Bottom-up and Shotgun Proteomics to Identify a Comprehensive Cochlear Proteome

Proteomics is a commonly used approach that can provide insights into complex biological systems. The cochlear sensory epithelium contains receptors that transduce the mechanical energy of sound into an electro-chemical energy processed by the peripheral and central nervous systems. Several proteomic techniques have been developed to study the cochlear inner ear, such as two-dimensional difference gel electrophoresis (2D-DIGE), antibody microarray, and mass spectrometry (MS). MS is the most comprehensive and versatile tool in proteomics and in conjunction with separation methods can provide an in-depth proteome of biological samples. Separation methods combined with MS has the ability to enrich protein samples, detect low molecular weight and hydrophobic proteins, and identify low abundant proteins by reducing the proteome dynamic range. Different digestion strategies can be applied to whole lysate or to fractionated protein lysate to enhance peptide and protein sequence coverage. Utilization of different separation techniques, including strong cation exchange (SCX), reversed-phase (RP), and gel-eluted liquid fraction entrapment electrophoresis (GELFrEE) can be applied to reduce sample complexity prior to MS analysis for protein identification.     

基于质谱的磷酸化蛋白质组学: 富集、检测、鉴定和定量

磷酸化是一种调控生命活动的重要翻译后修饰,调控生物的生长发育、信号转导、以及疾病的发生发展．从上世纪80年代开始,质谱应用于蛋白质磷酸化的检测中,极大地推动了磷酸化蛋白质组学的发展．质谱检测拥有高灵敏度、高通量的特点,更重要的是具有位点分辨率,因此基于质谱的磷酸化蛋白质组检测方法得到不断的发展和推广．常见的磷酸化蛋白质组研究,首先对磷酸化肽段进行富集,然后进行串联质谱分析,最后通过搜索引擎对修饰位点进行鉴定和定量．本文从这个三个基本方面,对磷酸化蛋白质组研究进行综述,并对未来研究发展方向进行讨论．     

ComplexBrowser: A Tool for Identification and Quantification of Protein Complexes in Large-scale Proteomics Datasets

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Highlights

• •Automated analysis of protein complexes in proteomic experiments.
• •Quantitative measurement of the coordinated changes in protein complex components.
• •Interactive visualizations for exploratory analysis of proteomic results.

     

A multiplex quantitation method for eicosanoids and platelet-activating factor using column-switching reversed-phase liquid chromatography-tandem mass spectrometry

Eicosanoids and platelet-activating factor (PAF) are phospholipid-derived lipid mediators produced by various tissues and cells through a cascade pathway. For a comprehensive analysis of these lipid mediators, a simultaneous quantitation method with sensitivity and reliability is necessary. This article details a development of column-switching reversed-phase liquid chromatography-tandem mass spectrometry for multiplex quantitation of eicosanoids and PAF. The adsorptive nature of lipids caused significant loss of signal in a conventional column-switching configuration. The use of an online-dilution method allowed use of 100% methanol as a sample solvent, which prevented sample adsorption to contacting surfaces. Addition of 0.2% formic acid to the sample solvent was required for the successful introduction of LTC4 to the trapping column and minimizing its carryover. The optimized method provided rapid analysis of 14 lipid mediators with a throughput of 96 samples/24 h, lower limits of quantitation of 5 pg on column, and linear calibration ranges up to 2000-5000 pg. The system was highly compatible with solid-phase-extracted samples, as methanol-eluted fractions were directly injected without reconstitution. The analysis of lipid mediator production of macrophage-like RAW264.7 cells demonstrated that the cell-based assay can be performed in a 96-well format, suitable for metabolomics analyses and/or screening strategies.     

Rapid development of proteomics in China: from the perspective of the Human Liver Proteome Project and technology development

Proteomics focuses on the systematic identification and quantification of entire proteomes and interpretation of proteins’biological functions.During the last decade,proteomics in China has grown much faster than other research fields in life sciences.At the beginning of the second decade of the 21st century,the rapid development of high-resolution and high-speed mass spectrometry makes proteomics a powerful tool to study the mechanisms underlying physiological/pathological processes in organisms.This article provides a brief overview of proteomics technology development and representative scientific progress of the Human Liver Proteome Project in China over the past three years.     

Assessment of Feasibility of Maillard Reaction between Baclofen and Lactose by Liquid Chromatography and Tandem Mass Spectrometry, Application to Pre Formulation Studies

The aim of this study was to determine any possible, baclofen–lactose Maillard reaction products. Granules and tablets of baclofen and lactose were prepared and maintained in heat ovens for a certain time period. The effects of lactose type, addition of magnesium stearate, and water were monitored. Heated lactose and baclofen were analyzed using reverse-phase HPLC. Liquid chromatography tandem mass spectroscopy revealed nominal mass values consistent with baclofen–lactose, early-stage Maillard reaction condensation products (ESMRP). Multiple reaction monitoring confirmed the presence of ESMRP as well. FTIR analysis proved the formation of imine bond. The results indicated that baclofen undergoes a Maillard-type reaction with lactose.     

In silico Proteome-wide Amino aCid and Elemental Composition (PACE) Analysis of Expression Proteomics Data Provides A Fingerprint of Dominant Metabolic Processes

Proteome-wide Amino aCid and Elemental composition (PACE) analysis is a novel and informative way of interrogating the proteome. The PACE approach consists of in silico decomposition of proteins detected and quantified in a proteomics experiment into 20 amino acids and five elements (C, H, N, O and S), with protein abundances converted to relative abundances of amino acids and elements. The method is robust and very sensitive; it provides statistically reliable differentiation between very similar proteomes. In addition, PACE provides novel insights into proteome-wide metabolic processes, occurring, e.g., during cell starvation. For instance, both Escherichia coli and Synechocystis down-regulate sulfur-rich proteins upon sulfur deprivation, but E. coli preferentially down-regulates cysteine-rich proteins while Synechocystis mainly down-regulates methionine-rich proteins. Due to its relative simplicity, flexibility, generality and wide applicability, PACE analysis has the potential of becoming a standard analytical tool in proteomics.     

AIAP: A Quality Control and Integrative Analysis Package to Improve ATAC-seq Data Analysis

Assay for transposase-accessible chromatin with high-throughput sequencing (ATAC-seq) is a technique widely used to investigate genome-wide chromatin accessibility. The recently published Omni-ATAC-seq protocol substantially improves the signal/noise ratio and reduces the input cell number. High-quality data are critical to ensure accurate analysis. Several tools have been developed for assessing sequencing quality and insertion size distribution for ATAC-seq data; however, key quality control (QC) metrics have not yet been established to accurately determine the quality of ATAC-seq data. Here, we optimized the analysis strategy for ATAC-seq and defined a series of QC metrics for ATAC-seq data, including reads under peak ratio (RUPr), background (BG), promoter enrichment (ProEn), subsampling enrichment (SubEn), and other measurements. We incorporated these QC tests into our recently developed ATAC-seq Integrative Analysis Package (AIAP) to provide a complete ATAC-seq analysis system, including quality assurance, improved peak calling, and downstream differential analysis. We demonstrated a significant improvement of sensitivity (20%–60%) in both peak calling and differential analysis by processing paired-end ATAC-seq datasets using AIAP. AIAP is compiled into Docker/Singularity, and it can be executed by one command line to generate a comprehensive QC report. We used ENCODE ATAC-seq data to benchmark and generate QC recommendations, and developed qATACViewer for the user-friendly interaction with the QC report. The software, source code, and documentation of AIAP are freely available at https://github.com/Zhang-lab/ATAC-seq_QC_analysis.     

Paclitaxel quantification in mouse plasma and tissues containing liposome-entrapped paclitaxel by liquid chromatography-tandem mass spectrometry: application to a pharmacokinetics study

A liquid chromatography-tandem mass spectrometry assay to quantify total paclitaxel in mouse plasma and tissue homogenates containing paclitaxel, Taxol, or liposome-entrapped paclitaxel-easy to use (LEP-ETU) was developed and validated. Docetaxel was used as the internal standard (IS). Liquid-liquid extraction with tert-butyl methyl ether was used for plasma sample preparation, and a one-step protein precipitation with acetonitrile containing 0.1% acetic acid was developed for tissue homogenates. Paclitaxel and IS are separated on a 50 x 2.1-mm C18 column and quantified using a triple-quadrupole mass spectrometer operating in positive ion electrospray multiple reaction monitoring mode, with a total run time of 3.5 min. The peak area of the m/z 854.4--> 286.2 transition of paclitaxel is measured versus that of the m/z 808.5--> 527.5 transition of IS to generate the standard curve. In plasma, the linear range is 0.2-500 ng/mL and could be extended by dilution to 100,000 ng/mL with acceptable precision and accuracy (< or = 15%). The lower limit of quantification is 0.5 ng/mL in tissue homogenates (10 ng/g tissue), and the standard curve is linear up to 1000 ng/mL, with precision and accuracy < or = 15%. This assay was used to support a pharmacokinetics and tissue distribution study of LEP-ETU in mice.     

MMS2plot: An R Package for Visualizing Multiple MS/MS Spectra for Groups of Modified and Non‐Modified Peptides

A large number of post‐translational modifications (PTMs) in proteins are buried in the unassigned mass spectrometric (MS) spectra in shot‐gun proteomics datasets. Because the modified peptide fragments are low in abundance relative to the corresponding non‐modified versions, it is critical to develop tools that allow facile evaluation of assignment of PTMs based on the MS/MS spectra. Such tools will preferably have the ability to allow comparison of fragment ion spectra and retention time between the modified and unmodified peptide pairs or group. Herein, MMS2plot, an R package for visualizing peptide‐spectrum matches (PSMs) for multiple peptides, is described. MMS2plot features a batch mode and generates the output images in vector graphics file format that facilitate evaluation and publication of the PSM assignment. MMS2plot is expected to play an important role in PTM discovery from large‐scale proteomics datasets generated by liquid chromatography‐MS/MS. The MMS2plot package is freely available at https://github.com/lileir/MMS2plot under the GPL‐3 license.     

Residual Pattern and Dietary Intake of Iprodione on Grapes under Egyptian Field Conditions: A Prelude to Risk Assessment Profile

Field experiments were conducted in two different locations in the Nile delta to determine the residue levels and dissipation rates of iprodione in grapes. Iprodione was applied in different rates (recommended dose and two times recommended dose) and spraying times. Analysis was carried out using liquid chromatography-tandem mass spectrometry (LC-MS/MS). The dissipation rates of iprodione were described using first-order kinetics and the half-life ranged from 8.8 to 9.4 days. There was a sharp decrease in the amount of iprodione residues 10 days after application. At harvest time, the remaining residues of iprodione were below the Food and Agriculture Organization (FAO)/World Health Organization (WHO) maximum residue level (MRL) of 10 mg/kg when measured 14 days after final application. The exposure to iprodione was assessed and compared to acceptable daily intake (ADI). Based on grape consumption, the estimated daily intakes of iprodione ranged from 0.2% to 1.1% of the ADI, showing insignificant risk to consumers.     

MALDI Mass Spectrometry Imaging: A Novel Tool for the Identification and Classification of Amyloidosis

Amyloidosis is a group of diseases caused by extracellular accumulation of fibrillar polypeptide aggregates. So far, diagnosis is performed by Congo red staining of tissue sections in combination with polarization microscopy. Subsequent identification of the causative protein by immunohistochemistry harbors some difficulties regarding sensitivity and specificity. Mass spectrometry based approaches have been demonstrated to constitute a reliable method to supplement typing of amyloidosis, but still depend on Congo red staining. In the present study, we used matrix‐assisted laser desorption/ionization mass spectrometry imaging coupled with ion mobility separation (MALDI‐IMS MSI) to investigate amyloid deposits in formalin‐fixed and paraffin‐embedded tissue samples. Utilizing a novel peptide filter method, we found a universal peptide signature for amyloidoses. Furthermore, differences in the peptide composition of ALλ and ATTR amyloid were revealed and used to build a reliable classification model. Integrating the peptide filter in MALDI‐IMS MSI analysis, we developed a bioinformatics workflow facilitating the identification and classification of amyloidosis in a less time and sample‐consuming experimental setup. Our findings demonstrate also the feasibility to investigate the amyloid's protein composition, thus paving the way to establish classification models for the diverse types of amyloidoses and to shed further light on the complex process of amyloidogenesis.     

New approach to evaluating the effects of a drug on protein complexes with quantitative proteomics,using the SILAC method and bioinformatic approach

ABSTRACT

Protein–protein interactions (PPIs) lead the formation of protein complexes that perform biochemical reactions that maintain the living state of the living cell. Although therapeutic drugs should influence the formation of protein complexes in addition to PPI network, the methodology analyzing such influences remain to be developed. Here, we demonstrate that a new approach combining HPLC (high performance liquid chromatography) for separating protein complexes, and the SILAC (stable isotope labeling using amino acids in cell culture) method for relative protein quantification, enable us to identify the protein complexes influenced by a drug. We applied this approach to the analysis of thalidomide action on HepG2 cells, assessed the identified proteins by clustering data analyses, and assigned 135 novel protein complexes affected by the drug. We propose that this approach is applicable to elucidating the mechanisms of actions of other therapeutic drugs on the PPI network, and the formation of protein complexes.     

Data‐Independent Acquisition Mass Spectrometry‐Based Proteomics and Software Tools: A Glimpse in 2020

This review provides a brief overview of the development of data‐independent acquisition (DIA) mass spectrometry‐based proteomics and selected DIA data analysis tools. Various DIA acquisition schemes for proteomics are summarized first including Shotgun‐CID, DIA, MS^E, PAcIFIC, AIF, SWATH, MSX, SONAR, WiSIM, BoxCar, Scanning SWATH, diaPASEF, and PulseDIA, as well as the mass spectrometers enabling these methods. Next, the software tools for DIA data analysis are classified into three groups: library‐based tools, library‐free tools, and statistical validation tools. The approaches are reviewed for generating spectral libraries for six selected library‐based DIA data analysis software tools which are tested by the authors, including OpenSWATH, Spectronaut, Skyline, PeakView, DIA‐NN, and EncyclopeDIA. An increasing number of library‐free DIA data analysis tools are developed including DIA‐Umpire, Group‐DIA, PECAN, PEAKS, which facilitate identification of novel proteoforms. The authors share their user experience of when to use DIA‐MS, and several selected DIA data analysis software tools. Finally, the state of the art DIA mass spectrometry and software tools, and the authors’ views of future directions are summarized.     

A simple and robust UPLC-SRM/MS method to quantify urinary eicosanoids

Eicosanoids are key mediators and regulators of inflammation and oxidative stress often used as biomarkers for diseases and pathological conditions such as cardiovascular and pulmonary diseases and cancer. Analytically, comprehensive and robust quantification of different eicosanoid species in a multi-method approach is problematic because most of these compounds are relatively unstable and may differ in their chemical properties. Here we describe a novel ultra-performance liquid chromatography-selected reaction monitoring mass spectroscopy (UPLC-SRM/MS) method for simultaneous quantification of key urinary eicosanoids, including the prostaglandins (PG) tetranor PGE-M, 8-iso-, and 2,3-dinor-8-iso-PGF_2α; the thromboxanes (TXs) 11-dehydro- and 2,3-dinor-TXB₂; leukotriene E₄; and 12-hydroxyeicosatetraenoic acid. In contrast to previous methods, which used time-consuming and complex solid phase extraction, we prepared samples with a simple liquid/liquid extraction procedure. Because collision-induced dissociation produced characteristic product ions for all analytes, no derivatization step for SRM/MS analysis was necessary. Analytes were separated with a short UPLC reversed-phase column (1.7 µm particles), allowing shorter run times than conventional HPLC columns. The method was validated and applied to human urine samples showing excellent precision, accuracy, detection limits, and robustness. In summary, the developed method allows robust and sensitive profiling of urinary eicosanoid species, making it a useful and valuable tool for biomarker profiling in clinical/toxicological studies.     

MhcVizPipe: A Quality Control Software for Rapid Assessment of Small- to Large-Scale Immunopeptidome Datasets

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Discovery and development of a type II collagen neoepitope (TIINE) biomarker for matrix metalloproteinase activity: from in vitro to in vivo

Destruction of cartilage by matrix metalloproteinases (MMPs) plays a significant role in the pathology of osteoarthritis (OA). A translatable biomarker of MMP activity would enable development of MMP inhibitors for the treatment of OA and potentially the improved diagnosis of OA. A directed approach to identifying specific MMP cleavage products as potential biomarkers has been undertaken. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) was used to identify peptides generated by MMP-driven degradation of human articular cartilage (HAC) in vivo. It was shown that a 45-mer peptide fragment of collagen type II with five hydroxyprolines (OH) can be selectively produced by the activity of collagenase, an enzyme purported to be involved in the pathology of OA. This 45-mer is the most abundant neoepitope peptide found in biological fluids such as urine and synovial fluid. An immunoaffinity LC-MS/MS assay has been developed to quantify collagen type II neoepitope peptides as biomarkers of collagenase modulation. The lower limit of quantification for this assay was established to be 0.035 nM. The assay was used to measure the levels of collagen type II peptides in the urine of both clinical (healthy human subjects) and preclinical species. The urinary levels of the most abundant peptides are reported for rat, rabbit, guinea pig, dog, and healthy human adult subjects. The utility of this peptide to monitor collagenase activity in vivo has been demonstrated through its detailed characterization in HAC explants as well as in the urine of human and other preclinical species.     

MS‐Rescue: A Computational Pipeline to Increase the Quality and Yield of Immunopeptidomics Experiments

LC–MS/MS has become the standard platform for the characterization of immunopeptidomes, the collection of peptides naturally presented by major histocompatibility complex molecules to the cell surface. The protocols and algorithms used for immunopeptidomics data analysis are based on tools developed for traditional bottom‐up proteomics that address the identification of peptides generated by tryptic digestion. Such algorithms are generally not tailored to the specific requirements of MHC ligand identification and, as a consequence, immunopeptidomics datasets suffer from dismissal of informative spectral information and high false discovery rates. Here, a new pipeline for the refinement of peptide‐spectrum matches (PSM) is proposed, based on the assumption that immunopeptidomes contain a limited number of recurring peptide motifs, corresponding to MHC specificities. Sequence motifs are learned directly from the individual peptidome by training a prediction model on high‐confidence PSMs. The model is then applied to PSM candidates with lower confidence, and sequences that score significantly higher than random peptides are rescued as likely true ligands. The pipeline is applied to MHC class I immunopeptidomes from three different species, and it is shown that it can increase the number of identified ligands by up to 20–30%, while effectively removing false positives and products of co‐precipitation. Spectral validation using synthetic peptides confirms the identity of a large proportion of rescued ligands in the experimental peptidome.