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Alves G, Ogurtsov AY, Porterfield H, Maity T, Jenkins LM, Sacks DB, Yu YK. Multiplexing the Identification of Microorganisms via Tandem Mass Tag Labeling Augmented by Interference Removal through a Novel Modification of the Expectation Maximization Algorithm. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2024. [PMID: 38740383 DOI: 10.1021/jasms.3c00445] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/16/2024]
Abstract
Having fast, accurate, and broad spectrum methods for the identification of microorganisms is of paramount importance to public health, research, and safety. Bottom-up mass spectrometer-based proteomics has emerged as an effective tool for the accurate identification of microorganisms from microbial isolates. However, one major hurdle that limits the deployment of this tool for routine clinical diagnosis, and other areas of research such as culturomics, is the instrument time required for the mass spectrometer to analyze a single sample, which can take ∼1 h per sample, when using mass spectrometers that are presently used in most institutes. To address this issue, in this study, we employed, for the first time, tandem mass tags (TMTs) in multiplex identifications of microorganisms from multiple TMT-labeled samples in one MS/MS experiment. A difficulty encountered when using TMT labeling is the presence of interference in the measured intensities of TMT reporter ions. To correct for interference, we employed in the proposed method a modified version of the expectation maximization (EM) algorithm that redistributes the signal from ion interference back to the correct TMT-labeled samples. We have evaluated the sensitivity and specificity of the proposed method using 94 MS/MS experiments (covering a broad range of protein concentration ratios across TMT-labeled channels and experimental parameters), containing a total of 1931 true positive TMT-labeled channels and 317 true negative TMT-labeled channels. The results of the evaluation show that the proposed method has an identification sensitivity of 93-97% and a specificity of 100% at the species level. Furthermore, as a proof of concept, using an in-house-generated data set composed of some of the most common urinary tract pathogens, we demonstrated that by using the proposed method the mass spectrometer time required per sample, using a 1 h LC-MS/MS run, can be reduced to 10 and 6 min when samples are labeled with TMT-6 and TMT-10, respectively. The proposed method can also be used along with Orbitrap mass spectrometers that have faster MS/MS acquisition rates, like the recently released Orbitrap Astral mass spectrometer, to further reduce the mass spectrometer time required per sample.
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Affiliation(s)
- Gelio Alves
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland 20894, United States
| | - Aleksey Y Ogurtsov
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland 20894, United States
| | - Harry Porterfield
- Department of Laboratory Medicine, Clinical Center, National Institutes of Health, Bethesda, Maryland 20892, United States
| | - Tapan Maity
- Laboratory of Cell Biology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland 20892, United States
| | - Lisa M Jenkins
- Laboratory of Cell Biology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland 20892, United States
| | - David B Sacks
- Department of Laboratory Medicine, Clinical Center, National Institutes of Health, Bethesda, Maryland 20892, United States
| | - Yi-Kuo Yu
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland 20894, United States
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2
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Faizan M, Sachan N, Verma O, Sarkar A, Rawat N, Pratap Singh M. Cerebrospinal fluid protein biomarkers in Parkinson's disease. Clin Chim Acta 2024; 556:117848. [PMID: 38417781 DOI: 10.1016/j.cca.2024.117848] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2024] [Revised: 02/24/2024] [Accepted: 02/25/2024] [Indexed: 03/01/2024]
Abstract
Proteomic profiling is an effective way to identify biomarkers for Parkinson's disease (PD). Cerebrospinal fluid (CSF) has direct connectivity with the brain and could be a source of finding biomarkers and their clinical implications. Comparative proteomic profiling has shown that a group of differentially displayed proteins exist. The studies performed using conventional and classical tools also supported the occurrence of these proteins. Many studies have highlighted the potential of CSF proteomic profiling for biomarker identification and their clinical applications. Some of these proteins are useful for disease diagnosis and prediction. Proteomic profiling of CSF also has immense potential to distinguish PD from similar neurodegenerative disorders. A few protein biomarkers help in fundamental knowledge generation and clinical interpretation. However, the specific biomarker of PD is not yet known. The use of proteomic approaches in clinical settings is also rare. A large-scale, multi-centric, multi-population and multi-continental study using multiple proteomic tools is warranted. Such a study can provide valuable, comprehensive and reliable information for a better understanding of PD and the development of specific biomarkers. The current article sheds light on the role of CSF proteomic profiling in identifying biomarkers of PD and their clinical implications. The article also explains the achievements, obstacles and hopes for future directions of this approach.
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Affiliation(s)
- Mohd Faizan
- Systems Toxicology Group, FEST Division, CSIR-Indian Institute of Toxicology Research (CSIR-IITR), Vishvigyan Bhawan, 31, Mahatma Gandhi Marg, Lucknow 226001, Uttar Pradesh, India; Academy of Scientific and Innovative Research (AcSIR), Ghaziabad 201002, Uttar Pradesh, India
| | - Nidhi Sachan
- Systems Toxicology Group, FEST Division, CSIR-Indian Institute of Toxicology Research (CSIR-IITR), Vishvigyan Bhawan, 31, Mahatma Gandhi Marg, Lucknow 226001, Uttar Pradesh, India
| | - Oyashvi Verma
- Systems Toxicology Group, FEST Division, CSIR-Indian Institute of Toxicology Research (CSIR-IITR), Vishvigyan Bhawan, 31, Mahatma Gandhi Marg, Lucknow 226001, Uttar Pradesh, India; Academy of Scientific and Innovative Research (AcSIR), Ghaziabad 201002, Uttar Pradesh, India
| | - Alika Sarkar
- Systems Toxicology Group, FEST Division, CSIR-Indian Institute of Toxicology Research (CSIR-IITR), Vishvigyan Bhawan, 31, Mahatma Gandhi Marg, Lucknow 226001, Uttar Pradesh, India; Academy of Scientific and Innovative Research (AcSIR), Ghaziabad 201002, Uttar Pradesh, India
| | - Neeraj Rawat
- Systems Toxicology Group, FEST Division, CSIR-Indian Institute of Toxicology Research (CSIR-IITR), Vishvigyan Bhawan, 31, Mahatma Gandhi Marg, Lucknow 226001, Uttar Pradesh, India; Academy of Scientific and Innovative Research (AcSIR), Ghaziabad 201002, Uttar Pradesh, India
| | - Mahendra Pratap Singh
- Systems Toxicology Group, FEST Division, CSIR-Indian Institute of Toxicology Research (CSIR-IITR), Vishvigyan Bhawan, 31, Mahatma Gandhi Marg, Lucknow 226001, Uttar Pradesh, India; Academy of Scientific and Innovative Research (AcSIR), Ghaziabad 201002, Uttar Pradesh, India; Capacity Building and Knowledge Services, ASSIST Division, CSIR-Indian Institute of Toxicology Research (CSIR-IITR), Vishvigyan Bhawan, 31, Mahatma Gandhi Marg, Lucknow 226001, Uttar Pradesh, India.
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Bader JM, Albrecht V, Mann M. MS-based proteomics of body fluids: The end of the beginning. Mol Cell Proteomics 2023:100577. [PMID: 37209816 PMCID: PMC10388585 DOI: 10.1016/j.mcpro.2023.100577] [Citation(s) in RCA: 15] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2023] [Revised: 05/07/2023] [Accepted: 05/11/2023] [Indexed: 05/22/2023] Open
Abstract
Accurate biomarkers are a crucial and necessary precondition for precision medicine, yet existing ones are often unspecific and new ones have been very slow to enter the clinic. Mass spectrometry (MS)-based proteomics excels by its untargeted nature, specificity of identification and quantification making it an ideal technology for biomarker discovery and routine measurement. It has unique attributes compared to affinity binder technologies, such as OLINK Proximity Extension Assay and SOMAscan. In a previous review we described technological and conceptual limitations that had held back success (Geyer et al., 2017). We proposed a 'rectangular strategy' to better separate true biomarkers by minimizing cohort-specific effects. Today, this has converged with advances in MS-based proteomics technology, such as increased sample throughput, depth of identification and quantification. As a result, biomarker discovery studies have become more successful, producing biomarker candidates that withstand independent verification and, in some cases, already outperform state-of-the-art clinical assays. We summarize developments over the last years, including the benefits of large and independent cohorts, which are necessary for clinical acceptance. They are also required for machine learning or deep learning. Shorter gradients, new scan modes and multiplexing are about to drastically increase throughput, cross-study integration, and quantification, including proxies for absolute levels. We have found that multi-protein panels are inherently more robust than current single analyte tests and better capture the complexity of human phenotypes. Routine MS measurement in the clinic is fast becoming a viable option. The full set of proteins in a body fluid (global proteome) is the most important reference and the best process control. Additionally, it increasingly has all the information that could be obtained from targeted analysis although the latter may be the most straightforward way to enter into regular use. Many challenges remain, not least of a regulatory and ethical nature, but the outlook for MS-based clinical applications has never been brighter.
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Affiliation(s)
- Jakob M Bader
- Department of Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, 82152 Martinsried, Germany
| | - Vincent Albrecht
- Department of Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, 82152 Martinsried, Germany
| | - Matthias Mann
- Department of Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, 82152 Martinsried, Germany; Novo Nordisk Foundation Center for Protein Research, Faculty of Health Sciences, University of Copenhagen, 2200 Copenhagen, Denmark.
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Chauhan S, Behl T, Sehgal A, Singh S, Sharma N, Gupta S, Albratty M, Najmi A, Meraya AM, Alhazmi HA. Understanding the Intricate Role of Exosomes in Pathogenesis of Alzheimer's Disease. Neurotox Res 2022; 40:1758-1773. [PMID: 36564606 DOI: 10.1007/s12640-022-00621-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2022] [Revised: 12/06/2022] [Accepted: 12/08/2022] [Indexed: 12/25/2022]
Abstract
Alzheimer's disease causes loss of memory and deterioration of mental abilities is utmost predominant neurodegenerative disease accounting 70-80% cases of dementia. The appearance of plaques of amyloid-β and neurofibrillary tangles in the brain post-mortems of Alzheimer's patients established them as key participants in the etiology of Alzheimer's disease. Exosomes exist as extracellular vesicles of nano-size which are present throughout the body. Exosomes are known to spread toxic hyperphosphorylated tau and amyloid-β between the cells and are linked to the loss of neurons by inducing apoptosis. Exosomes have progressed from cell trashcans to multifunctional organelles which are involved in various functions like internalisation and transmission of macromolecules such as lipids, proteins, and nucleic acids. This review covers current findings on relationship of exosomes in biogenesis and angiogenesis of Alzheimer's disease and functions of exosomes in the etiology of AD. Furthermore, the roles of exosomes in development, diagnosis, treatment, and its importance as therapeutic targets and biomarkers for Alzheimer's disease have also been highlighted.
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Affiliation(s)
- Simran Chauhan
- Chitkara College of Pharmacy, Chitkara University, Punjab, 140401, India
| | - Tapan Behl
- School of Health Sciences, University of Petroleum and Energy Studies, Uttarakhand, Dehradun, 248007, India.
| | - Aayush Sehgal
- GHG Khalsa College of Pharmacy, Sadhar, Ludhiana, Punjab, Gurusar, 141104, India
| | - Sukhbir Singh
- Department of Pharmaceutics, MM College of Pharmacy, Maharishi Markandeshwar (Deemed to be University), Haryana, Mullana-Ambala, 133207, India.
| | - Neelam Sharma
- Department of Pharmaceutics, MM College of Pharmacy, Maharishi Markandeshwar (Deemed to be University), Haryana, Mullana-Ambala, 133207, India
| | - Sumeet Gupta
- Department of Pharmacology, MM College of Pharmacy, Maharishi Markandeshwar (Deemed to be University), Haryana, Mullana-Ambala, 133207, India
| | - Mohammed Albratty
- Department of Pharmaceutical Chemistry and Pharmacognosy, College of Pharmacy, Jazan University, Jazan, 45142, Saudi Arabia
| | - Asim Najmi
- Department of Pharmaceutical Chemistry and Pharmacognosy, College of Pharmacy, Jazan University, Jazan, 45142, Saudi Arabia
| | - Abdulkarim M Meraya
- Pharmacy Practice Research Unit, Department of Clinical Pharmacy, Jazan Uniersity, Jazan, 45124, Saudi Arabia
| | - Hassan A Alhazmi
- Department of Pharmaceutical Chemistry, College of Pharmacy, Jzan University, Jazan, 45142, Saudi Arabia
- Substance Abuse and Toxicology Research Centre, Jzan University, Jazan, 45142, Saudi Arabia
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Lilley LM, Sanche S, Moore SC, Salemi MR, Vu D, Iyer S, Hengartner NW, Mukundan H. Methods to capture proteomic and metabolomic signatures from cerebrospinal fluid and serum of healthy individuals. Sci Rep 2022; 12:13339. [PMID: 35922450 PMCID: PMC9349260 DOI: 10.1038/s41598-022-16598-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2022] [Accepted: 05/17/2022] [Indexed: 11/20/2022] Open
Abstract
Discovery of reliable signatures for the empirical diagnosis of neurological diseases-both infectious and non-infectious-remains unrealized. One of the primary challenges encountered in such studies is the lack of a comprehensive database representative of a signature background that exists in healthy individuals, and against which an aberrant event can be assessed. For neurological insults and injuries, it is important to understand the normal profile in the neuronal (cerebrospinal fluid) and systemic fluids (e.g., blood). Here, we present the first comparative multi-omic human database of signatures derived from a population of 30 individuals (15 males, 15 females, 23-74 years) of serum and cerebrospinal fluid. In addition to empirical signatures, we also assigned common pathways between serum and CSF. Together, our findings provide a cohort against which aberrant signature profiles in individuals with neurological injuries/disease can be assessed-providing a pathway for comprehensive diagnostics and therapeutics discovery.
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Affiliation(s)
- Laura M Lilley
- Los Alamos National Laboratory, P.O. Box 1663, Los Alamos, NM, 87545, USA
| | - Steven Sanche
- Los Alamos National Laboratory, P.O. Box 1663, Los Alamos, NM, 87545, USA
| | - Shepard C Moore
- Los Alamos National Laboratory, P.O. Box 1663, Los Alamos, NM, 87545, USA
| | - Michelle R Salemi
- Genome Center, Proteomics Core Facility, University of California, Davis, CA, 95616, USA
| | - Dung Vu
- Los Alamos National Laboratory, P.O. Box 1663, Los Alamos, NM, 87545, USA
| | - Srinivas Iyer
- Los Alamos National Laboratory, P.O. Box 1663, Los Alamos, NM, 87545, USA
| | | | - Harshini Mukundan
- Los Alamos National Laboratory, P.O. Box 1663, Los Alamos, NM, 87545, USA.
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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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Cerebrospinal Fluid Proteome Alterations Associated with Neuropsychiatric Symptoms in Cognitive Decline and Alzheimer's Disease. Cells 2022; 11:cells11061030. [PMID: 35326481 PMCID: PMC8947516 DOI: 10.3390/cells11061030] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2022] [Revised: 03/12/2022] [Accepted: 03/14/2022] [Indexed: 01/27/2023] Open
Abstract
Although neuropsychiatric symptoms (NPS) are common and severely affect older people with cognitive decline, little is known about their underlying molecular mechanisms and relationships with Alzheimer’s disease (AD). The aim of this study was to identify and characterize cerebrospinal fluid (CSF) proteome alterations related to NPS. In a longitudinally followed-up cohort of subjects with normal cognition and patients with cognitive impairment (MCI and mild dementia) from a memory clinic setting, we quantified a panel of 790 proteins in CSF using an untargeted shotgun proteomic workflow. Regression models and pathway enrichment analysis were used to investigate protein alterations related to NPS, and to explore relationships with AD pathology and cognitive decline at follow-up visits. Regression analysis selected 27 CSF proteins associated with NPS. These associations were independent of the presence of cerebral AD pathology (defined as CSF p-tau181/Aβ1−42 > 0.0779, center cutoff). Gene ontology enrichment showed abundance alterations of proteins related to cell adhesion, immune response, and lipid metabolism, among others, in relation to NPS. Out of the selected proteins, three were associated with accelerated cognitive decline at follow-up visits after controlling for possible confounders. Specific CSF proteome alterations underlying NPS may both represent pathophysiological processes independent from AD and accelerate clinical disease progression.
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Dubois E, Galindo AN, Dayon L, Cominetti O. Assessing normalization methods in mass spectrometry-based proteome profiling of clinical samples. Biosystems 2022; 215-216:104661. [PMID: 35247480 DOI: 10.1016/j.biosystems.2022.104661] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2021] [Revised: 02/21/2022] [Accepted: 02/28/2022] [Indexed: 12/31/2022]
Abstract
BACKGROUND Large-scale proteomic studies have to deal with unwanted variability, especially when samples originate from different centers and multiple analytical batches are needed. Such variability is typically added throughout all the steps of a clinical research study, from human biological sample collection and storage, sample preparation, spectral data acquisition, to peptide and protein quantification. In order to remove such diverse and unwanted variability, normalization of the protein data is performed. There have been already several published reviews comparing normalization methods in the -omics field, but reports focusing on proteomic data generated with mass spectrometry (MS) are much fewer. Additionally, most of these reports have only dealt with small datasets. RESULTS As a case study, here we focused on the normalization of a large MS-based proteomic dataset obtained from an overweight and obese pan-European cohort, where different normalization methods were evaluated, namely: center standardize, quantile protein, quantile sample, global standardization, ComBat, median centering, mean centering, single standard and removal of unwanted variation (RUV); some of these are generic normalization methods while others have been specifically created to deal with genomic or metabolomic data. We checked how relationships between proteins and clinical variables (e.g., gender, levels of triglycerides or cholesterol) were improved after normalizing the data with the different methods. CONCLUSIONS Some normalization methods were better adapted for this particular large-scale shotgun proteomic dataset of human plasma samples labeled with isobaric tags and analyzed with liquid chromatography-tandem MS. In particular, quantile sample normalization, RUV, mean and median centering showed very good performance, while quantile protein normalization provided worse results than those obtained with unnormalized data.
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Affiliation(s)
- Etienne Dubois
- Nestlé Institute of Food Safety & Analytical Sciences, Nestlé Research, EPFL Innovation Park, 1015, Lausanne, Switzerland
| | - Antonio Núñez Galindo
- Nestlé Institute of Food Safety & Analytical Sciences, Nestlé Research, EPFL Innovation Park, 1015, Lausanne, Switzerland
| | - Loïc Dayon
- Nestlé Institute of Food Safety & Analytical Sciences, Nestlé Research, EPFL Innovation Park, 1015, Lausanne, Switzerland; Chemistry and Chemical Engineering Section, School of Basic Sciences, Ecole Polytechnique Fédérale de Lausanne, 1015, Lausanne, Switzerland
| | - Ornella Cominetti
- Nestlé Institute of Food Safety & Analytical Sciences, Nestlé Research, EPFL Innovation Park, 1015, Lausanne, Switzerland.
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McKetney J, Panyard DJ, Johnson SC, Carlsson CM, Engelman CD, Coon JJ. Pilot proteomic analysis of cerebrospinal fluid in Alzheimer's disease. Proteomics Clin Appl 2021; 15:e2000072. [PMID: 33682374 PMCID: PMC8197734 DOI: 10.1002/prca.202000072] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2020] [Revised: 02/24/2021] [Accepted: 03/01/2021] [Indexed: 01/10/2023]
Abstract
Proteomic analysis of cerebrospinal fluid (CSF) holds great promise in understanding the progression of neurodegenerative diseases, including Alzheimer's disease (AD). As one of the primary reservoirs of neuronal biomolecules, CSF provides a window into the biochemical and cellular aspects of the neurological environment. CSF can be drawn from living participants allowing the potential alignment of clinical changes with these biochemical markers. Using cutting-edge mass spectrometry technologies, we perform a streamlined proteomic analysis of CSF. We quantify greater than 700 proteins across 10 pairs of age- and sex-matched participants in approximately one hour of analysis time each. Using the paired participant study structure, we identify a small group of biologically relevant proteins that show substantial changes in abundance between cognitive normal and AD participants, which were then analyzed at the peptide level using parallel reaction monitoring experiments. Our findings suggest the utility of fractionating a single sample and using matching to increase proteomic depth in cerebrospinal fluid, as well as the potential power of an expanded study.
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Affiliation(s)
- Justin McKetney
- Department of Biomolecular Chemistry, University of Wisconsin-Madison, Madison, WI
- National Center for Quantitative Biology of Complex Systems, Madison, WI
| | - Daniel J. Panyard
- Department of Population Health Sciences, University of Wisconsin-Madison, Madison, WI
| | - Sterling C. Johnson
- Geriatric Research Education and Clinical Center, Middleton Memorial Veterans Hospital, Madison, WI
- Wisconsin Alzheimer’s Institute, University of Wisconsin-Madison School of Medicine, Madison, WI
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison School of Medicine, Madison, WI
| | - Cynthia M. Carlsson
- Geriatric Research Education and Clinical Center, Middleton Memorial Veterans Hospital, Madison, WI
- Wisconsin Alzheimer’s Institute, University of Wisconsin-Madison School of Medicine, Madison, WI
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison School of Medicine, Madison, WI
| | - Corinne D. Engelman
- Department of Population Health Sciences, University of Wisconsin-Madison, Madison, WI
- Wisconsin Alzheimer’s Institute, University of Wisconsin-Madison School of Medicine, Madison, WI
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison School of Medicine, Madison, WI
| | - Joshua J. Coon
- Department of Biomolecular Chemistry, University of Wisconsin-Madison, Madison, WI
- National Center for Quantitative Biology of Complex Systems, Madison, WI
- Department of Chemistry, University of Wisconsin-Madison, Madison, WI
- Morgridge Institute for Research, Madison, WI
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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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11
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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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12
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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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13
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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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14
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Sim SY, Choi YR, Lee JH, Lim JM, Lee SE, Kim KP, Kim JY, Lee SH, Kim MS. In-Depth Proteomic Analysis of Human Bronchoalveolar Lavage Fluid toward the Biomarker Discovery for Lung Cancers. Proteomics Clin Appl 2019; 13:e1900028. [PMID: 31119868 DOI: 10.1002/prca.201900028] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2019] [Revised: 04/30/2019] [Indexed: 12/18/2022]
Abstract
PURPOSE Lung cancer is among the most common cancers. Bronchoalveolar lavage fluid (BALF) can be easily obtained from patients with lung cancers. The aim is to develop a novel proteomic method of the molecule-based sensitive detection of biomarkers from BALF. EXPERIMENTAL DESIGN BALF samples are collected from segmental bronchus of 14 patients with lung cancers from Kyung Hee University Hospital. First, BALF proteome is depleted using a depletion column, and then peptides are prepared from the enriched low abundant proteins and fractionated by high pH reverse phase liquid chromatography prior to LC-MS/MS. Data are available via ProteomeXchange with identifier PXD012645. RESULTS A novel method is developed for in-depth proteomic analysis of BALF by combining antibody-based depletion of high abundant proteins from BALF with high pH peptide fractionation. Peptides are analyzed on a high resolution Orbitrap Fusion mass spectrometer. MaxQuant search result in the identification of 4615 protein groups mapped to 4534 genes. CONCLUSIONS AND CLINICAL RELEVANCE It is found that the method outperformed conventional BALF proteomic methods and it is believed that this method will facilitate the biomarker research for lung cancer. In addition, it is shown that BALF will be a great source of biomarkers of lung diseases.
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Affiliation(s)
- Seo Young Sim
- Department of Applied Chemistry, Global Center for Pharmaceutical Ingredient Materials, Institute of Natural Science, Kyung Hee University, Yongin, 17104, Republic of Korea
| | - Yu Ri Choi
- Department of Applied Chemistry, Global Center for Pharmaceutical Ingredient Materials, Institute of Natural Science, Kyung Hee University, Yongin, 17104, Republic of Korea
| | - Jun Hyung Lee
- Department of Applied Chemistry, Global Center for Pharmaceutical Ingredient Materials, Institute of Natural Science, Kyung Hee University, Yongin, 17104, Republic of Korea.,Department of New Biology, DGIST, Daegu, 42988, Republic of Korea
| | - Jae Min Lim
- Department of Applied Chemistry, Global Center for Pharmaceutical Ingredient Materials, Institute of Natural Science, Kyung Hee University, Yongin, 17104, Republic of Korea
| | - Seung-Eun Lee
- Department of Biomedical Science and Technology, Kyung Hee Medical Science Research Institute, Kyung Hee University, Seoul, 02447, Republic of Korea
| | - Kwang Pyo Kim
- Department of Applied Chemistry, Global Center for Pharmaceutical Ingredient Materials, Institute of Natural Science, Kyung Hee University, Yongin, 17104, Republic of Korea.,Department of Biomedical Science and Technology, Kyung Hee Medical Science Research Institute, Kyung Hee University, Seoul, 02447, Republic of Korea
| | - Jin Young Kim
- Biomedical Omic Research Group, Korea Basic Science Institute, Ochang, 28119, Republic of Korea
| | - Seung Hyeun Lee
- Department of Internal Medicine, Kyung Hee University School of Medicine, Seoul, 02447, Republic of Korea
| | - Min-Sik Kim
- Department of Applied Chemistry, Global Center for Pharmaceutical Ingredient Materials, Institute of Natural Science, Kyung Hee University, Yongin, 17104, Republic of Korea.,Department of New Biology, DGIST, Daegu, 42988, Republic of Korea.,Department of Biomedical Science and Technology, Kyung Hee Medical Science Research Institute, Kyung Hee University, Seoul, 02447, Republic of Korea
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15
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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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16
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Jankovska E, Svitek M, Holada K, Petrak J. Affinity depletion versus relative protein enrichment: a side-by-side comparison of two major strategies for increasing human cerebrospinal fluid proteome coverage. Clin Proteomics 2019; 16:9. [PMID: 30890900 PMCID: PMC6390343 DOI: 10.1186/s12014-019-9229-1] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2018] [Accepted: 02/19/2019] [Indexed: 02/07/2023] Open
Abstract
Cerebrospinal fluid (CSF) is in direct contact with the central nervous system. This makes human CSF an attractive source of potential biomarkers for neurologic diseases. Similarly to blood plasma, proteomic analysis of CSF is complicated by a high dynamic range of individual protein concentrations and by the presence of several highly abundant proteins. To deal with the abundant human CSF proteins, methods developed for blood plasma/serum are routinely used. Multiple affinity removal systems and protein enrichment of less abundant proteins using a combinatorial peptide ligand library are among the most frequent approaches. However, their relative impact on CSF proteome coverage has never been evaluated side-by-side in a single study. Therefore, we explored the effect of CSF depletion using MARS 14 cartridge and ProteoMiner ligand library on the number of CSF proteins identified in subsequent LC–MS/MS analysis. LC–MS/MS analysis of crude (non-treated) CSF provided roughly 500 identified proteins. Depletion of CSF by MARS 14 cartridge increased the number of identifications to nearly 800, while treatment of CSF using ProteoMiner enabled identification of 600 proteins. To explore the potential losses of CSF proteins during the depletion process, we also analyzed the “waste” fractions generated by both methods, i.e., proteins retained by the MARS 14 cartridge, and the molecules present in the flow-through fraction from ProteoMiner. More than 250 proteins were bound to MARS 14 cartridge, 100 of those were not identified in the corresponding depleted CSF. Similarly, analysis of the waste fraction in ProteoMiner workflow provided almost 70 unique proteins not found in the CSF depleted by the ligand library. Both depletion strategies significantly increased the number of identified CSF proteins compared to crude CSF. However, MARS 14 depletion provided a markedly higher number of identified proteins (773) compared to ProteoMiner (611). Further, we showed that CSF proteins are lost due to co-depletion (MARS 14) or exclusion (ProteoMiner) during the depletion process. This suggests that the routinely discarded “waste” fractions contain proteins of potential interest and should be included in CSF biomarker studies.
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Affiliation(s)
- Eliska Jankovska
- 1BIOCEV, First Faculty of Medicine, Charles University, Prague, Czech Republic
| | - Marek Svitek
- 2Department of Anesthesiology and Intensive Care, First Faculty of Medicine, Charles University, Prague, Czech Republic.,3General University Hospital, Prague, Czech Republic
| | - Karel Holada
- 4Institute of Immunology and Microbiology, First Faculty of Medicine, Charles University, Prague, Czech Republic
| | - Jiri Petrak
- 1BIOCEV, First Faculty of Medicine, Charles University, Prague, Czech Republic
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17
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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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18
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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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19
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Lachén-Montes M, González-Morales A, Fernández-Irigoyen J, Santamaría E. Determination of Cerebrospinal Fluid Proteome Variations by Isobaric Labeling Coupled with Strong Cation-Exchange Chromatography and Tandem Mass Spectrometry. Methods Mol Biol 2019; 2044:155-168. [PMID: 31432412 DOI: 10.1007/978-1-4939-9706-0_10] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Cerebrospinal fluid (CSF) is in direct contact with the brain and represents a valuable source of mediators that reflect metabolic processes occurring in the central nervous system (CNS). In this sense, mass spectrometry (MS) methods have proven to be sensitive in quantifying the proteomic profiles of CSF, therefore being able to detect biomarker candidates for neurological disorders. In particular, a key development has been the use of multiplexing technologies to easily identify and quantify complex protein mixtures. This chapter describes a workflow suitable for the analysis of CSF proteome using isobaric labeling coupled to strong cation-exchange chromatography fractionation for its potential use as a biomarker discovery platform. In this case, the isobaric tags for relative and absolute quantitation (iTRAQ) label all proteins in a sample via free amines at the N-terminus and on the side chain of lysine residues. Then, the labeled samples are pooled and chromatographically fractionated. These fractions with the pooled samples are afterward analyzed by tandem mass spectrometry (MS/MS), and proteins are quantified by the relative intensities of the reporter ions in the MS/MS spectra, simultaneously obtaining the amino acid sequence. This method complements the neuroproteomic toolbox to identify new protein biomarkers not only for the early clinical diagnosis and disease staging of CNS-related disorders but also to elucidate the molecular mechanisms related to the pathophysiology of these symptoms.
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Affiliation(s)
- Mercedes Lachén-Montes
- Proteomics Unit, Clinical Neuroproteomics Laboratory, Navarrabiomed, Complejo Hospitalario de Navarra (CHN), Universidad Pública de Navarra (UPNA), IdiSNA, Proteored-ISCIII, Pamplona, Spain
| | - Andrea González-Morales
- Proteomics Unit, Clinical Neuroproteomics Laboratory, Navarrabiomed, Complejo Hospitalario de Navarra (CHN), Universidad Pública de Navarra (UPNA), IdiSNA, Proteored-ISCIII, Pamplona, Spain
| | - Joaquín Fernández-Irigoyen
- Proteomics Unit, Clinical Neuroproteomics Laboratory, Navarrabiomed, Complejo Hospitalario de Navarra (CHN), Universidad Pública de Navarra (UPNA), IdiSNA, Proteored-ISCIII, Pamplona, Spain
| | - Enrique Santamaría
- Proteomics Unit, Clinical Neuroproteomics Laboratory, Navarrabiomed, Complejo Hospitalario de Navarra (CHN), Universidad Pública de Navarra (UPNA), IdiSNA, Proteored-ISCIII, Pamplona, Spain.
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20
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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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21
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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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22
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Proteomic approach to profiling immune complex antigens in cerebrospinal fluid samples from patients with central nervous system autoimmune diseases. Clin Chim Acta 2018; 484:26-31. [PMID: 29775619 DOI: 10.1016/j.cca.2018.05.026] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2018] [Revised: 04/23/2018] [Accepted: 05/11/2018] [Indexed: 01/01/2023]
Abstract
BACKGROUND Immune complexes (ICs) may clearly reflect immunological abnormalities caused by disease, especially for autoimmune diseases. Although ICs have been detected in cerebrospinal fluid (CSF) from patients with CNS autoimmune diseases, identities of antigens in such ICs have not been comprehensively determined. METHODS We used immune complexome analysis, in which nano-liquid chromatography-tandem mass spectrometry is employed to comprehensively identify antigens incorporated into ICs in biological fluids, to characterize ICs in CSF samples from patients with CNS autoimmune diseases, and to find disease-specific IC antigen to a certain CNS autoimmune disease. Also, we compared the IC antigens we identified with the reported CSF proteome or with the published plasma proteome to examine if the method is distinguished from the conventional CSF proteome analysis. RESULTS We identified 176 antigens in 78 CSF samples. We then assessed the overlaps among these antigens, the CSF proteome, and the plasma proteome; 140 of the 176 antigens were found to be exclusively detected by our method. Notably, IC-associated suprabasin in CSF was 100% specific to neuropsychiatric systemic lupus erythematosus (NPSLE). CONCLUSIONS This report is the first to comprehensively identify the antigens incorporated into ICs in CSF. There was limited overlap between the antigens we identified and the CSF proteome or the plasma proteome; therefore, our method can be distinguished from the conventional CSF proteome analysis. Although the sensitivity of disease-specific IC-antigens detected in immune complexome analysis screening, the sensitivity may be improved by developing an ELISA method specifically for detecting the ICs. Immune complexome analysis of CSF may be a new and promising path to biomarker discovery for diagnosis and study for CNS autoimmune diseases.
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23
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Preparation and Immunoaffinity Depletion of Fresh Frozen Tissue Homogenates for Mass Spectrometry-Based Proteomics in the Context of Drug Target/Biomarker Discovery. Methods Mol Biol 2018; 1647:71-90. [PMID: 28808996 DOI: 10.1007/978-1-4939-7201-2_5] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/19/2023]
Abstract
The discovery of novel drug targets and biomarkers via mass spectrometry (MS)-based proteomic analysis of clinical specimens has proven to be challenging. The wide dynamic range of protein concentration in clinical specimens and the high background/noise originating from highly abundant proteins in tissue homogenates and serum/plasma encompass two major analytical obstacles. Immunoaffinity depletion of highly abundant blood-derived proteins from serum/plasma is a well-established approach adopted by numerous researchers; however, the utilization of this technique for immunodepletion of tissue homogenates obtained from fresh frozen clinical specimens is lacking. We first developed immunoaffinity depletion of highly abundant blood-derived proteins from tissue homogenates, using renal cell carcinoma as a model disease, and followed this study by applying it to different tissue types. Tissue homogenate immunoaffinity depletion of highly abundant proteins may be equally important as is the recognized need for depletion of serum/plasma, enabling more sensitive MS-based discovery of novel drug targets, and/or clinical biomarkers from complex clinical samples. Provided is a detailed protocol designed to guide the researcher through the preparation and immunoaffinity depletion of fresh frozen tissue homogenates for two-dimensional liquid chromatography, tandem mass spectrometry (2D-LC-MS/MS)-based molecular profiling of tissue specimens in the context of drug target and/or biomarker discovery.
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24
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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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25
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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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26
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Ganau M, Syrmos N, Paris M, Ganau L, Ligarotti GKI, Moghaddamjou A, Chibbaro S, Soddu A, Ambu R, Prisco L. Current and Future Applications of Biomedical Engineering for Proteomic Profiling: Predictive Biomarkers in Neuro-Traumatology. MEDICINES 2018; 5:medicines5010019. [PMID: 29401743 PMCID: PMC5874584 DOI: 10.3390/medicines5010019] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/31/2017] [Revised: 01/29/2018] [Accepted: 01/30/2018] [Indexed: 12/18/2022]
Abstract
This systematic review aims to summarize the impact of nanotechnology and biomedical engineering in defining clinically meaningful predictive biomarkers in patients with traumatic brain injury (TBI), a critical worldwide health problem with an estimated 10 billion people affected annually worldwide. Data were collected through a review of the existing English literature performed on Scopus, MEDLINE, MEDLINE in Process, EMBASE, and/or Cochrane Central Register of Controlled Trials. Only experimental articles revolving around the management of TBI, in which the role of new devices based on innovative discoveries coming from the field of nanotechnology and biomedical engineering were highlighted, have been included and analyzed in this study. Based on theresults gathered from this research on innovative methods for genomics, epigenomics, and proteomics, their future application in this field seems promising. Despite the outstanding technical challenges of identifying reliable biosignatures for TBI and the mixed nature of studies herein described (single cells proteomics, biofilms, sensors, etc.), the clinical implementation of those discoveries will allow us to gain confidence in the use of advanced neuromonitoring modalities with a potential dramatic improvement in the management of those patients.
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Affiliation(s)
- Mario Ganau
- Department of Neurosurgery, Toronto Western Hospital, University of Toronto, Toronto, ON M5T 2S8, Canada.
- School of Medicine, University of Cagliari, 09124 Cagliari, Italy.
| | - Nikolaos Syrmos
- School of Medicine, Aristotle University of Thessaloniki, 54623 Thessaloniki, Greece.
| | - Marco Paris
- National Hospital for Neurology and Neurosurgery, University College London, London WC1N 3BG, UK.
| | - Laura Ganau
- School of Medicine, University of Cagliari, 09124 Cagliari, Italy.
| | | | - Ali Moghaddamjou
- Department of Neurosurgery, Toronto Western Hospital, University of Toronto, Toronto, ON M5T 2S8, Canada.
| | - Salvatore Chibbaro
- Division of Neurosurgery, University of Strasbourg, 67000 Strasbourg, France.
| | - Andrea Soddu
- Brain and Mind Institute, Physics & Astronomy Department, Western University, London, ON N6A 3K7, Canada.
| | - Rossano Ambu
- School of Medicine, University of Cagliari, 09124 Cagliari, Italy.
| | - Lara Prisco
- John Radcliffe Hospital, Oxford University, Oxford OX3 9DU, UK.
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27
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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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28
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Proteomic Biomarker Identification in Cerebrospinal Fluid for Leptomeningeal Metastases with Neurological Complications. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2017; 974:85-96. [PMID: 28353226 DOI: 10.1007/978-3-319-52479-5_5] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
Leptomeningeal metastases (LM) from solid tumours, lymphoma and leukaemia are characterized by multifocal neurological deficits with a high mortality rate. Early diagnosis and initiation of treatment are essential to kerb neurological deterioration. However, this is not always possible as 25% of cerebrospinal fluid samples produce false-negative results at first cytological examination. The identification of biomarkers that allow stratification of individuals according to risk for developing LM would be a major benefit. Proteomic-based approaches are now in increasing use for this purpose, and these are reviewed in this chapter with a focus on cerebrospinal fluid (CSF) analyses. The construction of a CSF proteome disease database would also facilitate analysis of other neurological disorders.
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29
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Santo-Domingo J, Chareyron I, Dayon L, Núñez Galindo A, Cominetti O, Pilar Giner Giménez M, De Marchi U, Canto C, Kussmann M, Wiederkehr A. Coordinated activation of mitochondrial respiration and exocytosis mediated by PKC signaling in pancreatic β cells. FASEB J 2016; 31:1028-1045. [PMID: 27927723 DOI: 10.1096/fj.201600837r] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2016] [Accepted: 11/22/2016] [Indexed: 12/17/2022]
Abstract
Mitochondria play a central role in pancreatic β-cell nutrient sensing by coupling their metabolism to plasma membrane excitability and insulin granule exocytosis. Whether non-nutrient secretagogues stimulate mitochondria as part of the molecular mechanism to promote insulin secretion is not known. Here, we show that PKC signaling, which is employed by many non-nutrient secretagogues, augments mitochondrial respiration in INS-1E (rat insulinoma cell line clone 1E) and human pancreatic β cells. The phorbol ester, phorbol 12-myristate 13-acetate, accelerates mitochondrial respiration at both resting and stimulatory glucose concentrations. A range of inhibitors of novel PKC isoforms prevent phorbol ester-induced respiration. Respiratory response was blocked by oligomycin that demonstrated PKC-dependent acceleration of mitochondrial ATP synthesis. Enhanced respiration was observed even when glycolysis was bypassed or fatty acid transport was blocked, which suggested that PKC regulates mitochondrial processes rather than upstream catabolic fluxes. A phosphoproteome study of phorbol ester-stimulated INS-1E cells maintained under resting (2.5 mM) glucose revealed a large number of phosphorylation sites that were altered during short-term activation of PKC signaling. The data set was enriched for proteins that are involved in gene expression, cytoskeleton remodeling, secretory vesicle transport, and exocytosis. Interactome analysis identified PKC, C-Raf, and ERK1/2 as the central phosphointeraction cluster. Prevention of ERK1/2 signaling by using a MEK1 inhibitor caused a marked decreased in phorbol 12-myristate 13-acetate-induced mitochondrial respiration. ERK1/2 signaling module therefore links PKC activation to downstream mitochondrial activation. We conclude that non-nutrient secretagogues act, in part, via PKC and downstream ERK1/2 signaling to stimulate mitochondrial energy production to compensate for energy expenditure that is linked to β-cell activation.-Santo-Domingo, J., Chareyron, I., Dayon, L., Galindo, A. N., Cominetti, O., Giménez, M. P. G., De Marchi, U., Canto, C., Kussmann, M., Wiederkehr, A. Coordinated activation of mitochondrial respiration and exocytosis mediated by PKC signaling in pancreatic β cells.
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Affiliation(s)
- Jaime Santo-Domingo
- Mitochondrial Function, Nestlé Institute of Health Sciences, Lausanne, Switzerland
| | - Isabelle Chareyron
- Mitochondrial Function, Nestlé Institute of Health Sciences, Lausanne, Switzerland
| | - Loïc Dayon
- 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
| | - Ornella Cominetti
- Systems Nutrition, Metabonomics and Proteomics, Nestlé Institute of Health Sciences, Lausanne, Switzerland
| | - María Pilar Giner Giménez
- Systems Nutrition, Metabonomics and Proteomics, Nestlé Institute of Health Sciences, Lausanne, Switzerland
| | - Umberto De Marchi
- Mitochondrial Function, Nestlé Institute of Health Sciences, Lausanne, Switzerland
| | - Carles Canto
- Diabetes and Metabolic Health, Nestlé Institute of Health Sciences, Lausanne, Switzerland
| | - Martin Kussmann
- Systems Nutrition, Metabonomics and Proteomics, Nestlé Institute of Health Sciences, Lausanne, Switzerland
| | - Andreas Wiederkehr
- Mitochondrial Function, Nestlé Institute of Health Sciences, Lausanne, Switzerland;
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30
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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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