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PubMed2006

In vacuo isotope coded alkylation technique (IVICAT); an N-terminal stable isotopic label for quantitative liquid chromatography/mass spectrometry proteomics.

We present a new isotopic labeling strategy to modify the N-terminal amino group of peptides in a quantifiable reaction without the use of expensive reagents or solvents. The In Vacuo Isotope Coded Alkylation Technique (IVICAT) is a methylation reaction, carried out at low pressure (<100 mTorr), that results in a stable quaternary trimethylammonium group, thus adding a permanent positive charge at the N-terminus of peptides without modifying the epsilon-amino groups of lysine. The methylation reaction increases the signal intensity of modified peptides in matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) and liquid chromatography (LC)/MS and the isotopic peak pair differs by 9 mass units which can be easily resolved by either instrument. N-terminally trimethylated peptides exhibit collision-induced dissociation (CID) mass spectra that differ from their unmodified analogues by an enhanced b-ion series in MS2 spectra due to the fixed positive charge. Using LC/MS/MS with an LTQ mass analyzer for quantification, the experimentally determined ratios of H9- to D9-trimethyl-labeled peptides of beta-casein provided accurate estimates of the actual ratios with low % error. IVICAT labeling also accurately quantified proteins in rat kidney inner medullary collecting duct cell types, as judged by comparison with relative quantification by subsequent immunoblotting experiments. IVICAT labeling, when used in conjunction with the new proteomics software QUIL, can accurately report relative protein abundances and increase the sequence coverage of proteins of tissue proteomes.

Amino Acid Sequence↗
PubMed2025

Benchmark for Quantitative Global and Redox Proteomics Analysis by Combining Protein-Aggregation Capture and Data Independent Acquisition.

Oxidative damage plays a critical role in various diseases including cardiovascular and neurological disorders. Thiol redox reactions, acting as oxidative stress sensors, influence protein structure and function. Redox proteomics, based on the differential alkylation of cysteine sites followed by mass spectrometry, enables the comprehensive analysis of thiol redox status in cells and tissues. However, these approaches require extensive sample manipulation and are not compatible with data-independent acquisition techniques. Here, we introduce PACREDOX, an innovative strategy based on protein aggregation capture (PAC), and demonstrate its compatibility with library-free DIA. Compared with traditional methods such as FASILOX, PACREDOX reduces preparation time and costs while maintaining thiol and proteome coverage. To enable library-free DIA, we corrected in silico spectral libraries in DIA-NN using experimental retention time data from methylthiolated-Cys peptides. PACREDOX with DIA was benchmarked against FASILOX in a myocardial infarction model, yielding the same biological insights, while enhancing peptide and protein coverage. Our results underscore the potential and efficiency of this methodology for studying oxidative damage. Overall, PACREDOX offers an automatable, high-throughput, and cost-effective strategy for redox proteomics.

Proteomics↗
PubMed2026

Kv11.1 (hERG) Protein Interaction Networks Connect Endocytic Trafficking to Polygenic Influences on Cardiac Repolarization.

Polygenic scores (PGS) capture the combined effect of many common genetic variants on quantitative traits and disease risk, yet their functional consequences at the protein level remain poorly defined. Here, we integrated quantitative and interaction proteomics to resolve how polygenic liability for cardiac repolarization manifests in human cells. We studied human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) from donors with extreme PGS for QT interval duration, a clinically relevant electrophysiologic trait associated with arrhythmia risk. Global quantitative proteomics revealed increased abundance of mitochondrial proteins in high-PGS cardiomyocytes. To define protein network-level effects on a key repolarizing ion channel, we performed multiplexed affinity purification-mass spectrometry (AP-MS) of Kv11.1. While mitochondrial changes did not directly explain Kv11.1-associated complexes, interactome analysis revealed increased association of Kv11.1 with myosin motor proteins and endosomal recycling machinery in high-PGS cells. These findings suggest altered channel trafficking dynamics of Kv11.1, distinct from the trafficking defects observed in monogenic Kv11.1 variants. Together, these data show that integrating global and interaction proteomics can resolve how polygenic variation reshapes protein networks. Future work using these methods could connect genomic risk to subcellular remodeling and our work provides a generalizable framework to probe the proteomic basis of complex traits. SIGNIFICANCE STATEMENT: Polygenic scores (PGS) predict disease risk, but how biological pathways are influenced by these common variants remains difficult to define. We generated human induced pluripotent stem cells from individuals with extreme high- and low- PGS for QT interval, a key electrocardiographic measure linked to arrhythmia risk. By combining global proteomics and interactomics for a common ion channel involved in regulating the QT interval (Kv11.1) we found potential mechanisms that are influenced by common genetic traits in patients. Our work provides an approach to connect polygenic scores to pathway-level molecular mechanisms in human cells and a general framework for uncovering how complex genetic architecture drives disease-relevant biology.

AP-MS↗
PubMed2002

Multidimensional peptide separations in proteomics.

Multidimensional peptide separation will play an increasingly important role in the drive to identify and quantitate the proteome. By increasing the peak and load capacity, multidimensional approaches increase the number and dynamic range of peptides that can be analyzed in a complex biological organism. Separation methods using different physical properties of peptides have been combined with varying degrees of success. The ultimate goal is a rapid separation strategy that can be coupled with analytical methods, such as mass spectrometry, to provide comprehensive monitoring of the changing concentration, interactions, and structures of proteins in the proteome.

Chromatography, Liquid↗
PubMed2003

Proteomic prediction of disease outcome in cancer : clinical framework and current status.

Better than gene sequencing or quantitative amplification, proteomics tools allow the study of tumor phenotype. Indeed, most current prognostic tests in cancer (carcinoembryonary antigen [CEA], prostate-specific antigen [PSA], CA 19-1, CA 125, alpha-fetoprotein [AFP], etc.) are based on the detection and quantification of single proteins in body fluids. However, a common characteristic of these tests is their relatively low predictive value, so that they are usually complemented with other procedures such as biopsy and/or endoscopy. Recently, improved analytical and bioinformatics tools have driven the attention on pattern recognition approaches rather then single-marker tests for prognostic forecasting. It is expected that predicting metastasization on the basis of tumoral protein patterns will soon be a reality. However, currently available technologies either limit the number of proteins that can be analyzed simultaneously or they are expensive, difficult, and time-consuming. Moreover, the tools adapted for expression proteomics might not be the same as those for prognostic studies that require investigation of protein function over time. We believe that clinical proteomics research designed within a precise clinical and pathology framework should be strongly supported, since many prognostic factors are determined not by the tumor itself, but by the patient, the treatment and the environment.

Animals↗
PubMed2006

Proteome dynamics during plastid differentiation in rice.

We have analyzed proteome dynamics during light-induced development of rice (Oryza sativa) chloroplasts from etioplasts using quantitative two-dimensional gel electrophoresis and tandem mass spectrometry protein identification. In the dark, the etioplast allocates the main proportion of total protein mass to carbohydrate and amino acid metabolism and a surprisingly high number of proteins to the regulation and expression of plastid genes. Chaperones, proteins for photosynthetic energy metabolism, and enzymes of the tetrapyrrole pathway were identified among the most abundant etioplast proteins. The detection of 13 N-terminal acetylated peptides allowed us to map the exact localization of the transit peptide cleavage site, demonstrating good agreement with the prediction for most proteins. Based on the quantitative etioplast proteome map, we examined early light-induced changes during chloroplast development. The transition from heterotrophic metabolism to photosynthesis-supported autotrophic metabolism was already detectable 2 h after illumination and affected most essential metabolic modules. Enzymes in carbohydrate metabolism, photosynthesis, and gene expression were up-regulated, whereas enzymes in amino acid and fatty acid metabolism were significantly decreased in relative abundance. Enzymes involved in nucleotide metabolism, tetrapyrrole biosynthesis, and redox regulation remained unchanged. Phosphoprotein-specific staining at different time points during chloroplast development revealed light-induced phosphorylation of a nuclear-encoded plastid RNA-binding protein, consistent with changes in plastid RNA metabolism. Quantitative information about all identified proteins and their regulation by light is available in plprot, the plastid proteome database (http://www.plprot.ethz.ch).

Down-Regulation↗
PubMed2002

Enhanced analysis of human breast cancer proteomes using micro-scale solution isoelectrofocusing combined with high resolution 1-D and 2-D gels.

Current methods for quantitatively comparing proteomes (protein profiling) have inadequate resolution and dynamic range for complex proteomes such as those from mammalian cells or tissues. More extensive profiling of complex proteomes would be obtained if the proteomes could be reproducibly divided into a moderate number of well-separated pools. But the utility of any prefractionation is dependent upon the resolution obtained because extensive cross contamination of many proteins among different pools would make quantitative comparisons impractical. The current study used a recently developed microscale solution isoelectrofocusing (musol-IEF) method to separate human breast cancer cell extracts into seven well-resolved pools. High resolution fractionation could be achieved in a series of small volume tandem chambers separated by thin acrylamide partitions containing covalently bound immobilines that establish discrete pH zones to separate proteins based upon their pIs. In contrast to analytical 2-D gels, this prefractionation method was capable of separating very large proteins (up to about 500 kDa) that could be subsequently profiled and quantitated using large-pore 1-D SDS gels. The pH 4.5-6.5 region was divided into four 0.5 pH unit ranges because this region had the greatest number of proteins. By using very narrow pH range fractions, sample amounts applied to narrow pH range 2-D gels could be increased to detect lower abundance proteins. Although 1.0 pH range 2-D gels were used in these experiments, further protein resolution should be feasible by using 2-D gels with pH ranges that are only slightly wider than the pH ranges of the musol-IEF fractions. By combining musol-IEF prefractionation with subsequent large pore 1-D SDS-PAGE (>100 kDa) and narrow range 2-D gels (<100 kDa), large proteins can be reliably quantitated, many more proteins can be resolved, and lower abundance proteins can be detected.

Electrophoresis, Polyacrylamide Gel↗
PubMed2006

Characterization of the mouse brain proteome using global proteomic analysis complemented with cysteinyl-peptide enrichment.

We report a global proteomic approach for analyzing brain tissue and for the first time a comprehensive characterization of the whole mouse brain proteome. Preparation of the whole brain sample incorporated a highly efficient cysteinyl-peptide enrichment (CPE) technique to complement a global enzymatic digestion method. Both the global and the cysteinyl-enriched peptide samples were analyzed by SCX fractionation coupled with reversed phase LC-MS/MS analysis. A total of 48,328 different peptides were confidently identified (>98% confidence level), covering 7792 nonredundant proteins ( approximately 34% of the predicted mouse proteome). A total of 1564 and 1859 proteins were identified exclusively from the cysteinyl-peptide and the global peptide samples, respectively, corresponding to 25% and 31% improvements in proteome coverage compared to analysis of only the global peptide or cysteinyl-peptide samples. The identified proteins provide a broad representation of the mouse proteome with little bias evident due to protein pI, molecular weight, and/or cellular localization. Approximately 26% of the identified proteins with gene ontology (GO) annotations were membrane proteins, with 1447 proteins predicted to have transmembrane domains, and many of the membrane proteins were found to be involved in transport and cell signaling. The MS/MS spectrum count information for the identified proteins was used to provide a measure of relative protein abundances. The mouse brain peptide/protein database generated from this study represents the most comprehensive proteome coverage for the mammalian brain to date, and the basis for future quantitative brain proteomic studies using mouse models. The proteomic approach presented here may have broad applications for rapid proteomic analyses of various mouse models of human brain diseases.

Animals↗
PubMed2005

Proteomic analysis using an unfinished bacterial genome: the effects of subminimum inhibitory concentrations of antibiotics on Mannheimia haemolytica virulence factor expression.

Here we identify, using nonelectrophoretic proteomics, effects of subminimum inhibitory concentrations (subMIC) of two antibiotic preparations, chlortetracycline (CTC), and chlortetracycline-sulfamethazine (CTC + SMZ), on protein expression in the bovine respiratory pathogen Mannheimia haemolytica. The M. haemolytica genome is currently in draft form, and annotation is incomplete. Relying on the principle of gene sequence conservation across species, we used annotated genomes from closely related species to identify, confirm, and functionally annotate 495 M. haemolytica proteins. To conduct quantitative comparative proteomics, we developed a protein quantitation method based on the cross correlation function of the SEQUEST algorithm. When M. haemolytica was cultivated in the presence of 1/4 MIC of CTC and CTC + SMZ, expression of proteins involved in energy production, nucleotide metabolism, translation, and the bacterial stress response (chaperones) were affected. The most notable subMIC effect was a significant decrease in the expression of leukotoxin A, which is an important M. haemolytica virulence factor. Reduction in leukotoxin expression could be one of the molecular mechanisms responsible for the efficacy of these antibiotics against bovine respiratory disease.

Algorithms↗
PubMed2006

Simultaneous qualitative and quantitative analysis of the Escherichia coli proteome: a sweet tale.

We describe a novel LCMS approach to the relative quantitation and simultaneous identification of proteins within the complex milieu of unfractionated Escherichia coli. This label-free, LCMS acquisition method observes all detectable, eluting peptides and their corresponding fragment ions. Postacquisition data analysis methods extract both the chromatographic and the mass spectrometric information on the tryptic peptides to provide time-resolved, accurate mass measurements, which are subsequently used for quantitation and identification of constituent proteins. The response of E. coli to carbon source variation is well understood, and it is thus commonly used as a model biological system when validating an analytical method. Using this LCMS approach, we characterized proteins isolated from E. coli grown in glucose, lactose, and acetate. The change in relative abundance of the corresponding proteins was measured from peptides common to both conditions. Protein identities were also determined for those peptides that were unique to each condition, and these identities were found to be consistent with the underlying biochemical restrictions imposed by the growth conditions. The relative change in abundance of the characterized proteins ranged from 0.1- to 90-fold among the three binary comparisons. The overall coverage of the characterized proteins ranged from 10 to 80%, consisting of one to 34 peptides per protein. The quantitative results obtained from our study were comparable to other existing proteomic and transcriptional profiling approaches. This study illustrates the robustness of this novel LCMS approach for the simultaneous quantitative and comprehensive qualitative analysis of proteins in complex mixtures.

Chromatography, High Pressure Liquid↗
PubMed2006

Semi-supervised LC/MS alignment for differential proteomics.

MOTIVATION: Mass spectrometry (MS) combined with high-performance liquid chromatography (LC) has received considerable attention for high-throughput analysis of proteomes. Isotopic labeling techniques such as ICAT [5,6] have been successfully applied to derive differential quantitative information for two protein samples, however at the price of significantly increased complexity of the experimental setup. To overcome these limitations, we consider a label-free setting where correspondences between elements of two samples have to be established prior to the comparative analysis. The alignment between samples is achieved by nonlinear robust ridge regression. The correspondence estimates are guided in a semi-supervised fashion by prior information which is derived from sequenced tandem mass spectra. RESULTS: The semi-supervised method for finding correspondences was successfully applied to aligning highly complex protein samples, even if they exhibit large variations due to different biological conditions. A large-scale experiment clearly demonstrates that the proposed method bridges the gap between statistical data analysis and label-free quantitative differential proteomics. AVAILABILITY: The software will be available on the website http://people.inf.ethz.ch/befische/proteomics.

Algorithms↗
PubMed2006

Multi-Q: a fully automated tool for multiplexed protein quantitation.

The iTRAQ labeling method combined with shotgun proteomic techniques represents a new dimension in multiplexed quantitation for relative protein expression measurement in different cell states. To expedite the analysis of vast amounts of spectral data, we present a fully automated software package, called Multi-Q, for multiplexed iTRAQ-based quantitation in protein profiling. Multi-Q is designed as a generic platform that can accommodate various input data formats from search engines and mass spectrometer manufacturers. To calculate peptide ratios, the software automatically processes iTRAQ's signature peaks, including peak detection, background subtraction, isotope correction, and normalization to remove systematic errors. Furthermore, Multi-Q allows users to define their own data-filtering thresholds based on semiempirical values or statistical models so that the computed results of fold changes in peptide ratios are statistically significant. This feature facilitates the use of Multi-Q with various instrument types with different dynamic ranges, which is an important aspect of iTRAQ analysis. The performance of Multi-Q is evaluated with a mixture of 10 standard proteins and human Jurkat T cells. The results are consistent with expected protein ratios and thus demonstrate the high accuracy, full automation, and high-throughput capability of Multi-Q as a large-scale quantitation proteomics tool. These features allow rapid interpretation of output from large proteomic datasets without the need for manual validation. Executable Multi-Q files are available on Windows platform at http://ms.iis.sinica.edu.tw/Multi-Q/.

Chromatography, Liquid↗
PubMedDate not supplied

Proteomic analysis of ductal carcinoma of the breast using laser capture microdissection, LC-MS, and 16O/18O isotopic labeling.

The goal of this study was the development of a method for quantitative expression proteomics on the limited sample amounts obtained through laser capture microdissection (LCM) of tissues, e.g., approximately 10 000 cells, which typically contain roughly 1-4 microg protein. The 16O/18O labeling method was selected as an approach to measure differential expression. A sample preparation protocol including lysis, digestion and 16O/18O labeling was first developed for LCM cell samples. The selected protocol was examined using two LCM caps of 10 000 cells from invasive ductal carcinoma of the breast and shown to be repeatable. A further test of LC-IT-MS/MS in combination with the 16O/18O post-digestion labeling method for studying low level samples was conducted first on a single protein (BSA) and then on a 5-standard protein mixture digest of different protein amounts, each with a total content approximately 1 microg. Next, protein expression was compared between 10 000 cells, each of microdissected normal ductal epithelium and metastatic ductal carcinoma, using the developed method. The proteins from the microdissected cells were extracted, precipitated, digested with trypsin and then 16O/18O labeled. The normal and metastatic cell samples were analyzed using reversed phase LC-ESI-MS/MS on the ion trap mass spectrometer. A total of 76 proteins were identified. Some, such as mitochondrial isocitrate dehydrogenase, actin and 14-3-3 protein xi/delta were found to be significantly up-regulated in the breast tumor cells.

Amino Acid Sequence↗
PubMed2005

Functional differentiation of bundle sheath and mesophyll maize chloroplasts determined by comparative proteomics.

Chloroplasts of maize (Zea mays) leaves differentiate into specific bundle sheath (BS) and mesophyll (M) types to accommodate C4 photosynthesis. Consequences for other plastid functions are not well understood but are addressed here through a quantitative comparative proteome analysis of purified M and BS chloroplast stroma. Three independent techniques were used, including cleavable stable isotope coded affinity tags. Enzymes involved in lipid biosynthesis, nitrogen import, and tetrapyrrole and isoprenoid biosynthesis are preferentially located in the M chloroplasts. By contrast, enzymes involved in starch synthesis and sulfur import preferentially accumulate in BS chloroplasts. The different soluble antioxidative systems, in particular peroxiredoxins, accumulate at higher levels in M chloroplasts. We also observed differential accumulation of proteins involved in expression of plastid-encoded proteins (e.g., EF-Tu, EF-G, and mRNA binding proteins) and thylakoid formation (VIPP1), whereas others were equally distributed. Enzymes related to the C4 shuttle, the carboxylation and regeneration phase of the Calvin cycle, and several regulators (e.g., CP12) distributed as expected. However, enzymes involved in triose phosphate reduction and triose phosphate isomerase are primarily located in the M chloroplasts, indicating that the M-localized triose phosphate shuttle should be viewed as part of the BS-localized Calvin cycle, rather than a parallel pathway.

Antioxidants↗
PubMed2025

Spatiotemporally resolved GPCR interactome uncovers unique mediators of receptor agonism.

Cellular signaling by membrane G protein-coupled receptors (GPCRs) is governed by a complex and diverse array of mechanisms. The dynamics of a GPCR interactome, as it evolves over time and space in response to an agonist, provide a unique perspective on pleiotropic signaling decoding and functional selectivity at the cellular level. In this study, we utilized proximity-based APEX2 proteomics to investigate the interaction network of the luteinizing hormone receptor (LHR) on a minute-to-minute timescale. We developed an analytical approach that integrates quantitative multiplexed proteomics with temporal reference profiles, creating a platform to identify the proteomic environment of APEX2-tagged LHR at the nanometer scale. LHR activity is finely regulated spatially, leading to the identification of putative interactors, including the Ras-related GTPase RAP2B, which modulate both receptor signaling and post-endocytic trafficking. This work provides a valuable resource for spatiotemporal nanodomain mapping of LHR interactors across subcellular compartments.

Humans↗
PubMed2026

A chromosomal gtrB homolog and dam differentially contribute to dry-heat and high hydrostatic pressure resistance in Salmonella enterica.

Salmonella enterica can persist in low-moisture foods and shows enhanced dry-heat resistance under low water activity, posing significant food safety challenges. However, the genetic basis of extreme dry-heat resistance and its relationship with other processing stresses remain unclear. In this study, twelve S. enterica strains were screened for dry-heat treatment at 60&#xa0;&#xb0;C and 80&#xa0;&#xb0;C, with S. Infantis CICC21649 identified as the most resistant strain. Comparative genomics and transcriptional analysis identified candidate genes related to envelope integrity and regulation, including gtrB and dam. Deletion of the chromosomal gtrB homolog reduced dry-heat resistance, producing an additional 0.91-log10 reduction relative to the parent strain at 80&#xa0;&#xb0;C. Deletion of dam caused broader stress sensitivity, reducing resistance to both dry heat and high hydrostatic pressure, with the stronger phenotype observed under high hydrostatic pressure. Proteomic analysis of the chromosomal gtrB homolog mutant revealed broad alterations in envelope-associated proteins, transport functions, oxidative stress pathways, and central metabolism under dry-heat stress. These findings indicate that the chromosomal gtrB homolog is an important contributor to extreme dry-heat resistance, whereas dam contributes to resistance against both dry-heat and high hydrostatic pressure, likely through a broader regulatory role in stress adaptation. These results reveal distinct structural and regulatory layers underlying stress adaptation in S. enterica and provide practical guidance for low-moisture food processing by highlighting the need to account for strain-dependent and stress-specific resistance during process validation.

Hydrostatic Pressure↗
PubMed2026

Proteome Profiling Reveals NQO2 Activity Contributing to Proteasome Inhibitor Resistance in Multiple Myeloma Cell Lines.

Proteasome inhibitors (PIs) are frontline therapies for multiple myeloma (MM). Although MM patients initially respond to PIs, resistance frequently emerges. While all PIs nominally target the same proteasomal catalytic subunit (PSMB5), the extent to which resistance mechanisms are the same or different among different PIs or between patients is poorly understood. To address this, we performed proteome and phosphoproteome profiling of 12 MM cell line models, comprising four parental lines (AMO-1, ARH77, L363, and RPMI8226) paired with lines that acquired resistance to bortezomib (BTZ) or carfilzomib (CFZ). Over 7000 proteins and up to 10,000 phosphopeptides were identified per cell line, enabling a comprehensive comparative analysis of shared and cell line-specific resistance signatures at the protein level. Data analysis revealed surprisingly few changes in the phosphoproteome but substantial reprogramming of the proteome in most models. Beyond known adaptations such as the overexpression of the PI target PSMB5 and the drug efflux transporter ABCB1, we identified the oxidoreductases NQO1 and NQO2 as significantly upregulated proteins under chronic proteotoxic stress across several models. Pharmacological follow up in PI resistant AMO-1 cells showed that NQO2 inhibition by imatinib fully restored CFZ sensitivity, validating NQO2 as a contributor to resistance formation in this model system.

Humans↗
PubMed2006

Salt stress response in rice: genetics, molecular biology, and comparative genomics.

Significant progress has been made in unraveling the molecular biology of rice in the past two decades. Today, rice stands as a forerunner amongst the cereals in terms of details known on its genetics. Evidence show that salt tolerance in plants is a quantitative trait. Several traditional cultivars, landraces, and wild types of rice like Pokkali, CSR types, and Porteresia coarctata appear as promising materials for donation of requisite salt tolerance genes. A large number of quantitative trait loci (QTL) have been identified for salt tolerance in rice through generation of recombinant inbred lines and are being mapped using different types of DNA markers. Salt-tolerant transgenic rice plants have been produced using a host of different genes and transcript profiling by micro- and macroarray-based methods has opened the gates for the discovery of novel salt stress mechanisms in rice, and comparative genomics is turning out to be a critical input in this respect. In this paper, we present a comprehensive review of the genetic, molecular biology, and comparative genomics effort towards the generation of salt-tolerant rice. From the data on comprehensive transcript expression profiling of clones representing salt-stress-associated genes of rice, it is shown that transcriptional and translational machineries are important determinants in controlling salt stress response, and gene expression response in tolerant and susceptible rice plants differs mainly in quantitative terms.

Acclimatization↗