Automated Liquid Handling Extraction and Rapid Quantification of Underivatized Amino Acids and Tryptophan Metabolites from Human Serum and Plasma Using Dual-Column U(H)PLC-MRM-MS and Its Application to Prostate Cancer Study.

Amino acids (AAs) and their metabolites are important building blocks, energy sources, and signaling molecules associated with various pathological phenotypes. The quantification of AA and tryptophan (TRP) metabolites in human serum and plasma is therefore of great diagnostic interest. Therefore, robust, reproducible sample extraction and processing workflows as well as rapid, sensitive absolute quantification are required to identify candidate biomarkers and to improve screening methods. We developed a validated semi-automated robotic liquid extraction and processing workflow and a rapid method for absolute quantification of 20 free, underivatized AAs and six TRP metabolites using dual-column U(H)PLC-MRM-MS. The extraction and sample preparation workflow in a 96-well plate was optimized for robust, reproducible high sample throughput allowing for transfer of samples to the U(H)PLC autosampler directly without additional cleanup steps. The U(H)PLC-MRM-MS method, using a mixed-mode reversed-phase anion exchange column with formic acid and a high-strength silica reversed-phase column with difluoro-acetic acid as mobile phase additive, provided absolute quantification with nanomolar lower limits of quantification within 7.9 min. The semi-automated extraction workflow and dual-column U(H)PLC-MRM-MS method was applied to a human prostate cancer study and was shown to discriminate between treatment regimens and to identify metabolites responsible for discriminating between healthy controls and patients on active surveillance.

Multiomic profiling of medulloblastoma reveals subtype-specific targetable alterations at the proteome and N-glycan level.

Medulloblastomas (MBs) are malignant pediatric brain tumors that are molecularly and clinically heterogenous. The application of omics technologies-mainly studying nucleic acids-has significantly improved MB classification and stratification, but treatment options are still unsatisfactory. The proteome and their N-glycans hold the potential to discover clinically relevant phenotypes and targetable pathways. We compile a harmonized proteome dataset of 167 MBs and integrate findings with DNA methylome, transcriptome and N-glycome data. We show six proteome MB subtypes, that can be assigned to two main molecular programs: transcription/translation (pSHHt, pWNT and pG3myc), and synapses/immunological processes (pSHHs, pG3 and pG4). Multiomic analysis reveals different conservation levels of proteome features across MB subtypes at the DNA methylome level. Aggressive pGroup3myc MBs and favorable pWNT MBs are most similar in cluster hierarchies concerning overall proteome patterns but show different protein abundances of the vincristine resistance-associated multiprotein complex TriC/CCT and of N-glycan turnover-associated factors. The N-glycome reflects proteome subtypes and complex-bisecting N-glycans characterize pGroup3myc tumors. Our results shed light on targetable alterations in MB and set a foundation for potential immunotherapies targeting glycan structures.

Integrative metabolomics-genomics analysis identifies key networks in a stem cell-based model of schizophrenia.

Schizophrenia (SCZ) is a neuropsychiatric disorder, caused by a combination of genetic and environmental factors. The etiology behind the disorder remains elusive although it is hypothesized to be associated with the aberrant response to neurotransmitters, such as dopamine and glutamate. Therefore, investigating the link between dysregulated metabolites and distorted neurodevelopment holds promise to offer valuable insights into the underlying mechanism of this complex disorder. In this study, we aimed to explore a presumed correlation between the transcriptome and the metabolome in a SCZ model based on patient-derived induced pluripotent stem cells (iPSCs). For this, iPSCs were differentiated towards cortical neurons and samples were collected longitudinally at various developmental stages, reflecting neuroepithelial-like cells, radial glia, young and mature neurons. The samples were analyzed by both RNA-sequencing and targeted metabolomics and the two modalities were used to construct integrative networks in silico. This multi-omics analysis revealed significant perturbations in the polyamine and gamma-aminobutyric acid (GABA) biosynthetic pathways during rosette maturation in SCZ lines. We particularly observed the downregulation of the glutamate decarboxylase encoding genes GAD1 and GAD2, as well as their protein product GAD65/67 and their biochemical product GABA in SCZ samples. Inhibition of ornithine decarboxylase resulted in further decrease of GABA levels suggesting a compensatory activation of the ornithine/putrescine pathway as an alternative route for GABA production. These findings indicate an imbalance of cortical excitatory/inhibitory dynamics occurring during early neurodevelopmental stages in SCZ. Our study supports the hypothesis of disruption of inhibitory circuits to be causative for SCZ and establishes a novel in silico approach that enables for integrative correlation of metabolic and transcriptomic data of psychiatric disease models.

Effects of lysine deacetylase inhibitor treatment on LPS responses of alveolar-like macrophages.

Macrophages are key immune cells that can adapt their metabolic phenotype in response to different stimuli. Lysine deacetylases are important enzymes regulating inflammatory gene expression and lysine deacetylase inhibitors have been shown to exert anti-inflammatory effects in models of chronic obstructive pulmonary disease. We hypothesized that these anti-inflammatory effects may be associated with metabolic changes in macrophages. To validate this hypothesis, we used an unbiased and a targeted proteomic approach to investigate metabolic enzymes, as well as liquid chromatography-mass spectrometry and gas chromatography-mass spectrometry, to quantify metabolites in combination with the measurement of functional parameters in primary murine alveolar-like macrophages after lipopolysaccharide-induced activation in the presence or absence of lysine deacetylase inhibition. We found that lysine deacetylase inhibition resulted in reduced production of inflammatory mediators such as tumor necrosis factor α and interleukin 1ß. However, only minor changes in macrophage metabolism were observed, as only one of the lysine deacetylase inhibitors slightly increased mitochondrial respiration while no changes in metabolite levels were seen. However, lysine deacetylase inhibition specifically enhanced expression of proteins involved in ubiquitination, which may be a driver of the anti-inflammatory effects of lysine deacetylase inhibitors. Our data illustrate that a multiomics approach provides novel insights into how macrophages interact with cues from their environment. More detailed studies investigating ubiquitination as a potential driver of lysine deacetylase inhibition will help developing novel anti-inflammatory drugs for difficult-to-treat diseases such as chronic obstructive pulmonary disease.

Collagen type I alters the proteomic signature of macrophages in a collagen morphology-dependent manner.

Idiopathic pulmonary fibrosis is a progressive lung disease that causes scarring and loss of lung function. Macrophages play a key role in fibrosis, but their responses to altered morphological and mechanical properties of the extracellular matrix in fibrosis is relatively unexplored. Our previous work showed functional changes in murine fetal liver-derived alveolar macrophages on fibrous or globular collagen morphologies. In this study, we applied differential proteomics to further investigate molecular mechanisms underlying the observed functional changes. Macrophages cultured on uncoated, fibrous, or globular collagen-coated plastic were analyzed by liquid chromatography-mass spectrometry. The presence of collagen affected expression of 77 proteins, while 142 were differentially expressed between macrophages grown on fibrous or globular collagen. Biological process and pathway enrichment analysis revealed that culturing on any type of collagen induced higher expression of enzymes involved in glycolysis. However, this did not lead to a higher rate of glycolysis, probably because of a concomitant decrease in activity of these enzymes. Our data suggest that macrophages sense collagen morphologies and can respond with changes in expression and activity of metabolism-related proteins. These findings suggest intimate interactions between macrophages and their surroundings that may be important in repair or fibrosis of lung tissue.

Detection and Isolation of Circulating Tumor Cells from Breast Cancer Patients Using CUB Domain-Containing Protein 1.

In cancer metastasis, single circulating tumor cells (CTCs) in the blood and disseminated tumor cells (DTCs) in the bone marrow mediate cancer metastasis. Because suitable biomarker proteins are lacking, CTCs and DTCs with mesenchymal attributes are difficult to isolate from the bulk of normal blood cells. To establish a procedure allowing the isolation of such cells, we analyzed the cell line BC-M1 established from DTCs in the bone marrow of a breast cancer patient by stable isotope labeling by amino acids in cell culture (SILAC) and mass spectrometry. We found high levels of the transmembrane protein CUB domain-containing protein 1 (CDCP1) in breast cancer cell lines with mesenchymal attributes. Peripheral blood mononuclear cells were virtually negative for CDCP1. Confirmation in vivo by CellSearch revealed CDCP1-positive CTCs in 8 of 30 analyzed breast cancer patients. Only EpCam-positive CTCs were enriched by CellSearch. Using the extracellular domain of CDCP1, we established a magnetic-activated cell sorting (MACS) approach enabling also the enrichment of EpCam-negative CTCs. Thus, our approach is particularly suited for the isolation of mesenchymal CTCs with downregulated epithelial cancer that occur, for example, in triple-negative breast cancer patients who are prone to therapy failure.

Proteome Coverage after Simultaneous Proteo-Metabolome Liquid-Liquid Extraction.

Proteomics and metabolomics are essential in systems biology, and simultaneous proteo-metabolome liquid-liquid extraction (SPM-LLE) allows isolation of the metabolome and proteome from the same sample. Since the proteome is present as a pellet in SPM-LLE, it must be solubilized for quantitative proteomics. Solubilization and proteome extraction are critical factors in the information obtained at the proteome level. In this study, we investigated the performance of two surfactants (sodium deoxycholate (SDC), sodium dodecyl sulfate (SDS)) and urea in terms of proteome coverage and extraction efficiency of an interphase proteome pellet generated by methanol-chloroform based SPM-LLE. We also investigated how the performance differs when the proteome is extracted from the interphase pellet or by direct cell lysis. We quantified 12 lipids covering triglycerides and various phospholipid classes, and 25 polar metabolites covering central energy metabolism in chloroform and methanol extracts. Our study reveals that the proteome coverages between the two surfactants and urea for the SPM-LLE interphase pellet were similar, but the extraction efficiencies differed significantly. While SDS led to enrichment of basic proteins, which were mainly ribosomal and ribonuclear proteins, urea was the most efficient extraction agent for simultaneous proteo-metabolome analysis. The results of our study also show that the performance of surfactants for quantitative proteomics is better when the proteome is extracted through direct cell lysis rather than an interphase pellet. In contrast, the performance of urea for quantitative proteomics was significantly better when the proteome was extracted from an interphase pellet than by direct cell lysis. We demonstrated that urea is superior to surfactants for proteome extraction from SPM-LLE interphase pellets, with a particularly good performance for the extraction of proteins associated with metabolic pathways. Data are available via ProteomeXchange with identifier PXD027338.

Characterization of RARRES1 Expression on Circulating Tumor Cells as Unfavorable Prognostic Marker in Resected Pancreatic Ductal Adenocarcinoma Patients.

BACKGROUND: In pancreatic ductal adenocarcinoma (PDAC), the characterization of circulating tumor cells (CTCs) opens new insights into cancer metastasis as the leading cause of cancer-related death. Here, we focused on the expression of retinoic acid receptor responder 1 (RARRES1) on CTCs as a novel marker for treatment failure and early relapse. METHODS: The stable isotope labeling of amino acids in cell culture (SILAC)-approach was applied for identifying and quantifying new biomarker proteins in PDAC cell lines HPDE and its chemoresistant counterpart, L3.6pl-Res. Fifty-five baseline and 36 follow-up (FUP) peripheral blood samples were processed via a marker-independent microfluidic-based CTC detection approach using RARRES1 as an additional marker. RESULTS: SILAC-based proteomics identified RARRES1 as an abundantly expressed protein in more aggressive chemoresistant PDAC cells. At baseline, CTCs were detected in 25.5% of all PDAC patients, while FUP analysis (median: 11 months FUP) showed CTC detection in 45.5% of the resected patients. CTC positivity (≥3 CTC) at FUP was significantly associated with short recurrence-free survival (p = 0.002). Furthermore, detection of RARRES1 positive CTCs was indicative of an even earlier relapse after surgery (p = 0.001). CONCLUSIONS: CTC detection in resected PDAC patients during FUP is associated with a worse prognosis, and RARRES1 expression might identify an aggressive subtype of CTCs that deserves further investigation.

Comparative Assessment of Quantification Methods for Tumor Tissue Phosphoproteomics.

With increasing sensitivity and accuracy in mass spectrometry, the tumor phosphoproteome is getting into reach. However, the selection of quantitation techniques best-suited to the biomedical question and diagnostic requirements remains a trial and error decision as no study has directly compared their performance for tumor tissue phosphoproteomics. We compared label-free quantification (LFQ), spike-in-SILAC (stable isotope labeling by amino acids in cell culture), and tandem mass tag (TMT) isobaric tandem mass tags technology for quantitative phosphosite profiling in tumor tissue. Compared to the classic SILAC method, spike-in-SILAC is not limited to cell culture analysis, making it suitable for quantitative analysis of tumor tissue samples. TMT offered the lowest accuracy and the highest precision and robustness toward different phosphosite abundances and matrices. Spike-in-SILAC offered the best compromise between these features but suffered from a low phosphosite coverage. LFQ offered the lowest precision but the highest number of identifications. Both spike-in-SILAC and LFQ presented susceptibility to matrix effects. Match between run (MBR)-based analysis enhanced the phosphosite coverage across technical replicates in LFQ and spike-in-SILAC but further reduced the precision and robustness of quantification. The choice of quantitative methodology is critical for both study design such as sample size in sample groups and quantified phosphosites and comparison of published cancer phosphoproteomes. Using ovarian cancer tissue as an example, our study builds a resource for the design and analysis of quantitative phosphoproteomic studies in cancer research and diagnostics.

3D-Printed High-Pressure-Resistant Immobilized Enzyme Microreactor (µIMER) for Protein Analysis.

Additive manufacturing (3D printing) has greatly revolutionized the way researchers approach certain technical challenges. Despite its outstanding print quality and resolution, stereolithography (SLA) printing is cost-effective and relatively accessible. However, applications involving mass spectrometry (MS) are few due to residual oligomers and additives leaching from SLA-printed devices that interfere with MS analyses. We identified the crosslinking agent urethane dimethacrylate as the main contaminant derived from SLA prints. A stringent washing and post-curing protocol mitigated sample contamination and rendered SLA prints suitable for MS hyphenation. Thereafter, SLA printing was used to produce 360 µm I.D. microcolumn chips with excellent structural properties. By packing the column with polystyrene microspheres and covalently immobilizing pepsin, an exceptionally effective microscale immobilized enzyme reactor (µIMER) was created. Implemented in an online liquid chromatography-MS/MS setup, the protease microcolumn enabled reproducible protein digestion and peptide mapping with 100% sequence coverage obtained for three different recombinant proteins. Additionally, when assessing the µIMER digestion efficiency for complex proteome samples, it delivered a 144-fold faster and significantly more efficient protein digestion compared to 24 h for bulk digestion. The 3D-printed µIMER withstands remarkably high pressures above 130 bar and retains its activity for several weeks. This versatile platform will enable researchers to produce tailored polymer-based enzyme reactors for various applications in analytical chemistry and beyond.

PI(18:1/18:1) is a SCD1-derived lipokine that limits stress signaling.

Cytotoxic stress activates stress-activated kinases, initiates adaptive mechanisms, including the unfolded protein response (UPR) and autophagy, and induces programmed cell death. Fatty acid unsaturation, controlled by stearoyl-CoA desaturase (SCD)1, prevents cytotoxic stress but the mechanisms are diffuse. Here, we show that 1,2-dioleoyl-sn-glycero-3-phospho-(1'-myo-inositol) [PI(18:1/18:1)] is a SCD1-derived signaling lipid, which inhibits p38 mitogen-activated protein kinase activation, counteracts UPR, endoplasmic reticulum-associated protein degradation, and apoptosis, regulates autophagy, and maintains cell morphology and proliferation. SCD1 expression and the cellular PI(18:1/18:1) proportion decrease during the onset of cell death, thereby repressing protein phosphatase 2 A and enhancing stress signaling. This counter-regulation applies to mechanistically diverse death-inducing conditions and is found in multiple human and mouse cell lines and tissues of Scd1-defective mice. PI(18:1/18:1) ratios reflect stress tolerance in tumorigenesis, chemoresistance, infection, high-fat diet, and immune aging. Together, PI(18:1/18:1) is a lipokine that links fatty acid unsaturation with stress responses, and its depletion evokes stress signaling.

Protein speciation is likely to increase the chance of proteins to be determined in 2-DE/MS.

Multiple spotting due to protein speciation might increase a protein's chance of being captured in a random selection of 2-DE spots. We tested this expectation in new (PXD015649) and previously published 2-DE/MS data of porcine and human tissues. For comparison, we included bottom-up proteomics studies (BU-LC/MS) of corresponding biological materials. Analyses of altogether ten datasets proposed that amino acid modification fosters multispotting in 2-DE. Thus, the number of 2-DE spots containing a particular protein more tightly associated with a peptide diversity measure accounting for amino acid modification than with an alternative one disregarding it. Furthermore, every 11th amino acid was a post-translational modification candidate site in 2-DE/MS proteins, whereas in BU-LC/MS proteins this was merely the case in every 21st amino acid. Alternative splicing might contribute to multispotting, since genes encoding 2-DE/MS proteins were found to have on average about 0.3 more transcript variants than their counterparts from BU-LC/MS studies. Correspondingly, resolution completeness as estimated from the representation of transcript variant-rich genes was higher in 2-DE/MS than BU-LC/MS datasets. These findings suggest that the ability to resolve proteomes down to protein species can lead to enrichment of multispotting proteins in 2-DE/MS. Low sensitivity of stains and MS instruments appears to enhance this effect.

Plasma sRAGE levels strongly associate with centrilobular emphysema assessed by HRCT scans.

BACKGROUND: There is a strong need for biomarkers to better characterize individuals with COPD and to take into account the heterogeneity of COPD. The blood protein sRAGE has been put forward as promising biomarker for COPD in general and emphysema in particular. Here, we measured plasma sRAGE levels using quantitative LC-MS and assessed whether the plasma sRAGE levels associate with (changes in) lung function, radiological emphysema parameters, and radiological subtypes of emphysema. METHODS: Three hundred and twenty-four COPD patients (mean FEV1: 63%predicted) and 185 healthy controls from the COPDGene study were selected. Plasma sRAGE was measured by immunoprecipitation in 96-well plate methodology to enrich sRAGE, followed by targeted quantitative liquid chromatography-mass spectrometry. Spirometry and HRCT scans (inspiration and expiration) with a 5-year follow-up were used; both subjected to high quality control standards. RESULTS: Lower sRAGE values significantly associated with the presence of COPD, the severity of airflow obstruction, the severity of emphysema on HRCT, the heterogeneous distribution of emphysema, centrilobular emphysema, and 5-year progression of emphysema. However, sRAGE values did not associate with airway wall thickness or paraseptal emphysema. CONCLUSIONS: Rather than being a general COPD biomarker, sRAGE is especially a promising biomarker for centrilobular emphysema. Follow-up studies should elucidate whether sRAGE can be used as a biomarker for other COPD phenotypes as well.

Circulating Cellular Communication Network Factor 1 Protein as a Sensitive Liquid Biopsy Marker for Early Detection of Breast Cancer.

BACKGROUND: Despite recent progress in liquid biopsy technologies, early blood-based detection of breast cancer is still a challenge. METHODS: We analyzed secretion of the protein cellular communication network factor 1 (CCN1, formerly cysteine-rich angiogenic inducer 61) in breast cancer cell lines by an enzyme-linked immunosorbent assay (ELISA). Soluble CCN1 in the plasma (2.5 µL) of 544 patients with breast cancer and 427 healthy controls was analyzed by ELISA. The breast cancer samples were acquired at the time of primary diagnosis prior to neoadjuvant therapy or surgery. A classifier was established on a training cohort of patients with breast cancer and age-adapted healthy controls and further validated on an independent cohort comprising breast cancer patients and healthy controls. Samples from patients with benign breast diseases were investigated as additional controls. Samples from patients with acute heart diseases (n = 127) were investigated as noncancer controls. The diagnostic accuracy was determined by receiver operating characteristic using the parameters area under the curve, sensitivity, and specificity. RESULTS: CCN1 was frequently secreted by breast cancer cell lines into the extracellular space. Subsequent analysis of clinical blood samples from patients with breast cancer and age-adjusted healthy controls revealed an overall specificity of 99.0% and sensitivity of 80.0% for cancer detection. Remarkably, 81.5% of small T1 cancers were already CCN1-positive, while CCN1 concentrations in patients with benign breast lesions were below the threshold for breast cancer detection. CONCLUSIONS: Circulating CCN1 is a potentially novel blood biomarker for the detection of breast cancer at the earliest invasive stage.

Meta-Inflammation and Metabolic Reprogramming of Macrophages in Diabetes and Obesity: The Importance of Metabolites.

Diabetes mellitus type II and obesity are two important causes of death in modern society. They are characterized by low-grade chronic inflammation and metabolic dysfunction (meta-inflammation), which is observed in all tissues involved in energy homeostasis. A substantial body of evidence has established an important role for macrophages in these tissues during the development of diabetes mellitus type II and obesity. Macrophages can activate into specialized subsets by cues from their microenvironment to handle a variety of tasks. Many different subsets have been described and in diabetes/obesity literature two main classifications are widely used that are also defined by differential metabolic reprogramming taking place to fuel their main functions. Classically activated, pro-inflammatory macrophages (often referred to as M1) favor glycolysis, produce lactate instead of metabolizing pyruvate to acetyl-CoA, and have a tricarboxylic acid cycle that is interrupted at two points. Alternatively activated macrophages (often referred to as M2) mainly use beta-oxidation of fatty acids and oxidative phosphorylation to create energy-rich molecules such as ATP and are involved in tissue repair and downregulation of inflammation. Since diabetes type II and obesity are characterized by metabolic alterations at the organism level, these alterations may also induce changes in macrophage metabolism resulting in unique macrophage activation patterns in diabetes and obesity. This review describes the interactions between metabolic reprogramming of macrophages and conditions of metabolic dysfunction like diabetes and obesity. We also focus on different possibilities of measuring a range of metabolites intra-and extracellularly in a precise and comprehensive manner to better identify the subsets of polarized macrophages that are unique to diabetes and obesity. Advantages and disadvantages of the currently most widely used metabolite analysis approaches are highlighted. We further describe how their combined use may serve to provide a comprehensive overview of the metabolic changes that take place intracellularly during macrophage activation in conditions like diabetes and obesity.

Adsorptive Microtiter Plates As Solid Supports in Affinity Purification Workflows.

Affinity ligands such as antibodies are widely used in (bio)medical research for purifying proteins from complex biological samples. These ligands are generally immobilized onto solid supports which facilitate the separation of a captured protein from the sample matrix. Adsorptive microtiter plates are commonly used as solid supports prior to immunochemical detection (e.g., immunoassays) but hardly ever prior to liquid chromatography-mass spectrometry (LC-MS-)-based detection. Here, we describe the use of adsorptive microtiter plates for protein enrichment prior to LC-MS detection, and we discuss opportunities and challenges of corresponding workflows, based on examples of targeted (i.e., soluble receptor for advanced glycation end-products (sRAGE) in human serum) and discovery-based workflows (i.e., transcription factor p65 (NF-κB) in lysed murine RAW 264.7 macrophages and peptidyl-prolyl cis-trans isomerase FKBP5 (FKBP5) in lysed human A549 alveolar basal epithelial cells). Thereby, we aim to highlight the potential usefulness of adsorptive microtiter plates in affinity purification workflows prior to LC-MS detection, which could increase their usage in mass spectrometry-based protein research.

The SZT2 Interactome Unravels New Functions of the KICSTOR Complex.

Seizure threshold 2 (SZT2) is a component of the KICSTOR complex which, under catabolic conditions, functions as a negative regulator in the amino acid-sensing branch of mTORC1. Mutations in this gene cause a severe neurodevelopmental and epileptic encephalopathy whose main symptoms include epilepsy, intellectual disability, and macrocephaly. As SZT2 remains one of the least characterized regulators of mTORC1, in this work we performed a systematic interactome analysis under catabolic and anabolic conditions. Besides numerous mTORC1 and AMPK signaling components, we identified clusters of proteins related to autophagy, ciliogenesis regulation, neurogenesis, and neurodegenerative processes. Moreover, analysis of SZT2 ablated cells revealed increased mTORC1 signaling activation that could be reversed by Rapamycin or Torin treatments. Strikingly, SZT2 KO cells also exhibited higher levels of autophagic components, independent of the physiological conditions tested. These results are consistent with our interactome data, in which we detected an enriched pool of selective autophagy receptors/regulators. Moreover, preliminary analyses indicated that SZT2 alters ciliogenesis. Overall, the data presented form the basis to comprehensively investigate the physiological functions of SZT2 that could explain major molecular events in the pathophysiology of developmental and epileptic encephalopathy in patients with SZT2 mutations.

Natural isotope correction improves analysis of protein modification dynamics.

Stable isotope labelling in combination with high-resolution mass spectrometry approaches are increasingly used to analyze both metabolite and protein modification dynamics. To enable correct estimation of the resulting dynamics, it is critical to correct the measured values for naturally occurring stable isotopes, a process commonly called isotopologue correction or deconvolution. While the importance of isotopologue correction is well recognized in metabolomics, it has received far less attention in proteomics approaches. Although several tools exist that enable isotopologue correction of mass spectrometry data, the majority is tailored for the analysis of low molecular weight metabolites. We here present PICor which has been developed for isotopologue correction of complex isotope labelling experiments in proteomics or metabolomics and demonstrate the importance of appropriate correction for accurate determination of protein modifications dynamics, using histone acetylation as an example.

Combined Metabolic and Chemical (CoMetChem) Labeling Using Stable Isotopes-a Strategy to Reveal Site-Specific Histone Acetylation and Deacetylation Rates by LC-MS.

Histone acetylation is an important, reversible post-translational protein modification and a hallmark of epigenetic regulation. However, little is known about the dynamics of this process, due to the lack of analytical methods that can capture site-specific acetylation and deacetylation reactions. We present a new approach that combines metabolic and chemical labeling (CoMetChem) using uniformly 13C-labeled glucose and stable isotope-labeled acetic anhydride. Thereby, chemically equivalent, fully acetylated histone species are generated, enabling accurate relative quantification of site-specific lysine acetylation dynamics in tryptic peptides using high-resolution mass spectrometry. We show that CoMetChem enables site-specific quantification of the incorporation or loss of lysine acetylation over time, allowing the determination of reaction rates for acetylation and deacetylation. Thus, the CoMetChem methodology provides a comprehensive description of site-specific acetylation dynamics.

Truncated O-GalNAc glycans impact on fundamental signaling pathways in pancreatic cancer.

Truncated O-GalNAc glycosylation is an important feature of pancreatic ductal adenocarcinomas (PDAC) and expression of truncated O-GalNAc glycans is strongly associated with decreased survival and poor prognosis. It has been proven, that aberrant O-GalNAc glycosylation influence PDAC signaling to promote oncogenic properties, but elucidation of the influence of truncated O-GalNAc glycosylation on different signaling molecules has just been started. We herein elucidated the impact of aberrant O-GalNAc glycosylation on two important PDAC signaling pathways, namely AKT/mTOR and RAS/MAPK. In PDAC cells expressing truncated O-GalNAc glycans, we identified differentially expressed proteins associated with AKT/mTOR and RAS/MAPK pathways using quantitative proteomics. Since AKT, a key-signaling molecule in PDAC, was among the identified proteins, we analyzed AKT and found a strikingly enhanced S473 phosphorylation and identified a previously unknown O-GalNAc-modification. Consecutive analysis of COSMC knockdowns in PDAC revealed strong effects on AKT upstream and downstream effector molecules. Interestingly, truncated O-GalNAc glycans could facilitate an mTORC1 inhibitor resistance using AZD8055. In addition, as AKT/mTOR pathway has extensive cross talks with RAS/MAPK pathway we analyzed the pathways and found it negatively regulated. Finally, we found that the expression of epithelial-mesenchymal-transition markers, key features of aggressive PDACs cells, are enhanced and truncated O-GalNAc glycans enhance pancreatic cancer cell growth in a xenograft mouse model. Our study demonstrates that truncated O-GalNAc glycans have a strong impact on AKT/mTOR and RAS/MAPK signaling pathways, are modulated by EGF or IGF-1 signaling and should be considered for targeted therapy of these pathways in PDAC.