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Relevant bibliographies by topics / Low-abundance proteome

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Academic literature on the topic 'Low-abundance proteome'

Author: Grafiati

Published: 11 March 2023

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Journal articles on the topic "Low-abundance proteome"

1

Zhang, Hui. "The Plasma Proteome: High Abundance versus Low Abundance." Expert Review of Proteomics 3, no. 2 (April 2006): 175–78. http://dx.doi.org/10.1586/14789450.3.2.175.

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Taoufiq, Zacharie, Momchil Ninov, Alejandro Villar-Briones, Han-Ying Wang, Toshio Sasaki, Michael C. Roy, Francois Beauchain, et al. "Hidden proteome of synaptic vesicles in the mammalian brain." Proceedings of the National Academy of Sciences 117, no. 52 (December 21, 2020): 33586–96. http://dx.doi.org/10.1073/pnas.2011870117.

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Current proteomic studies clarified canonical synaptic proteins that are common to many types of synapses. However, proteins of diversified functions in a subset of synapses are largely hidden because of their low abundance or structural similarities to abundant proteins. To overcome this limitation, we have developed an “ultra-definition” (UD) subcellular proteomic workflow. Using purified synaptic vesicle (SV) fraction from rat brain, we identified 1,466 proteins, three times more than reported previously. This refined proteome includes all canonical SV proteins, as well as numerous proteins of low abundance, many of which were hitherto undetected. Comparison of UD quantifications between SV and synaptosomal fractions has enabled us to distinguish SV-resident proteins from potential SV-visitor proteins. We found 134 SV residents, of which 86 are present in an average copy number per SV of less than one, including vesicular transporters of nonubiquitous neurotransmitters in the brain. We provide a fully annotated resource of all categorized SV-resident and potential SV-visitor proteins, which can be utilized to drive novel functional studies, as we characterized here Aak1 as a regulator of synaptic transmission. Moreover, proteins in the SV fraction are associated with more than 200 distinct brain diseases. Remarkably, a majority of these proteins was found in the low-abundance proteome range, highlighting its pathological significance. Our deep SV proteome will provide a fundamental resource for a variety of future investigations on the function of synapses in health and disease.

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Gerszten, Robert E., Frank Accurso, Gordon R. Bernard, Richard M. Caprioli, Eric W. Klee, George G. Klee, Iftikhar Kullo, et al. "Challenges in translating plasma proteomics from bench to bedside: update from the NHLBI Clinical Proteomics Programs." American Journal of Physiology-Lung Cellular and Molecular Physiology 295, no. 1 (July 2008): L16—L22. http://dx.doi.org/10.1152/ajplung.00044.2008.

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The emerging scientific field of proteomics encompasses the identification, characterization, and quantification of the protein content or proteome of whole cells, tissues, or body fluids. The potential for proteomic technologies to identify and quantify novel proteins in the plasma that can function as biomarkers of the presence or severity of clinical disease states holds great promise for clinical use. However, there are many challenges in translating plasma proteomics from bench to bedside, and relatively few plasma biomarkers have successfully transitioned from proteomic discovery to routine clinical use. Key barriers to this translation include the need for “orthogonal” biomarkers (i.e., uncorrelated with existing markers), the complexity of the proteome in biological samples, the presence of high abundance proteins such as albumin in biological samples that hinder detection of low abundance proteins, false positive associations that occur with analysis of high dimensional datasets, and the limited understanding of the effects of growth, development, and age on the normal plasma proteome. Strategies to overcome these challenges are discussed.

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Shkrigunov, Timur, Pavel Pogodin, Victor Zgoda, Olesya Larina, Yulia Kisrieva, Maria Klimenko, Oleg Latyshkevich, Peter Klimenko, Andrey Lisitsa, and Natalia Petushkova. "Protocol for Increasing the Sensitivity of MS-Based Protein Detection in Human Chorionic Villi." Current Issues in Molecular Biology 44, no. 5 (May 9, 2022): 2069–88. http://dx.doi.org/10.3390/cimb44050140.

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An important step in the proteomic analysis of missing proteins is the use of a wide range of tissues, optimal extraction, and the processing of protein material in order to ensure the highest sensitivity in downstream protein detection. This work describes a purification protocol for identifying low-abundance proteins in human chorionic villi using the proposed “1DE-gel concentration” method. This involves the removal of SDS in a short electrophoresis run in a stacking gel without protein separation. Following the in-gel digestion of the obtained holistic single protein band, we used the peptide mixture for further LC–MS/MS analysis. Statistically significant results were derived from six datasets, containing three treatments, each from two tissue sources (elective or missed abortions). The 1DE-gel concentration increased the coverage of the chorionic villus proteome. Our approach allowed the identification of 15 low-abundance proteins, of which some had not been previously detected via the mass spectrometry of trophoblasts. In the post hoc data analysis, we found a dubious or uncertain protein (PSG7) encoded on human chromosome 19 according to neXtProt. A proteomic sample preparation workflow with the 1DE-gel concentration can be used as a prospective tool for uncovering the low-abundance part of the human proteome.

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Tang, Xiaoyue, Juan Li, Wei-gang Zhao, Haidan Sun, Zhengguang Guo, Li Jing, Zhufang She, et al. "Comprehensive map and functional annotation of the mouse white adipose tissue proteome." PeerJ 7 (July 25, 2019): e7352. http://dx.doi.org/10.7717/peerj.7352.

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White adipose tissue (WAT) plays a significant role in energy metabolism and the obesity epidemic. In this study, we sought to (1) profile the mouse WAT proteome with advanced 2DLC/MS/MS approach, (2) provide insight into WAT function based on protein functional annotation, and (3) predict potentially secreted proteins. A label-free 2DLC/MS/MS proteomic approach was used to identify the WAT proteome from female mouse WAT. A total of 6,039 proteins in WAT were identified, among which 5,160 were quantified (spanning a magnitude of 106) using an intensity-based absolute quantification algorithm, and 3,117 proteins were reported by proteomics technology for the first time in WAT. To comprehensively analyze the function of WAT, the proteins were divided into three quantiles based on abundance and we found that proteins of different abundance performed different functions. High-abundance proteins (the top 90%, 1,219 proteins) were involved in energy metabolism; middle-abundance proteins (90–99%, 2,273 proteins) were involved in the regulation of protein synthesis; and low-abundance proteins (99–100%, 1,668 proteins) were associated with lipid metabolism and WAT beiging. Furthermore, 800 proteins were predicted by SignalP4.0 to have signal peptides, 265 proteins had never been reported, and five have been reported as adipokines. The above results provide a large dataset of the normal mouse WAT proteome, which might be useful for WAT function research.

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Baumann, Sven, Uta Ceglarek, Georg Martin Fiedler, Jan Lembcke, Alexander Leichtle, and Joachim Thiery. "Standardized Approach to Proteome Profiling of Human Serum Based on Magnetic Bead Separation and Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry." Clinical Chemistry 51, no. 6 (June 1, 2005): 973–80. http://dx.doi.org/10.1373/clinchem.2004.047308.

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Abstract Background: Magnetic bead purification for the analysis of low-abundance proteins in body fluids facilitates the identification of potential new biomarkers by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS). The aims of our study were to establish a proteome fractionation technique and to validate a standardized blood sampling, processing, and storage procedure for proteomic pattern analysis. Methods: We used magnetic bead separation for proteome profiling of human blood by MALDI-TOF MS (mass range, 1000–10 000 Da) and studied the effects on the quality and reproducibility of the proteome analysis of anticoagulants, blood clotting, time and temperature of sample storage, and the number of freeze–thaw cycles of samples. Results: The proteome pattern of human serum was characterized by ∼350 signals in the mass range of 1000–10 000 Da. The proteome profile showed time-dependent dynamic changes before and after centrifugation of the blood samples. Serum mass patterns differed between native samples and samples frozen once. The best reproducibility of proteomic patterns was with a single thawing of frozen serum samples. Conclusion: Application of the standardized preanalytical blood sampling and storage procedure in combination with magnetic bead-based fractionation decreases variability of proteome patterns in human serum assessed by MALDI-TOF MS.

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Fonslow, Bryan R., Paulo C. Carvalho, Katrina Academia, Steve Freeby, Tao Xu, Aleksey Nakorchevsky, Aran Paulus, and John R. Yates. "Improvements in Proteomic Metrics of Low Abundance Proteins through Proteome Equalization Using ProteoMiner Prior to MudPIT." Journal of Proteome Research 10, no. 8 (August 5, 2011): 3690–700. http://dx.doi.org/10.1021/pr200304u.

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Duport, Catherine, Ludivine Rousset, Béatrice Alpha-Bazin, and Jean Armengaud. "Bacillus cereus Decreases NHE and CLO Exotoxin Synthesis to Maintain Appropriate Proteome Dynamics During Growth at Low Temperature." Toxins 12, no. 10 (October 6, 2020): 645. http://dx.doi.org/10.3390/toxins12100645.

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Cellular proteomes and exoproteomes are dynamic, allowing pathogens to respond to environmental conditions to sustain growth and virulence. Bacillus cereus is an important food-borne pathogen causing intoxication via emetic toxin and/or multiple protein exotoxins. Here, we compared the dynamics of the cellular proteome and exoproteome of emetic B. cereus cells grown at low (16 °C) and high (30 °C) temperature. Tandem mass spectrometry (MS/MS)-based shotgun proteomics analysis identified 2063 cellular proteins and 900 extracellular proteins. Hierarchical clustering following principal component analysis indicated that in B. cereus the abundance of a subset of these proteins—including cold-stress responders, and exotoxins non-hemolytic enterotoxin (NHE) and hemolysin I (cereolysin O (CLO))—decreased at low temperature, and that this subset governs the dynamics of the cellular proteome. NHE, and to a lesser extent CLO, also contributed significantly to exoproteome dynamics; with decreased abundances in the low-temperature exoproteome, especially in late growth stages. Our data therefore indicate that B. cereus may reduce its production of secreted protein toxins to maintain appropriate proteome dynamics, perhaps using catabolite repression to conserve energy for growth in cold-stress conditions, at the expense of virulence.

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Deng, Ning, Zhenye Li, Chao Pan, and Huilong Duan. "freeQuant: A Mass Spectrometry Label-Free Quantification Software Tool for Complex Proteome Analysis." Scientific World Journal 2015 (2015): 1–11. http://dx.doi.org/10.1155/2015/137076.

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Study of complex proteome brings forward higher request for the quantification method using mass spectrometry technology. In this paper, we present a mass spectrometry label-free quantification tool for complex proteomes, called freeQuant, which integrated quantification with functional analysis effectively. freeQuant consists of two well-integrated modules: label-free quantification and functional analysis with biomedical knowledge. freeQuant supports label-free quantitative analysis which makes full use of tandem mass spectrometry (MS/MS) spectral count, protein sequence length, shared peptides, and ion intensity. It adopts spectral count for quantitative analysis and builds a new method for shared peptides to accurately evaluate abundance of isoforms. For proteins with low abundance, MS/MS total ion count coupled with spectral count is included to ensure accurate protein quantification. Furthermore, freeQuant supports the large-scale functional annotations for complex proteomes. Mitochondrial proteomes from the mouse heart, the mouse liver, and the human heart were used to evaluate the usability and performance of freeQuant. The evaluation showed that the quantitative algorithms implemented in freeQuant can improve accuracy of quantification with better dynamic range.

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Ly, Tony, Aki Endo, Alejandro Brenes, Marek Gierlinski, Vackar Afzal, Andrea Pawellek, and Angus I. Lamond. "Proteome-wide analysis of protein abundance and turnover remodelling during oncogenic transformation of human breast epithelial cells." Wellcome Open Research 3 (May 2, 2018): 51. http://dx.doi.org/10.12688/wellcomeopenres.14392.1.

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Background: Viral oncogenes and mutated proto-oncogenes are potent drivers of cancer malignancy. Downstream of the oncogenic trigger are alterations in protein properties that give rise to cellular transformation and the acquisition of malignant cellular phenotypes. Developments in mass spectrometry enable large-scale, multidimensional characterisation of proteomes. Such techniques could provide an unprecedented, unbiased view of how oncogene activation remodels a human cell proteome. Methods: Using quantitative MS-based proteomics and cellular assays, we analysed how transformation induced by activating v-Src kinase remodels the proteome and cellular phenotypes of breast epithelial (MCF10A) cells. SILAC MS was used to comprehensively characterise the MCF10A proteome and to measure v-Src-induced changes in protein abundance across seven time-points (1-72 hrs). We used pulse-SILAC MS (Boisvert et al., 2012), to compare protein synthesis and turnover in control and transformed cells. Follow-on experiments employed a combination of cellular and functional assays to characterise the roles of selected Src-responsive proteins. Results: Src-induced transformation changed the expression and/or turnover levels of ~3% of proteins, affecting ~1.5% of the total protein molecules in the cell. Transformation increased the average rate of proteome turnover and disrupted protein homeostasis. We identify distinct classes of protein kinetics in response to Src activation. We demonstrate that members of the polycomb repressive complex 1 (PRC1) are important regulators of invasion and migration in MCF10A cells. Many Src-regulated proteins are present in low abundance and some are regulated post-transcriptionally. The signature of Src-responsive proteins is highly predictive of poor patient survival across multiple cancer types. Open access to search and interactively explore all these proteomic data is provided via the EPD database (www.peptracker.com/epd). Conclusions: We present the first comprehensive analysis measuring how protein expression and protein turnover is affected by cell transformation, providing a detailed picture at the protein level of the consequences of activation of an oncogene.

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Dissertations / Theses on the topic "Low-abundance proteome"

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MENDIETHA, Martha Elena. "New methods for separations of proteins mixtures in capillary electrophoresis and for detection of "low-abundance" proteome." Doctoral thesis, 2008. http://hdl.handle.net/11562/337634.

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ANTONIOLI, Paolo. "Proteomic and biochemical studies of microorganism exploitable in bio-restoration and bio-remediation, and development of new strategies to cope with the "small and low-abundance proteome"." Doctoral thesis, 2007. http://hdl.handle.net/11562/337993.

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Books on the topic "Low-abundance proteome"

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Low-Abundance Proteome Discovery. Elsevier, 2013. http://dx.doi.org/10.1016/c2012-0-01145-3.

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Righetti, P. G., and Egisto Boschetti. Low-Abundance Proteome Discovery: State of the Art and Protocols. Elsevier, 2013.

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Righetti, Pier Giorgio, and Egisto Boschetti. Low-Abundance Proteome Discovery: State of the Art and Protocols. Elsevier, 2013.

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Book chapters on the topic "Low-abundance proteome"

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Figeys, Daniel, and Ruedi Aebersold. "Solid-Phase Extraction-Capillary Zone Electrophoresis-Mass Spectrometry Analysis of Low-Abundance Proteins." In Proteome Research: Mass Spectrometry, 75–101. Berlin, Heidelberg: Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/978-3-642-56895-4_5.

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Cho, Sang Yun, Eun-Young Lee, Joon Seok Lee, Hye-Young Kim, Jae Myun Park, Min-Seok Kwon, Young-Kew Park, et al. "Efficient prefractionation of low-abundance proteins in human plasma and construction of a two-dimensional map." In Exploring the Human Plasma Proteome, 201–19. Weinheim, Germany: Wiley-VCH Verlag GmbH & Co. KGaA, 2006. http://dx.doi.org/10.1002/9783527609482.ch9.

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Tang, Hsin-Yao, Nadeem Ali-Khan, Lynn A. Echan, Natasha Levenkova, John J. Rux, and David W. Speicher. "A novel four-dimensional strategy combining protein and peptide separation methods enables detection of low-abundance proteins in human plasma and serum proteomes." In Exploring the Human Plasma Proteome, 135–58. Weinheim, Germany: Wiley-VCH Verlag GmbH & Co. KGaA, 2006. http://dx.doi.org/10.1002/9783527609482.ch6.

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Bayer, Roman G., Simon Stael, and Markus Teige. "Chloroplast Isolation and Enrichment of Low-Abundance Proteins by Affinity Chromatography for Identification in Complex Proteomes." In Methods in Molecular Biology, 535–47. New York, NY: Springer US, 2021. http://dx.doi.org/10.1007/978-1-0716-1186-9_34.

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Percy, Andrew J., and Christoph H. Borchers. "Detailed Method for Performing the ExSTA Approach in Quantitative Bottom-Up Plasma." In Methods in Molecular Biology, 353–84. New York, NY: Springer US, 2021. http://dx.doi.org/10.1007/978-1-0716-1024-4_25.

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AbstractThe use of stable isotope-labeled standards (SIS) is an analytically valid means of quantifying proteins in biological samples. The nature of the labeled standards and their point of insertion in a bottom-up proteomic workflow can vary, with quantification methods utilizing curves in analytically sound practices. A promising quantification strategy for low sample amounts is external standard addition (ExSTA). In ExSTA, multipoint calibration curves are generated in buffer using serially diluted natural (NAT) peptides and a fixed concentration of SIS peptides. Equal concentrations of SIS peptides are spiked into experimental sample digests, with all digests (control and experimental) subjected to solid-phase extraction prior to liquid chromatography tandem mass spectrometry (LC-MS/MS) analysis. Endogenous peptide concentrations are then determined using the regression equation of the standard curves. Given the benefits of ExSTA in large-scale analysis, a detailed protocol is provided herein for quantifying a multiplexed panel of 125 high-to-moderate abundance proteins in undepleted and non-enriched human plasma samples. The procedural details and recommendations for successfully executing all phases of this quantification approach are described. As the proteins have been putatively correlated with various noncommunicable diseases, quantifying these by ExSTA in large-scale studies should help rapidly and precisely assess their true biomarker efficacy.

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Righetti, Pier Giorgio, and Egisto Boschetti. "Introducing Low-Abundance Species in Proteome Analysis." In Low-Abundance Proteome Discovery, 1–11. Elsevier, 2013. http://dx.doi.org/10.1016/b978-0-12-401734-4.00001-4.

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Righetti, Pier Giorgio, and Egisto Boschetti. "Chromatographic and Electrophoretic Prefractionation Tools in Proteome Analysis." In Low-Abundance Proteome Discovery, 13–40. Elsevier, 2013. http://dx.doi.org/10.1016/b978-0-12-401734-4.00002-6.

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Righetti, Pier Giorgio, and Egisto Boschetti. "Current Low-Abundance Protein Access." In Low-Abundance Proteome Discovery, 41–77. Elsevier, 2013. http://dx.doi.org/10.1016/b978-0-12-401734-4.00003-8.

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Righetti, Pier Giorgio, and Egisto Boschetti. "Low-Abundance Protein Access by Combinatorial Peptide Libraries." In Low-Abundance Proteome Discovery, 79–157. Elsevier, 2013. http://dx.doi.org/10.1016/b978-0-12-401734-4.00004-x.

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Righetti, Pier Giorgio, and Egisto Boschetti. "Plant Proteomics and Food and Beverage Analysis via CPLL Capture." In Low-Abundance Proteome Discovery, 159–96. Elsevier, 2013. http://dx.doi.org/10.1016/b978-0-12-401734-4.00005-1.

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