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At least 19 recordsLinked to original sources

Comparison of a Salmonella typhimurium proteome defined by shotgun proteomics directly on an LTQ-FT and by proteome pre-fractionation on an LCQ-DUO.

Shotgun proteomics is rapidly becoming one of the most efficient and popular tools to examine protein expression in cells. Numerous laboratories now have a wide array of low- and high-performance mass spectrometry instrumentation necessary to complete proteome-wide projects. Often these laboratories have time and financial constraints that prohibit all projects from being conducted on high-performance state-of-the-art mass spectrometers. Here, we compare shotgun proteomic results using a direct 'lyse, digest and analyse' approach on a high-performance mass spectrometer (i.e. the LTQ-FT) with the results from a much lower-performance instrument (i.e. the LCQ-DUO) where, for the latter, various traditional protein pre-fractionation steps and gas-phase fractionation were used to increase the proteome coverage. Our results demonstrate that shotgun proteomic analyses conducted on the lower-performance LCQ-DUO mass spectrometer could adequately characterize a PhoP constitutive strain of Salmonella typhimurium if proteome pre-fractionation steps and gas-phase fractionation were included.

Chromatography, High Pressure Liquid↗

Pilot study of the Human Proteome Organisation Brain Proteome Project: applying different 2-DE techniques to monitor proteomic changes during murine brain development.

The Human Proteome Organisation Brain Proteome Project aims at coordinating neuroproteomic activities with respect to analysis of development, aging, and evolution in human and mice and at analysing normal aging processes as well as neurodegenerative diseases. Our group participated in the mouse pilot study of this project using two different 2-DE systems, to find out the optimal conditions for comprehensive gel-based differential proteome analysis. Besides the assessment of the best methodical conditions the question of "How many biological replicate analyses have to be performed to get reliable statistically validated results?" was addressed. In total 420 differences were detected in all analyses. Both 2-DE methods were found to be suitable for comprehensive differential proteome analysis. Nevertheless, each of the methods showed substantial advantages and disadvantages resulting in the fact that modification of both systems is essential. From our results we can draw the conclusions that for the future optimal quantitative differential gel-based brain proteome analyses the sample preparation has to be slightly changed, the resolution of the first as well as the second dimension has to be advanced, the number of experiments has to be increased and that the 2D-DIGE system should be applied.

Aging↗

Rice proteomics: a cornerstone for cereal food crop proteomes.

Proteomics-a systematic study of proteins present in a cell, tissue, organ, or organism at a particular moment during the life cycle-that began with classical two-dimensional electrophoresis and its advancement during the 1990s, has been revolutionized by a series of tremendous technological developments in mass spectrometry (MS), a core technology. Proteomics is exerting its influence on biological function of genes and genomes in the era (21st century) of functional genomics, and for this reason yeast, bacterial, and mammalian systems are the best examples. Although plant proteomics is still in its infancy, evolving proteomic technologies and the availability of the genome sequences of Arabidopsis thaliana (L.) Heyhn, and rice (Oryza sativa L.), model dicotyledoneous and monocotyledoneous (monocot) species, respectively, are propelling it towards new heights, as evidenced by the rapid spurt in worldwide plant proteome research. Rice, with an immense socio-economic impact on human civilization, is a representative model of cereal food crops, and we consider it as a cornerstone for functional genomics of cereal plants. In this review, we look at the history and the current state of monocot proteomes, including barley, maize, and wheat, with a central focus on rice, which has the most extensive proteomic coverage to date. On one side, we highlight advances in technologies that have generated enormous amount of interest in plant proteomics, and the other side summarizes the achievements made towards establishing proteomes during plant growth & development and challenge to environmental factors, including disease, and for studying genetic relationships. In light of what we have learned from the proteomic journey in rice and other monocots, we finally reveal and assess their impact in our continuous strive towards completion of their full proteomes.

Crops, Agricultural↗

System, trends and perspectives of proteomics in dicot plants Part I: Technologies in proteome establishment.

The first 3 years of the 21st century have seen the impact of plant proteomics on functional genomics that has enhanced our understanding, not only on the plant genome(s), but also more importantly, on the functional aspect of proteins. This is mainly due to availability of the complete genome sequence of the Arabidopsis thaliana-a dicotyledoneous (dicot) model plant-and technological advancements in proteomics. Proteomic analyses of a variety of dicot plants, including both Arabidopsis and the model legume species, barrel medic (Medicago truncatula), have greatly helped in an efficient separation, identification and cataloguing of a large number of proteins, and thereby defining their proteomes. Therefore, we have composed an inclusive review on dicot plant materials, as of February 2004, that provides system, trends and perspectives of proteomics in growth and development and the environment. The review is summarized and discussed as three individual, but interlinked, entities: Part I, technologies in proteome establishment (this review), Part II, proteomes of the complex developmental stages [G.K. Agrawal, M. Yonekura, Y. Iwahashi, H. Iwahashi, R. Rakwal, J. Chromatogr. B (2004)], and Part III, unraveling the proteomes influenced by the environment, and at the levels of function and genetic relationships [G.K. Agrawal, M. Yonekura, Y. Iwahashi, H. Iwahashi, R. Rakwal, J. Chromatogr. B (2004)]. This review deals with the diverse proteomic technologies being used in proteome development of different dicot plants.

Arabidopsis↗

Single-Cell Proteomics Reveals Proteome Remodeling and Cellular Heterogeneity During NGF-Induced PC12 Neuronal Differentiation.

Single-cell proteomics enables direct measurement of cellular heterogeneity during dynamic biological processes, but its application to fragile and highly adherent neuronal models remains challenging. Here, we developed and applied an optimized single-cell proteomics workflow to characterize proteome remodeling during nerve growth factor (NGF)-induced differentiation of PC12 cells. To enable reliable single-cell analysis, we implemented gentle dissociation, antiaggregation strategies, and thermal inkjet-based cell dispensing, achieving high accuracy in single-cell isolation. Inclusion of n-dodecyl-β-d-maltoside (DDM) improved recovery of membrane-associated and low-solubility proteins. Coupled with LC-ion mobility-mass spectrometry, this workflow enabled quantification of 2,000-3,000 proteins per cell across the differentiation time course. Single-cell proteomic analysis revealed progressive and heterogeneous proteome remodeling during differentiation. While undifferentiated cells formed a relatively homogeneous population, later stages (Days 4-6) exhibited increased variability, including multimodal protein abundance distributions and separation into distinct subpopulations. Dimensionality reduction, clustering, and non-negative matrix factorization identified multiple coexisting proteomic states within the same time points, reflecting asynchronous differentiation trajectories. These subpopulations were characterized by coordinated differences in pathways related to intracellular trafficking, protein translation, cytoskeletal organization, and neuronal maturation. Comparison with bulk proteomics demonstrated that proteins associated with differentiated neuronal states, including those involved in neurite formation and structural remodeling, are underrepresented in population-averaged measurements but are enriched within specific single-cell subpopulations. Temporal and cluster-resolved analyses further revealed distinct protein expression trajectories, including early decreases in cell cycle and metabolic pathways and later increases in neuronal structural and regulatory proteins. Together, this study establishes an optimized workflow for single-cell proteomics of neuronal systems and demonstrates that NGF-induced PC12 differentiation proceeds through heterogeneous and divergent proteomic states that are not resolved by bulk analysis.

Animals↗

3D Proteomics: Structural, Functional, Chemical and Biomarker Discovery Proteomics With LiP-MS.

Protein structural dynamics drive changes in protein function, making the capture of such dynamics essential for interrogating biological systems. Here we review limited proteolysis coupled to mass spectrometry (LiP-MS), a structural and chemical proteomics method that uses changes in susceptibility to protease cleavage to profile proteome-wide protein structural changes within complex biological samples. In the decade since its development, LiP-MS has become a broadly used structural proteomics method, with peptide-level resolution. It has identified drug targets, delineated altered cellular pathways in response to complex perturbations, revealed structural information on otherwise challenging protein targets, and demonstrated the new concept of structural biomarkers of disease. Because LiP-MS simultaneously probes numerous types of molecular events, such as molecular binding, changes in enzyme activity, chemical modifications, allosteric conformational changes, aggregation, and unfolding, it supports a new proteomics workflow which we term 3D proteomics. This workflow enables the detection of specific functional sites within proteins that are altered upon perturbation, thereby guiding the generation of molecular hypotheses. Further, by globally profiling structural in addition to protein abundance changes, LiP-MS has proven able to greatly increase the information content of functional proteomics screens. In sum, LiP-MS has supported the development of a novel conceptual framework for generating, visualizing, and interpreting structural proteomics data with peptide level resolution, thereby comprehensively probing biological systems. Here we survey the applications of LiP-MS, discuss methodological variants developed by us and others, and describe the use of this new type of omics readout for structural, functional, chemical, and biomarker discovery proteomics.

Proteomics↗

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↗

Human plasma proteome analysis by reversed sequence database search and molecular weight correlation based on a bacterial proteome analysis.

In shotgun proteomics, proteins can be fractionated by 1-D gel electrophoresis and digested into peptides, followed by liquid chromatography to separate the peptide mixture. Mass spectrometry generates hundreds of thousands of tandem mass spectra from these fractions, and proteins are identified by database searching. However, the search scores are usually not sufficient to distinguish the correct peptides. In this study, we propose a confident protein identification method for high-throughput analysis of human proteome. To build a filtering protocol in database search, we chose Pseudomonas putida KT2440 as a reference because this bacterial proteome contains fewer modifications and is simpler than the human proteome. First, the P. putida KT2440 proteome was filtered by reversed sequence database search and correlated by the molecular weight in 1-D-gel band positions. The characterization protocol was then applied to determine the criteria for clustering of the human plasma proteome into three different groups. This protein filtering method, based on bacterial proteome data analysis, represents a rapid way to generate higher confidence protein list of the human proteome, which includes some of heavily modified and cleaved proteins.

Blood Proteins↗

[Advances in plant proteomics--I. Key techniques of proteome].

With the completion of genome sequences of the model plants, such as rice (Oryza sativa L.) and Arabidopsis thaliana, it has come into plant functional genomics era, which becomes a hard base of the appearance and development of plant proteomics. This review focuses on the background of proteomics, concept of proteomics and key techniques of proteomics. The key techniques of proteomics include separation, such as 2-DE (Two-Dimensional Electrophoresis), RP-HPLC (Reverse Phase High Performance Liquid Chromatography) and SELDI (Surface Enhanced Laser Desorption/ Ionization) protein chip, mass spectrometry, such as MALDI-TOF-MS (Matrix Assisted Laser Desorption/Ionization-Time Of Flight-Mass Spectrometry) and ESI-MS/MS (Electrospray Ionization Mass Spectrometry/Mass Spectrometry), databases related to proteomics, quantitative proteome, TAP (Tandem Affinity Purification) and yeast two-hybrid system. Challenges and prospects of proteomic techniques are discussed.

Computational Biology↗

A comparison of the HUPO Brain Proteome Project pilot with other proteomics studies.

The pilot phase of the Brain Proteome Project (BPP), the Human Proteome Organization (HUPO) initiative that focuses on studies of the brain of both humans and mice, has now been completed. Participating laboratories studied the proteomes of two human samples derived from biopsy and autopsy as well as three mouse samples from various developmental stages. With the combined and centrally reprocessed data now available, a comparison in terms of protein identifications and project organization is made between the HUPO BPP pilot and three other proteomics studies: the HUPO Plasma Proteome Project (PPP) pilot, a proteome of human blood platelets and a recently published comprehensive mouse proteome. Finally, as any comparison between large-scale proteomics datasets is decidedly non-trivial, we also evaluate and discuss several ways to go about comparing such different result sets.

Animals↗

Characterization of human tear proteome using multiple proteomic analysis techniques.

Tear proteome profiling may generate useful information for the understanding of the interaction between an eye and its contacting objects, such as a contact lens or a lens implant. This is important for designing improved eye-care devices and maintaining the health of an eye. Proteome profiles of tear fluids may also be used for disease diagnosis and prognosis. However, only a small volume of tear fluid (<5 microL) can be collected in a clinical laboratory under normal operational conditions, which makes proteome profiling a challenge. In this work we apply several proteomic analysis techniques, including gel-based and solution-based approaches with LC-ESI and LC-MALDI MS and MS/MS to gauge the relative merits of producing proteome profiles and to generate as broad a coverage of the tear proteome as possible from this small amount of sample. It is shown that a total of 54 proteins can be confidently identified using less than 5 microL of tear fluid. Of these, 44 proteins can be detected by LC-MALDI MS alone with a consumption of 2 microL of tear fluid. Furthermore, LC-MALDI can be used to determine post-translational modifications (PTMs), such as glycosylation and phosphorylation, without any sample enrichment or treatment. This work represents one of the most extensive proteome profiles (i.e., proteins identified and PTMs characterized) generated from tear fluids using clinically relevant amounts of sample.

Chromatography↗

A comparative proteomic strategy for subcellular proteome research: ICAT approach coupled with bioinformatics prediction to ascertain rat liver mitochondrial proteins and indication of mitochondrial localization for catalase.

Subcellular proteomics, as an important step to functional proteomics, has been a focus in proteomic research. However, the co-purification of "contaminating" proteins has been the major problem in all the subcellular proteomic research including all kinds of mitochondrial proteome research. It is often difficult to conclude whether these "contaminants" represent true endogenous partners or artificial associations induced by cell disruption or incomplete purification. To solve such a problem, we applied a high-throughput comparative proteome experimental strategy, ICAT approach performed with two-dimensional LC-MS/MS analysis, coupled with combinational usage of different bioinformatics tools, to study the proteome of rat liver mitochondria prepared with traditional centrifugation (CM) or further purified with a Nycodenz gradient (PM). A total of 169 proteins were identified and quantified convincingly in the ICAT analysis, in which 90 proteins have an ICAT ratio of PM:CM>1.0, while another 79 proteins have an ICAT ratio of PM:CM<1.0. Almost all the proteins annotated as mitochondrial according to Swiss-Prot annotation, bioinformatics prediction, and literature reports have a ratio of PM:CM>1.0, while proteins annotated as extracellular or secreted, cytoplasmic, endoplasmic reticulum, ribosomal, and so on have a ratio of PM:CM<1.0. Catalase and AP endonuclease 1, which have been known as peroxisomal and nuclear, respectively, have shown a ratio of PM:CM>1.0, confirming the reports about their mitochondrial location. Moreover, the 125 proteins with subcellular location annotation have been used as a testing dataset to evaluate the efficiency for ascertaining mitochondrial proteins by ICAT analysis and the bioinformatics tools such as PSORT, TargetP, SubLoc, MitoProt, and Predotar. The results indicated that ICAT analysis coupled with combinational usage of different bioinformatics tools could effectively ascertain mitochondrial proteins and distinguish contaminant proteins and even multilocation proteins. Using such a strategy, many novel proteins, known proteins without subcellular location annotation, and even known proteins that have been annotated as other locations have been strongly indicated for their mitochondrial location.

Animals↗

Toward simple, rapid, and deep plant proteome analysis with an in-cell proteomics strategy.

While liquid chromatography-mass spectrometry (LCMS) has revolutionized plant proteomics over the past decade, plant sample preparation remains a major challenge due to rigid cell walls, abundant secondary metabolites, and wide dynamic range of protein abundance. These hurdles demand laborious tissue disruption, complex precipitation, and extensive cleanup prior to LCMS analysis, limiting the widespread adoption of proteomic technologies within the plant biology community. To overcome these barriers, we introduced an "in-cell proteomics" strategy that bypasses cell lysis and protein extraction by performing digestion directly inside methanol-fixed cells. We systematically benchmarked this strategy against conventional lysate-based workflows across 4 model plants (Arabidopsis thaliana, Nicotiana benthamiana, Zea mays, and Sorghum bicolor) and 3 tissue types (leaves, pollen, and seeds). Combined with minimal input material and single-shot LCMS, the in-cell approach consistently identified 9,000 to 12,000 proteins from leaves, 7,000 to 9,000 from pollen grains, and approximately 8,000 from seeds. Our comprehensive dataset demonstrates that this in-cell digestion approach substantially simplifies plant sample preparation while delivering proteomic performance equivalent to established workflows. Finally, to demonstrate the biological utility of this approach, we characterized the proteomes of N. benthamiana leaves infected with 2 fungal strains that exhibit different host specificities. Our in-depth proteomic data revealed distinct host response signatures differentiating the host-adapted Colletotrichum destructivum from the nonhost-adapted Colletotrichum sublineola strain. Overall, this study provides a simple, unbiased alternative for plant proteomic analysis that can be readily applied to tackle complex agricultural and physiological challenges in plant biology.

Proteomics↗

Broad-based proteomic strategies: a practical guide to proteomics and functional screening.

Proteomics, the study of the proteome (the collection of all the proteins expressed from the genome in all isoforms, polymorphisms and post-translational modifications), is a rapidly developing field in which there are numerous new and often expensive technologies, making it imperative to use the most appropriate technology for the biological system and hypothesis being addressed. This review provides some guidelines on approaching a broad-based proteomics project, including strategies on refining hypotheses, choosing models and proteomic approaches with an emphasis on aspects of sample complexity (including abundance and protein characteristics), and separation technologies and their respective strengths and weaknesses. Finally, issues related to quantification, mass spectrometry and informatics strategies are discussed. The goal of this review is therefore twofold: the first section provides a brief outline of proteomic technologies, specifically with respect to their applications to broad-based proteomic approaches, and the second part provides more details about the application of these technologies in typical scenarios dealing with physiological and pathological processes. Proteomics at its best is the integration of carefully planned research and complementary techniques with the advantages of powerful discovery technologies that has the potential to make substantial contributions to the understanding of disease and disease processes.

Animals↗

The human platelet proteome mapped by peptide-centric proteomics: a functional protein profile.

Several studies have been published in which holistic approaches were used to characterise the proteome and transcriptome of human platelets. The key intent being that a deeper understanding of the normal and aberrant physiological functions of platelets can only be achieved if most biomolecular building blocks are mapped. Here we present the application of recently developed novel technologies that overcome some of the shortcomings of gel-based proteomics. Central in our approach is the so-called combined fractional diagonal chromatography (COFRADIC)-technology in which sets of representative peptides are sorted in a diagonal RP chromatographic system through a specific modification of their side chain. In this study we combined three different COFRADIC sorting techniques to analyse the proteome of human platelets. Methionyl, cysteinyl and amino terminal peptides were isolated and analysed by MS/MS. Merging the peptide identifications obtained after database searching resulted in a core set of 641 platelet proteins, which comprises the largest set identified today. In comparison to previously published platelet proteomes, we identified 404 novel platelet proteins containing a high number of hydrophobic membrane proteins and hypothetical proteins. Furthermore we discuss the observed characteristics and potential benefits of each of the different COFRADIC technologies for proteome analysis and highlight important issues that need to be considered when searching sequence databases using data obtained in peptide-centric, non-gel proteomics studies.

Animals↗

The HUPO proteomics standards initiative--overcoming the fragmentation of proteomics data.

Proteomics is a key field of modern biomolecular research, with many small and large scale efforts producing a wealth of proteomics data. However, the vast majority of this data is never exploited to its full potential. Even in publicly funded projects, often the raw data generated in a specific context is analysed, conclusions are drawn and published, but little attention is paid to systematic documentation, archiving, and public access to the data supporting the scientific results. It is often difficult to validate the results stated in a particular publication, and even simple global questions like "In which cellular contexts has my protein of interest been observed?" can currently not be answered with realistic effort, due to a lack of standardised reporting and collection of proteomics data. The Proteomics Standards Initiative (PSI), a work group of the Human Proteome Organisation (HUPO), defines community standards for data representation in proteomics to facilitate systematic data capture, comparison, exchange and verification. In this article we provide an overview of PSI organisational structure, activities, and current results, as well as ways to get involved in the broad-based, open PSI process.

Databases, Protein↗

P1D6 inhibits FnBP-induced extracellular proteome remodeling: proteomic evidence for a novel intervention strategy in atopic dermatitis.

Atopic dermatitis (AD) is an inflammatory skin disorder characterized by skin barrier impairment, chronic inflammation, and intense pruritus. Staphylococcus aureus (S. aureus) critically contributes to its pathogenesis; however, the mechanistic role of its virulence factor fibronectin-binding protein (FnBP) in keratinocytes remains poorly understood. This study used bibliometric analysis and quantitative proteomics to examine the relationship. We first performed a bibliometric analysis, revealing a sustained increase in publications on S. aureus and AD, peaking at 99 articles in 2023, with hotspots focused on skin barrier function, immune inflammation, and pediatrics. Quantitative proteomics was employed to investigate how FnBP reshapes the extracellular proteome and whether the anti-&#x3b1;5 integrin antibody P1D6 exerts interventional effects. HaCaT cells were stimulated with recombinant FnBP alone or in combination with P1D6, followed by data-independent acquisition (DIA)-based proteomic analysis of secretome changes. Proteomic analysis identified FnBP-induced differentially expressed proteins enriched in immune- and barrier-related pathways, including cell adhesion, cell junctions, and VEGFA-VEGFR2 signaling. P1D6 intervention significantly inhibited the secretome profile and identified 241 core responsive proteins, of which approximately 52% returned to baseline levels after intervention (P&#x2009;>&#x2009;0.05). These proteins were primarily enriched in pathways governing protein homeostasis, folding, proteasomal degradation, and interleukin-7 signaling. Notably, P1D6 modulated the downregulation of ATP5F1B and P4HB, key effectors within the interleukin-7 pathway. This study demonstrates that FnBP remodels the keratinocyte secretome by disrupting protein homeostasis, consequently inducing barrier injury and chronic inflammation related to AD, which can be effectively blocked by P1D6. Combined with bibliometric trends and proteomic evidence, this study focuses on FnBP, an underexplored virulence factor, and provides novel insights into AD pathogenesis and therapeutic interventions.

Humans↗

Improved proteome coverage by using high efficiency cysteinyl peptide enrichment: the human mammary epithelial cell proteome.

Automated multidimensional capillary liquid chromatography-tandem mass spectrometry (LC-MS/MS) has been increasingly applied in various large scale proteome profiling efforts. However, comprehensive global proteome analysis remains technically challenging due to issues associated with sample complexity and dynamic range of protein abundances, which is particularly apparent in mammalian biological systems. We report here the application of a high efficiency cysteinyl peptide enrichment (CPE) approach to the global proteome analysis of human mammary epithelial cells (HMECs) which significantly improved both sequence coverage of protein identifications and the overall proteome coverage. The cysteinyl peptides were specifically enriched by using a thiol-specific covalent resin, fractionated by strong cation exchange chromatography, and subsequently analyzed by reversed-phase capillary LC-MS/MS. An HMEC tryptic digest without CPE was also fractionated and analyzed under the same conditions for comparison. The combined analyses of HMEC tryptic digests with and without CPE resulted in a total of 14 416 confidently identified peptides covering 4294 different proteins with an estimated 10% gene coverage of the human genome. By using the high efficiency CPE, an additional 1096 relatively low abundance proteins were identified, resulting in 34.3% increase in proteome coverage; 1390 proteins were observed with increased sequence coverage. Comparative protein distribution analyses revealed that the CPE method is not biased with regard to protein M(r) , pI, cellular location, or biological functions. These results demonstrate that the use of the CPE approach provides improved efficiency in comprehensive proteome-wide analyses of highly complex mammalian biological systems.

Amino Acid Sequence↗