1
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Yildiz P, Ozcan S. A single protein to multiple peptides: Investigation of protein-peptide correlations using targeted alpha-2-macroglobulin analysis. Talanta 2023; 265:124878. [PMID: 37392709 DOI: 10.1016/j.talanta.2023.124878] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2023] [Revised: 04/30/2023] [Accepted: 06/22/2023] [Indexed: 07/03/2023]
Abstract
Recent advances in proteomics technologies have enabled the analysis of thousands of proteins in a high-throughput manner. Mass spectrometry (MS) based proteomics uses a peptide-centric approach where biological samples undergo specific proteolytic digestion and then only unique peptides are used for protein identification and quantification. Considering the fact that a single protein may have multiple unique peptides and a number of different forms, it becomes essential to understand dynamic protein-peptide relationships to ensure robust and reliable peptide-centric protein analysis. In this study, we investigated the correlation between protein concentration and corresponding unique peptide responses under a conventional proteolytic digestion condition. Protein-peptide correlation, digestion efficiency, matrix-effect, and concentration-effect were evaluated. Twelve unique peptides of alpha-2-macroglobulin (A2MG) were monitored using a targeted MS approach to acquire insights into protein-peptide dynamics. Although the peptide responses were reproducible between replicates, protein-peptide correlation was moderate in protein standards and low in complex matrices. The results suggest that reproducible peptide signal could be misleading in clinical studies and a peptide selection could dramatically change the outcome at protein level. This is the first study investigating quantitative protein-peptide correlations in biological samples using all unique peptides representing the same protein and opens a discussion on peptide-based proteomics.
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Affiliation(s)
- Pelin Yildiz
- Department of Chemistry, Middle East Technical University (METU), 06800, Ankara, Turkiye; Nanografi Nanotechnology Co, Middle East Technical University (METU) Technopolis, 06531, Ankara, Turkiye
| | - Sureyya Ozcan
- Department of Chemistry, Middle East Technical University (METU), 06800, Ankara, Turkiye; Cancer Systems Biology Laboratory (CanSyL), Middle East Technical University (METU), 06800, Ankara, Turkiye.
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2
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Label-free quantitative proteomics and stress responses in pigs-The case of short or long road transportation. PLoS One 2022; 17:e0277950. [PMID: 36417452 PMCID: PMC9683611 DOI: 10.1371/journal.pone.0277950] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2022] [Accepted: 11/07/2022] [Indexed: 11/25/2022] Open
Abstract
Ethical livestock production is currently a major concern for consumers. In parallel, research has shown that transport duration is an important factor affecting animal welfare and has a negative impact on the final product quality and on the production cost. This study applied proteomics methods to the animal stress/welfare problem in pigs muscle-exudate with the aim to identify proteins indicative of molecular processes underpinning transport stress and to better characterise this species as a biomedical model. A broader perspective of the problem was obtained by applying label-free LC-MS to characterise the proteome response to transport stress (short or long road transportation) in pigs within the same genetic line. A total of 1,464 proteins were identified, following statistical analysis 66 proteins clearly separating pigs subject to short road transportation and pigs subject long road transportation. These proteins were mainly involved in cellular and metabolic processes. Catalase and stress-induced phosphoprotein-1 were further confirmed by Western blot as being involved in the process of self-protection of the cells in response to stress. This study provide an insight into the molecular processes that are involved in pig adaptability to transport stress and are a step-forward for the development of an objective evaluation method of stress in order to improve animal care and management in farm animals.
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Xu L, Gimple RC, Lau WB, Lau B, Fei F, Shen Q, Liao X, Li Y, Wang W, He Y, Feng M, Bu H, Wang W, Zhou S. THE PRESENT AND FUTURE OF THE MASS SPECTROMETRY-BASED INVESTIGATION OF THE EXOSOME LANDSCAPE. MASS SPECTROMETRY REVIEWS 2020; 39:745-762. [PMID: 32469100 DOI: 10.1002/mas.21635] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/16/2019] [Revised: 02/03/2020] [Accepted: 02/05/2020] [Indexed: 02/05/2023]
Abstract
Exosomes are critical intercellular messengers released upon the fusion of multivesicular bodies with the cellular plasma membrane that deliver their cargo in the form of extracellular vesicles. Containing numerous nonrandomly packed functional proteins, lipids, and RNAs, exosomes are vital intercellular messengers that contribute to the physiologic processes of the healthy organism. During the post-genome era, exosome-oriented proteomics have garnered great interest. Since its establishment, mass spectrometry (MS) has been indispensable for the field of proteomics research and has advanced rapidly to interrogate biological samples at a higher resolution and sensitivity. Driven by new methodologies and more advanced instrumentation, MS-based approaches have revolutionized our understanding of protein biology. As the access to online proteomics database platforms has blossomed, experimental data processing occurs with more speed and accuracy. Here, we review recent advances in the technological progress of MS-based proteomics and several new detection strategies for MS-based proteomics research. We also summarize the use of integrated online databases for proteomics research in the era of big data. © 2020 John Wiley & Sons Ltd. Mass Spec Rev.
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Affiliation(s)
- Lian Xu
- Key Laboratory of Birth Defects and Related Diseases of Women and Children of MOE, State Key Laboratory of Biotherapy, Department of Obstetrics and Gynecology, West China Second University Hospital, Sichuan University and Collaborative Innovation Center, Chengdu, Sichuan, People's Republic of China.,Key Laboratory of Birth Defects and Related Diseases of Women and Children of MOE, Department of Pathology, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, People's Republic of China
| | - Ryan C Gimple
- Department of Medicine, Division of Regenerative Medicine, University of California, San Diego, La Jolla, CA.,Department of Pathology, Case Western Reserve University, Cleveland, OH
| | - Wayne Bond Lau
- Department of Emergency Medicine, Thomas Jefferson University Hospital, Philadelphia, PA
| | - Bonnie Lau
- Department of Emergency Medicine, Kaiser Permanente Santa Clara Medical Center, Affiliate of Stanford University, Stanford, CA
| | - Fan Fei
- Department of Neurosurgery, Sichuan People's Hospital, Chengdu, Sichuan, People's Republic of China
| | - Qiuhong Shen
- Key Laboratory of Birth Defects and Related Diseases of Women and Children of MOE, State Key Laboratory of Biotherapy, Department of Obstetrics and Gynecology, West China Second University Hospital, Sichuan University and Collaborative Innovation Center, Chengdu, Sichuan, People's Republic of China.,School of Biological Sciences, Chengdu Medical College, Chengdu, Sichuan, People's Republic of China
| | - Xiaolin Liao
- Department of Neurosurgery, Sichuan People's Hospital, Chengdu, Sichuan, People's Republic of China
| | - Yichen Li
- Department of Biomedical Sciences, City University of Hong Kong, Kowloon Tong, Hong Kong, People's Republic of China
| | - Wei Wang
- Key Laboratory of Birth Defects and Related Diseases of Women and Children of MOE, Department of Pathology, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, People's Republic of China
| | - Ying He
- Key Laboratory of Birth Defects and Related Diseases of Women and Children of MOE, Department of Pathology, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, People's Republic of China
| | - Min Feng
- Key Laboratory of Birth Defects and Related Diseases of Women and Children of MOE, Department of Pathology, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, People's Republic of China
| | - Hong Bu
- Laboratory of Pathology, Department of Pathology, West China Hospital, Sichuan University, Chengdu, Sichuan, People's Republic of China
| | - Wei Wang
- Key Laboratory of Birth Defects and Related Diseases of Women and Children of MOE, State Key Laboratory of Biotherapy, Department of Obstetrics and Gynecology, West China Second University Hospital, Sichuan University and Collaborative Innovation Center, Chengdu, Sichuan, People's Republic of China
| | - Shengtao Zhou
- Key Laboratory of Birth Defects and Related Diseases of Women and Children of MOE, State Key Laboratory of Biotherapy, Department of Obstetrics and Gynecology, West China Second University Hospital, Sichuan University and Collaborative Innovation Center, Chengdu, Sichuan, People's Republic of China
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4
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Zhang T, Gaffrey MJ, Monroe ME, Thomas DG, Weitz KK, Piehowski PD, Petyuk VA, Moore RJ, Thrall BD, Qian WJ. Block Design with Common Reference Samples Enables Robust Large-Scale Label-Free Quantitative Proteome Profiling. J Proteome Res 2020; 19:2863-2872. [PMID: 32407631 DOI: 10.1021/acs.jproteome.0c00310] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
Label-free quantitative proteomics has become an increasingly popular tool for profiling global protein abundances. However, one major limitation is the potential performance drift of the LC-MS platform over time, which, in turn, limits its utility for analyzing large-scale sample sets. To address this, we introduce an experimental and data analysis scheme based on a block design with common references within each block for enabling large-scale label-free quantification. In this scheme, a large number of samples (e.g., >100 samples) are analyzed in smaller and more manageable blocks, minimizing instrument drift and variability within individual blocks. Each designated block also contains common reference samples (e.g., controls) for normalization across all blocks. We demonstrated the robustness of this approach by profiling the proteome response of human macrophage THP-1 cells to 11 engineered nanomaterials at two different doses. A total of 116 samples were analyzed in six blocks, yielding an average coverage of 4500 proteins per sample. Following a common reference-based correction, 2537 proteins were quantified with high reproducibility without any imputation of missing values from 116 data sets. The data revealed the consistent quantification of proteins across all six blocks, as illustrated by the highly consistent abundances of house-keeping proteins in all samples and the high levels of correlation among samples from different blocks. The data also demonstrated that label-free quantification is robust and accurate enough to quantify even very subtle abundance changes as well as large fold-changes. Our streamlined workflow is easy to implement and can be readily adapted to other large cohort studies for reproducible label-free proteome quantification.
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Affiliation(s)
- Tong Zhang
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99352, United States
| | - Matthew J Gaffrey
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99352, United States
| | - Matthew E Monroe
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99352, United States
| | - Dennis G Thomas
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99352, United States
| | - Karl K Weitz
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99352, United States
| | - Paul D Piehowski
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99352, United States
| | - Vladislav A Petyuk
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99352, United States
| | - Ronald J Moore
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99352, United States
| | - Brian D Thrall
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99352, United States
| | - Wei-Jun Qian
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99352, United States
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Abstract
OBJECTIVES Modern critical care amasses unprecedented amounts of clinical data-so called "big data"-on a minute-by-minute basis. Innovative processing of these data has the potential to revolutionize clinical prognostics and decision support in the care of the critically ill but also forces clinicians to depend on new and complex tools of which they may have limited understanding and over which they have little control. This concise review aims to provide bedside clinicians with ways to think about common methods being used to extract information from clinical big datasets and to judge the quality and utility of that information. DATA SOURCES We searched the free-access search engines PubMed and Google Scholar using the MeSH terms "big data", "prediction", and "intensive care" with iterations of a range of additional potentially associated factors, along with published bibliographies, to find papers suggesting illustration of key points in the structuring and analysis of clinical "big data," with special focus on outcomes prediction and major clinical concerns in critical care. STUDY SELECTION Three reviewers independently screened preliminary citation lists. DATA EXTRACTION Summary data were tabulated for review. DATA SYNTHESIS To date, most relevant big data research has focused on development of and attempts to validate patient outcome scoring systems and has yet to fully make use of the potential for automation and novel uses of continuous data streams such as those available from clinical care monitoring devices. CONCLUSIONS Realizing the potential for big data to improve critical care patient outcomes will require unprecedented team building across disparate competencies. It will also require clinicians to develop statistical awareness and thinking as yet another critical judgment skill they bring to their patients' bedsides and to the array of evidence presented to them about their patients over the course of care.
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6
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Zhu Y, Piehowski PD, Zhao R, Chen J, Shen Y, Moore RJ, Shukla AK, Petyuk VA, Campbell-Thompson M, Mathews CE, Smith RD, Qian WJ, Kelly RT. Nanodroplet processing platform for deep and quantitative proteome profiling of 10-100 mammalian cells. Nat Commun 2018; 9:882. [PMID: 29491378 PMCID: PMC5830451 DOI: 10.1038/s41467-018-03367-w] [Citation(s) in RCA: 341] [Impact Index Per Article: 56.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2017] [Accepted: 02/02/2018] [Indexed: 12/24/2022] Open
Abstract
Nanoscale or single-cell technologies are critical for biomedical applications. However, current mass spectrometry (MS)-based proteomic approaches require samples comprising a minimum of thousands of cells to provide in-depth profiling. Here, we report the development of a nanoPOTS (nanodroplet processing in one pot for trace samples) platform for small cell population proteomics analysis. NanoPOTS enhances the efficiency and recovery of sample processing by downscaling processing volumes to <200 nL to minimize surface losses. When combined with ultrasensitive liquid chromatography-MS, nanoPOTS allows identification of ~1500 to ~3000 proteins from ~10 to ~140 cells, respectively. By incorporating the Match Between Runs algorithm of MaxQuant, >3000 proteins are consistently identified from as few as 10 cells. Furthermore, we demonstrate quantification of ~2400 proteins from single human pancreatic islet thin sections from type 1 diabetic and control donors, illustrating the application of nanoPOTS for spatially resolved proteome measurements from clinical tissues. There is a great need of developing highly sensitive mass spectrometry-based proteomics analysis for small cell populations. Here, the authors establish a robotically controlled chip-based nanodroplet processing platform and demonstrate its ability to profile the proteome from 10–100 mammalian cells.
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Affiliation(s)
- Ying Zhu
- The Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, WA, 99354, USA
| | - Paul D Piehowski
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, 99354, USA
| | - Rui Zhao
- The Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, WA, 99354, USA
| | - Jing Chen
- Department of Pathology, Immunology and Laboratory Medicine, University of Florida, Gainesville, FL, 32611, USA
| | - Yufeng Shen
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, 99354, USA
| | - Ronald J Moore
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, 99354, USA
| | - Anil K Shukla
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, 99354, USA
| | - Vladislav A Petyuk
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, 99354, USA
| | - Martha Campbell-Thompson
- Department of Pathology, Immunology and Laboratory Medicine, University of Florida, Gainesville, FL, 32611, USA
| | - Clayton E Mathews
- Department of Pathology, Immunology and Laboratory Medicine, University of Florida, Gainesville, FL, 32611, USA
| | - Richard D Smith
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, 99354, USA
| | - Wei-Jun Qian
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, 99354, USA
| | - Ryan T Kelly
- The Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, WA, 99354, USA.
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7
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Zhou JY, Chen L, Zhang B, Tian Y, Liu T, Thomas SN, Chen L, Schnaubelt M, Boja E, Hiltke T, Kinsinger CR, Rodriguez H, Davies SR, Li S, Snider JE, Erdmann-Gilmore P, Tabb DL, Townsend RR, Ellis MJ, Rodland KD, Smith RD, Carr SA, Zhang Z, Chan DW, Zhang H. Quality Assessments of Long-Term Quantitative Proteomic Analysis of Breast Cancer Xenograft Tissues. J Proteome Res 2017; 16:4523-4530. [PMID: 29124938 DOI: 10.1021/acs.jproteome.7b00362] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Clinical proteomics requires large-scale analysis of human specimens to achieve statistical significance. We evaluated the long-term reproducibility of an iTRAQ (isobaric tags for relative and absolute quantification)-based quantitative proteomics strategy using one channel for reference across all samples in different iTRAQ sets. A total of 148 liquid chromatography tandem mass spectrometric (LC-MS/MS) analyses were completed, generating six 2D LC-MS/MS data sets for human-in-mouse breast cancer xenograft tissues representative of basal and luminal subtypes. Such large-scale studies require the implementation of robust metrics to assess the contributions of technical and biological variability in the qualitative and quantitative data. Accordingly, we derived a quantification confidence score based on the quality of each peptide-spectrum match to remove quantification outliers from each analysis. After combining confidence score filtering and statistical analysis, reproducible protein identification and quantitative results were achieved from LC-MS/MS data sets collected over a 7-month period. This study provides the first quality assessment on long-term stability and technical considerations for study design of a large-scale clinical proteomics project.
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Affiliation(s)
- Jian-Ying Zhou
- Department of Pathology, Johns Hopkins University , Baltimore, Maryland 21231, United States
| | - Lijun Chen
- Department of Pathology, Johns Hopkins University , Baltimore, Maryland 21231, United States
| | - Bai Zhang
- Department of Pathology, Johns Hopkins University , Baltimore, Maryland 21231, United States
| | - Yuan Tian
- Department of Pathology, Johns Hopkins University , Baltimore, Maryland 21231, United States
| | - Tao Liu
- Biological Sciences Division, Pacific Northwest National Laboratory , Richland, Washington 99352, United States
| | - Stefani N Thomas
- Department of Pathology, Johns Hopkins University , Baltimore, Maryland 21231, United States
| | - Li Chen
- Department of Pathology, Johns Hopkins University , Baltimore, Maryland 21231, United States
| | - Michael Schnaubelt
- Department of Pathology, Johns Hopkins University , Baltimore, Maryland 21231, United States
| | - Emily Boja
- Office of Cancer Clinical Proteomics Research, National Cancer Institute , Bethesda, Maryland 20892, United States
| | - Tara Hiltke
- Office of Cancer Clinical Proteomics Research, National Cancer Institute , Bethesda, Maryland 20892, United States
| | - Christopher R Kinsinger
- Office of Cancer Clinical Proteomics Research, National Cancer Institute , Bethesda, Maryland 20892, United States
| | - Henry Rodriguez
- Office of Cancer Clinical Proteomics Research, National Cancer Institute , Bethesda, Maryland 20892, United States
| | - Sherri R Davies
- Department of Internal Medicine, Washington University School of Medicine , St. Louis, Missouri 63110, United States
| | - Shunqiang Li
- Department of Internal Medicine, Washington University School of Medicine , St. Louis, Missouri 63110, United States
| | - Jacqueline E Snider
- Department of Internal Medicine, Washington University School of Medicine , St. Louis, Missouri 63110, United States
| | - Petra Erdmann-Gilmore
- Department of Internal Medicine, Washington University School of Medicine , St. Louis, Missouri 63110, United States
| | - David L Tabb
- Department of Biomedical Informatics, Vanderbilt University Medical School , Nashville, Tennessee 37232, United States
| | - R Reid Townsend
- Department of Internal Medicine, Washington University School of Medicine , St. Louis, Missouri 63110, United States
| | - Matthew J Ellis
- Department of Internal Medicine, Washington University School of Medicine , St. Louis, Missouri 63110, United States
| | - Karin D Rodland
- Biological Sciences Division, Pacific Northwest National Laboratory , Richland, Washington 99352, United States
| | - Richard D Smith
- Biological Sciences Division, Pacific Northwest National Laboratory , Richland, Washington 99352, United States
| | - Steven A Carr
- The Broad Institute of MIT and Harvard , Cambridge, Massachusetts 02142, United States
| | - Zhen Zhang
- Department of Pathology, Johns Hopkins University , Baltimore, Maryland 21231, United States
| | - Daniel W Chan
- Department of Pathology, Johns Hopkins University , Baltimore, Maryland 21231, United States
| | - Hui Zhang
- Department of Pathology, Johns Hopkins University , Baltimore, Maryland 21231, United States
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8
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Kondratov O, Marsic D, Crosson SM, Mendez-Gomez HR, Moskalenko O, Mietzsch M, Heilbronn R, Allison JR, Green KB, Agbandje-McKenna M, Zolotukhin S. Direct Head-to-Head Evaluation of Recombinant Adeno-associated Viral Vectors Manufactured in Human versus Insect Cells. Mol Ther 2017; 25:2661-2675. [PMID: 28890324 DOI: 10.1016/j.ymthe.2017.08.003] [Citation(s) in RCA: 53] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2017] [Revised: 07/19/2017] [Accepted: 08/07/2017] [Indexed: 10/19/2022] Open
Abstract
The major drawback of the Baculovirus/Sf9 system for recombinant adeno-associated viral (rAAV) manufacturing is that most of the Bac-derived rAAV vector serotypes, with few exceptions, demonstrate altered capsid compositions and lower biological potencies. Here, we describe a new insect cell-based production platform utilizing attenuated Kozak sequence and a leaky ribosome scanning to achieve a serotype-specific modulation of AAV capsid proteins stoichiometry. By way of example, rAAV5 and rAAV9 were produced and comprehensively characterized side by side with HEK293-derived vectors. A mass spectrometry analysis documented a 3-fold increase in both viral protein (VP)1 and VP2 capsid protein content compared with human cell-derived vectors. Furthermore, we conducted an extensive analysis of encapsidated single-stranded viral DNA using next-generation sequencing and show a 6-fold reduction in collaterally packaged contaminating DNA for rAAV5 produced in insect cells. Consequently, the re-designed rAAVs demonstrated significantly higher biological potencies, even in a comparison with HEK293-manufactured rAAVs mediating, in the case of rAAV5, 4-fold higher transduction of brain tissues in mice. Thus, the described system yields rAAV vectors of superior infectivity and higher genetic identity providing a scalable platform for good manufacturing practice (GMP)-grade vector production.
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Affiliation(s)
- Oleksandr Kondratov
- Department of Pediatrics, University of Florida College of Medicine, Gainesville, FL 32610, USA
| | - Damien Marsic
- Department of Pediatrics, University of Florida College of Medicine, Gainesville, FL 32610, USA
| | - Sean M Crosson
- Department of Pediatrics, University of Florida College of Medicine, Gainesville, FL 32610, USA
| | - Hector R Mendez-Gomez
- Department of Molecular Genetics and Microbiology, University of Florida College of Medicine, Gainesville, FL 32610, USA
| | - Oleksandr Moskalenko
- UFIT Research Computing, University of Florida College of Medicine, Gainesville, FL 32610, USA
| | - Mario Mietzsch
- Department of Biochemistry and Molecular Biology, Center for Structural Biology, University of Florida College of Medicine, Gainesville, FL 32610, USA; Institute of Virology, Campus Benjamin Franklin, Charité Medical School, Berlin, Germany
| | - Regine Heilbronn
- Institute of Virology, Campus Benjamin Franklin, Charité Medical School, Berlin, Germany
| | | | - Kari B Green
- Department of Chemistry, University of Florida, Gainesville, FL, USA
| | - Mavis Agbandje-McKenna
- Department of Biochemistry and Molecular Biology, Center for Structural Biology, University of Florida College of Medicine, Gainesville, FL 32610, USA
| | - Sergei Zolotukhin
- Department of Pediatrics, University of Florida College of Medicine, Gainesville, FL 32610, USA.
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9
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A comparative proteomics method for multiple samples based on a 18 O-reference strategy and a quantitation and identification-decoupled strategy. Talanta 2017; 171:166-172. [DOI: 10.1016/j.talanta.2017.04.069] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2016] [Revised: 04/05/2017] [Accepted: 04/30/2017] [Indexed: 11/24/2022]
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10
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Maurye P, Basu A, Bandyopadhyay TK, Biswas JK, Mohanty BP. Multi-gel casting apparatus for vertical polyacrylamide gels with in-built solution flow system and liquid level detectors. Electrophoresis 2017; 38:2060-2068. [PMID: 28444798 DOI: 10.1002/elps.201700121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2017] [Revised: 04/20/2017] [Accepted: 04/20/2017] [Indexed: 10/19/2022]
Abstract
PAGE is the most widely used technique for the separation and biochemical analysis of biomolecules. The ever growing field of proteomics and genomics necessitates the analysis of many proteins and nucleic acid samples to understand further about the structure and function of cells. Simultaneous analysis of multiple protein samples often requires casting of many PAGE gels. Several variants of multi-gel casting/electrophoresis apparatuses are frequently used in research laboratories. Requirement of supplementary gels to match the growing demand for analyzing additional protein samples sometimes become a cause of concern. Available apparatuses are not amenable to and therefore, not recommended for any modification to accommodate additional gel casting units other than what is prescribed by the manufacturer. A novel apparatus is described here for casting multiple PAGE gels comprising four detachable components that provide enhanced practicability and performance of the apparatus. This newly modified apparatus promises to be a reliable source for making multiple gels in less time without hassle. Synchronized functioning of unique components broaden the possibilities of developing inexpensive, safe, and time-saving multi-gel casting apparatus. This apparatus can be easily fabricated and modified to accommodate desired number of gel casting units. The estimated cost (∼$300) for fabrication of the main apparatus is very competitive and effortless assembly procedure can be completed within ∼30 min.
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Affiliation(s)
- Praveen Maurye
- Fishery Resource and Environment Management Division, Central Inland Fisheries Research Institute (I.C.A.R.), Kolkata, West Bengal, India
| | - Arpita Basu
- Fishery Resource and Environment Management Division, Central Inland Fisheries Research Institute (I.C.A.R.), Kolkata, West Bengal, India
| | | | - Jayanta Kumar Biswas
- Department of Ecological Studies & International Centre for Ecological Engineering, University of Kalyani, Kalyani, West Bengal, India
| | - Bimal Prasana Mohanty
- Fishery Resource and Environment Management Division, Central Inland Fisheries Research Institute (I.C.A.R.), Kolkata, West Bengal, India
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11
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Borland K, Limbach PA. Applications and Advantages of Stable Isotope Phosphate Labeling of RNA in Mass Spectrometry. Top Curr Chem (Cham) 2017; 375:33. [DOI: 10.1007/s41061-017-0121-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2016] [Accepted: 02/17/2017] [Indexed: 01/17/2023]
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12
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Bringans SD, Ito J, Stoll T, Winfield K, Phillips M, Peters K, Davis WA, Davis TME, Lipscombe RJ. Comprehensive mass spectrometry based biomarker discovery and validation platform as applied to diabetic kidney disease. EUPA OPEN PROTEOMICS 2017; 14:1-10. [PMID: 29900119 PMCID: PMC5988498 DOI: 10.1016/j.euprot.2016.12.001] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/12/2016] [Revised: 10/21/2016] [Accepted: 12/30/2016] [Indexed: 11/25/2022]
Abstract
A protein biomarker discovery workflow was applied to plasma samples from patients at different stages of diabetic kidney disease. The proteomics platform produced a panel of significant plasma biomarkers that were statistically scrutinised against the current gold standard tests on an analysis of 572 patients. Five proteins were significantly associated with diabetic kidney disease defined by albuminuria, renal impairment (eGFR) and chronic kidney disease staging (CKD Stage ≥1, ROC curve of 0.77). The results prove the suitability and efficacy of the process used, and introduce a biomarker panel with the potential to improve diagnosis of diabetic kidney disease.
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Affiliation(s)
- Scott D Bringans
- Proteomics International, PO Box 3008, Broadway, Nedlands, Perth, Western Australia, WA 6009, Australia
| | - Jun Ito
- Proteomics International, PO Box 3008, Broadway, Nedlands, Perth, Western Australia, WA 6009, Australia
| | - Thomas Stoll
- Proteomics International, PO Box 3008, Broadway, Nedlands, Perth, Western Australia, WA 6009, Australia
| | - Kaye Winfield
- Proteomics International, PO Box 3008, Broadway, Nedlands, Perth, Western Australia, WA 6009, Australia
| | - Michael Phillips
- Harry Perkins Institute of Medial Research, QQ Block, QEII Medical Centre 6 Verdun Street, Nedlands, Perth, Western Australia, WA 6009, Australia
| | - Kirsten Peters
- Proteomics International, PO Box 3008, Broadway, Nedlands, Perth, Western Australia, WA 6009, Australia.,University of Western Australia, 35 Stirling Highway, Crawley, Perth, Western Australia, WA 6009, Australia
| | - Wendy A Davis
- University of Western Australia, 35 Stirling Highway, Crawley, Perth, Western Australia, WA 6009, Australia
| | - Timothy M E Davis
- University of Western Australia, 35 Stirling Highway, Crawley, Perth, Western Australia, WA 6009, Australia
| | - Richard J Lipscombe
- Proteomics International, PO Box 3008, Broadway, Nedlands, Perth, Western Australia, WA 6009, Australia
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13
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Liu Y, Liu K, Qin W, Liu C, Zheng X, Deng Y, Qing H. Effects of stem cell therapy on protein profile of parkinsonian rats using an(18) O-labeling quantitative proteomic approach. Proteomics 2016; 16:1023-32. [PMID: 26791447 DOI: 10.1002/pmic.201500421] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2015] [Revised: 12/24/2015] [Accepted: 01/18/2016] [Indexed: 01/26/2023]
Abstract
The application of neural stem cell (NSC) research to neurodegenerative diseases has led to promising clinical trials. Currently, NSC therapy is most promising for Parkinson's disease (PD). We conducted behavioral tests and immunoassays for the profiling of a PD model in rats to assess the therapeutic effects of NSC treatments. Further, using a multiple sample comparison workflow, combined with (18) O-labeled proteome mixtures, we compared the differentially expressed proteins from control, PD, and NSC-treated PD rats. The results were analyzed bioinformatically and verified by Western blot. Based on our initial findings, we believe that the proteomic approach is a valuable tool in evaluating the therapeutic effects of NSC transplantation on neurodegenerative disorders.
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Affiliation(s)
- Yahui Liu
- School of Life Science, Beijing Institute of Technology, Beijing, P. R. China
| | - Kefu Liu
- School of Life Science, Beijing Institute of Technology, Beijing, P. R. China
| | - Wei Qin
- School of Life Science, Beijing Institute of Technology, Beijing, P. R. China
| | - Chenghao Liu
- School of Life Science, Beijing Institute of Technology, Beijing, P. R. China
| | - Xiaowei Zheng
- School of Life Science, Beijing Institute of Technology, Beijing, P. R. China
| | - Yulin Deng
- School of Life Science, Beijing Institute of Technology, Beijing, P. R. China
| | - Hong Qing
- School of Life Science, Beijing Institute of Technology, Beijing, P. R. China
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14
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Gritsenko MA, Xu Z, Liu T, Smith RD. Large-Scale and Deep Quantitative Proteome Profiling Using Isobaric Labeling Coupled with Two-Dimensional LC-MS/MS. Methods Mol Biol 2016; 1410:237-47. [PMID: 26867748 DOI: 10.1007/978-1-4939-3524-6_14] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Comprehensive, quantitative information on abundances of proteins and their posttranslational modifications (PTMs) can potentially provide novel biological insights into diseases pathogenesis and therapeutic intervention. Herein, we introduce a quantitative strategy utilizing isobaric stable isotope-labeling techniques combined with two-dimensional liquid chromatography-tandem mass spectrometry (2D-LC-MS/MS) for large-scale, deep quantitative proteome profiling of biological samples or clinical specimens such as tumor tissues. The workflow includes isobaric labeling of tryptic peptides for multiplexed and accurate quantitative analysis, basic reversed-phase LC fractionation and concatenation for reduced sample complexity, and nano-LC coupled to high resolution and high mass accuracy MS analysis for high confidence identification and quantification of proteins. This proteomic analysis strategy has been successfully applied for in-depth quantitative proteomic analysis of tumor samples and can also be used for integrated proteome and PTM characterization, as well as comprehensive quantitative proteomic analysis across samples from large clinical cohorts.
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Affiliation(s)
- Marina A Gritsenko
- Biological Sciences Division and Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, WA, 99352, USA
| | - Zhe Xu
- Biological Sciences Division and Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, WA, 99352, USA
| | - Tao Liu
- Biological Sciences Division and Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, WA, 99352, USA.
| | - Richard D Smith
- Biological Sciences Division and Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, WA, 99352, USA.
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15
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Wang H, Shi T, Qian WJ, Liu T, Kagan J, Srivastava S, Smith RD, Rodland KD, Camp DG. The clinical impact of recent advances in LC-MS for cancer biomarker discovery and verification. Expert Rev Proteomics 2015; 13:99-114. [PMID: 26581546 DOI: 10.1586/14789450.2016.1122529] [Citation(s) in RCA: 43] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Mass spectrometry (MS) -based proteomics has become an indispensable tool with broad applications in systems biology and biomedical research. With recent advances in liquid chromatography (LC) and MS instrumentation, LC-MS is making increasingly significant contributions to clinical applications, especially in the area of cancer biomarker discovery and verification. To overcome challenges associated with analyses of clinical samples (for example, a wide dynamic range of protein concentrations in bodily fluids and the need to perform high throughput and accurate quantification of candidate biomarker proteins), significant efforts have been devoted to improve the overall performance of LC-MS-based clinical proteomics platforms. Reviewed here are the recent advances in LC-MS and its applications in cancer biomarker discovery and quantification, along with the potentials, limitations and future perspectives.
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Affiliation(s)
- Hui Wang
- a Biological Sciences Division , Pacific Northwest National Laboratory , Richland , WA , USA
| | - Tujin Shi
- a Biological Sciences Division , Pacific Northwest National Laboratory , Richland , WA , USA
| | - Wei-Jun Qian
- a Biological Sciences Division , Pacific Northwest National Laboratory , Richland , WA , USA
| | - Tao Liu
- a Biological Sciences Division , Pacific Northwest National Laboratory , Richland , WA , USA
| | - Jacob Kagan
- b Division of Cancer Prevention , National Cancer Institute (NCI) , Rockville , MD , USA
| | - Sudhir Srivastava
- b Division of Cancer Prevention , National Cancer Institute (NCI) , Rockville , MD , USA
| | - Richard D Smith
- a Biological Sciences Division , Pacific Northwest National Laboratory , Richland , WA , USA
| | - Karin D Rodland
- a Biological Sciences Division , Pacific Northwest National Laboratory , Richland , WA , USA
| | - David G Camp
- a Biological Sciences Division , Pacific Northwest National Laboratory , Richland , WA , USA
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16
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Gunawardena HP, O'Brien J, Wrobel JA, Xie L, Davies SR, Li S, Ellis MJ, Qaqish BF, Chen X. QuantFusion: Novel Unified Methodology for Enhanced Coverage and Precision in Quantifying Global Proteomic Changes in Whole Tissues. Mol Cell Proteomics 2015; 15:740-51. [PMID: 26598639 DOI: 10.1074/mcp.o115.049791] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2015] [Indexed: 11/06/2022] Open
Abstract
Single quantitative platforms such as label-based or label-free quantitation (LFQ) present compromises in accuracy, precision, protein sequence coverage, and speed of quantifiable proteomic measurements. To maximize the quantitative precision and the number of quantifiable proteins or the quantifiable coverage of tissue proteomes, we have developed a unified approach, termed QuantFusion, that combines the quantitative ratios of all peptides measured by both LFQ and label-based methodologies. Here, we demonstrate the use of QuantFusion in determining the proteins differentially expressed in a pair of patient-derived tumor xenografts (PDXs) representing two major breast cancer (BC) subtypes, basal and luminal. Label-based in-spectra quantitative peptides derived from amino acid-coded tagging (AACT, also known as SILAC) of a non-malignant mammary cell line were uniformly added to each xenograft with a constant predefined ratio, from which Ratio-of-Ratio estimates were obtained for the label-free peptides paired with AACT peptides in each PDX tumor. A mixed model statistical analysis was used to determine global differential protein expression by combining complementary quantifiable peptide ratios measured by LFQ and Ratio-of-Ratios, respectively. With minimum number of replicates required for obtaining the statistically significant ratios, QuantFusion uses the distinct mechanisms to "rescue" the missing data inherent to both LFQ and label-based quantitation. Combined quantifiable peptide data from both quantitative schemes increased the overall number of peptide level measurements and protein level estimates. In our analysis of the PDX tumor proteomes, QuantFusion increased the number of distinct peptide ratios by 65%, representing differentially expressed proteins between the BC subtypes. This quantifiable coverage improvement, in turn, not only increased the number of measurable protein fold-changes by 8% but also increased the average precision of quantitative estimates by 181% so that some BC subtypically expressed proteins were rescued by QuantFusion. Thus, incorporating data from multiple quantitative approaches while accounting for measurement variability at both the peptide and global protein levels make QuantFusion unique for obtaining increased coverage and quantitative precision for tissue proteomes.
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Affiliation(s)
- Harsha P Gunawardena
- From the ‡Department of Biochemistry and Biophysics, §Lineberger Comprehensive Cancer Center, and
| | - Jonathon O'Brien
- ¶Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599
| | - John A Wrobel
- From the ‡Department of Biochemistry and Biophysics, §Lineberger Comprehensive Cancer Center, and
| | - Ling Xie
- From the ‡Department of Biochemistry and Biophysics, §Lineberger Comprehensive Cancer Center, and
| | - Sherri R Davies
- ‖Division of Oncology, Washington University, St. Louis, Missouri 63110
| | - Shunqiang Li
- ‖Division of Oncology, Washington University, St. Louis, Missouri 63110
| | - Matthew J Ellis
- **Lester and Sue Smith Breast Center, Baylor College of Medicine, Houston, Texas 77030
| | - Bahjat F Qaqish
- ¶Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599
| | - Xian Chen
- From the ‡Department of Biochemistry and Biophysics, §Lineberger Comprehensive Cancer Center, and
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17
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El Ouaamari A, Zhou JY, Liew CW, Shirakawa J, Dirice E, Gedeon N, Kahraman S, De Jesus DF, Bhatt S, Kim JS, Clauss TR, Camp DG, Smith RD, Qian WJ, Kulkarni RN. Compensatory Islet Response to Insulin Resistance Revealed by Quantitative Proteomics. J Proteome Res 2015; 14:3111-3122. [PMID: 26151086 DOI: 10.1021/acs.jproteome.5b00587] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Compensatory islet response is a distinct feature of the prediabetic insulin-resistant state in humans and rodents. To identify alterations in the islet proteome that characterize the adaptive response, we analyzed islets from 5 month old male control, high-fat diet fed (HFD), or obese ob/ob mice by LC-MS/MS and quantified ~1100 islet proteins (at least two peptides) with a false discovery rate < 1%. Significant alterations in abundance were observed for ~350 proteins among groups. The majority of alterations were common to both models, and the changes of a subset of ~40 proteins and 12 proteins were verified by targeted quantification using selected reaction monitoring and western blots, respectively. The insulin-resistant islets in both groups exhibited reduced expression of proteins controlling energy metabolism, oxidative phosphorylation, hormone processing, and secretory pathways. Conversely, an increased expression of molecules involved in protein synthesis and folding suggested effects in endoplasmic reticulum stress response, cell survival, and proliferation in both insulin-resistant models. In summary, we report a unique comparison of the islet proteome that is focused on the compensatory response in two insulin-resistant rodent models that are not overtly diabetic. These data provide a valuable resource of candidate proteins to the scientific community to undertake further studies aimed at enhancing β-cell mass in patients with diabetes. The data are available via the MassIVE repository, under accession no. MSV000079093.
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Affiliation(s)
- Abdelfattah El Ouaamari
- Islet Cell & Regenerative Biology, Joslin Diabetes Center, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts 02215
| | - Jian-Ying Zhou
- Biological Sciences Division and Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington 99352
| | - Chong Wee Liew
- Department of Physiology and Biophysics, University of Illinois at Chicago, Chicago, IL 60612, USA
| | - Jun Shirakawa
- Islet Cell & Regenerative Biology, Joslin Diabetes Center, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts 02215
| | - Ercument Dirice
- Islet Cell & Regenerative Biology, Joslin Diabetes Center, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts 02215
| | - Nicholas Gedeon
- Islet Cell & Regenerative Biology, Joslin Diabetes Center, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts 02215
| | - Sevim Kahraman
- Islet Cell & Regenerative Biology, Joslin Diabetes Center, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts 02215
| | - Dario F De Jesus
- Islet Cell & Regenerative Biology, Joslin Diabetes Center, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts 02215
| | - Shweta Bhatt
- Islet Cell & Regenerative Biology, Joslin Diabetes Center, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts 02215
| | - Jong-Seo Kim
- Biological Sciences Division and Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington 99352
| | - Therese Rw Clauss
- Biological Sciences Division and Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington 99352
| | - David G Camp
- Biological Sciences Division and Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington 99352
| | - Richard D Smith
- Biological Sciences Division and Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington 99352
| | - Wei-Jun Qian
- Biological Sciences Division and Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington 99352
| | - Rohit N Kulkarni
- Islet Cell & Regenerative Biology, Joslin Diabetes Center, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts 02215
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18
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19
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Hyung SW, Piehowski PD, Moore RJ, Orton DJ, Schepmoes AA, Clauss TR, Chu RK, Fillmore TL, Brewer H, Liu T, Zhao R, Smith RD. Microscale depletion of high abundance proteins in human biofluids using IgY14 immunoaffinity resin: analysis of human plasma and cerebrospinal fluid. Anal Bioanal Chem 2014; 406:7117-25. [PMID: 25192788 DOI: 10.1007/s00216-014-8058-3] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2014] [Revised: 07/09/2014] [Accepted: 07/22/2014] [Indexed: 12/30/2022]
Abstract
Removal of highly abundant proteins in plasma is often carried out using immunoaffinity depletion to extend the dynamic range of measurements to lower abundance species. While commercial depletion columns are available for this purpose, they generally are not applicable to limited sample quantities (<20 μL) due to low yields stemming from losses caused by nonspecific binding to the column matrix and concentration of large eluent volumes. Additionally, the cost of the depletion media can be prohibitive for larger-scale studies. Modern LC-MS instrumentation provides the sensitivity necessary to scale-down depletion methods with minimal sacrifice to proteome coverage, which makes smaller volume depletion columns desirable for maximizing sample recovery when samples are limited, as well as for reducing the expense of large-scale studies. We characterized the performance of a 346 μL column volume microscale depletion system, using four different flow rates to determine the most effective depletion conditions for ∼6-μL injections of human plasma proteins and then evaluated depletion reproducibility at the optimum flow rate condition. Depletion of plasma using a commercial 10-mL depletion column served as the control. Results showed depletion efficiency of the microscale column increased as flow rate decreased, and that our microdepletion was reproducible. In an initial application, a 600-μL sample of human cerebrospinal fluid (CSF) pooled from multiple sclerosis patients was depleted and then analyzed using reversed phase liquid chromatography-mass spectrometry to demonstrate the utility of the system for this important biofluid where sample quantities are more commonly limited.
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Affiliation(s)
- Seok-Won Hyung
- Biological Sciences Division and Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, WA, 99352, USA,
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20
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Wu C, Shi T, Brown JN, He J, Gao Y, Fillmore TL, Shukla AK, Moore RJ, Camp DG, Rodland KD, Qian WJ, Liu T, Smith RD. Expediting SRM assay development for large-scale targeted proteomics experiments. J Proteome Res 2014; 13:4479-87. [PMID: 25145539 PMCID: PMC4184450 DOI: 10.1021/pr500500d] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
![]()
Because
of its high sensitivity and specificity, selected reaction
monitoring (SRM)-based targeted proteomics has become increasingly
popular for biological and translational applications. Selection of
optimal transitions and optimization of collision energy (CE) are
important assay development steps for achieving sensitive detection
and accurate quantification; however, these steps can be labor-intensive,
especially for large-scale applications. Herein, we explored several
options for accelerating SRM assay development evaluated in the context
of a relatively large set of 215 synthetic peptide targets. We first
showed that HCD fragmentation is very similar to that of CID in triple
quadrupole (QQQ) instrumentation and that by selection of the top
6 y fragment ions from HCD spectra, >86% of the top transitions
optimized
from direct infusion with QQQ instrumentation are covered. We also
demonstrated that the CE calculated by existing prediction tools was
less accurate for 3+ precursors and that a significant increase in
intensity for transitions could be obtained using a new CE prediction
equation constructed from the present experimental data. Overall,
our study illustrated the feasibility of expediting the development
of larger numbers of high-sensitivity SRM assays through automation
of transition selection and accurate prediction of optimal CE to improve
both SRM throughput and measurement quality.
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Affiliation(s)
- Chaochao Wu
- Biological Sciences Division and ‡Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory , Richland, Washington 99352, United States
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21
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Ryu SY. Bioinformatics tools to identify and quantify proteins using mass spectrometry data. ADVANCES IN PROTEIN CHEMISTRY AND STRUCTURAL BIOLOGY 2014; 94:1-17. [PMID: 24629183 DOI: 10.1016/b978-0-12-800168-4.00001-9] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
Abstract
Proteomics tries to understand biological function of an organism by studying its protein expressions. Mass spectrometry is used in the field of shotgun proteomics, and it generates mass spectra that are used to identify and quantify proteins in biological samples. In this chapter, we discuss the bioinformatics algorithms to analyze mass spectrometry data. After briefly describing how mass spectrometry generates data, we illustrate the bioinformatics algorithms and software for protein identification such as de novo approach and database-searching approach. We also discuss the bioinformatics algorithms and software to quantify proteins and detect the differential proteins using isotope-coded affinity tags and label-free mass spectrometry data.
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Affiliation(s)
- So Young Ryu
- Stanford Genome Technology Center, Biochemistry Department, Stanford University, Stanford, California, USA.
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22
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Abstract
OBJECTIVES Emerging proteomics techniques can be used to establish proteomic outcome signatures and to identify candidate biomarkers for survival following traumatic injury. We applied high-resolution liquid chromatography-mass spectrometry and multiplex cytokine analysis to profile the plasma proteome of survivors and nonsurvivors of massive burn injury to determine the proteomic survival signature following a major burn injury. DESIGN Proteomic discovery study. SETTING Five burn hospitals across the United States. PATIENTS Thirty-two burn patients (16 nonsurvivors and 16 survivors), 19-89 years old, were admitted within 96 hours of injury to the participating hospitals with burns covering more than 20% of the total body surface area and required at least one surgical intervention. INTERVENTIONS None. MEASUREMENTS AND MAIN RESULTS We found differences in circulating levels of 43 proteins involved in the acute-phase response, hepatic signaling, the complement cascade, inflammation, and insulin resistance. Thirty-two of the proteins identified were not previously known to play a role in the response to burn. Interleukin-4, interleukin-8, granulocyte macrophage colony-stimulating factor, monocyte chemotactic protein-1, and β2-microglobulin correlated well with survival and may serve as clinical biomarkers. CONCLUSIONS These results demonstrate the utility of these techniques for establishing proteomic survival signatures and for use as a discovery tool to identify candidate biomarkers for survival. This is the first clinical application of a high-throughput, large-scale liquid chromatography-mass spectrometry-based quantitative plasma proteomic approach for biomarker discovery for the prediction of patient outcome following burn, trauma, or critical illness.
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23
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Kim JS, Dai Z, Aryal UK, Moore RJ, Camp DG, Baker SE, Smith RD, Qian WJ. Resin-assisted enrichment of N-terminal peptides for characterizing proteolytic processing. Anal Chem 2013; 85:6826-32. [PMID: 23772796 DOI: 10.1021/ac401000q] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
A resin-assisted enrichment method has been developed for specific isolation of protein N-terminal peptides to facilitate LC-MS/MS characterization of proteolytic processing, a major form of posttranslational modifications. In this method, protein thiols are blocked by reduction and alkylation, and protein lysine residues are converted to homoarginines. Protein N-termini are selectively converted to reactive thiol groups, and the thiol-containing N-terminal peptides are then captured by a thiol-affinity resin with high specificity (>97%). The efficiencies of these sequential reactions were demonstrated to be nearly quantitative. The resin-assisted N-terminal peptide enrichment approach was initially applied to a cell lysate of the filamentous fungus Aspergillus niger. Subsequent C-MS/MS analyses resulted in the identification of 1672 unique protein N-termini or proteolytic cleavage sites from 690 unique proteins.
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Affiliation(s)
- Jong-Seo Kim
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99352, United States
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24
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Piehowski PD, Petyuk VA, Orton DJ, Xie F, Moore RJ, Ramirez-Restrepo M, Engel A, Lieberman AP, Albin RL, Camp DG, Smith RD, Myers AJ. Sources of technical variability in quantitative LC-MS proteomics: human brain tissue sample analysis. J Proteome Res 2013; 12:2128-37. [PMID: 23495885 DOI: 10.1021/pr301146m] [Citation(s) in RCA: 138] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
To design a robust quantitative proteomics study, an understanding of both the inherent heterogeneity of the biological samples being studied as well as the technical variability of the proteomics methods and platform is needed. Additionally, accurately identifying the technical steps associated with the largest variability would provide valuable information for the improvement and design of future processing pipelines. We present an experimental strategy that allows for a detailed examination of the variability of the quantitative LC-MS proteomics measurements. By replicating analyses at different stages of processing, various technical components can be estimated and their individual contribution to technical variability can be dissected. This design can be easily adapted to other quantitative proteomics pipelines. Herein, we applied this methodology to our label-free workflow for the processing of human brain tissue. For this application, the pipeline was divided into four critical components: Tissue dissection and homogenization (extraction), protein denaturation followed by trypsin digestion and SPE cleanup (digestion), short-term run-to-run instrumental response fluctuation (instrumental variance), and long-term drift of the quantitative response of the LC-MS/MS platform over the 2 week period of continuous analysis (instrumental stability). From this analysis, we found the following contributions to variability: extraction (72%) >> instrumental variance (16%) > instrumental stability (8.4%) > digestion (3.1%). Furthermore, the stability of the platform and its suitability for discovery proteomics studies is demonstrated.
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Affiliation(s)
- Paul D Piehowski
- Biological Sciences Division and Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington, USA
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25
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Baker ES, Liu T, Petyuk VA, Burnum-Johnson KE, Ibrahim YM, Anderson GA, Smith RD. Mass spectrometry for translational proteomics: progress and clinical implications. Genome Med 2012; 4:63. [PMID: 22943415 PMCID: PMC3580401 DOI: 10.1186/gm364] [Citation(s) in RCA: 60] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023] Open
Abstract
The utility of mass spectrometry (MS)-based proteomic analyses and their clinical applications have been increasingly recognized over the past decade due to their high sensitivity, specificity and throughput. MS-based proteomic measurements have been used in a wide range of biological and biomedical investigations, including analysis of cellular responses and disease-specific post-translational modifications. These studies greatly enhance our understanding of the complex and dynamic nature of the proteome in biology and disease. Some MS techniques, such as those for targeted analysis, are being successfully applied for biomarker verification, whereas others, including global quantitative analysis (for example, for biomarker discovery), are more challenging and require further development. However, recent technological improvements in sample processing, instrumental platforms, data acquisition approaches and informatics capabilities continue to advance MS-based applications. Improving the detection of significant changes in proteins through these advances shows great promise for the discovery of improved biomarker candidates that can be verified pre-clinically using targeted measurements, and ultimately used in clinical studies - for example, for early disease diagnosis or as targets for drug development and therapeutic intervention. Here, we review the current state of MS-based proteomics with regard to its advantages and current limitations, and we highlight its translational applications in studies of protein biomarkers.
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Affiliation(s)
- Erin Shammel Baker
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99352, USA
| | - Tao Liu
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99352, USA
| | - Vladislav A Petyuk
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99352, USA
| | | | - Yehia M Ibrahim
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99352, USA
| | - Gordon A Anderson
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99352, USA
| | - Richard D Smith
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99352, USA
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26
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Zhou JY, Dann GP, Liew CW, Smith RD, Kulkarni RN, Qian WJ. Unraveling pancreatic islet biology by quantitative proteomics. Expert Rev Proteomics 2012; 8:495-504. [PMID: 21819304 DOI: 10.1586/epr.11.39] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
The pancreatic islets of Langerhans play a critical role in maintaining blood glucose homeostasis by secreting insulin and several other important peptide hormones. Impaired insulin secretion due to islet dysfunction is linked to the pathogenesis underlying both Type 1 and Type 2 diabetes. Over the past 5 years, emerging proteomic technologies have been applied to dissect the signaling pathways that regulate islet functions and gain an understanding of the mechanisms of islet dysfunction relevant to diabetes. Herein, we briefly review some of the recent quantitative proteomic studies involving pancreatic islets geared towards gaining a better understanding of islet biology relevant to metabolic diseases.
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Affiliation(s)
- Jian-Ying Zhou
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99352, USA
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27
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Angel TE, Aryal UK, Hengel SM, Baker ES, Kelly RT, Robinson EW, Smith RD. Mass spectrometry-based proteomics: existing capabilities and future directions. Chem Soc Rev 2012. [PMID: 22498958 DOI: 10.1039/c2cs15331a.mass] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/17/2023]
Abstract
Mass spectrometry (MS)-based proteomics is emerging as a broadly effective means for identification, characterization, and quantification of proteins that are integral components of the processes essential for life. Characterization of proteins at the proteome and sub-proteome (e.g., the phosphoproteome, proteoglycome, or degradome/peptidome) levels provides a foundation for understanding fundamental aspects of biology. Emerging technologies such as ion mobility separations coupled with MS and microchip-based-proteome measurements combined with MS instrumentation and chromatographic separation techniques, such as nanoscale reversed phase liquid chromatography and capillary electrophoresis, show great promise for both broad undirected and targeted highly sensitive measurements. MS-based proteomics increasingly contribute to our understanding of the dynamics, interactions, and roles that proteins and peptides play, advancing our understanding of biology on a systems wide level for a wide range of applications including investigations of microbial communities, bioremediation, and human health.
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Affiliation(s)
- Thomas E Angel
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99352, USA
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28
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Angel TE, Aryal UK, Hengel SM, Baker ES, Kelly RT, Robinson EW, Smith RD. Mass spectrometry-based proteomics: existing capabilities and future directions. Chem Soc Rev 2012; 41:3912-28. [PMID: 22498958 DOI: 10.1039/c2cs15331a] [Citation(s) in RCA: 263] [Impact Index Per Article: 21.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Mass spectrometry (MS)-based proteomics is emerging as a broadly effective means for identification, characterization, and quantification of proteins that are integral components of the processes essential for life. Characterization of proteins at the proteome and sub-proteome (e.g., the phosphoproteome, proteoglycome, or degradome/peptidome) levels provides a foundation for understanding fundamental aspects of biology. Emerging technologies such as ion mobility separations coupled with MS and microchip-based-proteome measurements combined with MS instrumentation and chromatographic separation techniques, such as nanoscale reversed phase liquid chromatography and capillary electrophoresis, show great promise for both broad undirected and targeted highly sensitive measurements. MS-based proteomics increasingly contribute to our understanding of the dynamics, interactions, and roles that proteins and peptides play, advancing our understanding of biology on a systems wide level for a wide range of applications including investigations of microbial communities, bioremediation, and human health.
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Affiliation(s)
- Thomas E Angel
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99352, USA
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Huang X, Tian C, Liu M, Wang Y, Tolmachev AV, Sharma S, Yu F, Fu K, Zheng J, Ding SJ. Quantitative proteomic analysis of mouse embryonic fibroblasts and induced pluripotent stem cells using 16O/18O labeling. J Proteome Res 2012; 11:2091-102. [PMID: 22375802 DOI: 10.1021/pr300155r] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Induced pluripotent stem cells (iPSC) hold great promise for regenerative medicine as well as for investigations into the pathogenesis and treatment of various diseases. Understanding of key intracellular signaling pathways and protein targets that control development of iPSC from somatic cells is essential for designing new approaches to improve reprogramming efficiency. Here, we report the development and application of an integrated quantitative proteomics platform for investigating differences in protein expressions between mouse embryonic fibroblasts (MEF) and MEF-derived iPSC. This platform consists of 16O/18O labeling, multidimensional peptide separation coupled with tandem mass spectrometry, and data analysis with UNiquant software. With this platform, a total of 2481 proteins were identified and quantified from the 16O/18O-labeled MEF-iPSC proteome mixtures with a false discovery rate of 0.01. Among them, 218 proteins were significantly upregulated, while 247 proteins were significantly downregulated in iPSC compared to MEF. Many nuclear proteins, including Hdac1, Dnmt1, Pcna, Ccnd1, Smarcc1, and subunits in DNA replication and RNA polymerase II complex, were found to be enhanced in iPSC. Protein network analysis revealed that Pcna functions as a hub orchestrating complicated mechanisms including DNA replication, epigenetic inheritance (Dnmt1), and chromatin remodeling (Smarcc1) to reprogram MEF and maintain stemness of iPSC.
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Affiliation(s)
- Xin Huang
- Department of Pathology and Microbiology, Mass Spectrometry and Proteomics Core Facility, University of Nebraska Medical Center, Omaha, Nebraska 68198, United States
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Aryal UK, Stöckel J, Welsh EA, Gritsenko MA, Nicora CD, Koppenaal DW, Smith RD, Pakrasi HB, Jacobs JM. Dynamic proteome analysis of Cyanothece sp. ATCC 51142 under constant light. J Proteome Res 2011; 11:609-19. [PMID: 22060561 DOI: 10.1021/pr200959x] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
Understanding the dynamic nature of protein abundances provides insights into protein turnover not readily apparent from conventional, static mass spectrometry measurements. This level of data is particularly informative when surveying protein abundances in biological systems subjected to large perturbations or alterations in environment such as cyanobacteria. Our current analysis expands upon conventional proteomic approaches in cyanobacteria by measuring dynamic changes of the proteome using a (13)C(15)N-l-leucine metabolic labeling in Cyanothece ATCC51142. Metabolically labeled Cyanothece ATCC51142 cells grown under nitrogen-sufficient conditions in continuous light were monitored longitudinally for isotope incorporation over a 48 h period, revealing 414 proteins with dynamic changes in abundances. In particular, proteins involved in carbon fixation, pentose phosphate pathway, cellular protection, redox regulation, protein folding, assembly, and degradation showed higher levels of isotope incorporation, suggesting that these biochemical pathways are important for growth under continuous light. Calculation of relative isotope abundances (RIA) values allowed the measurement of actual active protein synthesis over time for different biochemical pathways under high light exposure. Overall results demonstrated the utility of "non-steady state" pulsed metabolic labeling for systems-wide dynamic quantification of the proteome in Cyanothece ATCC51142 that can also be applied to other cyanobacteria.
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Affiliation(s)
- Uma K Aryal
- Pacific Northwest National Laboratory , Richland, Washington 99352, United States
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31
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Zhang H, Burnum KE, Luna ML, Petritis BO, Kim JS, Qian WJ, Moore RJ, Heredia-Langner A, Webb-Robertson BJM, Thrall BD, Camp DG, Smith RD, Pounds JG, Liu T. Quantitative proteomics analysis of adsorbed plasma proteins classifies nanoparticles with different surface properties and size. Proteomics 2011; 11:4569-77. [PMID: 21956884 DOI: 10.1002/pmic.201100037] [Citation(s) in RCA: 100] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2011] [Revised: 06/10/2011] [Accepted: 09/13/2011] [Indexed: 12/21/2022]
Abstract
Nanoparticle biological activity, biocompatibility and fate can be directly affected by layers of readily adsorbed host proteins in biofluids. Here, we report a study on the interactions between human blood plasma proteins and nanoparticles with a controlled systematic variation of properties using (18)O-labeling and LC-MS-based quantitative proteomics. We developed a novel protocol to both simplify isolation of nanoparticle bound proteins and improve reproducibility. LC-MS analysis identified and quantified 88 human plasma proteins associated with polystyrene nanoparticles consisting of three different surface chemistries and two sizes, as well as, for four different exposure times (for a total of 24 different samples). Quantitative comparison of relative protein abundances was achieved by spiking an (18)O-labeled "universal" reference into each individually processed unlabeled sample as an internal standard, enabling simultaneous application of both label-free and isotopic labeling quantification across the entire sample set. Clustering analysis of the quantitative proteomics data resulted in distinctive patterns that classified the nanoparticles based on their surface properties and size. In addition, temporal data indicated that the formation of the stable protein corona was at equilibrium within 5 min. The comprehensive quantitative proteomics results obtained in this study provide rich data for computational modeling and have potential implications towards predicting nanoparticle biocompatibility.
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Affiliation(s)
- Haizhen Zhang
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99352, USA
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32
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Kim JS, Fillmore TL, Liu T, Robinson E, Hossain M, Champion BL, Moore RJ, Camp DG, Smith RD, Qian WJ. 18O-labeled proteome reference as global internal standards for targeted quantification by selected reaction monitoring-mass spectrometry. Mol Cell Proteomics 2011; 10:M110.007302. [PMID: 21988777 DOI: 10.1074/mcp.m110.007302] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022] Open
Abstract
Selected reaction monitoring (SRM)-MS is an emerging technology for high throughput targeted protein quantification and verification in biomarker discovery studies; however, the cost associated with the application of stable isotope-labeled synthetic peptides as internal standards can be prohibitive for screening a large number of candidate proteins as often required in the preverification phase of discovery studies. Herein we present a proof of concept study using an (18)O-labeled proteome reference as global internal standards (GIS) for SRM-based relative quantification. The (18)O-labeled proteome reference (or GIS) can be readily prepared and contains a heavy isotope ((18)O)-labeled internal standard for every possible tryptic peptide. Our results showed that the percentage of heavy isotope ((18)O) incorporation applying an improved protocol was >99.5% for most peptides investigated. The accuracy, reproducibility, and linear dynamic range of quantification were further assessed based on known ratios of standard proteins spiked into the labeled mouse plasma reference. Reliable quantification was observed with high reproducibility (i.e. coefficient of variance <10%) for analyte concentrations that were set at 100-fold higher or lower than those of the GIS based on the light ((16)O)/heavy ((18)O) peak area ratios. The utility of (18)O-labeled GIS was further illustrated by accurate relative quantification of 45 major human plasma proteins. Moreover, quantification of the concentrations of C-reactive protein and prostate-specific antigen was illustrated by coupling the GIS with standard additions of purified protein standards. Collectively, our results demonstrated that the use of (18)O-labeled proteome reference as GIS provides a convenient, low cost, and effective strategy for relative quantification of a large number of candidate proteins in biological or clinical samples using SRM.
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Affiliation(s)
- Jong-Seo Kim
- Biological Sciences Division and Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington 99352, USA
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López E, Wesselink JJ, López I, Mendieta J, Gómez-Puertas P, Muñoz SR. Technical phosphoproteomic and bioinformatic tools useful in cancer research. J Clin Bioinforma 2011; 1:26. [PMID: 21967744 PMCID: PMC3195713 DOI: 10.1186/2043-9113-1-26] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2011] [Accepted: 10/03/2011] [Indexed: 12/22/2022] Open
Abstract
Reversible protein phosphorylation is one of the most important forms of cellular regulation. Thus, phosphoproteomic analysis of protein phosphorylation in cells is a powerful tool to evaluate cell functional status. The importance of protein kinase-regulated signal transduction pathways in human cancer has led to the development of drugs that inhibit protein kinases at the apex or intermediary levels of these pathways. Phosphoproteomic analysis of these signalling pathways will provide important insights for operation and connectivity of these pathways to facilitate identification of the best targets for cancer therapies. Enrichment of phosphorylated proteins or peptides from tissue or bodily fluid samples is required. The application of technologies such as phosphoenrichments, mass spectrometry (MS) coupled to bioinformatics tools is crucial for the identification and quantification of protein phosphorylation sites for advancing in such relevant clinical research. A combination of different phosphopeptide enrichments, quantitative techniques and bioinformatic tools is necessary to achieve good phospho-regulation data and good structural analysis of protein studies. The current and most useful proteomics and bioinformatics techniques will be explained with research examples. Our aim in this article is to be helpful for cancer research via detailing proteomics and bioinformatic tools.
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Affiliation(s)
- Elena López
- Centro de Investigación i+12 del Hospital Universitario 12 de Octubre, Avda de Córdoba s/n Madrid, 28041, Spain
| | - Jan-Jaap Wesselink
- Centro de Biología Molecular "Severo Ochoa" (CSIC-UAM) Campus de Cantoblanco, c/Nicolás Cabrera, 1, 28049 Madrid, Spain.,Biomol-Informatics, S.L., Parque Científico de Madrid, Campus de Cantoblanco, c/Faraday 7, 28049 Madrid, Spain
| | - Isabel López
- Servicio de Hematología Hospital QUIRÓN, Madrid, Diego de Velázquez 1 28223, Pozuelo Madrid Spain
| | - Jesús Mendieta
- Centro de Biología Molecular "Severo Ochoa" (CSIC-UAM) Campus de Cantoblanco, c/Nicolás Cabrera, 1, 28049 Madrid, Spain.,Biomol-Informatics, S.L., Parque Científico de Madrid, Campus de Cantoblanco, c/Faraday 7, 28049 Madrid, Spain
| | - Paulino Gómez-Puertas
- Centro de Biología Molecular "Severo Ochoa" (CSIC-UAM) Campus de Cantoblanco, c/Nicolás Cabrera, 1, 28049 Madrid, Spain
| | - Sarbelio Rodríguez Muñoz
- Servicio de Digestivo, Hospital Universitario 12 Octubre, Avda de Córdoba s/n Madrid, 28041, Spain
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Ghazalpour A, Bennett B, Petyuk VA, Orozco L, Hagopian R, Mungrue IN, Farber CR, Sinsheimer J, Kang HM, Furlotte N, Park CC, Wen PZ, Brewer H, Weitz K, Camp DG, Pan C, Yordanova R, Neuhaus I, Tilford C, Siemers N, Gargalovic P, Eskin E, Kirchgessner T, Smith DJ, Smith RD, Lusis AJ. Comparative analysis of proteome and transcriptome variation in mouse. PLoS Genet 2011; 7:e1001393. [PMID: 21695224 PMCID: PMC3111477 DOI: 10.1371/journal.pgen.1001393] [Citation(s) in RCA: 444] [Impact Index Per Article: 34.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2010] [Accepted: 05/10/2011] [Indexed: 12/11/2022] Open
Abstract
The relationships between the levels of transcripts and the levels of the proteins they encode have not been examined comprehensively in mammals, although previous work in plants and yeast suggest a surprisingly modest correlation. We have examined this issue using a genetic approach in which natural variations were used to perturb both transcript levels and protein levels among inbred strains of mice. We quantified over 5,000 peptides and over 22,000 transcripts in livers of 97 inbred and recombinant inbred strains and focused on the 7,185 most heritable transcripts and 486 most reliable proteins. The transcript levels were quantified by microarray analysis in three replicates and the proteins were quantified by Liquid Chromatography–Mass Spectrometry using O(18)-reference-based isotope labeling approach. We show that the levels of transcripts and proteins correlate significantly for only about half of the genes tested, with an average correlation of 0.27, and the correlations of transcripts and proteins varied depending on the cellular location and biological function of the gene. We examined technical and biological factors that could contribute to the modest correlation. For example, differential splicing clearly affects the analyses for certain genes; but, based on deep sequencing, this does not substantially contribute to the overall estimate of the correlation. We also employed genome-wide association analyses to map loci controlling both transcript and protein levels. Surprisingly, little overlap was observed between the protein- and transcript-mapped loci. We have typed numerous clinically relevant traits among the strains, including adiposity, lipoprotein levels, and tissue parameters. Using correlation analysis, we found that a low number of clinical trait relationships are preserved between the protein and mRNA gene products and that the majority of such relationships are specific to either the protein levels or transcript levels. Surprisingly, transcript levels were more strongly correlated with clinical traits than protein levels. In light of the widespread use of high-throughput technologies in both clinical and basic research, the results presented have practical as well as basic implications. An old dogma in biology states that, in every cell, the flow of biological information is from DNA to RNA to proteins and that the latter act as a working force to determine the organism's phenotype. This model predicts that changes in DNA that affect the clinical phenotype should also similarly change the cellular levels of RNA and protein levels. In this report, we test this prediction by looking at the concordance between DNA variation in population of mouse inbred strains, the RNA and protein variation in the liver tissue of these mice, and variation in metabolic phenotypes. We show that the relationship between various biological traits is not simple and that there is relatively little concordance of RNA levels and the corresponding protein levels in response to DNA perturbations. In addition, we also find that, surprisingly, metabolic traits correlate better to RNA levels than to protein levels. In light of current efforts in searching for the molecular bases of disease susceptibility in humans, our findings highlight the complexity of information flow that underlies clinical outcomes.
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Affiliation(s)
- Anatole Ghazalpour
- Department of Medicine/Division of Cardiology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, United States of America.
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Xie F, Liu T, Qian WJ, Petyuk VA, Smith RD. Liquid chromatography-mass spectrometry-based quantitative proteomics. J Biol Chem 2011; 286:25443-9. [PMID: 21632532 DOI: 10.1074/jbc.r110.199703] [Citation(s) in RCA: 148] [Impact Index Per Article: 11.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
LC-MS-based quantitative proteomics has become increasingly applied to a wide range of biological applications due to growing capabilities for broad proteome coverage and good accuracy and precision in quantification. Herein, we review the current LC-MS-based quantification methods with respect to their advantages and limitations and highlight their potential applications.
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Affiliation(s)
- Fang Xie
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99352, USA
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Affiliation(s)
- Xudong Yao
- Department of Chemistry, University of Connecticut, Storrs, Connecticut 06269, USA.
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37
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Ning Z, Zhou H, Wang F, Abu-Farha M, Figeys D. Analytical Aspects of Proteomics: 2009–2010. Anal Chem 2011; 83:4407-26. [DOI: 10.1021/ac200857t] [Citation(s) in RCA: 27] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Affiliation(s)
| | - Hu Zhou
- Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, China 201203
| | - Fangjun Wang
- Key Lab of Separation Sciences for Analytical Chemistry, National Chromatographic Research and Analysis Center, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, China 116023
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38
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Shakey Q, Bates B, Wu J. An approach to quantifying N-linked glycoproteins by enzyme-catalyzed 18O3-labeling of solid-phase enriched glycopeptides. Anal Chem 2011; 82:7722-8. [PMID: 20795641 DOI: 10.1021/ac101564t] [Citation(s) in RCA: 35] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
Global analysis of glycoproteins shows great promise for the discovery of therapeutic targets and clinical biomarkers. Selective capture of glycopeptides by hydrazide resin followed by mass spectrometric identification of the peptides released by PNGaseF treatment has been most widely used. However, the majority of the reports using this approach focus on global profiling, rather than relative quantitation of glycoprotein alternations in pathological states. We describe an integrated strategy allowing for relative quantitation of glycoproteins in complex biological mixtures using this approach. The strategy includes periodate oxidation of tryptic digests, solid-phase enrichment of glycopeptides via hydrazide-coupled magnetic beads, in conjunction with (18)O stable isotope labeling catalyzed by both trypsin and PNGaseF, and subsequent identification and quantitation by LC-MS/MS analysis. Three (18)O atoms ((18)O(3)) are incorporated into N-linked glycopeptides for samples treated in (18)O-water, two at the carboxyl terminus by trypsin during hydrazide coupling and the third at the N-glycosylation site through PNGaseF-mediated deglycosylation. Thus, mass shifts of 6 and 8 Da are indicative of singly and doubly glycosylated peptides, respectively. Experimental conditions were optimized to promote the trypsin-mediated (18)O(2) incorporation and prevent backbone exchange. The accuracy, reproducibility, and linearity of relative quantitation were evaluated by using 15 glycoproteins spiked into mouse serum at different concentration ratios. Using this approach, we were able to identify and quantitate 224 N-glycopeptides representing 130 unique glycoproteins from 20 μL of the undepleted mouse serum samples. The strategy can be easily adapted to the analysis of glycoproteins in tissues, cell lines, and other sample origins.
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Affiliation(s)
- Quazi Shakey
- Global Biotherapeutics Technologies, Pfizer, Cambridge, Massachusetts 02140, USA
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39
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Qian WJ, Petritis BO, Kaushal A, Finnerty CC, Jeschke MG, Monroe ME, Moore RJ, Schepmoes AA, Xiao W, Moldawer LL, Davis RW, Tompkins RG, Herndon DN, Camp DG, Smith RD. Plasma proteome response to severe burn injury revealed by 18O-labeled "universal" reference-based quantitative proteomics. J Proteome Res 2011; 9:4779-89. [PMID: 20698492 DOI: 10.1021/pr1005026] [Citation(s) in RCA: 46] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
A burn injury represents one of the most severe forms of human trauma and is responsible for significant mortality worldwide. Here, we present the first quantitative proteomics investigation of the blood plasma proteome response to severe burn injury by comparing the plasma protein concentrations of 10 healthy control subjects with those of 15 severe burn patients at two time-points following the injury. The overall analytical strategy for this work integrated immunoaffinity depletion of the 12 most abundant plasma proteins with cysteinyl-peptide enrichment-based fractionation prior to LC-MS analyses of individual patient samples. Incorporation of an 18O-labeled "universal" reference among the sample sets enabled precise relative quantification across samples. In total, 313 plasma proteins confidently identified with two or more unique peptides were quantified. Following statistical analysis, 110 proteins exhibited significant abundance changes in response to the burn injury. The observed changes in protein concentrations suggest significant inflammatory and hypermetabolic response to the injury, which is supported by the fact that many of the identified proteins are associated with acute phase response signaling, the complement system, and coagulation system pathways. The regulation of approximately 35 proteins observed in this study is in agreement with previous results reported for inflammatory or burn response, but approximately 50 potentially novel proteins previously not known to be associated with burn response or inflammation are also found. Elucidating proteins involved in the response to severe burn injury may reveal novel targets for therapeutic interventions as well as potential predictive biomarkers for patient outcomes such as multiple organ failure.
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Affiliation(s)
- Wei-Jun Qian
- Biological Sciences Division and Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington 99352, USA
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40
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Abstract
Stable isotope labeling based on relative peptide/protein abundance measurements is commonly applied for quantitative proteomics. Recently, trypsin-catalyzed oxygen-18 labeling has grown in popularity due to its simplicity, cost-effectiveness, and its ability to universally label peptides with high sample recovery. In (18)O labeling, both C-terminal carboxyl group atoms of tryptic peptides can be enzymatically exchanged with (18)O, thus providing the labeled peptide with a 4 Da mass shift from the (16)O-labeled sample. Peptide (18)O labeling is ideally suited for generating a labeled "universal" reference sample used for obtaining accurate and reproducible quantitative measurements across large number of samples in quantitative discovery proteomics.
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41
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Santos HM, Glez-Peña D, Reboiro-Jato M, Fdez-Riverola F, Diniz MS, Lodeiro C, Capelo-Martínez JL. A novel 18O inverse labeling-based workflow for accurate bottom-up mass spectrometry quantification of proteins separated by gel electrophoresis. Electrophoresis 2010; 31:3407-19. [DOI: 10.1002/elps.201000251] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
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Schutzer SE, Liu T, Natelson BH, Angel TE, Schepmoes AA, Purvine SO, Hixson KK, Lipton MS, Camp DG, Coyle PK, Smith RD, Bergquist J. Establishing the proteome of normal human cerebrospinal fluid. PLoS One 2010; 5:e10980. [PMID: 20552007 PMCID: PMC2881861 DOI: 10.1371/journal.pone.0010980] [Citation(s) in RCA: 162] [Impact Index Per Article: 11.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2010] [Accepted: 04/17/2010] [Indexed: 11/18/2022] Open
Abstract
Background Knowledge of the entire protein content, the proteome, of normal human cerebrospinal fluid (CSF) would enable insights into neurologic and psychiatric disorders. Until now technologic hurdles and access to true normal samples hindered attaining this goal. Methods and Principal Findings We applied immunoaffinity separation and high sensitivity and resolution liquid chromatography-mass spectrometry to examine CSF from healthy normal individuals. 2630 proteins in CSF from normal subjects were identified, of which 56% were CSF-specific, not found in the much larger set of 3654 proteins we have identified in plasma. We also examined CSF from groups of subjects previously examined by others as surrogates for normals where neurologic symptoms warranted a lumbar puncture but where clinical laboratory were reported as normal. We found statistically significant differences between their CSF proteins and our non-neurological normals. We also examined CSF from 10 volunteer subjects who had lumbar punctures at least 4 weeks apart and found that there was little variability in CSF proteins in an individual as compared to subject to subject. Conclusions Our results represent the most comprehensive characterization of true normal CSF to date. This normal CSF proteome establishes a comparative standard and basis for investigations into a variety of diseases with neurological and psychiatric features.
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Affiliation(s)
- Steven E Schutzer
- Department of Medicine, University of Medicine and Dentistry of New Jersey-New Jersey Medical School, Newark, New Jersey, USA.
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Zhang X, Fang A, Riley CP, Wang M, Regnier FE, Buck C. Multi-dimensional liquid chromatography in proteomics--a review. Anal Chim Acta 2010; 664:101-13. [PMID: 20363391 PMCID: PMC2852180 DOI: 10.1016/j.aca.2010.02.001] [Citation(s) in RCA: 126] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2009] [Revised: 01/29/2010] [Accepted: 02/01/2010] [Indexed: 12/19/2022]
Abstract
Proteomics is the large-scale study of proteins, particularly their expression, structures and functions. This still-emerging combination of technologies aims to describe and characterize all expressed proteins in a biological system. Because of upper limits on mass detection of mass spectrometers, proteins are usually digested into peptides and the peptides are then separated, identified and quantified from this complex enzymatic digest. The problem in digesting proteins first and then analyzing the peptide cleavage fragments by mass spectrometry is that huge numbers of peptides are generated that overwhelm direct mass spectral analyses. The objective in the liquid chromatography approach to proteomics is to fractionate peptide mixtures to enable and maximize identification and quantification of the component peptides by mass spectrometry. This review will focus on existing multidimensional liquid chromatographic (MDLC) platforms developed for proteomics and their application in combination with other techniques such as stable isotope labeling. We also provide some perspectives on likely future developments.
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Affiliation(s)
- Xiang Zhang
- Department of Chemistry, University of Louisville, 2320 South Brook Street, Louisville, KY 40292, USA.
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44
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Timms JF, Cutillas PR. Overview of quantitative LC-MS techniques for proteomics and activitomics. Methods Mol Biol 2010; 658:19-45. [PMID: 20839096 DOI: 10.1007/978-1-60761-780-8_2] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/09/2023]
Abstract
LC-MS is a useful technique for protein and peptide quantification. In addition, as a powerful tool for systems biology research, LC-MS can also be used to quantify post-translational modifications and metabolites that reflect biochemical pathway activity. This review discusses the different analytical techniques that use LC-MS for the quantification of proteins, their modifications and activities in a multiplex manner.
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Affiliation(s)
- John F Timms
- Cancer Proteomics Laboratory, EGA Institute for Women's Health, University College London, London, UK
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45
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Elliott MH, Smith DS, Parker CE, Borchers C. Current trends in quantitative proteomics. JOURNAL OF MASS SPECTROMETRY : JMS 2009; 44:1637-1660. [PMID: 19957301 DOI: 10.1002/jms.1692] [Citation(s) in RCA: 63] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/28/2023]
Abstract
It was inevitable that as soon as mass spectrometrists were able to tell biologists which proteins were in their samples, the next question would be how much of these proteins were present. This has turned out to be a much more challenging question. In this review, we describe the multiple ways that mass spectrometry has attempted to address this issue, both for relative quantitation and for absolute quantitation of proteins. There is no single method that will work for every problem or for every sample. What we present here is a variety of techniques, with guidelines that we hope will assist the researcher in selecting the most appropriate technique for the particular biological problem that needs to be addressed. We need to emphasize that this is a very active area of proteomics research-new quantitative methods are continuously being introduced and some 'pitfalls' of older methods are just being discovered. However, even though there is no perfect technique--and a better technique may be developed tomorrow--valuable information on biomarkers and pathways can be obtained using these currently available methods.
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Affiliation(s)
- Monica H Elliott
- University of Victoria Genome BC Proteomics Centre, British Columbia, V8Z 7X8, Canada
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46
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López-Ferrer D, Hixson KK, Smallwood H, Squier TC, Petritis K, Smith RD. Evaluation of a high-intensity focused ultrasound-immobilized trypsin digestion and 18O-labeling method for quantitative proteomics. Anal Chem 2009; 81:6272-7. [PMID: 19555078 PMCID: PMC2765551 DOI: 10.1021/ac802540s] [Citation(s) in RCA: 30] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
A new method that uses immobilized trypsin concomitant with ultrasonic irradiation results in ultrarapid digestion and more thorough (18)O labeling for quantitative protein comparisons. The method was reproducible and provided effective digestions within <1 min with lower amounts of enzyme, compared to traditional methods. This method was demonstrated for digestion of both simple and complex protein mixtures, including bovine serum albumin, a global proteome extract from the bacteria Shewanella oneidensis, and mouse plasma, as well as (18)O labeling of complex protein mixtures, validating this method for differential proteomic measurements. This approach is simple, reproducible, cost-effective, rapid, and well suited for automation.
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Affiliation(s)
- Daniel López-Ferrer
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99352
| | - Kim K. Hixson
- Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, WA 99352
| | - Heather Smallwood
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99352
| | - Thomas C. Squier
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99352
| | - Konstantinos Petritis
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99352
| | - Richard D. Smith
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99352
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Elo LL, Hiissa J, Tuimala J, Kallio A, Korpelainen E, Aittokallio T. Optimized detection of differential expression in global profiling experiments: case studies in clinical transcriptomic and quantitative proteomic datasets. Brief Bioinform 2009; 10:547-55. [DOI: 10.1093/bib/bbp033] [Citation(s) in RCA: 23] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023] Open
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48
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Petritis BO, Qian WJ, Camp DG, Smith RD. A simple procedure for effective quenching of trypsin activity and prevention of 18O-labeling back-exchange. J Proteome Res 2009; 8:2157-63. [PMID: 19222237 DOI: 10.1021/pr800971w] [Citation(s) in RCA: 46] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Abstract
Trypsin-catalyzed stable isotope 16O/18O-labeling of the C-terminal carboxyl groups of peptides is increasingly used in shotgun proteomics for relative peptide/protein quantitation. However, precise quantitative measurements are often complicated by residual trypsin that can catalyze the back-exchange of 18O with 16O after labeling. Here, we demonstrate through a detailed evaluation that boiling the peptide sample for 10 min provides a simple means for completely quenching residual trypsin activity and preventing oxygen back-exchange in 18O-labeled samples. We also observed that the presence of organic solvents such as acetonitrile made boiling less efficient for inactivating trypsin. Finally, current 18O-labeling methods that typically employ immobilized trypsin result in significant sample losses due to nonspecific binding of peptides to the resin, making their application toward smaller biological samples increasingly impractical. We present here an improved 18O-labeling protocol that is more applicable to microscale biological samples by using solution-phase trypsin instead of immobilized trypsin. The ability to generate stably 18O-labeled samples without back-exchange should enable more effective applications of 18O-labeling toward large-scale biomarker discovery and validations where an 18O-labeled sample can be used as a common reference for quantitation.
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Fenselau C, Yao X. 18O2-Labeling in Quantitative Proteomic Strategies: A Status Report. J Proteome Res 2009; 8:2140-3. [DOI: 10.1021/pr8009879] [Citation(s) in RCA: 80] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Affiliation(s)
- Catherine Fenselau
- Department of Chemistry & Biochemistry, University of Maryland, College Park, Maryland 20742, and Department of Chemistry, University of Connecticut, Storrs, Connecticut 06269
| | - Xudong Yao
- Department of Chemistry & Biochemistry, University of Maryland, College Park, Maryland 20742, and Department of Chemistry, University of Connecticut, Storrs, Connecticut 06269
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