) to detect proteins with altered expression and N-glycosylation. We have identified 75 proteins with significantly changing expression during disease progression. The biological processes involved were assigned based on protein-protein interaction networks. These include cellular component organization, metabolic and localization processes. Multiple glycoproteins were identified with aberrant glycosylation in prostate cancer, where differences in glycosite-specific sialylation, fucosylation, and galactosylation were the most substantial. Many of the glycoproteins with altered N-glycosylation were extracellular matrix constituents, and are heavily involved in the establishment of the tumor microenvironment.

Phosphopeptide enrichment is a commonly used sample preparation step for investigating phosphorylation. TiO2-based enrichment has been demonstrated to have excellent performance both for large amounts of complex and for small amounts of simple samples. However, it has not yet been studied for complex samples in the nanogram range. Our objective was to develop a methodology applicable for complex samples in the low nanogram range, useful for mass spectrometry analysis of tissue microarrays. The selectivity and performance of two stationary phases (TiO2 nanoparticle-coated monolithic column and spin tip filled with TiO2 microspheres) and several loading solvents were studied. Based on this study, we developed an effective and robust method, based on a spin tip with a non-conventional 50 mM citric acid-based loading solvent. It gave excellent results for phosphopeptide enrichment from samples containing a few nanograms of a complex protein mixture.

In the present study, we describe the development of a fast, 2-step salt gradient for analysis of chondroitin sulfate disaccharides. Using salt gradients, which is somewhat unusual in HILIC-based separations, provides relatively fast chromatography with excellent sensitivity (15 min cycle time, 10-20 fmol/mu L detection, 30-50 fmol/mu L quantitation limit), and good linearity. The efficiency of the new method is demonstrated by measuring human tissue slices of healthy, cirrhotic, and cancerous liver samples. Preliminary results show major differences among the quantity and sulfation pattern of the various sample types. (C) 2020 The Authors. Published by Elsevier B.V.

Micro- and nano-sized vesicles (MVs and NVs, respectively) from edible plant resources are gaining increasing interest as green, sustainable, and biocompatible materials for the development of next-generation delivery vectors. The isolation of vesicles from complex plant matrix is a significant challenge considering the trade-off between yield and purity. Here, we used differential ultracentrifugation (dUC) for the bulk production of MVs and NVs from tomato (Solanum lycopersicum L.) fruit and analyzed their physical and morphological characteristics and biocargo profiles. The protein and phospholipid cargo shared considerable similarities between MVs and NVs. Phosphatidic acid was the most abundant phospholipid identified in NVs and MVs. The bulk vesicle isolates were further purified using sucrose density gradient ultracentrifugation (gUC) or size-exclusion chromatography (SEC). We showed that SEC using gravity column efficiently removed co-purifying matrix components including proteins and small molecular species. dUC/SEC yielded a high yield of purified vesicles in terms of number of particles (2.6 × 1015 particles) and protein quantities (6.9 ± 1.5 mg) per kilogram of tomato. dUC/gUC method separated two vesicle populations on the basis of buoyant density. Proteomics and in silico studies of the SEC-purified MVs and NVs support the presence of different intra- and extracellular vesicles with highly abundant lipoxygenase (LOX), ATPases, and heat shock proteins (HSPs), as well as a set of proteins that overlaps with that previously reported in tomato chromoplast.

We have characterized site-specific N-glycosylation of the HeLa cell line glycoproteins, using a complex workflow based on high and low energy tandem mass spectrometry of glycopeptides. The objective was to obtain highly reliable data on common glycoforms, so rigorous data evaluation was performed. The analysis revealed the presence of a high amount of bovine serum contaminants originating from the cell culture media - nearly 50% of all glycans were of bovine origin. Unaccounted, the presence of bovine serum components causes major bias in the human cellular glycosylation pattern; as is shown when literature results using released glycan analysis are compared. We have reliably identified 43 (human) glycoproteins, 69 N-glycosylation sites, and 178 glycoforms. HeLa glycoproteins were found to be highly (68.7%) fucosylated. A medium degree of sialylation was observed, on average 46.8% of possible sialylation sites were occupied. High-mannose sugars were expressed in large amounts, as expected in the case of a cancer cell line. Glycosylation in HeLa cells is highly variable. It is markedly different not only on various proteins but also at the different glycosylation sites of the same protein. Our method enabled the detailed characterization of site-specific N-glycosylation of several glycoproteins expressed in HeLa cell line.

HPLC-MS/MS analysis of various human cell lines shows the presence of a major amount of bovine protein contaminants. These likely originate from fetal bovine serum (FBS), typically used in cell cultures. If evaluated against a human protein database, on average 10% of the identified human proteins will be misleading (bovine proteins, but indicated as if they were human). Bovine contaminants therefore may cause major bias in proteomic studies of cell cultures, if not considered explicitly.

Glycoproteins have essential roles in biology and medicine. Glycosylation patterns often change during pathophysiological conditions which is also underlined by the fact that most tumor biomarkers are glycoproteins. Biopsies are generally stored in the form of tissue microarrays (TMA) facilitating parallel analysis of healthy, cancerous and metastatic tissues. The aim of our work is to characterize the glycosylation pattern of prostate cancer TMAs following on-surface tryptic digestion. For sensitive detection of minor glycoforms in tissues, especially that using very small sample amounts like that available in TMAs, it is essential to include a glycopeptide enrichment step in the analytical workflow. First we tested a mixed mode graphite and C18 SPE column, but this did not prove efficient in binding glycopeptides. Subsequently we used a solvent (acetone) based precipitation method1, which gave promising results. Following initial trials, we have optimized the method to achieve both high yield and high enrichment for glycopeptides. Modified parameters included the pH, salt concentration, the volume and the type of the precipitating solvent. Results were tested both on a model glycoprotein, alpha-1-acid glycoprotein (AGP) and also on a complex HeLa cell lysate. Glycopeptides and peptides were identified by tandem mass spectrometry in a nano-LC-MS/MS workflow using the Byonic software. Quantitation of the individual glycoforms was performed based on MS1 using our in-house GlycoPattern software. Results of the optimization and glycopeptide enrichment will be presented.