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PubMed2005

Proteomic profiling for cancer progression: Differential display analysis for the expression of intracellular proteins between regressive and progressive cancer cell lines.

Tumor development and progression consist of a series of complex processes involving multiple changes in gene expression (Paolo et al. Physiol. Rev., 1993, 73, 161-195; Lance et al. Cell., 1991, 64, 327-336). Tumor cells acquire an invasive and metastatic phenotype that is the main cause of death for cancer patients. Therefore, for early diagnosis and effective therapeutic intervention, we need to detect the alterations associated with transition from benign to malignant tumor cells on a molecular basis. To unravel alterations concerned with tumor progression, the proteomic approach has attracted great attention because it can identify qualitative and quantitative changes in protein composition, including post-translational modifications. In this study, we performed proteomic differential display analysis for the expression of intracellular proteins in the regressive cancer cell line QR-32 and the inflammatory cell-promoting progressive cancer cell line QRsP-11 of murine fibrosarcoma by two-dimensional gel electrophoresis and mass spectrometry using an Agilent 1100 LC/MSD Trap XCT. We found 11 protein spots whose expression was different between QR-32 and QRsP-11 cells and identified nine proteins, seven of which, calreticulin precursor, tropomyosin 1 alpha chain, annexin A5, heat shock protein (HSP)90-alpha, HSP90-beta, PEBP, and Prx II, were over-expressed, and two, Anp32e and HDGF, which were down-regulated. The results suggest an important complementary role for proteomics in identification of molecular abnormalities in tumor progression.

Animals↗

PubMed2002

The challenges of developing a sound proteomics strategy.

This paper will review the challenges of developing a proteomics strategy. A key issue is the integration of the two-dimensional (2-D) gel platform with mass spectrometry measurements. The use of both matrix-assisted laser/desorption ionization (on off-line coupling) and electrospray (on-line) ionization are complementary. While the use of one-dimensional and 2-D gels are essential to many aspects of proteomics research (sample preparation, preliminary fractionation and quantitation, storage of protein components), the emergence of shotgun sequencing based on high performance liquid chromatography and tandem mass spectrometry offers a powerful new approach. The latter has particular utility in the characterization of low level samples and complex post-translational modifications. The development of capillary columns, such as 75 to 150 micron, that can be packed in a reproducible manner has been a key step in the development of high sensitivity liquid chromatography/mass spectrometry analysis.

Chromatography↗

PubMed2006

Proteomic analysis of estrogen response of premalignant human breast cells using a 2-D liquid separation/mass mapping technique.

A 2-D liquid-phase separation method based on chromatofocusing and nonporous silica RP-HPLC followed by ESI-TOF-MS was used to analyze proteins in whole cell lysates from estrogen-treated and untreated premalignant, estrogen-responsive cell line MCF10AT1 cells. 2-D mass maps in the pH range 4.6-6.0 were generated with good correlation to theoretical M(r) values for intact proteins. Proteins were identified based on intact M(r), pI and PMF, or MS/MS sequencing. About 300 unique proteins were identified and 120 proteins in mass range 5-75 kDa were quantified upon treatment of estrogen. Around 40 proteins were found to be more highly expressed (>four-fold) and 17 were down-regulated (>four-fold) in treated cells. In our study, we found that many altered proteins have characteristics consistent with the development of a malignant phenotype. Some of them have a role in the ras pathway or play an important role in signal pathways. These changed proteins might be essential in the estrogen regulation mechanism. Our study highlights the use of the MCF10AT1 cell line to examine estrogen-induced changes in premalignant breast cells and the ability of the 2-D mass mapping technique to quantitatively study protein expression changes on a proteomic scale.

Blotting, Western↗

PubMed2006

IgA nephropathy associated with Hodgkin's disease in children: a case report, literature review and urinary proteome analysis.

We report herein a rare case of IgAN associated with Hodgkin's disease in a 14-year-old boy. Clinical manifestations and laboratory parameters were improved after treatment with CHOP chemotherapy and enalapril. Urinary proteins were isolated and examined using state-of-the-art proteomic technology, before and during the treatment course. Two-dimensional gel electrophoresis showed obvious alterations in the urinary proteome profile in response to such therapy. Quantitative intensity analysis and gel mapping revealed 14 altered proteins with reduced excretion levels during the treatment course, including albumin, albumin complexed with decanoic acid, alpha-1 antitrypsin, cadherin-11 precursor, collagen alpha 1 (VI) chain precursor, complement C1q tumor necrosis factor-related protein, Ig heavy chain, Ig light chain, kininogen, inter-alpha-trypsin inhibitor (alpha-1 microglobulin), inter-alpha-trypsin inhibitor heavy chain, leucine-rich alpha-2 glycoprotein, beta-2 microglobulin, and transferrin precursor. Their potential roles in the pathogenesis and pathophysiology of IgAN are discussed.

Adolescent↗

PubMed2006

Proteomic analysis of MCF-7 cell lines expressing the zinc-finger or the proline-rich domain of retinoblastoma-interacting-zinc-finger protein.

To identify a growth-promoting activity related to retinoblastoma-interacting-zinc-finger (RIZ) protein, differential protein expression of MCF-7 cell lines expressing the zinc-finger or the proline-rich domain of RIZ protein was analyzed by a robust bottom-up mass-spectrometry proteomic approach. Spots corresponding to qualitative and quantitative differences in protein expression have been selected and identified. Some of these proteins have been previously reported as being associated with different types of carcinomas or involved in cell proliferation and differentiation. Knowledge of specific differentially expressed proteins by MCF-7-derived cell lines expressing RIZ different domains will provide the basis for identifying a growth-promoting activity related to RIZ gene products.

Biomarkers, Tumor↗

PubMed2005

[Proteomics and its role in medicine].

Proteomics is a new methodological and conceptual approach to the study of live systems, which aims to map the whole proteom - the protein complement of genome. It aspires to describe quantitatively and qualitatively all proteins present at the given moment in the cell, tissue or the organism. The principal tools of proteomics are separation techniques based on electrophoresis and chromatography, which are used to fractionate complex protein mixtures and namely the mass spectrometry used for the identification of individual proteins. Proteomics represents very young and rapid developing specialization, which has already proved its valuable potential for the study of various physiological and pathlogical molecular mechanisms and for the direct use in the diagnostics of serious diseases.

Chromatography↗

PubMed2004

Computational physiology and the Physiome Project.

Bioengineering analyses of physiological systems use the computational solution of physical conservation laws on anatomically detailed geometric models to understand the physiological function of intact organs in terms of the properties and behaviour of the cells and tissues within the organ. By linking behaviour in a quantitative, mathematically defined sense across multiple scales of biological organization--from proteins to cells, tissues, organs and organ systems--these methods have the potential to link patient-specific knowledge at the two ends of these spatial scales. A genetic profile linked to cardiac ion channel mutations, for example, can be interpreted in relation to body surface ECG measurements via a mathematical model of the heart and torso, which includes the spatial distribution of cardiac ion channels throughout the myocardium and the individual kinetics for each of the approximately 50 types of ion channel, exchanger or pump known to be present in the heart. Similarly, linking molecular defects such as mutations of chloride ion channels in lung epithelial cells to the integrated function of the intact lung requires models that include the detailed anatomy of the lungs, the physics of air flow, blood flow and gas exchange, together with the large deformation mechanics of breathing. Organizing this large body of knowledge into a coherent framework for modelling requires the development of ontologies, markup languages for encoding models, and web-accessible distributed databases. In this article we review the state of the field at all the relevant levels, and the tools that are being developed to tackle such complexity. Integrative physiology is central to the interpretation of genomic and proteomic data, and is becoming a highly quantitative, computer-intensive discipline.

Biophysical Phenomena↗

PubMed2002

De novo peptide sequencing and quantitative profiling of complex protein mixtures using mass-coded abundance tagging.

Proteomic studies require efficient, robust, and practical methods of characterizing proteins present in biological samples. Here we describe an integrated strategy for systematic proteome analysis based on differential guanidination of C-terminal lysine residues on tryptic peptides followed by capillary liquid chromatography-electrospray tandem mass spectrometry. The approach, termed mass-coded abundance tagging (MCAT), facilitates the automated, large-scale, and comprehensive de novo determination of peptide sequence and relative quantitation of proteins in biological samples in a single analysis. MCAT offers marked advantages as compared with previously described methods and is simple, economic, and effective when applied to complex proteomic mixtures. MCAT is used to identify proteins, including polymorphic variants, from complex mixtures and measure variation in protein levels from diverse cell types.

Algorithms↗

PubMed2006

Evaluation of D10-Leu metabolic labeling coupled with MALDI-MS analysis in studying the response of the yeast proteome to H2O2 challenge.

An efficient D10-Leu metabolic-labeling method combined with isotope-ratio quantitation by MALDI-TOF MS was used to probe the response of the yeast proteome to H2O2. Control cultures correct for effects not associated with H2O2 challenge. A stress-response index to H2O2 (SRIH2O2) is defined, and values are reported for seven proteins at 45-225 min following exposure to 0.4 mM H2O2. The time course of protein accumulation in unstressed cells following the H10- to D10-SCD switch suggests that proteome responses at <45 min could be monitored by addition of excess D10-Leu to H10-cultures.

Deuterium↗

PubMed2007

Quantitative analysis of 2D gels.

The use of 2D electrophoresis for comparative proteomics allows the revelation of variations of protein relative amounts according to various physiological or genetic criteria. The statistical significance of these results is related to different factors, from the experimental design to the statistical tests. In this chapter we describe different parameters that should be taken into account in the experimental design and during image acquisition, and we present different programs for the normalization of quantitative data, the selection of reproducible spots according to user-defined criteria, and the selection of spots showing qualitative and significant quantitative variations.

Algorithms↗

PubMed2005

Peptidomic analysis of human blood specimens: comparison between plasma specimens and serum by differential peptide display.

The human Plasma Proteome Project pilot phase aims to analyze serum and plasma specimens to elucidate specimen characteristics by various proteomic techniques to ensure sufficient sample quality for the HUPO main phase. We used our proprietary peptidomics technologies to analyze the samples distributed by HUPO. Peptidomics summarizes technologies for visualization, quantitation, and identification of the low-molecular-weight proteome (<15 kDa), the "peptidome." We analyzed all four HUPO specimens (EDTA plasma, citrate plasma, heparin plasma, and serum) from African- and Asian-American donors and compared them to in-house collected Caucasian specimens. One main finding focuses on the most suitable method of plasma specimen collection. Gentle platelet removal from plasma samples is beneficial for improved specificity. Platelet contamination or activation of platelets by low temperature prior to their removal leads to distinct and multiple peptide signals in plasma samples. Two different specimen collection protocols for platelet-poor plasma are recommended. Further emphasis is placed on the differences between plasma and serum on a peptidomic level. A large number of peptides, many of them in rather high abundance, are only present in serum and not detectable in plasma. This ex vivo generation of multiple peptides hampers discovery efforts and is caused by a variety of factors: the release of platelet-derived peptides, other peptides derived from cellular components or the clot, enzymatic activities of coagulation cascades, and other proteases. We conclude that specimen collection is a crucial step for successful peptide biomarker discovery in human blood samples. For analysis of the low-molecular-weight proteome, we recommend the use of platelet-depleted EDTA or citrate plasma.

Anticoagulants↗

PubMed2025

Core passive and facultative mTOR-mediated mechanisms coordinate mammalian protein synthesis and decay.

The maintenance of cellular homeostasis requires tight regulation of proteome concentration and composition. To achieve this, protein production and elimination must be robustly coordinated. However, the mechanistic basis of this coordination remains unclear. Here, we address this question using quantitative live-cell imaging, computational modeling, transcriptomics, and proteomics approaches. We found that protein decay rates systematically adapt to global alterations of protein synthesis rates. This adaptation is driven by a core passive mechanism supplemented by facultative changes in mechanistic/mammalian target of rapamycin (mTOR) signaling. Passive adaptation hinges on changes in the production rate of the machinery governing protein decay and allows for partial maintenance of the cellular proteome. Sustained changes in mTOR signaling provide an additional layer of adaptation unique to naive pluripotent stem cells, allowing for near-perfect maintenance of proteome composition. Our work unravels the mechanisms protecting the integrity of mammalian proteomes upon variations in protein synthesis rates. A record of this paper's transparent peer review process is included in the supplemental information.

TOR Serine-Threonine Kinases↗

PubMed2026

Characterizing the impact of plasma protein levels on human brain structure and disorders leveraging integrative multi-omics analysis.

With recent advances in high-throughput proteomic technologies, population-scale plasma proteomics datasets, often linked to extensive genetic and phenotypic information, have become increasingly accessible. Yet the relationships between circulating protein levels, brain imaging phenotypes, and risk for neurological and psychiatric disorders remain largely unexplored. Proteome-wide association studies offer a promising approach for elucidating biological mechanisms that connect genetic variation to complex brain-related traits and diseases. In this study, we integrated protein quantitative trait loci (pQTLs) from the two largest plasma proteomic resources (the UK Biobank Pharma Proteomics Project [UKB-PPP] and Ferkingstad et al. [deCODE]) with genome-wide association studies of brain imaging-derived phenotypes in UK Biobank using Mendelian randomization and colocalization analyses. We identified 120 cis and 20 trans associations between plasma proteins and imaging phenotypes and validated these findings using brain tissue-derived proteomic and transcriptomic datasets. Multivariable Mendelian randomization revealed eleven plasma proteins (coding genes APOE, ARL3, MICB, NSF, RHOC, RSPO3, ENPP2, BTN2A1, EIF2AK3, MRVI1, and OPLAH) with significant direct effects on the risk of Alzheimer's disease, Parkinson's disease, multiple sclerosis, bipolar disorder, and schizophrenia. Single-cell expression and pathway enrichment analyses further revealed cell-type-specific effects and distinct biological processes underlying these protein-disease associations. Together, these findings demonstrate robust links between plasma protein variation and brain structure, delineate protein-disease pathways, and highlight the cellular and molecular mechanisms that contribute to neurobiological diversity and pathology.

Journal Article↗

PubMed2005

Analysis of the Escherichia coli RNA degradosome composition by a proteomic approach.

The RNA degradosome is a bacterial protein machine devoted to RNA degradation and processing. In Escherichia coli it is typically composed of the endoribonuclease RNase E, which also serves as a scaffold for the other components, the exoribonuclease PNPase, the RNA helicase RhlB, and enolase. Several other proteins have been found associated to the core complex. However, it remains unclear in most cases whether such proteins are occasional contaminants or specific components, and which is their function. To facilitate the analysis of the RNA degradosome composition under different physiological and genetic conditions we set up a simplified preparation procedure based on the affinity purification of FLAG epitope-tagged RNase E coupled to Multidimensional Protein Identification Technology (MudPIT) for the rapid and quantitative identification of the different components. By this proteomic approach, we show that the chaperone protein DnaK, previously identified as a "minor component" of the degradosome, associates with abnormal complexes under stressful conditions such as overexpression of RNase E, low temperature, and in the absence of PNPase; however, DnaK does not seem to be essential for RNA degradosome structure nor for its assembly. In addition, we show that normalized score values obtain by MudPIT analysis may be taken as quantitative estimates of the relative protein abundance in different degradosome preparations.

Endoribonucleases↗

PubMed2026

Cross-ancestry proteome-wide Mendelian randomization prioritizes 12 plasma protein candidates for breast cancer risk.

The plasma proteome provides a molecular bridge between genetic variation and disease risk, yet its contribution to breast cancer susceptibility across ancestries remains unclear. We conducted a proteome-wide Mendelian randomization (MR) study of 2,923 plasma proteins using cis-protein quantitative trait loci from 34,557 European participants in the UK Biobank Pharma Proteomics Project, integrated with genome-wide association studies of 156,901 breast cancer cases and 204,634 controls of European, East Asian, and African ancestries. Cross-ancestry meta-analysis identified 12 candidate proteins associated with breast cancer risk (P < 2.5×10-5), including six previously reported and six newly implicated in MR studies. DNPH1 showed cross-ancestry heterogeneity, with a risk-increasing association in European populations and a nominally inverse association in East Asian populations. CASP8, RALB, and USP28 displayed subtype-differentiated associations. Orthogonal validation provided variable support: six demonstrated strong evidence of statistical colocalization; four replicated in an independent European proteomic dataset (deCODE, n = 35,559); two replicated in an independent East Asian proteomic dataset (JCTF, n = 1,384); and four were supported by polygenic-score analyses in the ancestrally diverse All of Us cohort (9,250 cases, 214,857 controls). These findings prioritize a high-confidence subset of plasma proteins, including LRRC25, PARK7, and LRRC37A2, for future mechanistic and translational investigation.

Mendelian randomization↗

PubMed2005

The probability distribution for a random match between an experimental-theoretical spectral pair in tandem mass spectrometry.

Proteomic techniques are fast becoming the main method for qualitative and quantitative determination of the protein content in biological systems. Despite notable advances, efficient and accurate analysis of high throughput proteomic data generated by mass spectrometers remains one of the major stumbling blocks in the protein identification problem. We present a model for the number of random matches between an experimental MS-MS spectrum and a theoretical spectrum of a peptide. The shape of the probability distribution is a function of the experimental accuracy, the number of peaks in the experimental spectrum, the length of the interval over which the peaks are distributed, and the number of theoretical spectral peaks in this interval. Based on this probability distribution, a goodness-of-fit tool can be used to yield fast and accurate scoring schemes for peptide identification through database search. In this paper, we describe one possible implementation of such a method and compare the performance of the resulting scoring function with that of SEQUEST. In terms of speed, our algorithm is roughly two orders of magnitude faster than the SEQUEST program, and its accuracy of peptide identification compares favorably to that of SEQUEST. Moreover, our algorithm does not use information related to the intensities of the peaks.

Algorithms↗

PubMed2007

Banana (Musa spp.) as a model to study the meristem proteome: acclimation to osmotic stress.

Banana (Musa spp.) multiple shoot meristems are an excellent model to study the meristem proteome. Using a 2-DE protocol developed for small amounts of tissue and MS-based cross species polypeptide identification, we have revealed the meristem proteome and investigated the influence of sucrose-mediated osmotic stress in a dehydration-tolerant variety. Proteins that were significantly up- or down-regulated due to the high-sucrose treatment were classified using non-parametric univariate statistics. Our results suggest that the maintenance of an osmoprotective intracellular sucrose concentration, the enhanced expression of particular genes of the energy-conserving glycolysis and the conservation of the cell wall integrity are essential to maintain homeostasis, to acclimate and to survive dehydration. By comparing the dehydration-tolerant variety with a dehydration-sensitive variety, we were able to distinguish several genotype-specific proteins (isoforms), and could associate the dehydration-tolerant variety with proteins involved in energy metabolism (e.g., phosphoglycerate kinase, phosphoglucomutase, UDP-glucose pyrophosphorylase) and proteins that are associated with stress adaptation (e.g., OSR40-like protein, abscisic stress ripening protein-like protein). This work shows that proteome analysis can be used successfully to perform quantitative difference analysis and to characterize genetic variations in a recalcitrant crop.

Electrophoresis, Gel, Two-Dimensional↗

PubMed2003

Targeted lipidomics using electron capture atmospheric pressure chemical ionization mass spectrometry.

There is an increasing need to be able to conduct quantitative lipidomics analyses as a complement to proteomics studies. The highest specificity for proteomics analysis can be obtained using methodology based on electrospray ionization (ESI) or atmospheric pressure chemical ionization (APCI) coupled with liquid chromatography/tandem mass spectrometry (LC/MS/MS). For lipidomics analysis it is often necessary to be able to separate enantiomers and regioisomers. This can be very challenging when using methodology based on conventional reversed-phase chromatography. Normal-phase chromatography using chiral columns can provide dramatic improvements in the resolution of enantiomers and regioisomers. However, conventional ESI- and APCI-MS/MS has limited sensitivity, which makes it difficult to conduct studies in cell culture systems where only trace amounts of non-esterified bioactive lipids are present. The use of electron capture APCI-MS/MS overcomes this problem. Enantiomers and regioisomers of diverse bioactive lipids can be quantified using stable isotope dilution methodology coupled with normal-phase chiral chromatography and electron capture APCI-MS/MS. This methodology has allowed a lipidomics profile from rat epithelial cells maintained in culture to be delineated and allowed the effect of a non-selective lipoxygenase inhibitor to be assessed.

Animals↗