Label-free Protein Quantification Research Articles

PROTEOMICS IDENTIFICATION OF NOVEL CEREBROSPINAL FLUID BIOMARKER CANDIDATES OF DEMENTIA WITH LEWY BODIES

Cerebrospinal fluid (CSF) is considered an optimal source for the discovery of in vivo biomarkers for Dementia with Lewy bodies (DLB). Thus far, no reliable biomarker with both high sensitivity and specificity is available for DLB. CSF biomarkers could improve the early diagnostic accuracy, monitor disease progression and treatment response. We set out a proteomics study to identify novel CSF biomarker candidates for DLB. An in-depth proteomics workflow involving immune-depletion of high-abundant proteins, mono-dimensional SDS-PAGE in conjunction with nanoLC-MS/MS-based proteomics, database searching (MaxQuant) and label-free protein quantification was applied on CSF of 20 probable DLB patients and age and gender matched individuals with subjective cognitive decline (SCD, n=20). DLB patients had an abnormal (123)I-FP-CIT SPECT scan and normal CSF values of Aβ42, total tau and phosphorylated tau. Candidate biomarkers were selected based on the following criteria: (1) p<0.05, fold change>1.2, median normalized spectral count ≥2; (2) ≥50% separation between the two groups; and (3) identified peptide sequences covering ≥20% of the protein. Fifty-seven out of 2100 identified proteins were differentially expressed in DLB patients compared to SCD (p<0.05). 35 proteins were down-regulated and 22 proteins were up-regulated in DLB compared to SCD. We selected three proteins for validation by ELISA in a cohort including DLB, AD, Parkinson's disease (PD) and SCD. This validation is currently in progress. Our proteomics analysis of CSF identified several novel potential candidate biomarkers for DLB. Further validation of prioritized candidates in larger cohorts should delineate their potential as early diagnostic and/or progression biomarkers for DLB.

Label-free quantification of meat proteins for evaluation of species composition of processed meat products

This study evaluated the application of label-free, relative quantification of highly processed meat proteins to authenticate processed meat products. Quantitation was based on proteins for which heat-stable and species-specific peptide markers had been detected. Using nano-LC-QTOF-MS/MS, 20 new, heat-stable peptide markers unique to chicken, duck and goose were identified, with significant scores. The method enabled detection of 1%(w/w) of chicken and 1%(w/w) pork in a mixture of the meat of three species, as well as 0.8%(w/w) beef proteins in commercial poultry frankfurters. The proteins’ abundance was computed using a spectral matching technique, termed the absolute protein expression (APEX) proteomics tool. This method includes a correction factor for each protein, based on the peptide MS detection probabilities, which are influenced by the physicochemical properties of the peptide. Considerable differences in abundance of myofibrillar and sarcoplasmic proteins were observed between samples and illegal proportions of ingredients were discovered.

Quantification of egg proteome changes during fertilization in sterlet Acipenser ruthenus

Eggs of sterlet are discharged outside into ambient aquatic environment where egg activation and fertilization occur. Effects of different activation media including freshwater and clay suspension on protein abundances of egg were quantified in sterlet Acipenser ruthenus. In-gel digestion and high resolution mass spectrometry were used for label-free protein quantification in the eggs of five females. No significant (p > 0.05) difference was found between protein abundances in eggs activated with different media. However, results showed significant (p < 0.05, fold change ≥2) reduction in the abundances of nine proteins including six glycoproteins, enolase and heat shock protein in activated groups compared to freshly ovulated eggs as control. The fact that abundance of proteasome subunit alpha significantly reduced only in eggs which were activated by clay suspension suggests that activation medium can somehow intervene with protein regulation during fertilization. In conclusion, external fertilization in sturgeon egg is accompanied by huge release of proteins into the external environment that may participate in the construction of a transient microenvironment around egg for attraction and protection of spermatozoa to ensure ensuing fertilization. Data are available via ProteomeXchange with identifier PXD006232.

Label-free Analysis of CD8+ T Cell Subset Proteomes Supports a Progressive Differentiation Model of Human-Virus-Specific T Cells

Pathogens trigger Tcells to express distinct sets ofeffector proteins. To better understand the molecular mechanisms that drive functional specification, we used high-resolution mass spectrometry and label-free protein quantification to measure proteomic differences between the seven largest circulating human CD8+ Tcell subsets. Hierarchical clustering of the proteomes placed naive and CD45RA-expressing effector-type Tcells at the extremes of the spectrum,with central memory and other effector memory stages located in between. Prominent differences between the subsets included expression of specificgranzymes, signaling proteins, and molecules involved in metabolic regulation and cell adhesion. Remarkably, whereas most of the proteomic relationships between the subsets occurred in linear variations, a small proportion of proteins was regulated only in discrete subsets. The data obtained from this proteome analysis correspond best to a progressive differentiation model in which specific stable traits are gradually acquired during development.

Epsilon-Q: An Automated Analyzer Interface for Mass Spectral Library Search and Label-Free Protein Quantification.

Mass spectrometry (MS) is a widely used proteome analysis tool for biomedical science. In an MS-based bottom-up proteomic approach to protein identification, sequence database (DB) searching has been routinely used because of its simplicity and convenience. However, searching a sequence DB with multiple variable modification options can increase processing time, false-positive errors in large and complicated MS data sets. Spectral library searching is an alternative solution, avoiding the limitations of sequence DB searching and allowing the detection of more peptides with high sensitivity. Unfortunately, this technique has less proteome coverage, resulting in limitations in the detection of novel and whole peptide sequences in biological samples. To solve these problems, we previously developed the "Combo-Spec Search" method, which uses manually multiple references and simulated spectral library searching to analyze whole proteomes in a biological sample. In this study, we have developed a new analytical interface tool called "Epsilon-Q" to enhance the functions of both the Combo-Spec Search method and label-free protein quantification. Epsilon-Q performs automatically multiple spectral library searching, class-specific false-discovery rate control, and result integration. It has a user-friendly graphical interface and demonstrates good performance in identifying and quantifying proteins by supporting standard MS data formats and spectrum-to-spectrum matching powered by SpectraST. Furthermore, when the Epsilon-Q interface is combined with the Combo-Spec search method, called the Epsilon-Q system, it shows a synergistic function by outperforming other sequence DB search engines for identifying and quantifying low-abundance proteins in biological samples. The Epsilon-Q system can be a versatile tool for comparative proteome analysis based on multiple spectral libraries and label-free quantification.

Label-free protein quantification of sodium butyrate treated CHO cells by ESI-UHR-TOF-MS

Effects of butyrate on CHO producer cells are contradictory, promoting productivity and at the same time repressing proliferation. Though in previous omics studies the background of butyrate impact on producer cells has been investigated, the knowledge about the mechanism is still very limited. As previous proteomic results on this field are mainly based on 2DE-gels, we conducted a label-free MS quantification, based on fast high resolution ESI–MS and a straight forward software solution, to gain insight in shifted cellular processes of CHO cells 25h after butyrate treatment. 118 proteins or subunits with significantly altered abundances were identified suggesting changes in carbohydrate, protein metabolic and cell cycle processes. Effects of butyrate on the nucleosome assembly as a known direct epigenetic influence on HDAC activity turned out to be unexpectedly fast and persistent, as confirmed by Western blots of histone-H4 acetylation. Contradictory to increased cell specific productivity, most elements of protein metabolism exhibited decreased levels after butyrate treatment. In comparison to published results some overlap of our label free MS data could be observed but also apparently diverging findings, showing the need for complementary omics techniques for a holistic view on cellular processes such as response to butyrate.

Proteomics of rimmed vacuoles define new risk allele in inclusion body myositis.

Sporadic inclusion body myositis (sIBM) pathogenesis is unknown; however, rimmed vacuoles (RVs) are a constant feature. We propose to identify proteins that accumulate within RVs. RVs and intact myofibers were laser microdissected from skeletal muscle of 18 sIBM patients and analyzed by a sensitive mass spectrometry approach using label-free spectral count-based relative protein quantification. Whole exome sequencing was performed on 62 sIBM patients. Immunofluorescence was performed on patient and mouse skeletal muscle. A total of 213 proteins were enriched by >1.5 -fold in RVs compared to controls and included proteins previously reported to accumulate in sIBM tissue or when mutated cause myopathies with RVs. Proteins associated with protein folding and autophagy were the largest group represented. One autophagic adaptor protein not previously identified in sIBM was FYCO1. Rare missense coding FYCO1 variants were present in 11.3% of sIBM patients compared with 2.6% of controls (p = 0.003). FYCO1 colocalized at RVs with autophagic proteins such as MAP1LC3 and SQSTM1 in sIBM and other RV myopathies. One FYCO1 variant protein had reduced colocalization with MAP1LC3 when expressed in mouse muscle. This study used an unbiased proteomic approach to identify RV proteins in sIBM that included a novel protein involved in sIBM pathogenesis. FYCO1 accumulates at RVs, and rare missense variants in FYCO1 are overrepresented in sIBM patients. These FYCO1 variants may impair autophagic function, leading to RV formation in sIBM patient muscle. FYCO1 functionally connects autophagic and endocytic pathways, supporting the hypothesis that impaired endolysosomal degradation underlies the pathogenesis of sIBM. Ann Neurol 2017;81:227-239.

Proteomic analysis of the vitamin C effect on the doxorubicin cytotoxicity in the MCF-7 breast cancer cell line.

Doxorubicin is an anthracycline drug which inhibits the growth of breast cancer cell lines. However, a major factor limiting its use is a cumulative, dose-dependent cardiotoxicity, resulting in a permanent loss of cardiomyocytes. Vitamin C was found to potentiate the cytotoxic effects of a variety of chemotherapeutic drugs including doxorubicin. The aim of the study was to describe the changes in protein expression and proliferation of the MCF-7 cells induced by the vitamin C applied with doxorubicin. Label-free quantitative proteomics and real-time cell analysis methods were used to search for proteome and cell proliferation changes. These changes were induced by the pure DOX and by DOX combined with vitamin C applied on the MCF-7 cell line. From the real-time cell analysis experiments, it is clear that the highest anti-proliferative effect occurs with the addition of 200µM of vitamin C to 1µM of doxorubicin. By applying both the label-free protein quantification method and total ion current assay, we found statistically significant changes (p≤0.05) of 26 proteins induced by the addition of vitamin C to doxorubicin on the MCF-7 cell line. These differentially expressed proteins are involved in processes such as structural molecule activity, transcription and translation, immune system process and antioxidant, cellular signalling and transport. The detected proteins may be capable of predicting response to DOX therapy. This is a key tool in the treatment of breast cancer, and the combination with vit C seems to be of particular interest due to the fact that it can potentiate anti-proliferative effect of DOX.

LFQProfiler and RNP(xl): Open-Source Tools for Label-Free Quantification and Protein-RNA Cross-Linking Integrated into Proteome Discoverer.

Modern mass spectrometry setups used in today's proteomics studies generate vast amounts of raw data, calling for highly efficient data processing and analysis tools. Software for analyzing these data is either monolithic (easy to use, but sometimes too rigid) or workflow-driven (easy to customize, but sometimes complex). Thermo Proteome Discoverer (PD) is a powerful software for workflow-driven data analysis in proteomics which, in our eyes, achieves a good trade-off between flexibility and usability. Here, we present two open-source plugins for PD providing additional functionality: LFQProfiler for label-free quantification of peptides and proteins, and RNP(xl) for UV-induced peptide-RNA cross-linking data analysis. LFQProfiler interacts with existing PD nodes for peptide identification and validation and takes care of the entire quantitative part of the workflow. We show that it performs at least on par with other state-of-the-art software solutions for label-free quantification in a recently published benchmark ( Ramus, C.; J. Proteomics 2016 , 132 , 51 - 62 ). The second workflow, RNP(xl), represents the first software solution to date for identification of peptide-RNA cross-links including automatic localization of the cross-links at amino acid resolution and localization scoring. It comes with a customized integrated cross-link fragment spectrum viewer for convenient manual inspection and validation of the results.

Abstract LB-140: Scaling discovery proteomics to large lung cancer cohorts using data independent acquisition

Abstract The success of label free protein quantification relies on larger cohort sizes to accurately profile protein expression patterns enabling specific targets to be translated to confirmatory studies. Thus, proteome profiling experiments must satisfy two primary requirements: maximizing breadth and depth of protein sampling as well as facilitating automated data processing. The approach presented here integrates discovery experiments used to create reference databases and rapid data independent acquisition (DIA) methods to examine large clinical cohorts using &amp;lt; 3 hours of instrument time per individual patient's resected tumor specimen. The combination facilitates exhaustive, automated data mining for protein identification and relative quantitation. Samples used to evaluate the robustness of the study were collected from lung squamous cell carcinoma (LUSC) and lung adenocarcinoma (LUAD). A sample total of 159 (50 LUSC, 46 LUAD, and 63 adjacent control lung tissues) were analyzed using UHPLC separations coupled to a hybrid quadrupole-orbital ion trap mass spectrometer (QExactive Plus) for DIA. Automated data processing was performed by matching peptides in spectral libraries developed from expression proteomics experiments using pooled tissue proteomes. Data were evaluated to determine differences between LUSC, LUAD, and adjacent control tissue, which were then compared to previous literature to prioritize candidate biomarkers and evaluate the performance of DIA LC-MS/MS for tumor proteome profiling. Hierarchical clustering visualized potential tumor classification schemes based on proteomic phenotypes. In a further study, analysis of cores from a tissue microarray produced quantitative data for &amp;gt; 3,000 proteins per core, indicating that the technology can be applied to minimal amounts of formalin fixed paraffin embedded tumor tissue. Because TMAs are assembled to address specific clinical questions, further analysis of these cohorts is an extremely valuable use for DIA; tumor proteome profiles can be rapidly accumulated and mapped to the clinical variables used to select samples for the TMA. Data independent acquisition provides a method for discovery proteomics that balances a sufficient depth of coverage with the ability to analyze large cohorts of patients (n = 100-400) within 1-2 months on a single instrument. Initial data have been produced for lung squamous cell carcinoma and lung adenocarcinoma, which indicate its utility for assessment of patient groups. Citation Format: Scott Peterman, Bin Fang, Melissa Hoffmann, Amol Prakash, Paul A. Stewart, Richard Liu, Matthew Smith, Joseph Johnson, Steven Eschrich, Guolin Zhang, Eric Haura, John Koomen. Scaling discovery proteomics to large lung cancer cohorts using data independent acquisition. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr LB-140.

Human aqueous humor proteome in cataract, glaucoma, and pseudoexfoliation syndrome.

Twenty-nine human aqueous humor samples from patients with eye diseases such as cataract and glaucoma with and without pseudoexfoliation syndrome were characterized by LC-high resolution MS analysis. In total, 269 protein groups were identified with 1% false discovery rate including 32 groups that were not reported previously for this biological fluid. Since the samples were analyzed individually, but not pooled, 36 proteins were identified in all samples, comprising the constitutive proteome of the fluid. The most dominant molecular function of aqueous humor proteins as determined by GO analysis is endopeptidase inhibitor activity. Label-free protein quantification showed no significant difference between glaucoma and cataract aqueous humor proteomes. At the same time, we found decrease in the level of apolipoprotein D as a marker of the pseudoexfoliation syndrome. The data are available from ProteomeXchange repository (PXD002623).

7-Ketocholesterol overcomes drug resistance in chronic myeloid leukemia cell lines beyond MDR1 mechanism

Chronic myeloid leukemia (CML) is a myeloproliferative disease with a characteristic BCR-ABL tyrosine kinase (TK) fusion protein. Despite the clinical efficacy accomplished by TKIs therapies, disease progression may affect patient response rate to these inhibitors due to a multitude of factors that could lead to development of a mechanism known as multidrug resistance (MDR). 7-Ketocholesterol (7KC) is an oxidized cholesterol derivative that has been extensively reported to cause cell death in a variety of cancer models. In this study, we showed the in vitro efficacy of 7KC against MDR leukemia cell line, Lucena. 7KC treatment induced reduction in cell viability, together with apoptosis-mediated cell death. Moreover, downregulation of MDR protein caused intracellular drug accumulation and 7KC co-incubation with either Daunorubicin or Vincristine reduced cell viability compared to the use of each drug alone. Additionally, quantitative label-free mass spectrometry-based protein quantification showed alteration of different molecular pathways involved in cell cycle arrest, induction of apoptosis and misfolded protein response. Conclusively, this study highlights the effect of 7KC as a sensitizing agent of multidrug resistance CML and elucidates its molecular mechanisms. SignificanceCML patients treated with tyrosine kinase inhibitors (TKIs) have showed a 5-year estimated overall survival of 89%, with cumulative complete cytogenetic response of 87%. However, development of drug resistance is a common feature of the disease progression. This study aimed at showing the effect of 7KC as a cytotoxic and sensitizing agent of multidrug resistance CML cell lines. The cellular and molecular basis of this compound were elucidated using a comprehensive strategy based on quantitative proteomic and cell biology assays. We showed that 7KC induced cell death and overcomes drug resistance in CML through mechanisms that go beyond the classical MDR1 pathways.

Comparison of bull (Bos taurus) seminal plasma, seminal vesicles fluid and cauda epididymal fluid proteomes

Eggs of sterlet are discharged outside into ambient aquatic environment where egg activation and fertilization occur. Effects of different activation media including freshwater and clay suspension on protein abundances of egg were quantified in sterlet Acipenser ruthenus. In-gel digestion and high resolution mass spectrometry were used for label-free protein quantification in the eggs of five females. No significant (p > 0.05) difference was found between protein abundances in eggs activated with different media. However, results showed significant (p < 0.05, fold change ≥2) reduction in the abundances of nine proteins including six glycoproteins, enolase and heat shock protein in activated groups compared to freshly ovulated eggs as control. The fact that abundance of proteasome subunit alpha significantly reduced only in eggs which were activated by clay suspension suggests that activation medium can somehow intervene with protein regulation during fertilization. In conclusion, external fertilization in sturgeon egg is accompanied by huge release of proteins into the external environment that may participate in the construction of a transient microenvironment around egg for attraction and protection of spermatozoa to ensure ensuing fertilization. Data are available via ProteomeXchange with identifier PXD006232.

Optimizing the SWATH-MS-workflow for label-free proteomics

Quantification of proteins by mass spectrometry at the level of entire proteomes has become a central aspect in contemporary proteomics. Sequential Window Acquisition of all THeoretical fragment-ion spectra (SWATH) mass spectrometry is a label-free protein quantification method enabling parallel quantification of up to several thousand proteins, thereby granting a comprehensive overview of highly complex samples. We optimized several parameters of the mass spectrometrical detection to increase the size of the library, enhance the precision of protein quantifications and decrease systematic errors induced by fragment ion interference. By these means enhanced differential analyses facilitate the detection of more significantly regulated proteins with a dynamic range of over three orders of magnitude.

High-Throughput LC-MS/MS Proteomic Analysis of a Mouse Model of Mesiotemporal Lobe Epilepsy Predicts Microglial Activation Underlying Disease Development.

Uncovering the molecular mechanisms of mesiotemporal lobe epilepsy (MTLE) is critical to identify therapeutic targets. In this study, we performed global protein expression analysis of a kainic acid (KA) MTLE mouse model at various time-points (1, 3, and 30 days post-KA injection -dpi), representing specific stages of the syndrome. High-resolution liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS), in combination with label-free protein quantification using three processing approaches for quantification, was applied. Following comparison of KA versus NaCl-injected mice, 22, 53, and 175 proteins were differentially (statistically significant) expressed at 1, 3 and 30dpi, respectively, according to all three quantification approaches. Selected findings were confirmed by multiple reaction monitoring LC-MS/MS. As a positive control, the astrocyte marker GFAP was found to be upregulated (3dpi: 1.9 fold; 30dpi: 12.5 fold), also verified by IHC. The results collectively suggest that impairment in synaptic transmission occurs even right after initial status epilepticus (1dpi), with neurodegeneration becoming more extensive during epileptogenesis (3dpi) and sustained at the chronic phase (30dpi), where also extensive glial- and astrocyte-mediated inflammation is evident. This molecular profile is in line with observed phenotypic changes in human MTLE, providing the basis for future studies on new molecular targets for the disease.

Ion mobility-enhanced MSE-based label-free analysis reveals effects of low-dose radiation post contextual fear conditioning training on the mouse hippocampal proteome

Recent advances in the field of biodosimetry have shown that the response of biological systems to ionizing radiation is complex and depends on the type and dose of radiation, the tissue(s) exposed, and the time lapsed after exposure. The biological effects of low dose radiation on learning and memory are not well understood. An ion mobility-enhanced data-independent acquisition (MSE) approach in conjunction with the ISOQuant software tool was utilized for label-free quantification of hippocampal proteins with the goal of determining protein alteration associated with low-dose whole body ionizing radiation (X-rays, 1Gy) of 5.5-month-old male C57BL/6J mice post contextual fear conditioning training. Global proteome analysis revealed deregulation of 73 proteins (out of 399 proteins). Deregulated proteins indicated adverse effects of irradiation on myelination and perturbation of energy metabolism pathways involving a shift from the TCA cycle to glutamate oxidation. Our findings also indicate that proteins associated with synaptic activity, including vesicle recycling and neurotransmission, were altered in the irradiated mice. The elevated LTP and decreased LTD suggest improved synaptic transmission and enhanced efficiency of neurotransmitter release which would be consistent with the observed comparable contextual fear memory performance of the mice following post-training whole body or sham-irradiation. SignificanceThis study is significant because the biological consequences of low dose radiation on learning and memory are complex and not yet well understood. We conducted a IMS-enhanced MSE-based label-free quantitative proteomic analysis of hippocampal tissue with the goal of determining protein alteration associated with low-dose whole body ionizing radiation (X-ray, 1Gy) of 5.5-month-old male C57BL/6J mice post contextual fear conditioning training. The IMS-enhanced MSE approach in conjunction with ISOQuant software was robust and accurate with low median CV values of 0.99% for the technical replicates of samples from both the sham and irradiated group. The biological variance was as low as 1.61% for the sham group and 1.31% for the irradiated group. The applied data generation and processing workflow allowed the quantitative evaluation of 399 proteins.The current proteomic analysis indicates that myelination is sensitive to low dose radiation. The observed protein level changes imply modulation of energy metabolism pathways in the radiation exposed group, specifically changes in protein abundance levels suggest a shift from TCA cycle to glutamate oxidation to satisfy energy demands. Most significantly, our study reveals deregulation of proteins involved in processes that govern synaptic activity including enhanced synaptic vesicle cycling, and altered long-term potentiation (LTP) and depression (LTD). An elevated LTP and decreased LTD suggest improved synaptic transmission and enhanced efficiency of neurotransmitter release which is consistent with the observed comparable contextual fear memory performance of the mice following post-training whole body or sham-irradiation. Overall, our results underscore the importance of low dose radiation experiments for illuminating the sensitivity of biochemical pathways to radiation, and the modulation of potential repair and compensatory response mechanisms. This kind of studies and associated findings may ultimately lead to the design of strategies for ameliorating hippocampal and CNS injury following radiation exposure as part of medical therapies or as a consequence of occupational hazards.

LASIK surgery of granular corneal dystrophy type 2 patients leads to accumulation and differential proteolytic processing of transforming growth factor beta-induced protein (TGFBIp).

More than 60 mutations in transforming growth factor beta-induced protein (TGFBIp) have been reported in humans causing a variety of phenotypic protein aggregates in the cornea, commonly termed corneal dystrophies. One mutation, generating an arginine to histidine amino acid substitution at position 124 in mature TGFBIp leads to granular corneal dystrophy type 2 (GCD2). Homozygous GCD2 cases develop massive protein accumulation early in life whereas heterozygous GCD2 cases become affected much later and generally with a much less severe outcome. However, if heterozygous GCD2 patients undergo laser-assisted in situ keratomileusis (LASIK) surgery protein accumulation is accelerated and they develop massive protein accumulations a few years after surgery. Here, we present the protein profile of aggregate-containing corneal tissue from GCD2 patients with a history of LASIK surgery using LC-MS/MS. Label-free quantification of corneal extracellular matrix proteins showed accumulation of TGFBIp. This was supported by 2DE and immunoblotting against TGFBIp that revealed the accumulation of full-length TGFBIp. In addition, a high molecular weight TGFBIp complex was more apparent in GCD2 patients after LASIK surgery, which may be important for the disease progression. Lastly, 2DE also revealed differential processing between GCD2 patients with a history of LASIK surgery when compared to healthy individuals.

Label-Free Identification and Quantification of SUMO Target Proteins.

Mass spectrometry-based approaches are utilized with increasing frequency to facilitate identification of novel SUMO target proteins and to elucidate the dynamics of SUMOylation in response to cellular stresses. Here, we describe a robust method for the identification of SUMO target proteins, and the relative quantification of SUMOylation dynamics, using a label-free approach. The method relies on a decahistidine (His10)-tagged SUMO, which is expressed at a low level in a mammalian cell line or model organism. The His10-tag allows for a single-step, high-yield, and high-purity enrichment of SUMOylated proteins, which are then digested and analyzed by high-resolution mass spectrometry. Matching between runs and label-free quantification integrated in the freely available MaxQuant software allow for a high rate and accuracy of quantification, providing a strong alternative to laborious sample or cell labeling techniques. The method described here allows for identification of >1000 SUMO target proteins, and characterization of their SUMOylation dynamics, without requiring sample fractionation. The purification procedure, starting from total lysate, can be performed in ~4 days.

Metabolic and molecular regulation of dietary polyunsaturated fatty acids on prostate cancer.

The aim of this study is to investigate the role of n-3 and n-9 fatty acids in crucial processes involved in prostate cancer cell growth through a large-scale proteomic analysis. We used a label-free protein quantification method to profile global protein expression of fish oil and oleic acid treated PCa cells and validated a panel of differentially expressed proteins by either Western blot or multiple reaction monitoring. Bioinformatic analysis was also performed to uncover the pathways involved in fatty acid metabolism. Fish oil, not oleic acid, suppresses prostate cancer cell viability. Assessment of fatty acid synthesis pathway activity also shows that oleic acid is a more potent inhibitor than fish oil on de novo fatty acid synthesis. Although fatty acid synthase activity decreases with fish oil treatment, the inhibition of its activity occurs over time while reduction in viability occurs within 24 h. Bioinformatic analysis revealed the pathways altered by these fatty acid treatments. This study suggests that suppression of cell viability by fish oil is independent of fatty acid synthase and fish oil regulates prostate cancer cells through activation of other pathways depending upon length of exposure to fish oil.

Insights into immune responses in oral cancer through proteomic analysis of saliva and salivary extracellular vesicles.

The development and progression of oral cavity squamous cell carcinoma (OSCC) involves complex cellular mechanisms that contribute to the low five-year survival rate of approximately 20% among diagnosed patients. However, the biological processes essential to tumor progression are not completely understood. Therefore, detecting alterations in the salivary proteome may assist in elucidating the cellular mechanisms modulated in OSCC and improve the clinical prognosis of the disease. The proteome of whole saliva and salivary extracellular vesicles (EVs) from patients with OSCC and healthy individuals were analyzed by LC-MS/MS and label-free protein quantification. Proteome data analysis was performed using statistical, machine learning and feature selection methods with additional functional annotation. Biological processes related to immune responses, peptidase inhibitor activity, iron coordination and protease binding were overrepresented in the group of differentially expressed proteins. Proteins related to the inflammatory system, transport of metals and cellular growth and proliferation were identified in the proteome of salivary EVs. The proteomics data were robust and could classify OSCC with 90% accuracy. The saliva proteome analysis revealed that immune processes are related to the presence of OSCC and indicate that proteomics data can contribute to determining OSCC prognosis.