1
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Chen Y, Gin JW, Wang Y, de Raad M, Tan S, Hillson NJ, Northen TR, Adams PD, Petzold CJ. Alkaline-SDS cell lysis of microbes with acetone protein precipitation for proteomic sample preparation in 96-well plate format. PLoS One 2023; 18:e0288102. [PMID: 37418444 DOI: 10.1371/journal.pone.0288102] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2023] [Accepted: 06/20/2023] [Indexed: 07/09/2023] Open
Abstract
Plate-based proteomic sample preparation offers a solution to the large sample throughput demands in the biotechnology field where hundreds or thousands of engineered microbes are constructed for testing is routine. Meanwhile, sample preparation methods that work efficiently on broader microbial groups are desirable for new applications of proteomics in other fields, such as microbial communities. Here, we detail a step-by-step protocol that consists of cell lysis in an alkaline chemical buffer (NaOH/SDS) followed by protein precipitation with high-ionic strength acetone in 96-well format. The protocol works for a broad range of microbes (e.g., Gram-negative bacteria, Gram-positive bacteria, non-filamentous fungi) and the resulting proteins are ready for tryptic digestion for bottom-up quantitative proteomic analysis without the need for desalting column cleanup. The yield of protein using this protocol increases linearly with respect to the amount of starting biomass from 0.5-2.0 OD*mL of cells. By using a bench-top automated liquid dispenser, a cost-effective and environmentally-friendly option to eliminating pipette tips and reducing reagent waste, the protocol takes approximately 30 minutes to extract protein from 96 samples. Tests on mock mixtures showed expected results that the biomass composition structure is in close agreement with the experimental design. Lastly, we applied the protocol for the composition analysis of a synthetic community of environmental isolates grown on two different media. This protocol has been developed to facilitate rapid, low-variance sample preparation of hundreds of samples and allow flexibility for future protocol development.
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Affiliation(s)
- Yan Chen
- Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, California, United States of America
- DOE Joint BioEnergy Institute, Emeryville, California, United States of America
- DOE Agile BioFoundry, Emeryville, California, United States of America
| | - Jennifer W Gin
- Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, California, United States of America
- DOE Joint BioEnergy Institute, Emeryville, California, United States of America
- DOE Agile BioFoundry, Emeryville, California, United States of America
| | - Ying Wang
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, California, United States of America
| | - Markus de Raad
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, California, United States of America
| | - Stephen Tan
- Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, California, United States of America
- DOE Joint BioEnergy Institute, Emeryville, California, United States of America
- DOE Agile BioFoundry, Emeryville, California, United States of America
| | - Nathan J Hillson
- Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, California, United States of America
- DOE Joint BioEnergy Institute, Emeryville, California, United States of America
- DOE Agile BioFoundry, Emeryville, California, United States of America
| | - Trent R Northen
- DOE Joint BioEnergy Institute, Emeryville, California, United States of America
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, California, United States of America
| | - Paul D Adams
- DOE Joint BioEnergy Institute, Emeryville, California, United States of America
- Department of Bioengineering, University of California Berkeley, Berkeley, California, United States of America
- Molecular Biophysics and Bioimaging Division, Lawrence Berkeley National Laboratory, Berkeley, California, United States of America
| | - Christopher J Petzold
- Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, California, United States of America
- DOE Joint BioEnergy Institute, Emeryville, California, United States of America
- DOE Agile BioFoundry, Emeryville, California, United States of America
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2
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Bowser BL, Robinson RAS. Enhanced Multiplexing Technology for Proteomics. ANNUAL REVIEW OF ANALYTICAL CHEMISTRY (PALO ALTO, CALIF.) 2023; 16:379-400. [PMID: 36854207 DOI: 10.1146/annurev-anchem-091622-092353] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
The identification of thousands of proteins and their relative levels of expression has furthered understanding of biological processes and disease and stimulated new systems biology hypotheses. Quantitative proteomics workflows that rely on analytical assays such as mass spectrometry have facilitated high-throughput measurements of proteins partially due to multiplexing. Multiplexing allows proteome differences across multiple samples to be measured simultaneously, resulting in more accurate quantitation, increased statistical robustness, reduced analysis times, and lower experimental costs. The number of samples that can be multiplexed has evolved from as few as two to more than 50, with studies involving more than 10 samples being denoted as enhanced multiplexing or hyperplexing. In this review, we give an update on emerging multiplexing proteomics techniques and highlight advantages and limitations for enhanced multiplexing strategies.
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Affiliation(s)
- Bailey L Bowser
- Department of Chemistry, Vanderbilt University, Nashville, Tennessee, USA;
| | - Renã A S Robinson
- Department of Chemistry, Vanderbilt University, Nashville, Tennessee, USA;
- Department of Neurology, Vanderbilt University Medical Center, Vanderbilt University, Nashville, Tennessee, USA
- Vanderbilt Memory and Alzheimer's Center, Nashville, Tennessee, USA
- Vanderbilt Institute of Chemical Biology, Vanderbilt School of Medicine, Nashville, Tennessee, USA
- Vanderbilt Brain Institute, Vanderbilt School of Medicine, Nashville, Tennessee, USA
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3
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Monteiro JP, Morine MJ, Ued FV, Kaput J. Identifying and Analyzing Topic Clusters in a Nutri-, Food-, and Diet-Proteomic Corpus Using Machine Reading. Nutrients 2023; 15:nu15020270. [PMID: 36678141 PMCID: PMC9863309 DOI: 10.3390/nu15020270] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2022] [Revised: 12/27/2022] [Accepted: 12/30/2022] [Indexed: 01/06/2023] Open
Abstract
Nutrition affects the early stages of disease development, but the mechanisms remain poorly understood. High-throughput proteomic methods are being used to generate data and information on the effects of nutrients, foods, and diets on health and disease processes. In this report, a novel machine reading pipeline was used to identify all articles and abstracts on proteomics, diet, food, and nutrition in humans. The resulting proteomic corpus was further analyzed to produce seven clusters of "thematic" content defined as documents that have similar word content. Examples of publications from several of these clusters were then described in a similar way to a typical descriptive review.
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Affiliation(s)
- Jacqueline Pontes Monteiro
- Department of Pediatrics, Ribeirão Preto Medical School, University of São Paulo, Bandeirantes Avenue, 3900, Ribeirão Preto 14049-900, Brazil
- Correspondence:
| | | | - Fabio V. Ued
- Department of Pediatrics, Ribeirão Preto Medical School, University of São Paulo, Bandeirantes Avenue, 3900, Ribeirão Preto 14049-900, Brazil
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4
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King CD, Kapp KL, Arul AB, Choi MJ, Robinson RAS. Advancements in automation for plasma proteomics sample preparation. Mol Omics 2022; 18:828-839. [PMID: 36048090 PMCID: PMC9879274 DOI: 10.1039/d2mo00122e] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/28/2023]
Abstract
Automation is necessary to increase sample processing throughput for large-scale clinical analyses. Replacement of manual pipettes with robotic liquid handler systems is especially helpful in processing blood-based samples, such as plasma and serum. These samples are very heterogenous, and protein expression can vary greatly from sample-to-sample, even for healthy controls. Detection of true biological changes requires that variation from sample preparation steps and downstream analytical detection methods, such as mass spectrometry, remains low. In this mini-review, we discuss plasma proteomics protocols and the benefits of automation towards enabling detection of low abundant proteins and providing low sample error and increased sample throughput. This discussion includes considerations for automation of major sample depletion and/or enrichment strategies for plasma toward mass spectrometry detection.
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Affiliation(s)
- Christina D King
- Department of Chemistry, Vanderbilt University, Nashville, Tennessee 37235, USA
| | - Kathryn L Kapp
- Department of Chemistry, Vanderbilt University, Nashville, Tennessee 37235, USA
- Vanderbilt Institute of Chemical Biology, Vanderbilt University, Nashville, Tennessee 37232, USA
| | - Albert B Arul
- Department of Chemistry, Vanderbilt University, Nashville, Tennessee 37235, USA
| | - Min Ji Choi
- Department of Chemistry, Vanderbilt University, Nashville, Tennessee 37235, USA
| | - Renã A S Robinson
- Department of Chemistry, Vanderbilt University, Nashville, Tennessee 37235, USA
- Vanderbilt Institute of Chemical Biology, Vanderbilt University, Nashville, Tennessee 37232, USA
- Department of Neurology, Vanderbilt University Medical Center, Nashville, Tennessee 37232, USA
- Vanderbilt Memory & Alzheimer's Center, Vanderbilt University Medical Center, Nashville, Tennessee 37212, USA
- Vanderbilt Brain Institute, Vanderbilt University, Nashville, Tennessee 37232, USA
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5
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Cominetti O, Núñez Galindo A, Corthésy J, Carayol J, Germain N, Galusca B, Estour B, Hager J, Gheldof N, Dayon L. Proteomics reveals unique plasma signatures in constitutional thinness. Proteomics Clin Appl 2022; 16:e2100114. [PMID: 35579096 PMCID: PMC9787820 DOI: 10.1002/prca.202100114] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2021] [Revised: 04/14/2022] [Accepted: 05/13/2022] [Indexed: 12/30/2022]
Abstract
PURPOSE Studying the plasma proteome of control versus constitutionally thin (CT) individuals, exposed to overfeeding, may give insights into weight-gain management, providing relevant information to the clinical entity of weight-gain resistant CT, and discovering new markers for the condition. EXPERIMENTAL DESIGN Untargeted protein relative quantification of 63 CT and normal-weight individuals was obtained in blood plasma at baseline, during and after an overfeeding challenge using mass spectrometry-based proteomics. RESULTS The plasma proteome of CT subjects presented limited specificity with respect to controls at baseline. Yet, CT showed lower levels of inflammatory C-reactive protein and larger levels of protective insulin-like growth factor-binding protein 2. Differences were more marked during and after overfeeding. CT plasma proteome showed larger magnitude and significance in response, suggesting enhanced "resilience" and more rapid adaptation to changes. Four proteins behaved similarly between CT and controls, while five were regulated in opposite fashion. Ten proteins were differential during overfeeding in CT only (including increased fatty acid-binding protein and glyceraldehyde-3-phosphate dehydrogenase, and decreased apolipoprotein C-II and transferrin receptor protein 1). CONCLUSIONS AND CLINICAL RELEVANCE This first proteomic profiling of a CT cohort reveals different plasma proteomes between CT subjects and controls in a longitudinal clinical trial. Our molecular observations further support that the resistance to weight gain in CT subjects appears predominantly biological. CLINICALTRIALS gov Identifier: NCT02004821.
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Affiliation(s)
- Ornella Cominetti
- Nestlé Institute of Food Safety & Analytical SciencesNestlé ResearchLausanneSwitzerland
| | - Antonio Núñez Galindo
- Nestlé Institute of Food Safety & Analytical SciencesNestlé ResearchLausanneSwitzerland
| | - John Corthésy
- Nestlé Institute of Food Safety & Analytical SciencesNestlé ResearchLausanneSwitzerland
| | - Jérôme Carayol
- Nestlé Institute of Health SciencesNestlé ResearchLausanneSwitzerland,Present address:
Playtika Switzerland SARue du Port‐Franc 2ALausanne1003Switzerland
| | - Natacha Germain
- Division of EndocrinologyDiabetes, Metabolism and Eating Disorders, CHU St‐EtienneFrance
| | - Bogdan Galusca
- Division of EndocrinologyDiabetes, Metabolism and Eating Disorders, CHU St‐EtienneFrance
| | - Bruno Estour
- Division of EndocrinologyDiabetes, Metabolism and Eating Disorders, CHU St‐EtienneFrance
| | - Jörg Hager
- Nestlé Institute of Health SciencesNestlé ResearchLausanneSwitzerland
| | - Nele Gheldof
- Nestlé Institute of Health SciencesNestlé ResearchLausanneSwitzerland,Present address:
VPA ‐ AVP‐R‐Administration, EPFLBI A2 483, Station 7Lausanne1015Switzerland
| | - Loïc Dayon
- Nestlé Institute of Food Safety & Analytical SciencesNestlé ResearchLausanneSwitzerland,Institut des Sciences et Ingénierie ChimiquesÉcole Polytechnique Fédérale de Lausanne (EPFL)LausanneSwitzerland
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6
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Dayon L, Cominetti O, Affolter M. Proteomics of Human Biological Fluids for Biomarker Discoveries: Technical Advances and Recent Applications. Expert Rev Proteomics 2022; 19:131-151. [PMID: 35466824 DOI: 10.1080/14789450.2022.2070477] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
INTRODUCTION Biological fluids are routine samples for diagnostic testing and monitoring. Blood samples are typically measured because of their moderate collection invasiveness and high information content on health and disease. Several body fluids, such as cerebrospinal fluid (CSF), are also studied and suited to specific pathologies. Over the last two decades proteomics has quested to identify protein biomarkers but with limited success. Recent technologies and refined pipelines have accelerated the profiling of human biological fluids. AREAS COVERED We review proteomic technologies for the identification of biomarkers. Those are based on antibodies/aptamers arrays or mass spectrometry (MS), but new ones are emerging. Advances in scalability and throughput have allowed to better design studies and cope with the limited sample size that had until now prevailed due to technological constraints. With these enablers, plasma/serum, CSF, saliva, tears, urine, and milk proteomes have been further profiled; we provide a non-exhaustive picture of some recent highlights (mainly covering literature from last five years in the Scopus database) using MS-based proteomics. EXPERT OPINION While proteomics has been in the shadow of genomics for years, proteomic tools and methodologies have reached a certain maturity. They are better suited to discover innovative and robust biofluid biomarkers.
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Affiliation(s)
- Loïc Dayon
- Proteomics, Nestlé Institute of Food Safety & Analytical Sciences, Nestlé Research, CH-1015 Lausanne, Switzerland.,Institut des Sciences et Ingénierie Chimiques, Ecole Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland
| | - Ornella Cominetti
- Proteomics, Nestlé Institute of Food Safety & Analytical Sciences, Nestlé Research, CH-1015 Lausanne, Switzerland
| | - Michael Affolter
- Proteomics, Nestlé Institute of Food Safety & Analytical Sciences, Nestlé Research, CH-1015 Lausanne, Switzerland
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Chen Y, Kaplan Lease N, Gin JW, Ogorzalek TL, Adams PD, Hillson NJ, Petzold CJ. Modular automated bottom-up proteomic sample preparation for high-throughput applications. PLoS One 2022; 17:e0264467. [PMID: 35213656 PMCID: PMC8880914 DOI: 10.1371/journal.pone.0264467] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2021] [Accepted: 02/09/2022] [Indexed: 11/24/2022] Open
Abstract
Manual proteomic sample preparation methods limit sample throughput and often lead to poor data quality when thousands of samples must be analyzed. Automated liquid handler systems are increasingly used to overcome these issues for many of the sample preparation steps. Here, we detail a step-by-step protocol to prepare samples for bottom-up proteomic analysis for Gram-negative bacterial and fungal cells. The full modular protocol consists of three optimized protocols to: (A) lyse Gram-negative bacteria and fungal cells; (B) quantify the amount of protein extracted; and (C) normalize the amount of protein and set up tryptic digestion. These protocols have been developed to facilitate rapid, low variance sample preparation of hundreds of samples, be easily implemented on widely-available Beckman-Coulter Biomek automated liquid handlers, and allow flexibility for future protocol development. By using this workflow 50 micrograms of protein from 96 samples can be prepared for tryptic digestion in under an hour. We validate these protocols by analyzing 47 Pseudomonas putida and Rhodosporidium toruloides samples and show that this modular workflow provides robust, reproducible proteomic samples for high-throughput applications. The expected results from these protocols are 94 peptide samples from Gram-negative bacterial and fungal cells prepared for bottom-up quantitative proteomic analysis without the need for desalting column cleanup and with protein relative quantity variance (CV%) below 15%.
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Affiliation(s)
- Yan Chen
- Joint BioEnergy Institute, Lawrence Berkeley National Laboratory, Emeryville, CA, United States of America
- Agile BioFoundry, Lawrence Berkeley National Laboratory, Emeryville, CA, United States of America
- Biological Systems & Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, CA, United States of America
| | - Nurgul Kaplan Lease
- Joint BioEnergy Institute, Lawrence Berkeley National Laboratory, Emeryville, CA, United States of America
- Agile BioFoundry, Lawrence Berkeley National Laboratory, Emeryville, CA, United States of America
- Biological Systems & Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, CA, United States of America
| | - Jennifer W. Gin
- Joint BioEnergy Institute, Lawrence Berkeley National Laboratory, Emeryville, CA, United States of America
- Agile BioFoundry, Lawrence Berkeley National Laboratory, Emeryville, CA, United States of America
- Biological Systems & Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, CA, United States of America
| | - Tadeusz L. Ogorzalek
- Joint BioEnergy Institute, Lawrence Berkeley National Laboratory, Emeryville, CA, United States of America
- Agile BioFoundry, Lawrence Berkeley National Laboratory, Emeryville, CA, United States of America
- Biological Systems & Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, CA, United States of America
| | - Paul D. Adams
- Joint BioEnergy Institute, Lawrence Berkeley National Laboratory, Emeryville, CA, United States of America
- Department of Bioengineering, University of California Berkeley, Berkeley, CA, United States of America
- Molecular Biophysics and Bioimaging Division, Lawrence Berkeley National Laboratory, Berkeley, CA, United States of America
| | - Nathan J. Hillson
- Joint BioEnergy Institute, Lawrence Berkeley National Laboratory, Emeryville, CA, United States of America
- Agile BioFoundry, Lawrence Berkeley National Laboratory, Emeryville, CA, United States of America
- Biological Systems & Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, CA, United States of America
| | - Christopher J. Petzold
- Joint BioEnergy Institute, Lawrence Berkeley National Laboratory, Emeryville, CA, United States of America
- Agile BioFoundry, Lawrence Berkeley National Laboratory, Emeryville, CA, United States of America
- Biological Systems & Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, CA, United States of America
- * E-mail:
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8
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Burns AP, Zhang YQ, Xu T, Wei Z, Yao Q, Fang Y, Cebotaru V, Xia M, Hall MD, Huang R, Simeonov A, LeClair CA, Tao D. A Universal and High-Throughput Proteomics Sample Preparation Platform. Anal Chem 2021; 93:8423-8431. [PMID: 34110797 PMCID: PMC9876622 DOI: 10.1021/acs.analchem.1c00265] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
Abstract
Major advances have been made to improve the sensitivity of mass analyzers, spectral quality, and speed of data processing enabling more comprehensive proteome discovery and quantitation. While focus has recently begun shifting toward robust proteomics sample preparation efforts, a high-throughput proteomics sample preparation is still lacking. We report the development of a highly automated universal 384-well plate sample preparation platform with high reproducibility and adaptability for extraction of proteins from cells within a culture plate. Digestion efficiency was excellent in comparison to a commercial digest peptide standard with minimal sample loss while improving sample preparation throughput by 20- to 40-fold (the entire process from plated cells to clean peptides is complete in ∼300 min). Analysis of six human cell types, including two primary cell samples, identified and quantified ∼4,000 proteins for each sample in a single high-performance liquid chromatography (HPLC)-tandem mass spectrometry injection with only 100-10K cells, thus demonstrating universality of the platform. The selected protein was further quantified using a developed HPLC-multiple reaction monitoring method for HeLa digests with two heavy labeled internal standard peptides spiked in. Excellent linearity was achieved across different cell numbers indicating a potential for target protein quantitation in clinical research.
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Affiliation(s)
- Andrew P. Burns
- National Center for Advancing Translational Sciences, National Institutes of Health, 9800 Medical Center Drive, Rockville, Maryland 20850, United States
| | - Ya-Qin Zhang
- National Center for Advancing Translational Sciences, National Institutes of Health, 9800 Medical Center Drive, Rockville, Maryland 20850, United States
| | - Tuan Xu
- National Center for Advancing Translational Sciences, National Institutes of Health, 9800 Medical Center Drive, Rockville, Maryland 20850, United States
| | - Zhengxi Wei
- National Center for Advancing Translational Sciences, National Institutes of Health, 9800 Medical Center Drive, Rockville, Maryland 20850, United States
| | - Qin Yao
- Division of Nephrology, Department of Medicine, University of Maryland School of Medicine, Baltimore, Maryland 21201, United States
| | - Yuhong Fang
- National Center for Advancing Translational Sciences, National Institutes of Health, 9800 Medical Center Drive, Rockville, Maryland 20850, United States
| | - Valeriu Cebotaru
- Division of Nephrology, Department of Medicine, University of Maryland School of Medicine, Baltimore, Maryland 21201, United States
| | - Menghang Xia
- National Center for Advancing Translational Sciences, National Institutes of Health, 9800 Medical Center Drive, Rockville, Maryland 20850, United States
| | - Matthew D. Hall
- National Center for Advancing Translational Sciences, National Institutes of Health, 9800 Medical Center Drive, Rockville, Maryland 20850, United States
| | - Ruili Huang
- National Center for Advancing Translational Sciences, National Institutes of Health, 9800 Medical Center Drive, Rockville, Maryland 20850, United States
| | - Anton Simeonov
- National Center for Advancing Translational Sciences, National Institutes of Health, 9800 Medical Center Drive, Rockville, Maryland 20850, United States
| | - Christopher A. LeClair
- National Center for Advancing Translational Sciences, National Institutes of Health, 9800 Medical Center Drive, Rockville, Maryland 20850, United States.,Corresponding authors: Dr. Christopher A. LeClair, and Dr. Dingyin Tao,
| | - Dingyin Tao
- National Center for Advancing Translational Sciences, National Institutes of Health, 9800 Medical Center Drive, Rockville, Maryland 20850, United States.,Corresponding authors: Dr. Christopher A. LeClair, and Dr. Dingyin Tao,
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Abstract
Proteases play a central role in regulating renal pathophysiology and are increasingly evaluated as actionable drug targets. Here, we review the role of proteolytic systems in inflammatory kidney disease. Inflammatory kidney diseases are associated with broad dysregulations of extracellular and intracellular proteolysis. As an example of a proteolytic system, the complement system plays a significant role in glomerular inflammatory kidney disease and is currently under clinical investigation. Based on two glomerular kidney diseases, lupus nephritis, and membranous nephropathy, we portrait two proteolytic pathomechanisms and the role of the complement system. We discuss how profiling proteolytic activity in patient samples could be used to stratify patients for more targeted interventions in inflammatory kidney diseases. We also describe novel comprehensive, quantitative tools to investigate the entirety of proteolytic processes in a tissue sample. Emphasis is placed on mass spectrometric approaches that enable the comprehensive analysis of the complement system, as well as protease activities and regulation in general.
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10
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Clark C, Dayon L, Masoodi M, Bowman GL, Popp J. An integrative multi-omics approach reveals new central nervous system pathway alterations in Alzheimer's disease. ALZHEIMERS RESEARCH & THERAPY 2021; 13:71. [PMID: 33794997 PMCID: PMC8015070 DOI: 10.1186/s13195-021-00814-7] [Citation(s) in RCA: 40] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/30/2020] [Accepted: 03/23/2021] [Indexed: 02/06/2023]
Abstract
BACKGROUND Multiple pathophysiological processes have been described in Alzheimer's disease (AD). Their inter-individual variations, complex interrelations, and relevance for clinical manifestation and disease progression remain poorly understood. We hypothesize that specific molecular patterns indicating both known and yet unidentified pathway alterations are associated with distinct aspects of AD pathology. METHODS We performed multi-level cerebrospinal fluid (CSF) omics in a well-characterized cohort of older adults with normal cognition, mild cognitive impairment, and mild dementia. Proteomics, metabolomics, lipidomics, one-carbon metabolism, and neuroinflammation related molecules were analyzed at single-omic level with correlation and regression approaches. Multi-omics factor analysis was used to integrate all biological levels. Identified analytes were used to construct best predictive models of the presence of AD pathology and of cognitive decline with multifactorial regression analysis. Pathway enrichment analysis identified pathway alterations in AD. RESULTS Multi-omics integration identified five major dimensions of heterogeneity explaining the variance within the cohort and differentially associated with AD. Further analysis exposed multiple interactions between single 'omics modalities and distinct multi-omics molecular signatures differentially related to amyloid pathology, neuronal injury, and tau hyperphosphorylation. Enrichment pathway analysis revealed overrepresentation of the hemostasis, immune response, and extracellular matrix signaling pathways in association with AD. Finally, combinations of four molecules improved prediction of both AD (protein 14-3-3 zeta/delta, clusterin, interleukin-15, and transgelin-2) and cognitive decline (protein 14-3-3 zeta/delta, clusterin, cholesteryl ester 27:1 16:0 and monocyte chemoattractant protein-1). CONCLUSIONS Applying an integrative multi-omics approach we report novel molecular and pathways alterations associated with AD pathology. These findings are relevant for the development of personalized diagnosis and treatment approaches in AD.
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Affiliation(s)
- Christopher Clark
- Institute for Regenerative Medicine, University of Zürich, Wagistrasse 12, 8952, Schlieren, Switzerland
| | - Loïc Dayon
- Nestlé Institute of Health Sciences, Nestlé Research, EPFL Innovation Park, 1015, Lausanne, Switzerland.,Nestlé Institute of Food Safety & Analytical Sciences, Nestlé Research, EPFL Innovation Park, 1015, Lausanne, Switzerland.,Institut des Sciences et Ingénierie Chimiques, Ecole Polytechnique Fédérale de Lausanne, 1015, Lausanne, Switzerland
| | - Mojgan Masoodi
- Nestlé Institute of Health Sciences, Nestlé Research, EPFL Innovation Park, 1015, Lausanne, Switzerland.,Institute of Clinical Chemistry, University Hospital Bern, Bern, Switzerland
| | - Gene L Bowman
- Nestlé Institute of Health Sciences, Nestlé Research, EPFL Innovation Park, 1015, Lausanne, Switzerland.,Department of Neurology, NIA-Layton Aging and Alzheimer's Disease Center, Oregon Health & Science University, Portland, USA
| | - Julius Popp
- Old Age Psychiatry, Centre Hospitalier Universitaire Vaudois, Rue du Bugnon 46, 1011, Lausanne, Switzerland. .,Department of Geriatric Psychiatry, University Hospital of Psychiatry Zürich, Centre for Gerontopsychiatric Medicine, Minervastrasse 145, P.O. Box 341, 8032, Zürich, Switzerland.
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11
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Dayon L, Macron C, Lahrichi S, Núñez Galindo A, Affolter M. Proteomics of Human Milk: Definition of a Discovery Workflow for Clinical Research Studies. J Proteome Res 2021; 20:2283-2290. [PMID: 33769819 DOI: 10.1021/acs.jproteome.0c00816] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Milk is a complex biological fluid composed mainly of water, carbohydrates, lipids, proteins, and diverse bioactive factors. Human milk represents a unique tailored source of nutrients that adapts during lactation to the specific needs of the developing infant. Proteins in milk have been studied for decades, and proteomics, peptidomics, and glycoproteomics are the main approaches previously deployed to decipher the proteome of human milk. In the present work, we aimed at implementing a highly automated pipeline for the proteomic analysis of human milk with liquid chromatography mass spectrometry (MS). Commercial human milk samples were used to evaluate and optimize workflows. Centrifugation for defatting milk samples was assessed before and after reduction, alkylation, and enzymatic digestion of proteins, without and with presence of surfactants. Skimmed milk samples were analyzed using isobaric labeling-based quantitative MS on an Orbitrap Tribrid mass spectrometer. Sample fractionation using isoelectric focusing was also evaluated to more deeply profile the human milk proteome. Finally, the most appropriate workflow was transferred to a liquid handling workstation for automated sample preparation. In conclusion, we have defined and describe herein an efficient highly automated proteomic workflow for human milk sample analysis. It is compatible with clinical research, possibly allowing the analysis of sufficiently large cohorts of samples.
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Affiliation(s)
- Loïc Dayon
- Proteomics, Nestlé Institute of Food Safety & Analytical Sciences, Nestlé Research, Lausanne 1015, Switzerland.,Institut des Sciences et Ingénierie Chimiques, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne 1015, Switzerland
| | - Charlotte Macron
- Proteomics, Nestlé Institute of Food Safety & Analytical Sciences, Nestlé Research, Lausanne 1015, Switzerland
| | - Sabine Lahrichi
- Proteomics, Nestlé Institute of Food Safety & Analytical Sciences, Nestlé Research, Lausanne 1015, Switzerland
| | - Antonio Núñez Galindo
- Proteomics, Nestlé Institute of Food Safety & Analytical Sciences, Nestlé Research, Lausanne 1015, Switzerland
| | - Michael Affolter
- Proteomics, Nestlé Institute of Food Safety & Analytical Sciences, Nestlé Research, Lausanne 1015, Switzerland
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12
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Higginbotham L, Ping L, Dammer EB, Duong DM, Zhou M, Gearing M, Hurst C, Glass JD, Factor SA, Johnson ECB, Hajjar I, Lah JJ, Levey AI, Seyfried NT. Integrated proteomics reveals brain-based cerebrospinal fluid biomarkers in asymptomatic and symptomatic Alzheimer's disease. SCIENCE ADVANCES 2020; 6:eaaz9360. [PMID: 33087358 PMCID: PMC7577712 DOI: 10.1126/sciadv.aaz9360] [Citation(s) in RCA: 158] [Impact Index Per Article: 39.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/21/2019] [Accepted: 09/03/2020] [Indexed: 05/02/2023]
Abstract
Alzheimer's disease (AD) lacks protein biomarkers reflective of its diverse underlying pathophysiology, hindering diagnostic and therapeutic advancements. Here, we used integrative proteomics to identify cerebrospinal fluid (CSF) biomarkers representing a wide spectrum of AD pathophysiology. Multiplex mass spectrometry identified ~3500 and ~12,000 proteins in AD CSF and brain, respectively. Network analysis of the brain proteome resolved 44 biologically diverse modules, 15 of which overlapped with the CSF proteome. CSF AD markers in these overlapping modules were collapsed into five protein panels representing distinct pathophysiological processes. Synaptic and metabolic panels were decreased in AD brain but increased in CSF, while glial-enriched myelination and immunity panels were increased in brain and CSF. The consistency and disease specificity of panel changes were confirmed in >500 additional CSF samples. These panels also identified biological subpopulations within asymptomatic AD. Overall, these results are a promising step toward a network-based biomarker tool for AD clinical applications.
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Affiliation(s)
- Lenora Higginbotham
- Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA
- Center for Neurodegenerative Disease, Emory University School of Medicine, Atlanta, GA, USA
- Goizueta Alzheimer's Disease Research Center, Emory University, Atlanta, GA, USA
| | - Lingyan Ping
- Center for Neurodegenerative Disease, Emory University School of Medicine, Atlanta, GA, USA
- Goizueta Alzheimer's Disease Research Center, Emory University, Atlanta, GA, USA
- Department of Biochemistry, Emory University School of Medicine, Atlanta, GA, USA
| | - Eric B Dammer
- Center for Neurodegenerative Disease, Emory University School of Medicine, Atlanta, GA, USA
- Goizueta Alzheimer's Disease Research Center, Emory University, Atlanta, GA, USA
- Department of Biochemistry, Emory University School of Medicine, Atlanta, GA, USA
| | - Duc M Duong
- Center for Neurodegenerative Disease, Emory University School of Medicine, Atlanta, GA, USA
- Goizueta Alzheimer's Disease Research Center, Emory University, Atlanta, GA, USA
- Department of Biochemistry, Emory University School of Medicine, Atlanta, GA, USA
| | - Maotian Zhou
- Center for Neurodegenerative Disease, Emory University School of Medicine, Atlanta, GA, USA
- Goizueta Alzheimer's Disease Research Center, Emory University, Atlanta, GA, USA
- Department of Biochemistry, Emory University School of Medicine, Atlanta, GA, USA
| | - Marla Gearing
- Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA
- Goizueta Alzheimer's Disease Research Center, Emory University, Atlanta, GA, USA
- Department of Pathology and Laboratory Medicine, Emory University School of Medicine, Atlanta, GA, USA
| | - Cheyenne Hurst
- Center for Neurodegenerative Disease, Emory University School of Medicine, Atlanta, GA, USA
| | - Jonathan D Glass
- Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA
- Center for Neurodegenerative Disease, Emory University School of Medicine, Atlanta, GA, USA
- Goizueta Alzheimer's Disease Research Center, Emory University, Atlanta, GA, USA
| | - Stewart A Factor
- Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA
| | - Erik C B Johnson
- Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA
- Center for Neurodegenerative Disease, Emory University School of Medicine, Atlanta, GA, USA
- Goizueta Alzheimer's Disease Research Center, Emory University, Atlanta, GA, USA
| | - Ihab Hajjar
- Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA
- Goizueta Alzheimer's Disease Research Center, Emory University, Atlanta, GA, USA
| | - James J Lah
- Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA
- Center for Neurodegenerative Disease, Emory University School of Medicine, Atlanta, GA, USA
- Goizueta Alzheimer's Disease Research Center, Emory University, Atlanta, GA, USA
| | - Allan I Levey
- Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA.
- Center for Neurodegenerative Disease, Emory University School of Medicine, Atlanta, GA, USA
- Goizueta Alzheimer's Disease Research Center, Emory University, Atlanta, GA, USA
| | - Nicholas T Seyfried
- Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA.
- Center for Neurodegenerative Disease, Emory University School of Medicine, Atlanta, GA, USA
- Goizueta Alzheimer's Disease Research Center, Emory University, Atlanta, GA, USA
- Department of Biochemistry, Emory University School of Medicine, Atlanta, GA, USA
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13
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High-throughput proteotyping of bacterial isolates by double barrel chromatography-tandem mass spectrometry based on microplate paramagnetic beads and phylopeptidomics. J Proteomics 2020; 226:103887. [PMID: 32619772 DOI: 10.1016/j.jprot.2020.103887] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2020] [Revised: 06/19/2020] [Accepted: 06/25/2020] [Indexed: 12/18/2022]
Abstract
Tandem mass spectrometry-based proteotyping of microorganisms presents several advantages over whole-cell MALDI-TOF mass spectrometry: because a larger number of signals are recorded with better accuracy and precision, the approach allows for the identification of microorganisms at more resolved taxonomic levels, and can easily manage complex samples. Additionally, the use of SP3 paramagnetic beads for cell lysis and protein cleanup simplifies sample preparation for proteotyping. Based on these features, we have developed and tested a 96-well plate platform for high-throughput proteotyping of a large variety of bacteria. We evaluated the performance of the platform in terms of bacterial load and found no cross-contamination between wells. Likewise, phylopeptidomics analysis revealed no alteration in the relative quantifications of microorganisms. Finally, we applied this new format for rapid proteotyping of a large set of dental isolates using double-barrel chromatography coupled to tandem mass spectrometry, which maximizes the number of spectra per unit of time. The procedure allowed us to establish whether these isolates were pure strains or mixtures of strains and to identify the microorganisms at the most resolved taxonomic level. SIGNIFICANCE: The rapid and accurate identification of microorganisms is a clinical priority in medical diagnostics; however, specimens containing mixtures of microorganisms are difficult to analyze and the procedure is time-consuming. Tandem mass spectrometry proteotyping allows the fast identification of complex mixtures of microorganisms, known or unknown, and can also establish the biomass ratio of each component. We describe here a new workflow for preparing microbial samples in a 96-well-plate format for tandem mass spectrometry proteotyping and document its advantages and limitations. We demonstrate that this new format coupled to a highly efficient double-barrel LC-MS/MS system allows proteotyping of 96 isolates in 55 h.
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14
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Macron C, Núñez Galindo A, Cominetti O, Dayon L. A Versatile Workflow for Cerebrospinal Fluid Proteomic Analysis with Mass Spectrometry: A Matter of Choice between Deep Coverage and Sample Throughput. Methods Mol Biol 2020; 2044:129-154. [PMID: 31432411 DOI: 10.1007/978-1-4939-9706-0_9] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Human cerebrospinal fluid (CSF) is a sample of choice in the study of brain disorders. This biological fluid circulates in the brain and the spinal cord and contains tissue-specific proteins, indicative of health and disease conditions. Despite its potential as a valid source of biological markers, CSF remains largely understudied as compared to blood, in particular due to its more invasive way of sampling.Challenges remain when performing proteomic analysis in clinical research studies. State-of-the-art mass spectrometry (MS) enables deep characterization of the human proteome. But some technical limitations are cardinal to be addressed, such as the capacity to routinely analyze large cohorts of samples. Importantly, a trade-off still needs to be made between the proteome coverage depth and the number of measured samples. In this context, we developed a scalable automated proteomic pipeline for the analysis of CSF. Because of its versatility, this workflow can be adapted to accommodate proteome coverage and/or sample throughput. It allows us to prepare and quantitatively analyze hundreds to thousands of CSF samples; it can also allow identification of more than 3000 proteins in a CSF sample when coupled with isoelectric focusing fractionation.In this chapter, we describe an end-to-end pipeline for the proteomic analysis of CSF. The main steps of the sample preparation comprise spiking of a standard, protein digestion, isobaric labeling, and purification; these are performed in a 96-well plate format enabling automation. Depending on the targeted depth of the CSF proteome, optional analytical steps can be included, such as the removal of abundant proteins and sample pre-fractionation. Liquid chromatography tandem MS as well as data processing and analysis complete the pipeline.
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Affiliation(s)
- Charlotte Macron
- Proteomics, Nestlé Institute of Health Sciences, Nestlé Research, Lausanne, Switzerland
| | - Antonio Núñez Galindo
- Proteomics, Nestlé Institute of Health Sciences, Nestlé Research, Lausanne, Switzerland
| | - Ornella Cominetti
- Proteomics, Nestlé Institute of Health Sciences, Nestlé Research, Lausanne, Switzerland
| | - Loïc Dayon
- Proteomics, Nestlé Institute of Health Sciences, Nestlé Research, Lausanne, Switzerland.
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15
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Macron C, Lavigne R, Núñez Galindo A, Affolter M, Pineau C, Dayon L. Exploration of human cerebrospinal fluid: A large proteome dataset revealed by trapped ion mobility time-of-flight mass spectrometry. Data Brief 2020; 31:105704. [PMID: 32478154 PMCID: PMC7251648 DOI: 10.1016/j.dib.2020.105704] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2020] [Accepted: 05/06/2020] [Indexed: 01/16/2023] Open
Abstract
Cerebrospinal fluid (CSF) is a biofluid in direct contact with the brain and as such constitutes a sample of choice in neurological disorder research, including neurodegenerative diseases such as Alzheimer or Parkinson. Human CSF has still been less studied using proteomic technologies compared to other biological fluids such as blood plasma or serum. In this work, a pool of "normal" human CSF samples was analysed using a shotgun proteomic workflow that combined removal of highly abundant proteins by immunoaffinity depletion and isoelectric focussing fractionation of tryptic peptides to alleviate the complexity of the biofluid. The resulting 24 fractions were analysed using liquid chromatography coupled to a high-resolution and high-accuracy timsTOF Pro mass spectrometer. This state-of-the-art mass spectrometry-based proteomic workflow allowed the identification of 3'174 proteins in CSF. The dataset reported herein completes the pool of the most comprehensive human CSF proteomes obtained so far. An overview of the identified proteins is provided based on gene ontology annotation. Mass and tandem mass spectra are made available as a possible starting point for further studies exploring the human CSF proteome.
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Affiliation(s)
- Charlotte Macron
- Proteomics, Nestlé Institute for Food Safety & Analytical Sciences, Nestlé Research, 1015 Lausanne, Switzerland
| | - Regis Lavigne
- Univ Rennes, Inserm, EHESP, Irset (Institut de recherche en santé, environnement et travail)-UMR_S 1085, 35042 Rennes cedex, France.,Protim, Univ Rennes, F-35042 Rennes, France
| | - Antonio Núñez Galindo
- Proteomics, Nestlé Institute for Food Safety & Analytical Sciences, Nestlé Research, 1015 Lausanne, Switzerland
| | - Michael Affolter
- Proteomics, Nestlé Institute for Food Safety & Analytical Sciences, Nestlé Research, 1015 Lausanne, Switzerland
| | - Charles Pineau
- Univ Rennes, Inserm, EHESP, Irset (Institut de recherche en santé, environnement et travail)-UMR_S 1085, 35042 Rennes cedex, France.,Protim, Univ Rennes, F-35042 Rennes, France
| | - Loïc Dayon
- Proteomics, Nestlé Institute for Food Safety & Analytical Sciences, Nestlé Research, 1015 Lausanne, Switzerland.,Institut des Sciences et Ingénierie Chimiques, Ecole Polytechnique Fédérale de Lausanne (EPFL), 1015 Lausanne, Switzerland
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16
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Alexovič M, Urban PL, Tabani H, Sabo J. Recent advances in robotic protein sample preparation for clinical analysis and other biomedical applications. Clin Chim Acta 2020; 507:104-116. [PMID: 32305536 DOI: 10.1016/j.cca.2020.04.015] [Citation(s) in RCA: 40] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2020] [Revised: 04/11/2020] [Accepted: 04/13/2020] [Indexed: 02/06/2023]
Abstract
Discovery of new protein biomarker candidates has become a major research goal in the areas of clinical chemistry, analytical chemistry, and biomedicine. These important species constitute the molecular target when it comes to diagnosis, prognosis, and further monitoring of disease. However, their analysis requires powerful, selective and high-throughput sample preparation and product (analyte) characterisation approaches. In general, manual sample processing is tedious, complex and time-consuming, especially when large numbers of samples have to be processed (e.g., in clinical studies). Automation via microtiter-plate platforms involving robotics has brought improvements in high-throughput performance while comparable or even better precisions and repeatability (intra-day, inter-day) were achieved. At the same time, waste production and exposure of laboratory personnel to hazards were reduced. In comprehensive protein analysis workflows (e.g., liquid chromatography-tandem mass spectrometry analysis), sample preparation is an unavoidable step. This review surveys the recent achievements in automation of bottom-up and top-down protein and/or proteomics approaches. Emphasis is put on high-end multi-well plate robotic platforms developed for clinical analysis and other biomedical applications. The literature from 2013 to date has been covered.
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Affiliation(s)
- Michal Alexovič
- Department of Medical and Clinical Biophysics, Faculty of Medicine, University of P.J. Šafárik in Košice, 04011 Košice, Slovakia.
| | - Pawel L Urban
- Department of Chemistry, National Tsing Hua University, 101, Sec 2, Kuang-Fu Rd., Hsinchu 30013, Taiwan
| | - Hadi Tabani
- Department of Environmental Geology, Research Institute of Applied Sciences (ACECR), Shahid Beheshti University, Tehran, Iran
| | - Ján Sabo
- Department of Medical and Clinical Biophysics, Faculty of Medicine, University of P.J. Šafárik in Košice, 04011 Košice, Slovakia
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17
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Dayon L, Affolter M. Progress and pitfalls of using isobaric mass tags for proteome profiling. Expert Rev Proteomics 2020; 17:149-161. [PMID: 32067523 DOI: 10.1080/14789450.2020.1731309] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
Introduction: Quantitative proteomics using mass spectrometry is performed via label-free or label-based approaches. Labeling strategies rely on the incorporation of stable heavy isotopes by metabolic, enzymatic, or chemical routes. Isobaric labeling uses chemical labels of identical masses but of different fragmentation behaviors to allow the relative quantitative comparison of peptide/protein abundances between biological samples.Areas covered: We have carried out a systematic review on the use of isobaric mass tags in proteomic research since their inception in 2003. We focused on their quantitative performances, their multiplexing evolution, as well as their broad use for relative quantification of proteins in pre-clinical models and clinical studies. Current limitations, primarily linked to the quantitative ratio distortion, as well as state-of-the-art and emerging solutions to improve their quantitative readouts are discussed.Expert opinion: The isobaric mass tag technology offers a unique opportunity to compare multiple protein samples simultaneously, allowing higher sample throughput and internal relative quantification for improved trueness and precision. Large studies can be performed when shared reference samples are introduced in multiple experiments. The technology is well suited for proteome profiling in the context of proteomic discovery studies.
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Affiliation(s)
- Loïc Dayon
- Proteomics, Nestlé Institute of Food Safety & Analytical Sciences, Nestlé Research, Lausanne, Switzerland.,Institut des Sciences et Ingénierie Chimiques, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Michael Affolter
- Proteomics, Nestlé Institute of Food Safety & Analytical Sciences, Nestlé Research, Lausanne, Switzerland
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18
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Chen Y, Guenther JM, Gin JW, Chan LJG, Costello Z, Ogorzalek TL, Tran HM, Blake-Hedges JM, Keasling JD, Adams PD, García Martín H, Hillson NJ, Petzold CJ. Automated “Cells-To-Peptides” Sample Preparation Workflow for High-Throughput, Quantitative Proteomic Assays of Microbes. J Proteome Res 2019; 18:3752-3761. [DOI: 10.1021/acs.jproteome.9b00455] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/17/2023]
Affiliation(s)
| | - Joel M. Guenther
- Sandia National Laboratories (NTESS), Livermore, California 94551, United States
| | | | | | | | | | - Huu M. Tran
- Sandia National Laboratories (NTESS), Livermore, California 94551, United States
| | | | - Jay D. Keasling
- Department of Chemical and Biomolecular Engineering, University of California, Berkeley, California 94720-1460, United States
- The Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Kongens Lyngby 2800, Denmark
- Center for Synthetic Biochemistry, Synthetic Biology Institute, Shenzhen Institutes for Advanced Technologies, Shenzhen 518000, China
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19
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Lee J, Kim H, Sohn A, Yeo I, Kim Y. Cost-Effective Automated Preparation of Serum Samples for Reproducible Quantitative Clinical Proteomics. J Proteome Res 2019; 18:2337-2345. [PMID: 30985128 DOI: 10.1021/acs.jproteome.9b00023] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
Reproducible sample preparation remains a significant challenge in large-scale clinical research using selected reaction monitoring-mass spectrometry (SRM-MS), which enables a highly sensitive multiplexed assay. Although automated liquid-handling platforms have tremendous potential for addressing this issue, the high cost of their consumables is a drawback that renders routine operation expensive. Here we evaluated the performance of a liquid-handling platform in preparing serum samples compared with a standard experiment while reducing the outlay for consumables, such as tips, wasted reagents, and reagent stock plates. A total of 26 multiplex assays were quantified by SRM-MS using four sets of 24 pooled human serum aliquots; the four sets used a fixed number (1, 4, 8, or 24) of tips to dispense digestion reagents. This study demonstrated that the use of 4 or 8 tips is comparable to 24 tips (standard experiment), as evidenced by their coefficients of variation: 13.5% (for 4 and 8 tips) versus 12.0% (24 tips). Thus we can save 37% of the total experimental cost compared with the standard experiment, maintaining nearly equivalent reproducibility. The routine operation of cost-effective liquid-handling platforms can enable researchers to process large-scale samples with high throughput, adding credibility to their findings by minimizing human error.
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Affiliation(s)
| | - Hyunsoo Kim
- Institute of Medical and Biological Engineering, MRC , Seoul National University , Seoul , Korea
| | | | - Injoon Yeo
- Interdisciplinary Program of Bioengineering , Seoul National University College of Engineering , Seoul , Korea
| | - Youngsoo Kim
- Institute of Medical and Biological Engineering, MRC , Seoul National University , Seoul , Korea.,Interdisciplinary Program of Bioengineering , Seoul National University College of Engineering , Seoul , Korea
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20
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Spodzieja M, Rodziewicz-Motowidło S, Szymanska A. Hyphenated Mass Spectrometry Techniques in the Diagnosis of Amyloidosis. Curr Med Chem 2019; 26:104-120. [DOI: 10.2174/0929867324666171003113019] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2016] [Revised: 07/25/2016] [Accepted: 09/01/2016] [Indexed: 12/18/2022]
Abstract
Amyloidoses are a group of diseases caused by the extracellular deposition of proteins forming amyloid fibrils. The amyloidosis is classified according to the main protein or peptide that constitutes the amyloid fibrils. The most effective methods for the diagnosis of amyloidosis are based on mass spectrometry. Mass spectrometry enables confirmation of the identity of the protein precursor of amyloid fibrils in biological samples with very high sensitivity and specificity, which is crucial for proper amyloid typing. Due to the fact that biological samples are very complex, mass spectrometry is usually connected with techniques such as liquid chromatography or capillary electrophoresis, which enable the separation of proteins before MS analysis. Therefore mass spectrometry constitutes an important part of the so called “hyphenated techniques” combining, preferentially in-line, different analytical methods to provide comprehensive information about the studied problem. Hyphenated methods are very useful in the discovery of biomarkers in different types of amyloidosis. In systemic forms of amyloidosis, the analysis of aggregated proteins is usually performed based on the tissues obtained during a biopsy of an affected organ or a subcutaneous adipose tissue. In some cases, when the diagnostic biopsy is not possible due to the fact that amyloid fibrils are formed in organs like the brain (Alzheimer’s disease), the study of biomarkers presented in body fluids can be carried out. Currently, large-scale studies are performed to find and validate more effective biomarkers, which can be used in diagnostic procedures. We would like to present the methods connected with mass spectrometry which are used in the diagnosis of amyloidosis based on the analysis of proteins occurring in tissues, blood and cerebrospinal fluid.
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Affiliation(s)
- Marta Spodzieja
- Department of Biomedical Chemistry, Faculty of Chemistry, University of Gdansk, Wita Stwosza 63, 80-308 Gdansk, Poland
| | - Sylwia Rodziewicz-Motowidło
- Department of Biomedical Chemistry, Faculty of Chemistry, University of Gdansk, Wita Stwosza 63, 80-308 Gdansk, Poland
| | - Aneta Szymanska
- Department of Biomedical Chemistry, Faculty of Chemistry, University of Gdansk, Wita Stwosza 63, 80-308 Gdansk, Poland
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21
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Dayon L, Cominetti O, Wojcik J, Galindo AN, Oikonomidi A, Henry H, Migliavacca E, Kussmann M, Bowman GL, Popp J. Proteomes of Paired Human Cerebrospinal Fluid and Plasma: Relation to Blood–Brain Barrier Permeability in Older Adults. J Proteome Res 2019; 18:1162-1174. [DOI: 10.1021/acs.jproteome.8b00809] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- Loïc Dayon
- Nestlé Institute of Health Sciences, 1015 Lausanne, Switzerland
| | | | | | | | | | - Hugues Henry
- Department of Laboratories, CHUV, 1011 Lausanne, Switzerland
| | | | - Martin Kussmann
- Nestlé Institute of Health Sciences, 1015 Lausanne, Switzerland
| | - Gene L. Bowman
- Nestlé Institute of Health Sciences, 1015 Lausanne, Switzerland
| | - Julius Popp
- Old Age Psychiatry, Department of Psychiatry, CHUV, 1011 Lausanne, Switzerland
- Geriatric Psychiatry, Department of Mental Health and Psychiatry, HUG, 1226 Geneva, Switzerland
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22
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Analyzing Cerebrospinal Fluid Proteomes to Characterize Central Nervous System Disorders: A Highly Automated Mass Spectrometry-Based Pipeline for Biomarker Discovery. Methods Mol Biol 2019; 1959:89-112. [PMID: 30852817 DOI: 10.1007/978-1-4939-9164-8_6] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/15/2023]
Abstract
Over the past decade, liquid chromatography tandem mass spectrometry (LC MS/MS)-based workflows become standard for biomarker discovery in proteomics. These medium- to high-throughput (in terms of protein content) profiling approaches have been applied to clinical research. As a result, human proteomes have been characterized to a greater extent than ever before. However, proteomics in clinical research and biomarker discovery studies has generally been performed with small cohorts of subjects (or pooled samples from larger cohorts). This is problematic, as when aiming to identify novel biomarkers, small studies suffer from inherent and important limitations, as a result of the reduced biological diversity and representativity of human populations. Consequently, larger-scale proteomics will be key to delivering robust biomarker candidates and enabling translation to clinical practice.Cerebrospinal fluid (CSF) is a highly clinically relevant body fluid, and an important source of potential biomarkers for brain-associated damage, such as that induced by traumatic brain injury and stroke, and brain diseases, such as Alzheimer's disease and Parkinson's disease. We have developed a scalable automated proteomic pipeline (ASAP2) for biomarker discovery. This workflow is compatible with larger clinical research studies in terms of sample size, while still allowing several hundred proteins to be measured in CSF by MS. In this chapter, we describe the whole proteomic workflow to analyze human CSF. We further illustrate our protocol with some examples from an analysis of hundreds of human CSF samples, in the specific context of biomarker discovery to characterize central nervous system disorders.
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23
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Cominetti O, Núñez Galindo A, Corthésy J, Valsesia A, Irincheeva I, Kussmann M, Saris WHM, Astrup A, McPherson R, Harper ME, Dent R, Hager J, Dayon L. Obesity shows preserved plasma proteome in large independent clinical cohorts. Sci Rep 2018; 8:16981. [PMID: 30451909 PMCID: PMC6242904 DOI: 10.1038/s41598-018-35321-7] [Citation(s) in RCA: 32] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2018] [Accepted: 11/02/2018] [Indexed: 12/21/2022] Open
Abstract
Holistic human proteome maps are expected to complement comprehensive profile assessment of health and disease phenotypes. However, methodologies to analyze proteomes in human tissue or body fluid samples at relevant scale and performance are still limited in clinical research. Their deployment and demonstration in large enough human populations are even sparser. In the present study, we have characterized and compared the plasma proteomes of two large independent cohorts of obese and overweight individuals using shotgun mass spectrometry (MS)-based proteomics. Herein, we showed, in both populations from different continents of about 500 individuals each, the concordance of plasma protein MS measurements in terms of variability, gender-specificity, and age-relationship. Additionally, we replicated several known and new associations between proteins, clinical and molecular variables, such as insulin and glucose concentrations. In conclusion, our MS-based analyses of plasma samples from independent human cohorts proved the practical feasibility and efficiency of a large and unified discovery/replication approach in proteomics, which was also recently coined “rectangular” design.
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Affiliation(s)
- Ornella Cominetti
- Proteomics, Nestlé Institute of Health Sciences, Lausanne, Switzerland
| | | | - John Corthésy
- Proteomics, Nestlé Institute of Health Sciences, Lausanne, Switzerland.,Nutrition Analytics, Nestlé Institute of Health Sciences, Lausanne, Switzerland
| | - Armand Valsesia
- Nutrition and Metabolic Health, Nestlé Institute of Health Sciences, Lausanne, Switzerland
| | - Irina Irincheeva
- Nutrition and Metabolic Health, Nestlé Institute of Health Sciences, Lausanne, Switzerland.,Clinical Trial Unit, University of Bern, Bern, Switzerland
| | - Martin Kussmann
- Proteomics, Nestlé Institute of Health Sciences, Lausanne, Switzerland.,The Liggins Institute, University of Auckland, Auckland, New Zealand
| | - Wim H M Saris
- NUTRIM, School for Nutrition, Toxicology and Metabolism, Department of Human Biology, Maastricht University Medical Centre, Maastricht, The Netherlands
| | - Arne Astrup
- Department of Nutrition, Exercise and Sports, Faculty of Science, University of Copenhagen, Copenhagen, Denmark
| | - Ruth McPherson
- Ruddy Canadian Cardiovascular Genetics Centre, University of Ottawa Heart Institute, Ottawa, Canada
| | - Mary-Ellen Harper
- Department of Biochemistry, Microbiology and Immunology, Faculty of Medicine, University of Ottawa, Ottawa, Canada
| | - Robert Dent
- Ottawa Hospital Weight Management Clinic, The Ottawa Hospital, Ottawa, Canada
| | - Jörg Hager
- Nutrition and Metabolic Health, Nestlé Institute of Health Sciences, Lausanne, Switzerland
| | - Loïc Dayon
- Proteomics, Nestlé Institute of Health Sciences, Lausanne, Switzerland.
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24
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Van Eyk JE, Snyder MP. Precision Medicine: Role of Proteomics in Changing Clinical Management and Care. J Proteome Res 2018; 18:1-6. [PMID: 30296097 PMCID: PMC10372929 DOI: 10.1021/acs.jproteome.8b00504] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Abstract
It is now possible to collect large sums of health-related data which has the potential to transform healthcare. Proteomics, with its central position as downstream of genetics and epigenetic inputs and upstream of biochemical outputs and integrators of environmental signals, is well-positioned to contribute to health discoveries and management. We present our perspective on the role of proteomics and other Omics in precision health and medicine.
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Affiliation(s)
- Jennifer E Van Eyk
- Advanced Clinical Biosystems Research Institute, The Smidt Heart Institute , Cedars Sinai Medical Center , Los Angeles , California 90048 , United States
| | - Michael P Snyder
- Department of Genetics , Stanford University School of Medicine , Stanford , California 94305 , United States
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25
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Jensen SB, Hindberg K, Solomon T, Smith EN, Lapek JD, Gonzalez DJ, Latysheva N, Frazer KA, Braekkan SK, Hansen JB. Discovery of novel plasma biomarkers for future incident venous thromboembolism by untargeted synchronous precursor selection mass spectrometry proteomics. J Thromb Haemost 2018; 16:1763-1774. [PMID: 29964323 PMCID: PMC6123273 DOI: 10.1111/jth.14220] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2018] [Indexed: 01/08/2023]
Abstract
Essentials Discovery of predictive biomarkers of venous thromboembolism (VTE) may aid risk stratification. A case-control study where plasma was sampled before the occurrence of VTE was established. We generated untargeted plasma proteomic profiles of 200 individuals by use of mass spectrometry. Assessment of the biomarker potential of 501 proteins yielded 46 biomarker candidates. ABSTRACT Background Prophylactic anticoagulant treatment may substantially reduce the incidence of venous thromboembolism (VTE) but entails considerable risk of severe bleeding. Identification of individuals at high risk of VTE through the use of predictive biomarkers is desirable in order to achieve a favorable benefit-to-harm ratio. Objective We aimed to identify predictive protein biomarker candidates of VTE. Methods We performed a case-control study of 200 individuals that participated in the Tromsø Study, a population-based cohort, where blood samples were collected before the VTE events occurred. Untargeted tandem mass tag-synchronous precursor selection-mass spectrometry (TMT-SPS-MS3)-based proteomic profiling was used to study the plasma proteomes of each individual. Results Of the 501 proteins detected in a sufficient number of samples to allow multivariate analysis, 46 proteins were associated with VTE case-control status with P-values below the 0.05 significance threshold. The strongest predictive biomarker candidates, assessed by statistical significance, were transthyretin, vitamin K-dependent protein Z and protein/nucleic acid deglycase DJ-1. Conclusions Our untargeted approach of plasma proteome profiling revealed novel predictive biomarker candidates of VTE and confirmed previously reported candidates, thereby providing conceptual support for the validity of the study. A larger nested case-control study will be conducted to validate our findings.
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Affiliation(s)
- S B Jensen
- K. G. Jebsen Thrombosis Research and Expertise Center, Department of Clinical Medicine, UiT - The Arctic University of Norway, Tromsø, Norway
| | - K Hindberg
- K. G. Jebsen Thrombosis Research and Expertise Center, Department of Clinical Medicine, UiT - The Arctic University of Norway, Tromsø, Norway
| | - T Solomon
- Biomedical Sciences Graduate Program, University of California San Diego, La Jolla, California, USA
| | - E N Smith
- K. G. Jebsen Thrombosis Research and Expertise Center, Department of Clinical Medicine, UiT - The Arctic University of Norway, Tromsø, Norway
- Department of Pediatrics and Rady's Children's Hospital, University of California San Diego, La Jolla, California, USA
| | - J D Lapek
- Department of Pharmacology, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, California, USA
| | - D J Gonzalez
- Department of Pharmacology, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, California, USA
| | - N Latysheva
- K. G. Jebsen Thrombosis Research and Expertise Center, Department of Clinical Medicine, UiT - The Arctic University of Norway, Tromsø, Norway
| | - K A Frazer
- K. G. Jebsen Thrombosis Research and Expertise Center, Department of Clinical Medicine, UiT - The Arctic University of Norway, Tromsø, Norway
- Department of Pediatrics and Rady's Children's Hospital, University of California San Diego, La Jolla, California, USA
- Institute of Genomic Medicine, University of California San Diego, La Jolla, California, USA
| | - S K Braekkan
- K. G. Jebsen Thrombosis Research and Expertise Center, Department of Clinical Medicine, UiT - The Arctic University of Norway, Tromsø, Norway
- Division of Internal Medicine, University Hospital of North Norway, Tromsø, Norway
| | - J-B Hansen
- K. G. Jebsen Thrombosis Research and Expertise Center, Department of Clinical Medicine, UiT - The Arctic University of Norway, Tromsø, Norway
- Division of Internal Medicine, University Hospital of North Norway, Tromsø, Norway
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Moulder R, Bhosale SD, Goodlett DR, Lahesmaa R. Analysis of the plasma proteome using iTRAQ and TMT-based Isobaric labeling. MASS SPECTROMETRY REVIEWS 2018; 37:583-606. [PMID: 29120501 DOI: 10.1002/mas.21550] [Citation(s) in RCA: 94] [Impact Index Per Article: 15.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/24/2017] [Accepted: 09/26/2017] [Indexed: 05/23/2023]
Abstract
Over the past decade, chemical labeling with isobaric tandem mass tags, such as isobaric tags for relative and absolute quantification reagents (iTRAQ) and tandem mass tag (TMT) reagents, has been employed in a wide range of different clinically orientated serum and plasma proteomics studies. In this review the scope of these works is presented with attention to the areas of research, methods employed and performance limitations. These applications have covered a wide range of diseases, disorders and infections, and have implemented a variety of different preparative and mass spectrometric approaches. In contrast to earlier works, which struggled to quantify more than a few hundred proteins, increasingly these studies have provided deeper insight into the plasma proteome extending the numbers of quantified proteins to over a thousand.
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Affiliation(s)
- Robert Moulder
- Turku Centre for Biotechnology, University of Turku and Åbo Akademi University, Turku, Finland
| | - Santosh D Bhosale
- Turku Centre for Biotechnology, University of Turku and Åbo Akademi University, Turku, Finland
| | | | - Riitta Lahesmaa
- Turku Centre for Biotechnology, University of Turku and Åbo Akademi University, Turku, Finland
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27
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Macron C, Lane L, Núñez Galindo A, Dayon L. Deep Dive on the Proteome of Human Cerebrospinal Fluid: A Valuable Data Resource for Biomarker Discovery and Missing Protein Identification. J Proteome Res 2018; 17:4113-4126. [PMID: 30124047 DOI: 10.1021/acs.jproteome.8b00300] [Citation(s) in RCA: 46] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
Cerebrospinal fluid (CSF) is a body fluid of choice for biomarker studies of brain disorders but remains relatively under-studied compared with other biological fluids such as plasma, partly due to the more invasive means of its sample collection. The present study establishes an in-depth CSF proteome through the analysis of a unique CSF sample from a pool of donors. After immunoaffinity depletion, the CSF sample was fractionated using off-gel electrophoresis and analyzed with liquid chromatography tandem mass spectrometry (MS) using the latest generation of hybrid Orbitrap mass spectrometers. The shotgun proteomic analysis allowed the identification of 20 689 peptides mapping on 3379 proteins. To the best of our knowledge, the obtained data set constitutes the largest CSF proteome published so far. Among the CSF proteins identified, 34% correspond to genes whose transcripts are highly expressed in brain according to the Human Protein Atlas. The principal Alzheimer's disease biomarkers (e.g., tau protein, amyloid-β, apolipoprotein E, and neurogranin) were detected. Importantly, our data set significantly contributes to the Chromosome-centric Human Proteome Project (C-HPP), and 12 proteins considered as missing are proposed for validation in accordance with the HPP guidelines. Of these 12 proteins, 8 proteins are based on 2 to 6 uniquely mapping peptides from this CSF analysis, and 4 match a new peptide with a "stranded" single peptide in PeptideAtlas from previous CSF studies. The MS proteomic data are available to the ProteomeXchange Consortium ( http://www.proteomexchange.org/ ) with the data set identifier PXD009646.
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Affiliation(s)
- Charlotte Macron
- Proteomics , Nestlé Institute of Health Sciences , 1015 Lausanne , Switzerland
| | - Lydie Lane
- CALIPHO Group , SIB-Swiss Institute of Bioinformatics , CMU, rue Michel-Servet 1 , 1211 Geneva 4 , Switzerland.,Department of Microbiology and Molecular Medicine, Faculty of Medicine , University of Geneva , rue Michel-Servet 1 , 1211 Geneva 4 , Switzerland
| | | | - Loïc Dayon
- Proteomics , Nestlé Institute of Health Sciences , 1015 Lausanne , Switzerland
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28
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Dong MX, Feng X, Xu XM, Hu L, Liu Y, Jia SY, Li B, Chen W, Wei YD. Integrated Analysis Reveals Altered Lipid and Glucose Metabolism and Identifies NOTCH2 as a Biomarker for Parkinson's Disease Related Depression. Front Mol Neurosci 2018; 11:257. [PMID: 30233306 PMCID: PMC6127515 DOI: 10.3389/fnmol.2018.00257] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2018] [Accepted: 07/06/2018] [Indexed: 12/21/2022] Open
Abstract
Depression is a common comorbidity in Parkinson's disease (PD) but is underdiagnosed. We aim to investigate the altered metabolic pathways of Parkinson's disease-related depression (PDD) in plasma and to identify potential biomarkers for clinical diagnosis. Consecutive patients with PD were recruited, clinically assessed, and patients with PDD identified. Fasting plasma samples were collected from 99 patients and differentially expressed metabolites and proteins between patients with PDD and PD were identified using non-targeted liquid chromatography-mass spectrometry (LC-MS)-based metabolomics and tandem mass tag (TMT)-based proteomics analysis, followed by an integrated analysis. Based on the above results, enzyme-linked immune sorbent assay (ELISA) tests were then performed to identify potential biomarkers for PDD. In clinics, patients with PDD suffered less hypertension and had lower serum low-density lipoprotein cholesterol and apolipoprotein B levels when compared to the other patients with PD. A total of 85 differentially expressed metabolites were identified in metabolomics analysis. These metabolites were mainly lipids and lipid-like molecules, involved in lipid and glucose metabolic pathways. According to proteomics analysis, 17 differentially expressed proteins were identified, and 12 metabolic pathways were enriched, which were predominantly related to glucose metabolism. Integrated analysis indicated that altered lipid and glucose metabolism in PDD may induce cellular injury through oxidative stress. Additionally, plasma levels of several proteins were confirmed to be significantly altered and correlated with depressive severity. NOTCH2 may be a potential blood biomarker for PDD, with an optimal cut-off point of 0.91 ng/ml, a sensitivity value of 95.65%, and a specificity value of 81.58%. Depressive symptoms are associated with lipid and glucose metabolism in patients with PD and NOTCH2 may be a potential blood biomarker for the clinical diagnosis of PDD.
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Affiliation(s)
- Mei-Xue Dong
- Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.,Department of Neurology, Renmin Hospital of Wuhan University, Hubei General Hospital, Hubei, China
| | - Xia Feng
- Department of Neurology, The People's Hospital of Tongliang District, Chongqing, China
| | - Xiao-Min Xu
- Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Ling Hu
- Department of Neurology, The Fifth People's Hospital of Chongqing, Chongqing, China
| | - Yang Liu
- Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Si-Yu Jia
- Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Bo Li
- Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Wei Chen
- Shanghai Applied Protein Technology Co. Ltd., Shanghai, China
| | - You-Dong Wei
- Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
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29
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Méhul B, Perrin A, Grisendi K, Galindo AN, Dayon L, Ménigot C, Rival Y, Voegel JJ. Mass spectrometry and DigiWest technology emphasize protein acetylation profile from Quisinostat-treated HuT78 CTCL cell line. J Proteomics 2018; 187:126-143. [PMID: 30012418 DOI: 10.1016/j.jprot.2018.07.003] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2018] [Revised: 06/20/2018] [Accepted: 07/12/2018] [Indexed: 02/07/2023]
Abstract
Histone deacetylases (HDACs) are key enzymes involved in epigenetic modulation and were targeted by HDAC inhibitors (HDACis) for cancer treatment. The action of HDACis is not restricted to histones and also prevents deacetylation of other proteins, supporting their wide biological actions. The HuT78 cell line is recognized as a key tool to support and understand cutaneous T-cell lymphoma (CTCL) biology and was used as a predictive model since HDACi such as Vorinostat and Panobinostat have both demonstrated apoptotic activities in HuT78 cells and in primary blood CTCL cells. In this study, Quisinostat (JNJ-26481585) a novel second-generation HDACi with highest potency for HDAC1, was tested on HuT78 cell line. Quantitative mass spectrometry (MS)-based proteomics after acetylated-lysine peptide enrichment and a targeted antibody-based immunoassay (DigiWest) were used as complementary technologies to assess the modifications of the acetylated proteome. As expected, several acetylated lysines of histones were increased by the HDACi. Additional acetylated non-histone proteins were modulated after treatment with Quisinostat including the nucleolin (a major nucleolar protein), the replication protein A 70 kDa DNA-binding subunit, the phosphoglycerate kinase 1, the stress-70 protein, the proto-oncogene Myc and the serine hydroxymethyltransferase. A better knowledge of histone and non-histone acetylated protein profile after Quisinostat treatment can strongly support the understanding of non-clinical and clinical results of this HDACi. These technological tools can also help in designing new HDACis in a pharmaceutical drug discovery program. SIGNIFICANCE A better knowledge of histone and non-histone acetylated protein profile after HDAC inhibitors (HDACis) treatment can strongly support the understanding of non-clinical and clinical investigations in a pharmaceutical drug discovery program. Relative quantification using mass spectrometry -based proteomics after acetylated-lysine peptide enrichment and a targeted antibody-based immunoassay (DigiWest) are proposed as complementary technologies to assess the modifications of the acetylated proteome. Quisinostat (JNJ-26481585) a novel second-generation HDACi with highest potency for HDAC1 was better characterized in vitro in HuT78 cells to support and understand cutaneous T-cell lymphoma (CTCL) therapeutic research program.
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Affiliation(s)
- Bruno Méhul
- Galderma, Nestlé Skin Health R & D, 2400, route des Colles, 06410 Biot, France.
| | - Agnes Perrin
- Galderma, Nestlé Skin Health R & D, 2400, route des Colles, 06410 Biot, France
| | - Karine Grisendi
- Galderma, Nestlé Skin Health R & D, 2400, route des Colles, 06410 Biot, France
| | | | - Loïc Dayon
- Proteomics, Nestlé Institute of Health Sciences, 1015 Lausanne, Switzerland
| | - Corinne Ménigot
- Galderma, Nestlé Skin Health R & D, 2400, route des Colles, 06410 Biot, France
| | - Yves Rival
- Galderma, Nestlé Skin Health R & D, 2400, route des Colles, 06410 Biot, France
| | - Johannes J Voegel
- Galderma, Nestlé Skin Health R & D, 2400, route des Colles, 06410 Biot, France
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30
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Dayon L, Núñez Galindo A, Wojcik J, Cominetti O, Corthésy J, Oikonomidi A, Henry H, Kussmann M, Migliavacca E, Severin I, Bowman GL, Popp J. Alzheimer disease pathology and the cerebrospinal fluid proteome. Alzheimers Res Ther 2018; 10:66. [PMID: 30021611 PMCID: PMC6052524 DOI: 10.1186/s13195-018-0397-4] [Citation(s) in RCA: 53] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2017] [Accepted: 06/11/2018] [Indexed: 12/18/2022]
Abstract
BACKGROUND Altered proteome profiles have been reported in both postmortem brain tissues and body fluids of subjects with Alzheimer disease (AD), but their broad relationships with AD pathology, amyloid pathology, and tau-related neurodegeneration have not yet been fully explored. Using a robust automated MS-based proteomic biomarker discovery workflow, we measured cerebrospinal fluid (CSF) proteomes to explore their association with well-established markers of core AD pathology. METHODS Cross-sectional analysis was performed on CSF collected from 120 older community-dwelling adults with normal (n = 48) or impaired cognition (n = 72). LC-MS quantified hundreds of proteins in the CSF. CSF concentrations of β-amyloid 1-42 (Aβ1-42), tau, and tau phosphorylated at threonine 181 (P-tau181) were determined with immunoassays. First, we explored proteins relevant to biomarker-defined AD. Then, correlation analysis of CSF proteins with CSF markers of amyloid pathology, neuronal injury, and tau hyperphosphorylation (i.e., Aβ1-42, tau, P-tau181) was performed using Pearson's correlation coefficient and Bonferroni correction for multiple comparisons. RESULTS We quantified 790 proteins in CSF samples with MS. Four CSF proteins showed an association with CSF Aβ1-42 levels (p value ≤ 0.05 with correlation coefficient (R) ≥ 0.38). We identified 50 additional CSF proteins associated with CSF tau and 46 proteins associated with CSF P-tau181 (p value ≤ 0.05 with R ≥ 0.37). The majority of those proteins that showed such associations were brain-enriched proteins. Gene Ontology annotation revealed an enrichment for synaptic proteins and proteins originating from reelin-producing cells and the myelin sheath. CONCLUSIONS We used an MS-based proteomic workflow to profile the CSF proteome in relation to cerebral AD pathology. We report strong evidence of previously reported CSF proteins and several novel CSF proteins specifically associated with amyloid pathology or neuronal injury and tau hyperphosphorylation.
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Affiliation(s)
- Loïc Dayon
- Nestlé Institute of Health Sciences, Lausanne, Switzerland
| | | | | | | | - John Corthésy
- Nestlé Institute of Health Sciences, Lausanne, Switzerland
| | | | - Hugues Henry
- Department of Laboratories, CHUV, Lausanne, Switzerland
| | - Martin Kussmann
- Nestlé Institute of Health Sciences, Lausanne, Switzerland
- Present address: Liggins Institute, University of Auckland, Auckland, New Zealand
| | | | - India Severin
- Nestlé Institute of Health Sciences, Lausanne, Switzerland
| | - Gene L. Bowman
- Nestlé Institute of Health Sciences, Lausanne, Switzerland
| | - Julius Popp
- Old Age Psychiatry, Department of Psychiatry, CHUV, Lausanne, Switzerland
- Geriatric Psychiatry, Department of Mental Health and Psychiatry, HUG, Geneva, Switzerland
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31
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Corthésy J, Theofilatos K, Mavroudi S, Macron C, Cominetti O, Remlawi M, Ferraro F, Núñez Galindo A, Kussmann M, Likothanassis S, Dayon L. An Adaptive Pipeline To Maximize Isobaric Tagging Data in Large-Scale MS-Based Proteomics. J Proteome Res 2018; 17:2165-2173. [DOI: 10.1021/acs.jproteome.8b00110] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- John Corthésy
- Nestlé Institute of Health Sciences, Lausanne 1015, Switzerland
| | | | - Seferina Mavroudi
- InSybio, Ltd., Innovations House, 19 Staple Gardens, Winchester SO238SR, United Kingdom
- Department of Social Work, School of Sciences of Health and Care, Technological Educational Institute of Western Greece, Patras 26334, Greece
| | | | | | - Mona Remlawi
- Nestlé Institute of Health Sciences, Lausanne 1015, Switzerland
| | | | | | - Martin Kussmann
- Nestlé Institute of Health Sciences, Lausanne 1015, Switzerland
| | - Spiridon Likothanassis
- InSybio, Ltd., Innovations House, 19 Staple Gardens, Winchester SO238SR, United Kingdom
- Department of Computer Engineering and Informatics, University of Patras, Patras 26500, Greece
| | - Loïc Dayon
- Nestlé Institute of Health Sciences, Lausanne 1015, Switzerland
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32
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Lan J, Núñez Galindo A, Doecke J, Fowler C, Martins RN, Rainey-Smith SR, Cominetti O, Dayon L. Systematic Evaluation of the Use of Human Plasma and Serum for Mass-Spectrometry-Based Shotgun Proteomics. J Proteome Res 2018; 17:1426-1435. [DOI: 10.1021/acs.jproteome.7b00788] [Citation(s) in RCA: 25] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Jiayi Lan
- Proteomics, Nestlé Institute of Health Sciences, 1015 Lausanne, Switzerland
| | | | - James Doecke
- CSIRO Health and Biosecurity/Australian E-Health Research Centre, Brisbane, Queensland 4029, Australia
| | - Christopher Fowler
- The Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, Victoria 3010, Australia
| | - Ralph N. Martins
- Centre of Excellence for Alzheimer’s Disease Research and Care, School of Medical and Health Sciences, Edith Cowan University, Joondalup, Western Australia 6027, Australia
- Department of Biomedical Sciences, Macquarie University, North Ryde, New South Wales 2109, Australia
| | - Stephanie R. Rainey-Smith
- Centre of Excellence for Alzheimer’s Disease Research and Care, School of Medical and Health Sciences, Edith Cowan University, Joondalup, Western Australia 6027, Australia
| | - Ornella Cominetti
- Proteomics, Nestlé Institute of Health Sciences, 1015 Lausanne, Switzerland
| | - Loïc Dayon
- Proteomics, Nestlé Institute of Health Sciences, 1015 Lausanne, Switzerland
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33
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A robust and effective intact protein fractionation strategy by GO/PEI/Au/PEG nanocomposites for human plasma proteome analysis. Talanta 2018; 178:49-56. [DOI: 10.1016/j.talanta.2017.08.079] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2017] [Revised: 08/24/2017] [Accepted: 08/25/2017] [Indexed: 12/22/2022]
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Dayon L, Wojcik J, Núñez Galindo A, Corthésy J, Cominetti O, Oikonomidi A, Henry H, Migliavacca E, Bowman GL, Popp J. Plasma Proteomic Profiles of Cerebrospinal Fluid-Defined Alzheimer’s Disease Pathology in Older Adults. J Alzheimers Dis 2017; 60:1641-1652. [DOI: 10.3233/jad-170426] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Affiliation(s)
- Loïc Dayon
- Nestlé Institute of Health Sciences, Lausanne, Switzerland
| | | | | | - John Corthésy
- Nestlé Institute of Health Sciences, Lausanne, Switzerland
| | | | | | - Hugues Henry
- CHUV, Department of Laboratories, Lausanne, Switzerland
| | | | - Gene L. Bowman
- Nestlé Institute of Health Sciences, Lausanne, Switzerland
| | - Julius Popp
- CHUV, Old Age Psychiatry, Department of Psychiatry, Lausanne, Switzerland
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35
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Keshishian H, Burgess MW, Specht H, Wallace L, Clauser KR, Gillette MA, Carr SA. Quantitative, multiplexed workflow for deep analysis of human blood plasma and biomarker discovery by mass spectrometry. Nat Protoc 2017; 12:1683-1701. [PMID: 28749931 PMCID: PMC6057147 DOI: 10.1038/nprot.2017.054] [Citation(s) in RCA: 111] [Impact Index Per Article: 15.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/16/2023]
Abstract
Proteomic characterization of blood plasma is of central importance to clinical proteomics and particularly to biomarker discovery studies. The vast dynamic range and high complexity of the plasma proteome have, however, proven to be serious challenges and have often led to unacceptable tradeoffs between depth of coverage and sample throughput. We present an optimized sample-processing pipeline for analysis of the human plasma proteome that provides greatly increased depth of detection, improved quantitative precision and much higher sample analysis throughput as compared with prior methods. The process includes abundant protein depletion, isobaric labeling at the peptide level for multiplexed relative quantification and ultra-high-performance liquid chromatography coupled to accurate-mass, high-resolution tandem mass spectrometry analysis of peptides fractionated off-line by basic pH reversed-phase (bRP) chromatography. The overall reproducibility of the process, including immunoaffinity depletion, is high, with a process replicate coefficient of variation (CV) of <12%. Using isobaric tags for relative and absolute quantitation (iTRAQ) 4-plex, >4,500 proteins are detected and quantified per patient sample on average, with two or more peptides per protein and starting from as little as 200 μl of plasma. The approach can be multiplexed up to 10-plex using tandem mass tags (TMT) reagents, further increasing throughput, albeit with some decrease in the number of proteins quantified. In addition, we provide a rapid protocol for analysis of nonfractionated depleted plasma samples analyzed in 10-plex. This provides ∼600 quantified proteins for each of the ten samples in ∼5 h of instrument time.
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Affiliation(s)
| | | | - Harrison Specht
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
| | - Luke Wallace
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
| | - Karl R Clauser
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
| | - Michael A Gillette
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
- Massachusetts General Hospital, Boston, USA
| | - Steven A Carr
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
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36
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Oller Moreno S, Cominetti O, Núñez Galindo A, Irincheeva I, Corthésy J, Astrup A, Saris WHM, Hager J, Kussmann M, Dayon L. The differential plasma proteome of obese and overweight individuals undergoing a nutritional weight loss and maintenance intervention. Proteomics Clin Appl 2017; 12. [PMID: 28371297 DOI: 10.1002/prca.201600150] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2016] [Revised: 03/01/2017] [Accepted: 03/27/2017] [Indexed: 01/24/2023]
Abstract
PURPOSE The nutritional intervention program "DiOGenes" focuses on how obesity can be prevented and treated from a dietary perspective. We generated differential plasma proteome profiles in the DiOGenes cohort to identify proteins associated with weight loss and maintenance and explore their relation to body mass index, fat mass, insulin resistance, and sensitivity. EXPERIMENTAL DESIGN Relative protein quantification was obtained at baseline and after combined weight loss/maintenance phases using isobaric tagging and MS/MS. A Welch t-test determined proteins differentially present after intervention. Protein relationships with clinical variables were explored using univariate linear models, considering collection center, gender and age as confounding factors. RESULTS Four hundred and seventy three subjects were measured at baseline and end of the intervention; 39 proteins were longitudinally differential. Proteins with largest changes were sex hormone-binding globulin, adiponectin, C-reactive protein, calprotectin, serum amyloid A, and proteoglycan 4 (PRG4), whose association with obesity and weight loss is known. We identified new putative biomarkers for weight loss/maintenance. Correlation between PRG4 and proline-rich acidic protein 1 variation and Matsuda insulin sensitivity increment was showed. CONCLUSION AND CLINICAL RELEVANCE MS-based proteomic analysis of a large cohort of non-diabetic overweight and obese individuals concomitantly identified known and novel proteins associated with weight loss and maintenance.
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Affiliation(s)
- Sergio Oller Moreno
- Systems Nutrition, Metabonomics and Proteomics, Nestlé Institute of Health Sciences, Lausanne, Switzerland
- Signal and Information Processing for Sensing Systems, Institute for Bioengineering of Catalonia, Barcelona, Spain
| | - Ornella Cominetti
- Systems Nutrition, Metabonomics and Proteomics, Nestlé Institute of Health Sciences, Lausanne, Switzerland
| | - Antonio Núñez Galindo
- Systems Nutrition, Metabonomics and Proteomics, Nestlé Institute of Health Sciences, Lausanne, Switzerland
| | - Irina Irincheeva
- Nutrition and Metabolic Health, Nestlé Institute of Health Sciences, Lausanne, Switzerland
| | - John Corthésy
- Systems Nutrition, Metabonomics and Proteomics, Nestlé Institute of Health Sciences, Lausanne, Switzerland
| | - Arne Astrup
- Department of Nutrition, Exercise and Sports, Faculty of Science, University of Copenhagen, Copenhagen, Denmark
| | - Wim H M Saris
- Department of Human Biology, NUTRIM, School for Nutrition, Toxicology and Metabolism, Maastricht University Medical Centre, Maastricht, The Netherlands
| | - Jörg Hager
- Nutrition and Metabolic Health, Nestlé Institute of Health Sciences, Lausanne, Switzerland
| | - Martin Kussmann
- Systems Nutrition, Metabonomics and Proteomics, Nestlé Institute of Health Sciences, Lausanne, Switzerland
| | - Loïc Dayon
- Systems Nutrition, Metabonomics and Proteomics, Nestlé Institute of Health Sciences, Lausanne, Switzerland
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Dayon L, Núñez Galindo A, Cominetti O, Corthésy J, Kussmann M. A Highly Automated Shotgun Proteomic Workflow: Clinical Scale and Robustness for Biomarker Discovery in Blood. Methods Mol Biol 2017; 1619:433-449. [PMID: 28674902 DOI: 10.1007/978-1-4939-7057-5_30] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/07/2023]
Abstract
With recent technological developments, protein biomarker discoveries directly from blood have regained interest due to elevated feasibility. Mass spectrometry (MS)-based proteomics can now characterize human plasma proteomes to a greater extent than has ever been possible before. Such deep proteome coverage comes, however, with important limitations in terms of analysis time which is a critical factor in the case of clinical studies. As a consequence, compromises still need to be made to balance the proteome coverage with realistic analysis time frame in clinical research. The analysis of a sufficient number of samples is compulsory to empower statistically robust candidate biomarker findings. We have, therefore, recently developed a scalable automated proteomic pipeline (ASAP2) to enable the proteomic analysis of large numbers of plasma and cerebrospinal fluid (CSF) samples, from dozens to a thousand of samples, with the latter number being currently processed in 15 weeks. A distinct characteristic of ASAP2 relies on the possibility to prepare samples in a highly automated way, mostly using 96-well plates. We describe herein a sample preparation procedure for human plasma that includes internal standard spiking, abundant protein removal, buffer exchange, reduction, alkylation, tryptic digestion, isobaric labeling, pooling, and sample purification. Other key elements of the pipeline (i.e., study design, sample tracking, liquid chromatography (LC) tandem MS (MS/MS), data processing, and data analysis) are also highlighted.
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Affiliation(s)
- Loïc Dayon
- Nestlé Institute of Health Sciences SA, EPFL Innovation Park, Bâtiment H, 1015, Lausanne, Switzerland.
| | - Antonio Núñez Galindo
- Nestlé Institute of Health Sciences SA, EPFL Innovation Park, Bâtiment H, 1015, Lausanne, Switzerland
| | - Ornella Cominetti
- Nestlé Institute of Health Sciences SA, EPFL Innovation Park, Bâtiment H, 1015, Lausanne, Switzerland
| | - John Corthésy
- Nestlé Institute of Health Sciences SA, EPFL Innovation Park, Bâtiment H, 1015, Lausanne, Switzerland
| | - Martin Kussmann
- Nestlé Institute of Health Sciences SA, EPFL Innovation Park, Bâtiment H, 1015, Lausanne, Switzerland
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38
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de Graaf EL, Pellegrini D, McDonnell LA. Set of Novel Automated Quantitative Microproteomics Protocols for Small Sample Amounts and Its Application to Kidney Tissue Substructures. J Proteome Res 2016; 15:4722-4730. [PMID: 27809536 DOI: 10.1021/acs.jproteome.6b00889] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Here we assessed the ability of an automated sample preparation device equipped with disposable microcolumns to prepare mass-limited samples for high-sensitivity quantitative proteomics, using both label-free and isobaric labeling approaches. First, we compared peptide label-free quantification reproducibility for 1.5-150 μg of cell lysates and found that labware preconditioning was essential for reproducible quantification of <7.5 μg digest. Second, in-solution and on-column tandem mass tag (TMT) labeling protocols were compared and optimized for 1 μg of sample. Surprisingly, standard methods for in-solution and on-column labeling showed poor TMT labeling (50-85%); however, novel optimized and automated protocols restored efficient labeling to >98%. Third, compared with a single long gradient experiment, a simple robotized high-pH fractionation protocol using only 6 μg of starting material doubled the number of unique peptides and increased proteome coverage 1.43-fold. To facilitate the analysis of heterogeneous tissue samples, such as those obtained from laser capture microdissection, a modified BCA protein assay was developed that consumes and detects down to 15 ng of protein. As a proof-of-principle, the modular automated workflow was applied to 0.5 and 1 mm2 mouse kidney cortex and medulla microdissections to show the method's potential for real-life small sample sources and to create kidney substructure-specific proteomes.
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Affiliation(s)
| | - Davide Pellegrini
- Fondazione Pisana per la Scienza ONLUS , Pisa 56121, Italy.,NEST, Scuola Normale Superiore , Pisa 56127, Italy
| | - Liam A McDonnell
- Fondazione Pisana per la Scienza ONLUS , Pisa 56121, Italy.,Leiden University Medical Center , Leiden 2333 ZA, The Netherlands
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39
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Sun Z, Liu X, Jiang J, Huang H, Wang J, Wu D, Li L. Toward Biomarker Development in Large Clinical Cohorts: An Integrated High-Throughput 96-Well-Plate-Based Sample Preparation Workflow for Versatile Downstream Proteomic Analyses. Anal Chem 2016; 88:8518-25. [PMID: 27471874 DOI: 10.1021/acs.analchem.6b01333] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
We describe a cheap, robust, fast, high-throughput, and flexible proteomic sample processing method based on a regular 96-well plate by acetone precipitation under low centrifuge speed (96PACS), which enables predigestion processing of 96 samples within 2 h. Tested on a complex Huh-7 total lysate, 96PACS produced comparable proteome coverage and even showed better reproducibility than FASP. Quantitative performance of 96PACS was further tested using data-independent acquisition and parallel reaction monitoring quantitation in a set of 6 benchmark samples consisting of 6 serial dilutions of BSA spiked in complex E. coli proteome background. The protocol was also successfully modified for automation and was validated in a comparative label-free proteomic study to develop serum markers for early detection of liver fibrosis and necroinflammation in patients chronically infected with hepatitis B virus.
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Affiliation(s)
- Zeyu Sun
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University , 310003 Hangzhou, People's Republic of China
| | - Xiaoli Liu
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University , 310003 Hangzhou, People's Republic of China
| | - Jing Jiang
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University , 310003 Hangzhou, People's Republic of China
| | - Haijun Huang
- Department of Infectious Diseases, Zhejiang Provincial People's Hospital , 310024 Hangzhou, Zhejiang, People's Republic of China
| | - Jie Wang
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University , 310003 Hangzhou, People's Republic of China
| | - Daxian Wu
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University , 310003 Hangzhou, People's Republic of China
| | - Lanjuan Li
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University , 310003 Hangzhou, People's Republic of China
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40
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Wallace MAG, Kormos TM, Pleil JD. Blood-borne biomarkers and bioindicators for linking exposure to health effects in environmental health science. JOURNAL OF TOXICOLOGY AND ENVIRONMENTAL HEALTH. PART B, CRITICAL REVIEWS 2016; 19:380-409. [PMID: 27759495 PMCID: PMC6147038 DOI: 10.1080/10937404.2016.1215772] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/19/2023]
Abstract
Environmental health science aims to link environmental pollution sources to adverse health outcomes to develop effective exposure intervention strategies that reduce long-term disease risks. Over the past few decades, the public health community recognized that health risk is driven by interaction between the human genome and external environment. Now that the human genetic code has been sequenced, establishing this "G × E" (gene-environment) interaction requires a similar effort to decode the human exposome, which is the accumulation of an individual's environmental exposures and metabolic responses throughout the person's lifetime. The exposome is composed of endogenous and exogenous chemicals, many of which are measurable as biomarkers in blood, breath, and urine. Exposure to pollutants is assessed by analyzing biofluids for the pollutant itself or its metabolic products. New methods are being developed to use a subset of biomarkers, termed bioindicators, to demonstrate biological changes indicative of future adverse health effects. Typically, environmental biomarkers are assessed using noninvasive (excreted) media, such as breath and urine. Blood is often avoided for biomonitoring due to practical reasons such as medical personnel, infectious waste, or clinical setting, despite the fact that blood represents the central compartment that interacts with every living cell and is the most relevant biofluid for certain applications and analyses. The aims of this study were to (1) review the current use of blood samples in environmental health research, (2) briefly contrast blood with other biological media, and (3) propose additional applications for blood analysis in human exposure research.
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Affiliation(s)
- M Ariel Geer Wallace
- a Exposure Methods and Measurement Division, National Exposure Research Laboratory, Office of Research and Development , U.S. Environmental Protection Agency , Research Triangle Park , North Carolina , USA
| | | | - Joachim D Pleil
- a Exposure Methods and Measurement Division, National Exposure Research Laboratory, Office of Research and Development , U.S. Environmental Protection Agency , Research Triangle Park , North Carolina , USA
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41
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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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Cominetti O, Núñez Galindo A, Corthésy J, Oller Moreno S, Irincheeva I, Valsesia A, Astrup A, Saris WHM, Hager J, Kussmann M, Dayon L. Proteomic Biomarker Discovery in 1000 Human Plasma Samples with Mass Spectrometry. J Proteome Res 2015; 15:389-99. [DOI: 10.1021/acs.jproteome.5b00901] [Citation(s) in RCA: 73] [Impact Index Per Article: 8.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/28/2023]
Affiliation(s)
- Ornella Cominetti
- Molecular
Biomarkers Core, Nestlé Institute of Health Sciences, CH-1015 Lausanne, Switzerland
| | - Antonio Núñez Galindo
- Molecular
Biomarkers Core, Nestlé Institute of Health Sciences, CH-1015 Lausanne, Switzerland
| | - John Corthésy
- Molecular
Biomarkers Core, Nestlé Institute of Health Sciences, CH-1015 Lausanne, Switzerland
| | - Sergio Oller Moreno
- Molecular
Biomarkers Core, Nestlé Institute of Health Sciences, CH-1015 Lausanne, Switzerland
| | - Irina Irincheeva
- Nutrition
and Metabolic Health Group, Nestlé Institute of Health Sciences, CH-1015
Lausanne, Switzerland
| | - Armand Valsesia
- Nutrition
and Metabolic Health Group, Nestlé Institute of Health Sciences, CH-1015
Lausanne, Switzerland
| | - Arne Astrup
- Department
of Nutrition, Exercise and Sports, Faculty of Science, University of Copenhagen, DK-2200 Copenhagen, Denmark
| | - Wim H. M. Saris
- NUTRIM,
School for Nutrition and Translational Research In Metabolism, Maastricht University Medical Centre, 6200 MD Maastricht, Netherlands
| | - Jörg Hager
- Nutrition
and Metabolic Health Group, Nestlé Institute of Health Sciences, CH-1015
Lausanne, Switzerland
| | - Martin Kussmann
- Molecular
Biomarkers Core, Nestlé Institute of Health Sciences, CH-1015 Lausanne, Switzerland
| | - Loïc Dayon
- Molecular
Biomarkers Core, Nestlé Institute of Health Sciences, CH-1015 Lausanne, Switzerland
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43
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Núñez Galindo A, Kussmann M, Dayon L. Proteomics of Cerebrospinal Fluid: Throughput and Robustness Using a Scalable Automated Analysis Pipeline for Biomarker Discovery. Anal Chem 2015; 87:10755-61. [PMID: 26452177 DOI: 10.1021/acs.analchem.5b02748] [Citation(s) in RCA: 29] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
Cerebrospinal fluid (CSF) is a body fluid of high clinical relevance and an important source of potential biomarkers for brain-associated damages, such as traumatic brain injury and stroke, and for brain diseases, such as Alzheimer's and Parkinson's. Herein, we have implemented, evaluated, and validated a scalable automated proteomic pipeline (ASAP(2)) for the sample preparation and proteomic analysis of CSF, enabling increased throughput and robustness for biomarker discovery. Human CSF samples were depleted from abundant proteins and subjected to automated reduction, alkylation, protein digestion, tandem mass tag (TMT) 6-plex labeling, pooling, and sample cleanup in a 96-well-plate format before reversed-phase liquid chromatography tandem mass spectrometry (RP-LC MS/MS). We showed the impact on the CSF proteome coverage of applying the depletion of abundant proteins, which is usually performed on blood plasma or serum samples. Using ASAP(2) to analyze 96 identical CSF samples, we determined the analytical figures of merit of our shotgun proteomic approach regarding proteome coverage consistency (i.e., 387 proteins), quantitative accuracy, and individual protein variability. We demonstrated that, as for human plasma samples, ASAP(2) is efficient in analyzing large numbers of human CSF samples and is a valuable tool for biomarker discovery. The data has been deposited to the ProteomeXchange with identifier PXD003024.
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Affiliation(s)
- Antonio Núñez Galindo
- Molecular Biomarkers Core, Nestlé Institute of Health Sciences SA , EPFL Innovation Park, Bâtiment H, Lausanne, Switzerland
| | - Martin Kussmann
- Molecular Biomarkers Core, Nestlé Institute of Health Sciences SA , EPFL Innovation Park, Bâtiment H, Lausanne, Switzerland
| | - Loïc Dayon
- Molecular Biomarkers Core, Nestlé Institute of Health Sciences SA , EPFL Innovation Park, Bâtiment H, Lausanne, Switzerland
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44
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Liu Y, Buil A, Collins BC, Gillet LCJ, Blum LC, Cheng LY, Vitek O, Mouritsen J, Lachance G, Spector TD, Dermitzakis ET, Aebersold R. Quantitative variability of 342 plasma proteins in a human twin population. Mol Syst Biol 2015; 11:786. [PMID: 25652787 PMCID: PMC4358658 DOI: 10.15252/msb.20145728] [Citation(s) in RCA: 241] [Impact Index Per Article: 26.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
The degree and the origins of quantitative variability of most human plasma proteins are largely unknown. Because the twin study design provides a natural opportunity to estimate the relative contribution of heritability and environment to different traits in human population, we applied here the highly accurate and reproducible SWATH mass spectrometry technique to quantify 1,904 peptides defining 342 unique plasma proteins in 232 plasma samples collected longitudinally from pairs of monozygotic and dizygotic twins at intervals of 2–7 years, and proportioned the observed total quantitative variability to its root causes, genes, and environmental and longitudinal factors. The data indicate that different proteins show vastly different patterns of abundance variability among humans and that genetic control and longitudinal variation affect protein levels and biological processes to different degrees. The data further strongly suggest that the plasma concentrations of clinical biomarkers need to be calibrated against genetic and temporal factors. Moreover, we identified 13 cis-SNPs significantly influencing the level of specific plasma proteins. These results therefore have immediate implications for the effective design of blood-based biomarker studies.
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Affiliation(s)
- Yansheng Liu
- Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland
| | - Alfonso Buil
- Department of Genetic Medicine and Development, University of Geneva Medical School, Geneva, Switzerland
| | - Ben C Collins
- Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland
| | - Ludovic C J Gillet
- Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland
| | - Lorenz C Blum
- Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland
| | - Lin-Yang Cheng
- Department of Statistics and Department of Computer Science, Purdue University, West Lafayette, IN, USA
| | - Olga Vitek
- Department of Statistics and Department of Computer Science, Purdue University, West Lafayette, IN, USA
| | - Jeppe Mouritsen
- Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland
| | - Genevieve Lachance
- Department of Twin Research and Genetic Epidemiology, King's College London St Tomas' Hospital Campus, London, UK
| | - Tim D Spector
- Department of Twin Research and Genetic Epidemiology, King's College London St Tomas' Hospital Campus, London, UK
| | - Emmanouil T Dermitzakis
- Department of Genetic Medicine and Development, University of Geneva Medical School, Geneva, Switzerland
| | - Ruedi Aebersold
- Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland Faculty of Science, University of Zurich, Zurich, Switzerland
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