Tau PTM Profiles Identify Patient Heterogeneity and Stages of Alzheimer's Disease.

To elucidate the role of Tau isoforms and post-translational modification (PTM) stoichiometry in Alzheimer's disease (AD), we generated a high-resolution quantitative proteomics map of 95 PTMs on multiple isoforms of Tau isolated from postmortem human tissue from 49 AD and 42 control subjects. Although Tau PTM maps reveal heterogeneity across subjects, a subset of PTMs display high occupancy and frequency for AD, suggesting importance in disease. Unsupervised analyses indicate that PTMs occur in an ordered manner, leading to Tau aggregation. The processive addition and minimal set of PTMs associated with seeding activity was further defined by analysis of size-fractionated Tau. To summarize, features in the Tau protein critical for disease intervention at different stages of disease are identified, including enrichment of 0N and 4R isoforms, underrepresentation of the C terminus, an increase in negative charge in the proline-rich region (PRR), and a decrease in positive charge in the microtubule binding domain (MBD).

Composition and Regulation of the Cellular Repertoire of SCF Ubiquitin Ligases.

SCF (Skp1-Cullin-F-box) ubiquitin ligases comprise several dozen modular enzymes that have diverse roles in biological regulation. SCF enzymes share a common catalytic core containing Cul1⋅Rbx1, which is directed toward different substrates by a variable substrate receptor (SR) module comprising 1 of 69 F-box proteins bound to Skp1. Despite the broad cellular impact of SCF enzymes, important questions remain about the architecture and regulation of the SCF repertoire, including whether SRs compete for Cul1 and, if so, how this competition is managed. Here, we devise methods that preserve the in vivo assemblages of SCF complexes and apply quantitative mass spectrometry to perform a census of these complexes (the "SCFome") in various states. We show that Nedd8 conjugation and the SR exchange factor Cand1 have a profound effect on shaping the SCFome. Together, these factors enable rapid remodeling of SCF complexes to promote biased assembly of SR modules bound to substrate.

A Targeted LC-MRM3 Proteomic Approach for the Diagnosis of SARS-CoV-2 Infection in Nasopharyngeal Swabs.

Since its first appearance, severe acute respiratory syndrome coronavirus 2 quickly spread around the world and the lack of adequate PCR testing capacities, especially during the early pandemic, led the scientific community to explore new approaches such as mass spectrometry (MS). We developed a proteomics workflow to target several tryptic peptides of the nucleocapsid protein. A highly selective multiple reaction monitoring-cubed (MRM3) strategy provided a sensitivity increase in comparison to conventional MRM acquisition. Our MRM3 approach was first tested on an Amsterdam public health cohort (alpha-variant, 760 participants) detecting viral nucleocapsid protein peptides from nasopharyngeal swabs samples presenting a cycle threshold value down to 35 with sensitivity and specificity of 94.2% and 100.0%, without immunopurification. A second iteration of the MS-diagnostic test, able to analyze more than 400 samples per day, was clinically validated on a Leiden-Rijswijk public health cohort (delta-variant, 2536 participants) achieving 99.9% specificity and 93.1% sensitivity for patients with cycle threshold values up to 35. In this manuscript, we also developed and brought the first proof of the concept of viral variant monitoring in a complex matrix using targeted MS.

MRMPro: a web-based tool to improve the speed of manual calibration for multiple reaction monitoring data analysis by mass spectrometry.

BACKGROUND: As a gold-standard quantitative technique based on mass spectrometry, multiple reaction monitoring (MRM) has been widely used in proteomics and metabolomics. In the analysis of MRM data, as no peak picking algorithm can achieve perfect accuracy, manual inspection is necessary to correct the errors. In large cohort analysis scenarios, the time required for manual inspection is often considerable. Apart from the commercial software that comes with mass spectrometers, the open-source and free software Skyline is the most popular software for quantitative omics. However, this software is not optimized for manual inspection of hundreds of samples, the interactive experience also needs to be improved. RESULTS: Here we introduce MRMPro, a web-based MRM data analysis platform for efficient manual inspection. MRMPro supports data analysis of MRM and schedule MRM data acquired by mass spectrometers of mainstream vendors. With the goal of improving the speed of manual inspection, we implemented a collaborative review system based on cloud architecture, allowing multiple users to review through browsers. To reduce bandwidth usage and improve data retrieval speed, we proposed a MRM data compression algorithm, which reduced data volume by more than 60% and 80% respectively compared to vendor and mzML format. To improve the efficiency of manual inspection, we proposed a retention time drift estimation algorithm based on similarity of chromatograms. The estimated retention time drifts were then used for peak alignment and automatic EIC grouping. Compared with Skyline, MRMPro has higher quantification accuracy and better manual inspection support. CONCLUSIONS: In this study, we proposed MRMPro to improve the usability of manual calibration for MRM data analysis. MRMPro is free for non-commercial use. Researchers can access MRMPro through http://mrmpro.csibio.com/ . All major mass spectrometry formats (wiff, raw, mzML, etc.) can be analyzed on the platform. The final identification results can be exported to a common.xlsx format for subsequent analysis.

A Simplified Proteomics LC-MRM-MS Assay for Determination of apoE Genotypes in Plasma Samples.

Apolipoprotein E (apoE), a polymorphic plasma protein, plays a pivotal role in lipid transportation. The human apoE gene possesses three major alleles (ε2, ε3, and ε4), which differ by single amino acid (cysteine to arginine) substitutions. The ε4 allele represents the primary genetic risk factor for Alzheimer's disease (AD), whereas the ε2 allele protects against the disease. Knowledge of a patient's apoE genotype has high diagnostic value. A recent study has introduced an LC-MRM-MS-based proteomic approach for apoE isoform genotyping using stable isotope-labeled peptide internal standards (SIS). Here, our goal was to develop a simplified LC-MRM-MS assay for identifying apoE genotypes in plasma samples, eliminating the need for the use of SIS peptides. To determine the apoE genotypes, we monitored the chromatographic peak area ratios of isoform-specific peptides relative to a peptide that is common to all apoE isoforms. The assay results correlated well with the standard TaqMan allelic discrimination assay, and we observed a concordance between the two methods for all but three out of 172 samples. DNA sequencing of these three samples has confirmed that the results of the LC-MRM-MS method were correct. Thus, our simplified UPLC-MRM-MS assay is a feasible and reliable method for identifying apoE genotypes without using SIS internal standard peptides. The approach can be seamlessly incorporated into existing quantitative proteomics assays and kits, providing additional valuable apoE genotype information. The principle of using signal ratios of the protein isoform-specific peptides to the peptide common for all of the protein isoforms has the potential to be used for protein isoform determination in general.

Evaluation of a Nondepleted Plasma Multiprotein-Based Model for Discriminating Psychiatric Disorders Using Multiple Reaction Monitoring-Mass Spectrometry: Proof-of-Concept Study.

Psychiatric evaluation relies on subjective symptoms and behavioral observation, which sometimes leads to misdiagnosis. Despite previous efforts to utilize plasma proteins as objective markers, the depletion method is time-consuming. Therefore, this study aimed to enhance previous quantification methods and construct objective discriminative models for major psychiatric disorders using nondepleted plasma. Multiple reaction monitoring-mass spectrometry (MRM-MS) assays for quantifying 453 peptides in nondepleted plasma from 132 individuals [35 major depressive disorder (MDD), 47 bipolar disorder (BD), 23 schizophrenia (SCZ) patients, and 27 healthy controls (HC)] were developed. Pairwise discriminative models for MDD, BD, and SCZ, and a discriminative model between patients and HC were constructed by machine learning approaches. In addition, the proteins from nondepleted plasma-based discriminative models were compared with previously developed depleted plasma-based discriminative models. Discriminative models for MDD versus BD, BD versus SCZ, MDD versus SCZ, and patients versus HC were constructed with 11 to 13 proteins and showed reasonable performances (AUROC = 0.890-0.955). Most of the shared proteins between nondepleted and depleted plasma models had consistent directions of expression levels and were associated with neural signaling, inflammatory, and lipid metabolism pathways. These results suggest that multiprotein markers from nondepleted plasma have a potential role in psychiatric evaluation.

Proteomic analysis of human aqueous humor from fuchs uveitis syndrome.

Fuchs uveitis syndrome (FUS) is a commonly misdiagnosed uveitis syndrome often presenting as an asymptomatic mild inflammatory condition until complications arise. The diagnosis of this disease remains clinical because of the lack of specific laboratory tests. The aqueous humor (AH) is a complex fluid containing nutrients and metabolic wastes from the eye. Changes in the AH protein provide important information for diagnosing intraocular diseases. This study aimed to analyze the proteomic profile of AH in individuals diagnosed with FUS and to identify potential biomarkers of the disease. We used liquid chromatography-tandem mass spectrometry-based proteomic methods to evaluate the AH protein profiles of all 37 samples, comprising 15 patients with FUS, six patients with Posner-Schlossman syndrome (PSS), and 16 patients with age-related cataract. A total of 538 proteins were identified from a comprehensive spectral library of 634 proteins. Subsequent differential expression analysis, enrichment analysis, and construction of key sub-networks revealed that the inflammatory response, complement activation and hypoxia might be crucial in mediating the process of FUS. The hypoxia inducible factor-1 may serve as a key regulator and therapeutic target. Additionally, the innate and adaptive immune responses are considered dominant in the patients with FUS. A diagnostic model was constructed using machine-learning algorithm to classify FUS, PSS, and normal controls. Two proteins, complement C1q subcomponent subunit B and secretogranin-1, were found to have the highest scores by the Extreme Gradient Boosting, suggesting their potential utility as a biomarker panel. Furthermore, these two proteins as biomarkers were validated in a cohort of 18 patients using high resolution multiple reaction monitoring assays. Therefore, this study contributes to advancing of the current knowledge of FUS pathogenesis and promotes the development of effective diagnostic strategies.

A novel SPE-LC-MRM strategy for serum demethylzeylasteral quantitation developed with an 18O-labeled internal standard.

Natural bioactive compounds (NBCs) are widely used in clinical treatment. For example, Tripterygium wilfordii Hook f. is commonly known in China as Lei-Gong-Teng which means thunder god vine. This herb is widely distributed in Eastern and Southern China, Korea, and Japan. The natural bioactive compounds of this herb can be extracted and made into tripterygium glycoside tablets. It is one of the most commonly used and effective traditional Chinese herbal medicines against rheumatoid arthritis (RA), nephrotic syndrome (NS), autoimmune hepatis (AIH), and so on. However, many NBCs are difficult to reliably quantify in the serum due to the effects of matrix and RSD. In addition, the targeted compound's internal standard (IS) is rarely sold due to the complex isotope internal standard synthesis pathway. In this study, a new quantitation method for 18O labeling combined with off-line SPE was formulated. We contrasted the recoveries and matrix effects of various separation methods in order to choose the best method. Furthermore, we optimized the conditions for SPE loading and washing. An isotopic internal standard was prepared by the 16O/18O exchanging reaction in order to eliminate the matrix effects. The method's accuracy and precision met the requirements for method validation. The recovery of this method was close to 60%. The relative standard deviation (RSD) of the high-concentration sample was 2%, and the limit of detection (LOD) was 1 ng/mL. This method could be used to analyze the clinical serum concentration of demethylzeylasteral. Sixty samples were collected from 10 patients with diabetes nephropathy. The quantitation results of demethylzeylasteral in patients' serum obtained using this method exhibited a correlation between therapeutic drug monitoring (TDM) and decreased urinary protein. This work may have broad implications for the study of drug metabolism in vivo and the clinical application of low-abundance and difficult-to-quantify NBCs.

Establishment of a targeted analysis method for gangliosides in mouse tissues by HILIC-ESI-MS/MS.

Gangliosides play an imperative role in cell signaling, neuronal recovery, apoptosis, and other physiological processes. For example, GM3 can regulate hypothalamic leptin resistance and control energy homeostasis, GD3 can mediate cell proliferation and differentiation and induce apoptosis, and GQ1b can stimulate neurogenesis. Therefore, the present study sought to establish and optimize the targeted analysis method for ganglioside subclasses and their molecular species using hydrophilic interaction liquid chromatography-triple quadrupole-MS/MS (HILIC-QQQ-MS/MS). Additionally, the fragmentation pattern of different ganglioside subclasses and their retention time patterns were analyzed, providing more accurate qualitative results. The limit of quantitation (LOQ) was as low as 10-4 ng. Moreover, the molecular species of gangliosides in the liver, cortex, and hypothalamus of C57BL/6 mice were analyzed using the established method. A total of 23 ganglioside subclasses with 164 molecular species, including 40 O-acetylated ganglioside molecular species and 28 NeuGc ganglioside molecular species, were identified using the semi-quantitative analysis method of an external standard curve corrected by an internal standard. In addition to NeuGc gangliosides, the contents of ganglioside subclasses were more abundant in the mouse brain than those in the mouse liver; especially, the contents of unsaturated gangliosides in the hypothalamus were much higher than those in the liver. Among them, O-acetylated gangliosides were detected only in the cortex and hypothalamus at a concentration of up to 100 µg/mg protein (40 molecular species). Overall, the proposed method expanded the detectable number of ganglioside subclasses and molecular species in biological samples and provided more opportunities for further study of the biological functions of gangliosides.

Insight into protein cross-linking and casein polymerization in pre- and post-hydrolyzed lactose-free UHT milk during long-term storage.

During processing and storage of both conventional and lactose-hydrolyzed UHT milk (LHM), aggregation of milk proteins occurs. Protein aggregation can inter alia occur via non-reducible covalent cross-links derived from either Maillard or dehydroalanine (DHA) pathways. To study this further in relation to processing method and lactase enzyme purity, LHM was produced using 3 different lactase preparations, with lactase enzymes added in a dairy setting either before (pre-hydrolysis) or after (post-hydrolysis) UHT treatment. The prepared LHM types were subsequently stored at either 25°C or 35°C for up to one year. Mass spectrometry was used to absolutely quantify the level of furosine, N-ɛ-(carboxymethyl)lysine (CML) and N-ɛ-(carboxyethyl)lysine (CEL), lanthionine (LAN) and lysinoalanine (LAL) in these products using a newly developed method on Triple Q for these processing-induced markers. The results showed higher levels of Maillard related processing markers in pre-hydrolyzed LHM compared with post-hydrolyzed LHM and conventional UHT milk which, on the other hand, contained higher concentrations of DHA-derived cross-links. Proteomics of collected particles from asymmetrical flow field-flow fractionation (AsFlFFF) in combination with gel electrophoresis indicated presence of intra-micellar cross-links during storage, for especially larger particles involving αS1- and αS2-caseins.

An Optimized Method for LC-MS-Based Quantification of Endogenous Organic Acids: Metabolic Perturbations in Pancreatic Cancer.

Accurate and reliable quantification of organic acids with carboxylic acid functional groups in complex biological samples remains a major analytical challenge in clinical chemistry. Issues such as spontaneous decarboxylation during ionization, poor chromatographic resolution, and retention on a reverse-phase column hinder sensitivity, specificity, and reproducibility in multiple-reaction monitoring (MRM)-based LC-MS assays. We report a targeted metabolomics method using phenylenediamine derivatization for quantifying carboxylic acid-containing metabolites (CCMs). This method achieves accurate and sensitive quantification in various biological matrices, with recovery rates from 90% to 105% and CVs ≤ 10%. It shows linearity from 0.1 ng/mL to 10 µg/mL with linear regression coefficients of 0.99 and LODs as low as 0.01 ng/mL. The library included a wide variety of structurally variant CCMs such as amino acids/conjugates, short- to medium-chain organic acids, di/tri-carboxylic acids/conjugates, fatty acids, and some ring-containing CCMs. Comparing CCM profiles of pancreatic cancer cells to normal pancreatic cells identified potential biomarkers and their correlation with key metabolic pathways. This method enables sensitive, specific, and high-throughput quantification of CCMs from small samples, supporting a wide range of applications in basic, clinical, and translational research.

Targeted Proteomics Reveals Quantitative Differences in Low-Abundance Glycosyltransferases of Patients with Congenital Disorders of Glycosylation.

Protein glycosylation is an essential post-translational modification in all domains of life. Its impairment in humans can result in severe diseases named congenital disorders of glycosylation (CDGs). Most of the glycosyltransferases (GTs) responsible for proper glycosylation are polytopic membrane proteins that represent challenging targets in proteomics. We established a multiple reaction monitoring (MRM) assay to comprehensively quantify GTs involved in the processes of N-glycosylation and O- and C-mannosylation in the endoplasmic reticulum. High robustness was achieved by using an enriched membrane protein fraction of isotopically labeled HEK 293T cells as an internal protein standard. The analysis of primary skin fibroblasts from eight CDG type I patients with impaired ALG1, ALG2, and ALG11 genes, respectively, revealed a substantial reduction in the corresponding protein levels. The abundance of the other GTs, however, remained unchanged at the transcript and protein levels, indicating that there is no fail-safe mechanism for the early steps of glycosylation in the endoplasmic reticulum. The established MRM assay was shared with the scientific community via the commonly used open source Skyline software environment, including Skyline Batch for automated data analysis. We demonstrate that another research group could easily reproduce all analysis steps, even while using different LC-MS hardware.

In-vitro antioxidant and anti-inflammatory potential along with p.o. pharmacokinetic profile of key bioactive phytocompounds of Snow Mountain Garlic: a comparative analysis vis-à-vis normal garlic.

Snow mountain garlic (SMG) is a trans-Himalayan medicinal plant used in the traditional medicine system for several ailments, including inflammatory arthritis. Research studies are insufficient to validate its folk medicinal applications. In the present study, the comparative abundance of its key bioactive phytocompounds, viz., S-allyl-L-cysteine (SAC), alliin, and S-methyl-L-cysteine (SMC) against normal garlic were assessed using the LC-MS/MS-MRM method. In addition, the study also explored the antioxidant and anti-inflammatory potency of crude extract of SMG and purified signature phytocompounds (i.e., SMC, SAC, and alliin) in comparison with normal garlic and dexamethasone in LPS-stimulated RAW264.7 macrophage cells. The LC-MS/MS-MRM study revealed significant differences among SMG and normal garlic, viz., alliin 22.8-fold higher in SMG, and SMC could be detected only in SMG. In the bioassays, SMG extract and purified signature phytocompounds significantly downregulated oxidative damage in activated macrophages, boosting endogenous antioxidants' activity. SMG extract-treated macrophages significantly suppressed NF-κB expression and related inflammatory indicators such as cytokines, COX-2, iNOS, and NO. Notably, the observed anti-inflammatory and antioxidant bioactivities of SMG extract were comparable to signature phytocompounds and dexamethasone. In addition, SAC being uniformly found in SMG and normal garlic, its comparative pharmacokinetics was studied to validate the pharmacodynamic superiority of SMG over normal garlic. Significantly higher plasma concentrations (Cmax), half-life (t1/2), and area under curve (AUC) of SAC following SMG extract administration than normal garlic validated the proposed hypothesis. Thus, the abundance of bioactive phytocompounds and their better pharmacokinetics in SMG extract might be underlying its medicinal merits over normal garlic.

[Simultaneous determination of seven artemisinin-related compounds in Artemisia annua by UPLC-QQQ-MS/MS].

A variety of compounds in Artemisia annua were simultaneously determined to evaluate the quality of A. annua from multiple perspectives. A method based on ultra-high performance liquid chromatography-triple quadrupole tandem mass spectrometry(UPLC-QQQ-MS/MS) was established for the simultaneous determination of seven compounds: amorpha-4,11-diene, artemisinic aldehyde, dihydroartemisinic acid, artemisinic acid, artemisinin B, artemisitene, and artemisinin, in A. annua. The content of the seven compounds in different tissues(roots, stems, leaves, and lateral branches) of A. annua were compared. The roots, stems, leaves, and lateral branches of four-month-old A. annua were collected and the content of seven artemisinin-related compounds in different tissues was determined. A multi-reaction monitoring(MRM) acquisition mode of UPLC-QQQ-MS/MS was used, with a positive ion mode of atmospheric pressure chemical ion source(APCI). Chromatographic separation was achieved on an Eclipse Plus RRHD C_(18) column(2.1 mm×50 mm, 1.8 µm). The gradient elution was performed with the mobile phase consisted of formic acid(0.1%)-ammonium formate(5 mmol·L~(-1))(A) and the methanol(B) gradient program of 0-8 min, 55%-100% B, 8-11 min, 100% B, and equilibrium for 3 min, the flow rate of 0.6 mL·min~(-1), the column temperature of 40 ℃, the injection volume of 5 µL, and the detection time of 8 min. Through methodological investigation, a method based on UPLC-QQQ-MS/MS was established for the simultaneous quantitative determination of seven representative compounds involved in the biosynthesis of artemisinin. The content of artemisinin in A. annua was higher than that of artemisinin B, and the content of artemisinin and dihydroartemisinic acid were high in all the tissues of A. annua. The content of the seven compounds varied considerably in different tissues, with the highest levels in the leaves and neither artemisinene nor artemisinic aldehyde was detected in the roots. In this study, a quantitative method based on UPLC-QQQ-MS/MS for the simultaneous determination of seven representative compounds involved in the biosynthesis of artemisinin was established, which was accurate, sensitive, and highly efficient, and can be used for determining the content of artemisinin-related compounds in A. annua, breeding new varieties, and controlling the quality of Chinese medicinal materials.

Simultaneous Quantification of Apolipoprotein C-III O-Glycoforms by Protein-MRM.

Apolipoprotein C-III (APOC-III) regulates triglyceride levels, associated with a risk of cardiovascular disease. One gene generates several proteoforms, each with a different molecular mass and a unique function. Unlike peptide multiple reaction monitoring (MRM), protein-MRM without digestion is required to analyze clinically relevant individual proteoforms. We developed a protein-MRM method without digestion to individually quantify APOC-III proteoforms in human serum. We optimized the protein-MRM method following 60% acetonitrile extraction with C18 filtration. Bovine serum and myoglobin served as supporting cushions and the internal standard during sample preparation, respectively. Furthermore, we evaluated the LOD, lower limit of quantification, linearity, accuracy, and precision. Good correlation compared with turbidimetric immunoassay (TIA) and peptide-MRM was observed using 30 clinical sera. Individual APOC-III O-glycoforms were identified by top-down proteomics and simultaneously quantified using the protein-MRM method. The sum abundance of APOC-III proteoforms was significantly correlated with TIA and peptide-MRM. Our protein-MRM method provides an affordable and rapid quantification of potential disease-specific proteoforms. Precise quantification of each proteoform allows investigators to identify novel biological roles potentially related to cardiovascular disease or novel biomarkers. We expect our protein-oriented method to be more clinically useful than antibody-based immunoassays and peptide-oriented MRM analysis, especially for quantification of a biomarker proteoform with certain post-translational modifications.

Glial cell proteome using targeted quantitative methods for potential multi-diagnostic biomarkers.

Glioblastoma is one of the most malignant primary brain cancer. Despite surgical resection with modern technology followed by chemo-radiation therapy with temozolomide, resistance to the treatment and recurrence is common due to its aggressive and infiltrating nature of the tumor with high proliferation index. The median survival time of the patients with glioblastomas is less than 15 months. Till now there has been no report of molecular target specific for glioblastomas. Early diagnosis and development of molecular target specific for glioblastomas are essential for longer survival of the patients with glioblastomas. Development of biomarkers specific for glioblastomas is most important for early diagnosis, estimation of the prognosis, and molecular target therapy of glioblastomas. To that end, in this study, we have conducted a comprehensive proteome study using primary cells and tissues from patients with glioblastoma. In the discovery stage, we have identified 7429 glioblastoma-specific proteins, where 476 proteins were quantitated using Tandem Mass Tag (TMT) method; 228 and 248 proteins showed up and down-regulated pattern, respectively. In the validation stage (20 selected target proteins), we developed quantitative targeted method (MRM: Multiple reaction monitoring) using stable isotope standards (SIS) peptide. In this study, five proteins (CCT3, PCMT1, TKT, TOMM34, UBA1) showed the significantly different protein levels (t-test: p value ≤ 0.05, AUC ≥ 0.7) between control and cancer groups and the result of multiplex assay using logistic regression showed the 5-marker panel showed better sensitivity (0.80 and 0.90), specificity (0.92 and 1.00), error rate (10 and 2%), and AUC value (0.94 and 0.98) than the best single marker (TOMM34) in primary cells and tissues, respectively. Although we acknowledge that the model requires further validation in a large sample size, the 5 protein marker panel can be used as baseline data for the discovery of novel biomarkers of the glioblastoma.

A large-scale targeted proteomics of serum and tissue shows the utility of classifying high grade and low grade meningioma tumors.

BACKGROUND: Meningiomas are the most prevalent primary brain tumors. Due to their increasing burden on healthcare, meningiomas have become a pivot of translational research globally. Despite many studies in the field of discovery proteomics, the identification of grade-specific markers for meningioma is still a paradox and requires thorough investigation. The potential of the reported markers in different studies needs further verification in large and independent sample cohorts to identify the best set of markers with a better clinical perspective. METHODS: A total of 53 fresh frozen tumor tissue and 51 serum samples were acquired from meningioma patients respectively along with healthy controls, to validate the prospect of reported differentially expressed proteins and claimed markers of Meningioma mined from numerous manuscripts and knowledgebases. A small subset of Glioma/Glioblastoma samples were also included to investigate inter-tumor segregation. Furthermore, a simple Machine Learning (ML) based analysis was performed to evaluate the classification accuracy of the list of proteins. RESULTS: A list of 15 proteins from tissue and 12 proteins from serum were found to be the best segregator using a feature selection-based machine learning strategy with an accuracy of around 80% in predicting low grade (WHO grade I) and high grade (WHO grade II and WHO grade III) meningiomas. In addition, the discriminant analysis could also unveil the complexity of meningioma grading from a segregation pattern, which leads to the understanding of transition phases between the grades. CONCLUSIONS: The identified list of validated markers could play an instrumental role in the classification of meningioma as well as provide novel clinical perspectives in regard to prognosis and therapeutic targets.

Amino acid analysis for peptide quantitation using reversed-phase liquid chromatography combined with multiple reaction monitoring mass spectrometry.

Amino acid analysis (AAA) can be used for absolute quantitation of standard peptides after acid hydrolysis using 6 M HCl. Obtained individual amino acids can then be quantified by liquid chromatography-mass spectrometry (LC-MS). Achieving baseline separation of non-derivatized amino acids is challenging when reversed-phase (RP) chromatography is used. Several derivatization methods are commonly utilized to address this issue; however, derivatization has several drawbacks, such as derivative instability and lack of reproducibility. Currently, separation of non-derivatized amino acids is typically done using HILIC, but HILIC has problems of poor reproducibility and long column equilibration times. We developed a method to quantify non-derivatized amino acids, including methionine and cysteine, from peptide hydrolysates by RP-LC-MS without special pre-treatment of the samples. Samples were spiked with certified isotopically labeled (13C- and/or 15N-) amino acids as internal standards. The amino acids released from acid hydrolysis were then analyzed by RP-UPLC-MRM-MS and quantified using the analyte/internal standard chromatographic peak area ratios. Peptide quantitation was based on the sum of the individual amino acid concentrations from the known peptide sequences. The resulting method did not require derivatization, used standard C18-based reversed-phase liquid chromatography, did not require external calibration, was robust, and was able to quantify all 17 amino acids for which we had internal standards, including the sulfur-containing amino acids, cysteine and methionine, in their respective oxidized forms. This simple and robust method enabled the absolute quantitation of standard peptides using only acid hydrolysis and a standard RP-UPLC-MRM-MS setup.

An Introduction to Advanced Targeted Acquisition Methods.

Targeted proteomics via selected reaction monitoring (SRM) or parallel reaction monitoring (PRM) enables fast and sensitive detection of a preselected set of target peptides. However, the number of peptides that can be monitored in conventional targeting methods is usually rather small. Recently, a series of methods has been described that employ intelligent acquisition strategies to increase the efficiency of mass spectrometers to detect target peptides. These methods are based on one of two strategies. First, retention time adjustment-based methods enable intelligent scheduling of target peptide retention times. These include Picky, iRT, as well as spike-in free real-time adjustment methods such as MaxQuant.Live. Second, in spike-in triggered acquisition methods such as SureQuant, Pseudo-PRM, TOMAHAQ, and Scout-MRM, targeted scans are initiated by abundant labeled synthetic peptides added to samples before the run. Both strategies enable the mass spectrometer to better focus data acquisition time on target peptides. This either enables more sensitive detection or a higher number of targets per run. Here, we provide an overview of available advanced targeting methods and highlight their intrinsic strengths and weaknesses and compatibility with specific experimental setups. Our goal is to provide a basic introduction to advanced targeting methods for people starting to work in this field.

First trimester serum apolipoproteins in the prediction of late-onset preeclampsia.

Late-onset preeclampsia occurring after 34 weeks of gestation is the most common form of preeclampsia, but little is known about either etiology or prevention. Current detection methods for preeclampsia in early pregnancy have not shown promising results in detecting late-onset preeclampsia. The aim of this study was to assess whether apolipoproteins in combination with maternal medical history and biophysical factors can be used as an early detection method for late-onset preeclampsia. This nested case-cohort study was based at Odense University Hospital, Denmark. Women attending their first trimester scan were invited to participate if they understood Danish or English, were above the age of 18, and had singleton pregnancies. Blood pressure, maternal medical history, uterine artery pulsatility indices, and blood samples were collected at inclusion. Outcome data were collected from participants' medical files postpartum, and cases were selected when preeclampsia diagnostics were present. Serum samples were analyzed by targeted mass spectrometry using a biomarker panel consisting of 12 apolipoproteins. Logistic regression analyses were performed and finally receiver operating curves were completed. The cohort consisted of 27 cases and 194 normotensive controls, randomized from 340 eligible participants. Significant differences were found between the two groups' baseline characteristics but none of the apolipoproteins showed significant difference (p < 0.05). The ROC-curve combining maternal characteristics, mean arterial pressure and two apolipoproteins showed the best sensitivity of 55.5% at a 10% false-positive rate and an area under the curve of 0.873. In conclusion, apolipoproteins did not improve the detection of late-onset preeclampsia in a combined screening model.