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Feliu J, Gámez-Pozo A, Martínez-Pérez D, Pérez-Wert P, Matamala-Luengo D, Viñal D, Kunz L, López-Vacas R, Dittmann A, Rodríguez-Salas N, Custodio A, Fresno Vara JÁ, Trilla-Fuertes L. Functional proteomics of colon cancer Consensus Molecular Subtypes. Br J Cancer 2024; 130:1670-1678. [PMID: 38486123 DOI: 10.1038/s41416-024-02650-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2023] [Revised: 02/26/2024] [Accepted: 03/01/2024] [Indexed: 05/15/2024] Open
Abstract
BACKGROUND The Colorectal Cancer Subtyping Consortium established four Consensus Molecular Subtypes (CMS) in colorectal cancer: CMS1 (microsatellite-instability [MSI], Immune), CMS2 (Canonical, epithelial), CMS3 (Metabolic), and CMS4 (Mesenchymal). However, only MSI tumour patients have seen a change in their disease management in clinical practice. This study aims to characterise the proteome of colon cancer CMS and broaden CMS's clinical utility. METHODS One-hundred fifty-eight paraffin samples from stage II-III colon cancer patients treated with adjuvant chemotherapy were analysed through DIA-based mass-spectrometry proteomics. RESULTS CMS1 exhibited overexpression of immune-related proteins, specifically related to neutrophils, phagocytosis, antimicrobial response, and a glycolytic profile. These findings suggested potential therapeutic strategies involving immunotherapy and glycolytic inhibitors. CMS3 showed overexpression of metabolic proteins. CMS2 displayed a heterogeneous protein profile. Notably, two proteomics subtypes within CMS2, with different protein characteristics and prognoses, were identified. CMS4 emerged as the most distinct group, featuring overexpression of proteins related to angiogenesis, extracellular matrix, focal adhesion, and complement activation. CMS4 showed a high metastatic profile and suggested possible chemoresistance that may explain its worse prognosis. CONCLUSIONS DIA proteomics revealed new features for each colon cancer CMS subtype. These findings provide valuable insights into potential therapeutic targets for colorectal cancer subtypes in the future.
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Affiliation(s)
- Jaime Feliu
- Medical Oncology Department, La Paz University Hospital, Paseo de la Castellana 261, 28046, Madrid, Spain.
- Cátedra UAM-Amgen, Universidad Autónoma de Madrid, Madrid, Spain.
- Biomedical Research Networking Center on Oncology-CIBERONC, ISCIII, Madrid, Spain.
| | - Angelo Gámez-Pozo
- Molecular Oncology Lab, La Paz University Hospital-IdiPAZ, Madrid, Spain
| | - Daniel Martínez-Pérez
- Medical Oncology Department, La Paz University Hospital, Paseo de la Castellana 261, 28046, Madrid, Spain
| | - Pablo Pérez-Wert
- Medical Oncology Department, La Paz University Hospital, Paseo de la Castellana 261, 28046, Madrid, Spain
| | | | - David Viñal
- Medical Oncology Department, La Paz University Hospital, Paseo de la Castellana 261, 28046, Madrid, Spain
| | - Laura Kunz
- Functional Genomics Center Zurich, Zurich, Switzerland
| | - Rocío López-Vacas
- Molecular Oncology Lab, La Paz University Hospital-IdiPAZ, Madrid, Spain
| | | | - Nuria Rodríguez-Salas
- Medical Oncology Department, La Paz University Hospital, Paseo de la Castellana 261, 28046, Madrid, Spain
| | - Ana Custodio
- Medical Oncology Department, La Paz University Hospital, Paseo de la Castellana 261, 28046, Madrid, Spain
| | - Juan Ángel Fresno Vara
- Biomedical Research Networking Center on Oncology-CIBERONC, ISCIII, Madrid, Spain
- Molecular Oncology Lab, La Paz University Hospital-IdiPAZ, Madrid, Spain
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2
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Kverneland AH, Harking F, Vej-Nielsen JM, Huusfeldt M, Bekker-Jensen DB, Svane IM, Bache N, Olsen JV. Fully automated workflow for integrated sample digestion and Evotip loading enabling high-throughput clinical proteomics. Mol Cell Proteomics 2024:100790. [PMID: 38777088 DOI: 10.1016/j.mcpro.2024.100790] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2024] [Revised: 05/02/2024] [Accepted: 05/19/2024] [Indexed: 05/25/2024] Open
Abstract
Protein identification and quantification is an important tool for biomarker discovery. With the increased sensitivity and speed of modern mass spectrometers, sample-preparation remains a bottleneck for studying large cohorts. To address this issue, we prepared and evaluated a simple and efficient workflow on the Opentrons OT-2 (OT-2) robot that combines sample digestion, cleanup and loading on Evotips in a fully automated manner, allowing the processing of up to 192 samples in 6 hours. Analysis of 192 automated HeLa cell sample preparations consistently identified ∼8000 protein groups and ∼130,000 peptide precursors with an 11.5 minute active LC gradient with the Evosep One and narrow-window data-independent acquisition with the Orbitrap Astral mass spectrometer providing a throughput of 100-samples-per-day. Our results demonstrate a highly sensitive workflow yielding both reproducibility and stability at low sample inputs. The workflow is optimized for minimal sample starting amount to reduce the costs for reagents needed for sample preparation, which is critical when analyzing large biological cohorts. Building on the digesting workflow, we incorporated an automated phosphopeptide enrichment step using magnetic Ti-IMAC beads. This allows for a fully automated proteome and phosphoproteome sample preparation in a single step with high sensitivity. Using the integrated digestion and Evotip loading workflow, we evaluated the effects of cancer immune therapy on the plasma proteome in metastatic melanoma patients.
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Affiliation(s)
- Anders H Kverneland
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark; National Center of Cancer Immune Therapy, Department of Oncology, Copenhagen University Hospital - Herlev and Gentofte, Herlev, Denmark
| | - Florian Harking
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark
| | | | | | | | - Inge Marie Svane
- National Center of Cancer Immune Therapy, Department of Oncology, Copenhagen University Hospital - Herlev and Gentofte, Herlev, Denmark
| | | | - Jesper V Olsen
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark.
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3
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Wu CC, Tsantilas KA, Park J, Plubell D, Sanders JA, Naicker P, Govender I, Buthelezi S, Stoychev S, Jordaan J, Merrihew G, Huang E, Parker ED, Riffle M, Hoofnagle AN, Noble WS, Poston KL, Montine TJ, MacCoss MJ. Mag-Net: Rapid enrichment of membrane-bound particles enables high coverage quantitative analysis of the plasma proteome. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.06.10.544439. [PMID: 38617345 PMCID: PMC11014469 DOI: 10.1101/2023.06.10.544439] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/16/2024]
Abstract
Membrane-bound particles in plasma are composed of exosomes, microvesicles, and apoptotic bodies and represent ~1-2% of the total protein composition. Proteomic interrogation of this subset of plasma proteins augments the representation of tissue-specific proteins, representing a "liquid biopsy," while enabling the detection of proteins that would otherwise be beyond the dynamic range of liquid chromatography-tandem mass spectrometry of unfractionated plasma. We have developed an enrichment strategy (Mag-Net) using hyper-porous strong-anion exchange magnetic microparticles to sieve membrane-bound particles from plasma. The Mag-Net method is robust, reproducible, inexpensive, and requires <100 μL plasma input. Coupled to a quantitative data-independent mass spectrometry analytical strategy, we demonstrate that we can collect results for >37,000 peptides from >4,000 plasma proteins with high precision. Using this analytical pipeline on a small cohort of patients with neurodegenerative disease and healthy age-matched controls, we discovered 204 proteins that differentiate (q-value < 0.05) patients with Alzheimer's disease dementia (ADD) from those without ADD. Our method also discovered 310 proteins that were different between Parkinson's disease and those with either ADD or healthy cognitively normal individuals. Using machine learning we were able to distinguish between ADD and not ADD with a mean ROC AUC = 0.98 ± 0.06.
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Affiliation(s)
- Christine C. Wu
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | | | - Jea Park
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Deanna Plubell
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Justin A. Sanders
- Department of Computer Science, University of Washington, Seattle, WA, USA
| | | | | | | | | | | | - Gennifer Merrihew
- Department of Computer Science, University of Washington, Seattle, WA, USA
| | - Eric Huang
- Department of Computer Science, University of Washington, Seattle, WA, USA
| | - Edward D. Parker
- Vision Core Lab, Department of Ophthalmology, University of Washington, Seattle, WA, USA
| | - Michael Riffle
- Department of Biochemistry, University of Washington, Seattle, WA, USA
| | - Andrew N. Hoofnagle
- Department of Lab Medicine and Pathology, University of Washington, Seattle, WA, USA
| | - William S. Noble
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
- Department of Computer Science, University of Washington, Seattle, WA, USA
| | - Kathleen L. Poston
- Department of Neurology & Neurological Sciences, Stanford University, Palo Alto CA, USA
| | | | - Michael J. MacCoss
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
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4
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Guan X, Hu R, Choi Y, Srivats S, Nabet BY, Silva J, McGinnis L, Hendricks R, Nutsch K, Banta KL, Duong E, Dunkle A, Chang PS, Han CJ, Mittman S, Molden N, Daggumati P, Connolly W, Johnson M, Abreu DR, Cho BC, Italiano A, Gil-Bazo I, Felip E, Mellman I, Mariathasan S, Shames DS, Meng R, Chiang EY, Johnston RJ, Patil NS. Anti-TIGIT antibody improves PD-L1 blockade through myeloid and T reg cells. Nature 2024; 627:646-655. [PMID: 38418879 PMCID: PMC11139643 DOI: 10.1038/s41586-024-07121-9] [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: 01/27/2022] [Accepted: 01/26/2024] [Indexed: 03/02/2024]
Abstract
Tiragolumab, an anti-TIGIT antibody with an active IgG1κ Fc, demonstrated improved outcomes in the phase 2 CITYSCAPE trial (ClinicalTrials.gov: NCT03563716 ) when combined with atezolizumab (anti-PD-L1) versus atezolizumab alone1. However, there remains little consensus on the mechanism(s) of response with this combination2. Here we find that a high baseline of intratumoural macrophages and regulatory T cells is associated with better outcomes in patients treated with atezolizumab plus tiragolumab but not with atezolizumab alone. Serum sample analysis revealed that macrophage activation is associated with a clinical benefit in patients who received the combination treatment. In mouse tumour models, tiragolumab surrogate antibodies inflamed tumour-associated macrophages, monocytes and dendritic cells through Fcγ receptors (FcγR), in turn driving anti-tumour CD8+ T cells from an exhausted effector-like state to a more memory-like state. These results reveal a mechanism of action through which TIGIT checkpoint inhibitors can remodel immunosuppressive tumour microenvironments, and suggest that FcγR engagement is an important consideration in anti-TIGIT antibody development.
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Affiliation(s)
| | - Ruozhen Hu
- Genentech Inc., South San Francisco, CA, USA
| | - Yoonha Choi
- Genentech Inc., South San Francisco, CA, USA
| | | | | | - John Silva
- Genentech Inc., South San Francisco, CA, USA
| | | | | | | | | | - Ellen Duong
- Genentech Inc., South San Francisco, CA, USA
| | | | | | | | | | | | | | | | - Melissa Johnson
- Sarah Cannon Research Institute/Tennessee Oncology, PLLC, Nashville, TN, USA
| | | | - Byoung Chul Cho
- Yonsei Cancer Centre, Yonsei University College of Medicine, Seoul, South Korea
| | - Antoine Italiano
- Institut Bergonie CLCC Bordeaux, Bordeaux, France
- Faculty of Medicine, University of Bordeaux, Bordeaux, France
| | - Ignacio Gil-Bazo
- Clínica Universidad de Navarra, CIMA Universidad de Navarra Pamplona, Pamplona, Spain
| | - Enriqueta Felip
- Vall d'Hebron Institute of Oncology (VHIO), Barcelona, Spain
| | - Ira Mellman
- Genentech Inc., South San Francisco, CA, USA
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5
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Zhou Y, Zheng H, Tan Z, Kang E, Xue P, Li X, Guan F. Optimizing and integrating depletion and precipitation methods for plasma proteomics through data-independent acquisition-mass spectrometry. J Chromatogr B Analyt Technol Biomed Life Sci 2024; 1235:124046. [PMID: 38382157 DOI: 10.1016/j.jchromb.2024.124046] [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: 12/09/2023] [Revised: 01/29/2024] [Accepted: 02/10/2024] [Indexed: 02/23/2024]
Abstract
The application of plasma proteomics is a reliable approach for the discovery of biomarkers. However, the utilization of mass spectrometry-based proteomics in plasma encounters limitations due to the presence of high-abundant proteins (HAPs) and the vast dynamic range. To address this issue, we conducted an optimization and integration of depletion and precipitation strategies eliminating interference from HAPs. The optimized procedure involved utilizing 40 µL of beads for the removal of 1 µL of plasma, and maintaining a ratio of 1:1:1 between plasma, urea, and trichloroacetic acid for the precipitation of 50 µL of plasma. To facilitate high-throughput processing, experimental procedures were carried out utilizing 96-well plates. The depletion method identified a total of 1510 proteins, whereas the precipitated method yielded a total of 802 proteins. The integration of these methods yielded a total of 1794 proteins, including a wide concentration range spanning over 8 orders of magnitude. Furthermore, these approaches exhibited a commendable level of reproducibility, as indicated by median coefficients of variation of 14.7 % and 21.1 % for protein intensities, respectively. The integrative method was found to be effective in precisely quantifying yeast proteins that were intentionally spiked in plasma at predetermined rations of 5, 2, 0.5, and 0.2 with a high genuine positive recovery with a range of 71 % to 91 % of all yeast proteins. The use of a complementary and finely tuned approach involving depletion and precipitation demonstrates tremendous potential in the field of discovering protein biomarkers from large-scale cohort studies.
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Affiliation(s)
- Yue Zhou
- College of Life Science, Northwest University, Xi'an, Shaanxi, China
| | - Helong Zheng
- College of Life Science, Northwest University, Xi'an, Shaanxi, China
| | - Zengqi Tan
- College of Life Science, Northwest University, Xi'an, Shaanxi, China
| | - Enci Kang
- Xi'an Gaoxin No.1 High School International Division, Xi'an, Shaanxi, China
| | - Peng Xue
- Guangzhou National Laboratory, Guangzhou, Guangdong, China
| | - Xiang Li
- College of Life Science, Northwest University, Xi'an, Shaanxi, China
| | - Feng Guan
- College of Life Science, Northwest University, Xi'an, Shaanxi, China.
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6
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Steigerwald S, Sinha A, Fort KL, Zeng WF, Niu L, Wichmann C, Kreutzmann A, Mourad D, Aizikov K, Grinfeld D, Makarov A, Mann M, Meier F. Full Mass Range ΦSDM Orbitrap Mass Spectrometry for DIA Proteome Analysis. Mol Cell Proteomics 2024; 23:100713. [PMID: 38184013 PMCID: PMC10851225 DOI: 10.1016/j.mcpro.2024.100713] [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: 08/30/2023] [Revised: 12/21/2023] [Accepted: 01/03/2024] [Indexed: 01/08/2024] Open
Abstract
Optimizing data-independent acquisition methods for proteomics applications often requires balancing spectral resolution and acquisition speed. Here, we describe a real-time full mass range implementation of the phase-constrained spectrum deconvolution method (ΦSDM) for Orbitrap mass spectrometry that increases mass resolving power without increasing scan time. Comparing its performance to the standard enhanced Fourier transformation signal processing revealed that the increased resolving power of ΦSDM is beneficial in areas of high peptide density and comes with a greater ability to resolve low-abundance signals. In a standard 2 h analysis of a 200 ng HeLa digest, this resulted in an increase of 16% in the number of quantified peptides. As the acquisition speed becomes even more important when using fast chromatographic gradients, we further applied ΦSDM methods to a range of shorter gradient lengths (21, 12, and 5 min). While ΦSDM improved identification rates and spectral quality in all tested gradients, it proved particularly advantageous for the 5 min gradient. Here, the number of identified protein groups and peptides increased by >15% in comparison to enhanced Fourier transformation processing. In conclusion, ΦSDM is an alternative signal processing algorithm for processing Orbitrap data that can improve spectral quality and benefit quantitative accuracy in typical proteomics experiments, especially when using short gradients.
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Affiliation(s)
- Sophia Steigerwald
- Department Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Martinsried, Germany
| | - Ankit Sinha
- Department Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Martinsried, Germany
| | - Kyle L Fort
- Thermo Fisher Scientific (GmbH), Bremen, Germany
| | - Wen-Feng Zeng
- Department Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Martinsried, Germany
| | - Lili Niu
- Department Clinical Proteomics, NNF Center for Protein Research, University of Copenhagen, Copenhagen, Denmark
| | - Christoph Wichmann
- Department Computational Systems Biochemistry, Max Planck Institute of Biochemistry, Martinsried, Germany
| | | | | | | | | | | | - Matthias Mann
- Department Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Martinsried, Germany; Department Clinical Proteomics, NNF Center for Protein Research, University of Copenhagen, Copenhagen, Denmark
| | - Florian Meier
- Department Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Martinsried, Germany; Functional Proteomics, Jena University Hospital, Jena, Germany.
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7
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Tobaruela EDC, Brasili E, Zeraik L, Milenkovic D, Hassimotto NMA, Lajolo FM. Plasma proteome profiling reveals molecular mechanisms underlying the effects of daily consumption of 'Bahia' and 'Cara Cara' orange juices. Food Funct 2024; 15:1031-1049. [PMID: 38193367 DOI: 10.1039/d3fo04091g] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2024]
Abstract
Orange juice is an important food source of bioactive compounds, mainly the flavanones hesperidin and narirutin. This study aimed to investigate the underlying molecular mechanisms of action of orange juice's health properties by analyzing changes in the plasma proteome of healthy Brazilian volunteers after consuming juices made from 'Bahia' (BOJ-source of flavanones) and 'Cara Cara' (CCOJ-source of flavanones and carotenoids) oranges cultivated in Brazil. We used an untargeted proteomic approach, with a particular emphasis on the juices' effects on blood coagulant activity. We identified 247 differentially expressed proteins, of which 170 significantly increased or decreased after BOJ consumption and 145 after CCOJ. These proteins are involved in 105 processes that can significantly regulate cell adhesion, cell signaling, cell metabolism, inflammation, or others. Bioinformatic analysis evidenced proteins with major cellular regulatory capacity (e.g., FN1 and GAPDH) and predicted transcription factors (TFs) (e.g., SP1 and CEBPA) and miRNAs (e.g., miR-1-3p and miR-615-3p) that could be involved in the regulation of differentially expressed proteins. In-silico docking analyses between flavanone metabolites and TFs evidenced the higher binding capacity of narirutin phase II metabolites with akt1 and p38, interactions that suggest how the expression of genes of differentially expressed proteins were activated or inhibited. Moreover, the study shed light on proteins of coagulation cascade that presented expression modulated by both juices, proposing the modulation of blood coagulant activity as a potential benefit of OJ (mainly CCOJ) consumption. Taken together, this study revealed that BOJ and CCOJ consumption affected plasma proteome in healthy individuals, suggesting potential molecular targets and mechanisms of OJ bioactive compounds in humans.
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Affiliation(s)
- Eric de Castro Tobaruela
- Food Research Center (FoRC), Department of Food and Experimental Nutrition, School of Pharmaceutical Sciences, University of São Paulo (USP), São Paulo, SP, Brazil.
| | - Elisa Brasili
- Department of Environmental Biology, Sapienza University of Rome, Rome, Italy
| | - Laila Zeraik
- Food Research Center (FoRC), Department of Food and Experimental Nutrition, School of Pharmaceutical Sciences, University of São Paulo (USP), São Paulo, SP, Brazil.
| | - Dragan Milenkovic
- Department of Nutrition, University of California Davis, 95616 Davis, CA, USA
| | - Neuza Mariko Aymoto Hassimotto
- Food Research Center (FoRC), Department of Food and Experimental Nutrition, School of Pharmaceutical Sciences, University of São Paulo (USP), São Paulo, SP, Brazil.
| | - Franco Maria Lajolo
- Food Research Center (FoRC), Department of Food and Experimental Nutrition, School of Pharmaceutical Sciences, University of São Paulo (USP), São Paulo, SP, Brazil.
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8
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Gerdle B, Dahlqvist Leinhard O, Lund E, Lundberg P, Forsgren MF, Ghafouri B. Pain and the biochemistry of fibromyalgia: patterns of peripheral cytokines and chemokines contribute to the differentiation between fibromyalgia and controls and are associated with pain, fat infiltration and content. FRONTIERS IN PAIN RESEARCH 2024; 5:1288024. [PMID: 38304854 PMCID: PMC10830731 DOI: 10.3389/fpain.2024.1288024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2023] [Accepted: 01/05/2024] [Indexed: 02/03/2024] Open
Abstract
Objectives This explorative study analyses interrelationships between peripheral compounds in saliva, plasma, and muscles together with body composition variables in healthy subjects and in fibromyalgia patients (FM). There is a need to better understand the extent cytokines and chemokines are associated with body composition and which cytokines and chemokines differentiate FM from healthy controls. Methods Here, 32 female FM patients and 30 age-matched female healthy controls underwent a clinical examination that included blood sample, saliva samples, and pain threshold tests. In addition, the subjects completed a health questionnaire. From these blood and saliva samples, a panel of 68 mainly cytokines and chemokines were determined. Microdialysis of trapezius and erector spinae muscles, phosphorus-31 magnetic resonance spectroscopy of erector spinae muscle, and whole-body magnetic resonance imaging for determination of body composition (BC)-i.e., muscle volume, fat content and infiltration-were also performed. Results After standardizing BC measurements to remove the confounding effect of Body Mass Index, fat infiltration and content are generally increased, and fat-free muscle volume is decreased in FM. Mainly saliva proteins differentiated FM from controls. When including all investigated compounds and BC variables, fat infiltration and content variables were most important, followed by muscle compounds and cytokines and chemokines from saliva and plasma. Various plasma proteins correlated positively with pain intensity in FM and negatively with pain thresholds in all subjects taken together. A mix of increased plasma cytokines and chemokines correlated with an index covering fat infiltration and content in different tissues. When muscle compounds were included in the analysis, several of these were identified as the most important regressors, although many plasma and saliva proteins remained significant. Discussion Peripheral factors were important for group differentiation between FM and controls. In saliva (but not plasma), cytokines and chemokines were significantly associated with group membership as saliva compounds were increased in FM. The importance of peripheral factors for group differentiation increased when muscle compounds and body composition variables were also included. Plasma proteins were important for pain intensity and sensitivity. Cytokines and chemokines mainly from plasma were also significantly and positively associated with a fat infiltration and content index. Conclusion Our findings of associations between cytokines and chemokines and fat infiltration and content in different tissues confirm that inflammation and immune factors are secreted from adipose tissue. FM is clearly characterized by complex interactions between peripheral tissues and the peripheral and central nervous systems, including nociceptive, immune, and neuroendocrine processes.
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Affiliation(s)
- Björn Gerdle
- Pain and Rehabilitation Centre, and Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden
- Center for Medical Image Science and Visualization (CMIV), Linköping, Sweden
| | - Olof Dahlqvist Leinhard
- Center for Medical Image Science and Visualization (CMIV), Linköping, Sweden
- Radiation Physics, Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden
- AMRA Medical AB, Linköping, Sweden
| | - Eva Lund
- Radiation Physics, Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden
| | - Peter Lundberg
- Center for Medical Image Science and Visualization (CMIV), Linköping, Sweden
- Department of Radiation Physics, and Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden
| | - Mikael Fredrik Forsgren
- Center for Medical Image Science and Visualization (CMIV), Linköping, Sweden
- Radiation Physics, Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden
- AMRA Medical AB, Linköping, Sweden
| | - Bijar Ghafouri
- Pain and Rehabilitation Centre, and Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden
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9
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Lacar B, Ferdosi S, Alavi A, Stukalov A, Venkataraman GR, de Geus M, Dodge H, Wu CY, Kivisakk P, Das S, Guturu H, Hyman B, Batzoglou S, Arnold SE, Siddiqui A. Identification of Novel Biomarkers for Alzheimer's Disease and Related Dementias Using Unbiased Plasma Proteomics. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.05.574446. [PMID: 38260620 PMCID: PMC10802486 DOI: 10.1101/2024.01.05.574446] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/24/2024]
Abstract
Alzheimer's disease (AD) and related dementias (ADRD) is a complex disease with multiple pathophysiological drivers that determine clinical symptomology and disease progression. These diseases develop insidiously over time, through many pathways and disease mechanisms and continue to have a huge societal impact for affected individuals and their families. While emerging blood-based biomarkers, such as plasma p-tau181 and p-tau217, accurately detect Alzheimer neuropthology and are associated with faster cognitive decline, the full extension of plasma proteomic changes in ADRD remains unknown. Earlier detection and better classification of the different subtypes may provide opportunities for earlier, more targeted interventions, and perhaps a higher likelihood of successful therapeutic development. In this study, we aim to leverage unbiased mass spectrometry proteomics to identify novel, blood-based biomarkers associated with cognitive decline. 1,786 plasma samples from 1,005 patients were collected over 12 years from partcipants in the Massachusetts Alzheimer's Disease Research Center Longitudinal Cohort Study. Patient metadata includes demographics, final diagnoses, and clinical dementia rating (CDR) scores taken concurrently. The Proteograph™ Product Suite (Seer, Inc.) and liquid-chromatography mass-spectrometry (LC-MS) analysis were used to process the plasma samples in this cohort and generate unbiased proteomics data. Data-independent acquisition (DIA) mass spectrometry results yielded 36,259 peptides and 4,007 protein groups. Linear mixed effects models revealed 138 differentially abundant proteins between AD and healthy controls. Machine learning classification models for AD diagnosis identified potential candidate biomarkers including MBP, BGLAP, and APoD. Cox regression models were created to determine the association of proteins with disease progression and suggest CLNS1A, CRISPLD2, and GOLPH3 as targets of further investigation as potential biomarkers. The Proteograph workflow provided deep, unbiased coverage of the plasma proteome at a speed that enabled a cohort study of almost 1,800 samples, which is the largest, deep, unbiased proteomics study of ADRD conducted to date.
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Affiliation(s)
| | | | | | | | | | - Matthijs de Geus
- Massachusetts General Hospital (MGH), 55 Fruit Street, Boston, Massachusetts 02114
| | - Hiroko Dodge
- Massachusetts General Hospital (MGH), 55 Fruit Street, Boston, Massachusetts 02114
| | - Chao-Yi Wu
- Massachusetts General Hospital (MGH), 55 Fruit Street, Boston, Massachusetts 02114
| | - Pia Kivisakk
- Massachusetts General Hospital (MGH), 55 Fruit Street, Boston, Massachusetts 02114
| | - Sudeshna Das
- Massachusetts General Hospital (MGH), 55 Fruit Street, Boston, Massachusetts 02114
| | | | - Brad Hyman
- Massachusetts General Hospital (MGH), 55 Fruit Street, Boston, Massachusetts 02114
| | | | - Steven E. Arnold
- Massachusetts General Hospital (MGH), 55 Fruit Street, Boston, Massachusetts 02114
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10
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Kardell O, von Toerne C, Merl-Pham J, König AC, Blindert M, Barth TK, Mergner J, Ludwig C, Tüshaus J, Eckert S, Müller SA, Breimann S, Giesbertz P, Bernhardt AM, Schweizer L, Albrecht V, Teupser D, Imhof A, Kuster B, Lichtenthaler SF, Mann M, Cox J, Hauck SM. Multicenter Collaborative Study to Optimize Mass Spectrometry Workflows of Clinical Specimens. J Proteome Res 2024; 23:117-129. [PMID: 38015820 PMCID: PMC10775142 DOI: 10.1021/acs.jproteome.3c00473] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Revised: 11/02/2023] [Accepted: 11/14/2023] [Indexed: 11/30/2023]
Abstract
The foundation for integrating mass spectrometry (MS)-based proteomics into systems medicine is the development of standardized start-to-finish and fit-for-purpose workflows for clinical specimens. An essential step in this pursuit is to highlight the common ground in a diverse landscape of different sample preparation techniques and liquid chromatography-mass spectrometry (LC-MS) setups. With the aim to benchmark and improve the current best practices among the proteomics MS laboratories of the CLINSPECT-M consortium, we performed two consecutive round-robin studies with full freedom to operate in terms of sample preparation and MS measurements. The six study partners were provided with two clinically relevant sample matrices: plasma and cerebrospinal fluid (CSF). In the first round, each laboratory applied their current best practice protocol for the respective matrix. Based on the achieved results and following a transparent exchange of all lab-specific protocols within the consortium, each laboratory could advance their methods before measuring the same samples in the second acquisition round. Both time points are compared with respect to identifications (IDs), data completeness, and precision, as well as reproducibility. As a result, the individual performances of participating study centers were improved in the second measurement, emphasizing the effect and importance of the expert-driven exchange of best practices for direct practical improvements.
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Affiliation(s)
- Oliver Kardell
- Metabolomics
and Proteomics Core (MPC), Helmholtz Zentrum
München,German Research Center for Environmental Health (GmbH), Munich 80939, Germany
| | - Christine von Toerne
- Metabolomics
and Proteomics Core (MPC), Helmholtz Zentrum
München,German Research Center for Environmental Health (GmbH), Munich 80939, Germany
| | - Juliane Merl-Pham
- Metabolomics
and Proteomics Core (MPC), Helmholtz Zentrum
München,German Research Center for Environmental Health (GmbH), Munich 80939, Germany
| | - Ann-Christine König
- Metabolomics
and Proteomics Core (MPC), Helmholtz Zentrum
München,German Research Center for Environmental Health (GmbH), Munich 80939, Germany
| | - Marcel Blindert
- Metabolomics
and Proteomics Core (MPC), Helmholtz Zentrum
München,German Research Center for Environmental Health (GmbH), Munich 80939, Germany
| | - Teresa K. Barth
- Clinical
Protein Analysis Unit (ClinZfP), Biomedical Center (BMC), Faculty
of Medicine, Ludwig-Maximilians-University
(LMU) Munich, Großhaderner Straße 9, Martinsried 82152, Germany
| | - Julia Mergner
- Bavarian
Center for Biomolecular Mass Spectrometry at Klinikum Rechts der Isar
(BayBioMS@MRI), Technical University of
Munich, Munich 80333, Germany
| | - Christina Ludwig
- Bavarian
Center for Biomolecular Mass Spectrometry (BayBioMS), TUM School of
Life Sciences, Technical University of Munich, Freising 85354, Germany
| | - Johanna Tüshaus
- Chair
of Proteomics and Bioanalytics, Technical
University of Munich, Freising 85354, Germany
| | - Stephan Eckert
- Chair
of Proteomics and Bioanalytics, Technical
University of Munich, Freising 85354, Germany
| | - Stephan A. Müller
- German
Center
for Neurodegenerative Diseases (DZNE) Munich, DZNE, Munich 81377, Germany
- Neuroproteomics,
School of Medicine, Klinikum Rechts der Isar, Technical University of Munich, Munich 81675, Germany
| | - Stephan Breimann
- German
Center
for Neurodegenerative Diseases (DZNE) Munich, DZNE, Munich 81377, Germany
- Neuroproteomics,
School of Medicine, Klinikum Rechts der Isar, Technical University of Munich, Munich 81675, Germany
| | - Pieter Giesbertz
- German
Center
for Neurodegenerative Diseases (DZNE) Munich, DZNE, Munich 81377, Germany
- Neuroproteomics,
School of Medicine, Klinikum Rechts der Isar, Technical University of Munich, Munich 81675, Germany
| | - Alexander M. Bernhardt
- German
Center
for Neurodegenerative Diseases (DZNE) Munich, DZNE, Munich 81377, Germany
- Department
of Neurology, Ludwig-Maximilians-Universität
München, Munich 80539, Germany
| | - Lisa Schweizer
- Department
of Proteomics and Signal Transduction, Max-Planck
Institute of Biochemistry, Martinsried 82152, Germany
| | - Vincent Albrecht
- Department
of Proteomics and Signal Transduction, Max-Planck
Institute of Biochemistry, Martinsried 82152, Germany
| | - Daniel Teupser
- Institute
of Laboratory Medicine, University Hospital,
LMU Munich, Munich 81377, Germany
| | - Axel Imhof
- Clinical
Protein Analysis Unit (ClinZfP), Biomedical Center (BMC), Faculty
of Medicine, Ludwig-Maximilians-University
(LMU) Munich, Großhaderner Straße 9, Martinsried 82152, Germany
| | - Bernhard Kuster
- Bavarian
Center for Biomolecular Mass Spectrometry (BayBioMS), TUM School of
Life Sciences, Technical University of Munich, Freising 85354, Germany
- Chair
of Proteomics and Bioanalytics, Technical
University of Munich, Freising 85354, Germany
| | - Stefan F. Lichtenthaler
- German
Center
for Neurodegenerative Diseases (DZNE) Munich, DZNE, Munich 81377, Germany
- Neuroproteomics,
School of Medicine, Klinikum Rechts der Isar, Technical University of Munich, Munich 81675, Germany
- Munich Cluster for Systems Neurology (SyNergy), Munich 81377, Germany
| | - Matthias Mann
- Department
of Proteomics and Signal Transduction, Max-Planck
Institute of Biochemistry, Martinsried 82152, Germany
| | - Jürgen Cox
- Computational Systems
Biochemistry Research Group, Max-Planck
Institute of Biochemistry, Martinsried 82152, Germany
| | - Stefanie M. Hauck
- Metabolomics
and Proteomics Core (MPC), Helmholtz Zentrum
München,German Research Center for Environmental Health (GmbH), Munich 80939, Germany
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11
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Szyrwiel L, Gille C, Mülleder M, Demichev V, Ralser M. Fast proteomics with dia-PASEF and analytical flow-rate chromatography. Proteomics 2024; 24:e2300100. [PMID: 37287406 DOI: 10.1002/pmic.202300100] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2023] [Revised: 05/22/2023] [Accepted: 05/22/2023] [Indexed: 06/09/2023]
Abstract
Increased throughput in proteomic experiments can improve accessibility of proteomic platforms, reduce costs, and facilitate new approaches in systems biology and biomedical research. Here we propose combination of analytical flow rate chromatography with ion mobility separation of peptide ions, data-independent acquisition, and data analysis with the DIA-NN software suite, to achieve high-quality proteomic experiments from limited sample amounts, at a throughput of up to 400 samples per day. For instance, when benchmarking our workflow using a 500-μL/min flow rate and 3-min chromatographic gradients, we report the quantification of 5211 proteins from 2 μg of a mammalian cell-line standard at high quantitative accuracy and precision. We further used this platform to analyze blood plasma samples from a cohort of COVID-19 inpatients, using a 3-min chromatographic gradient and alternating column regeneration on a dual pump system. The method delivered a comprehensive view of the COVID-19 plasma proteome, allowing classification of the patients according to disease severity and revealing plasma biomarker candidates.
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Affiliation(s)
- Lukasz Szyrwiel
- Department of Biochemistry, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Christoph Gille
- Department of Biochemistry, Charité - Universitätsmedizin Berlin, Berlin, Germany
- Core Facility High-Throughput Mass Spectrometry, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Michael Mülleder
- Core Facility High-Throughput Mass Spectrometry, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Vadim Demichev
- Department of Biochemistry, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Markus Ralser
- Department of Biochemistry, Charité - Universitätsmedizin Berlin, Berlin, Germany
- The Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK
- Max Planck Institute for Molecular Genetics, Berlin, Germany
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12
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Goudswaard LJ, Smith ML, Hughes DA, Taylor R, Lean M, Sattar N, Welsh P, McConnachie A, Blazeby JM, Rogers CA, Suhre K, Zaghlool SB, Hers I, Timpson NJ, Corbin LJ. Using trials of caloric restriction and bariatric surgery to explore the effects of body mass index on the circulating proteome. Sci Rep 2023; 13:21077. [PMID: 38030643 PMCID: PMC10686974 DOI: 10.1038/s41598-023-47030-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2023] [Accepted: 11/08/2023] [Indexed: 12/01/2023] Open
Abstract
Thousands of proteins circulate in the bloodstream; identifying those which associate with weight and intervention-induced weight loss may help explain mechanisms of diseases associated with adiposity. We aimed to identify consistent protein signatures of weight loss across independent studies capturing changes in body mass index (BMI). We analysed proteomic data from studies implementing caloric restriction (Diabetes Remission Clinical trial) and bariatric surgery (By-Band-Sleeve), using SomaLogic and Olink Explore1536 technologies, respectively. Linear mixed models were used to estimate the effect of the interventions on circulating proteins. Twenty-three proteins were altered in a consistent direction after both bariatric surgery and caloric restriction, suggesting that these proteins are modulated by weight change, independent of intervention type. We also integrated Mendelian randomisation (MR) estimates of the effect of BMI on proteins measured by SomaLogic from a UK blood donor cohort as a third line of causal evidence. These MR estimates provided further corroborative evidence for a role of BMI in regulating the levels of six proteins including alcohol dehydrogenase-4, nogo receptor and interleukin-1 receptor antagonist protein. These results indicate the importance of triangulation in interrogating causal relationships; further study into the role of proteins modulated by weight in disease is now warranted.
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Affiliation(s)
- Lucy J Goudswaard
- Population Health Sciences, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK.
- MRC Integrative Epidemiology Unit, Bristol, UK.
- Physiology, Pharmacology & Neuroscience, University of Bristol, Biomedical Sciences Building, University Walk, Bristol, BS8 1TD, UK.
| | - Madeleine L Smith
- Population Health Sciences, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
- MRC Integrative Epidemiology Unit, Bristol, UK
| | - David A Hughes
- Population Health Sciences, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
- MRC Integrative Epidemiology Unit, Bristol, UK
| | - Roy Taylor
- Newcastle Magnetic Resonance Centre, Translational and Clinical Research Institute, Newcastle University, Newcastle Upon Tyne, NE4 5PL, UK
| | - Michael Lean
- Human Nutrition, School of Medicine, Dentistry and Nursing, College of Medical, Veterinary & Life Sciences, University of Glasgow, Glasgow, G31 2ER, UK
| | - Naveed Sattar
- School of Cardiovascular and Medical Science, University of Glasgow, Glasgow, G12 8TA, UK
| | - Paul Welsh
- School of Cardiovascular and Medical Science, University of Glasgow, Glasgow, G12 8TA, UK
| | - Alex McConnachie
- Robertson Centre for Biostatistics, School of Health and Wellbeing, University of Glasgow, Glasgow, G12 8QQ, UK
| | - Jane M Blazeby
- Population Health Sciences, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
| | - Chris A Rogers
- Bristol Medical School, Bristol Trials Centre, University of Bristol, Bristol, BS8 1NU, UK
| | - Karsten Suhre
- Department of Biophysics and Physiology, Weill Cornell Medicine - Qatar, Doha, Qatar
| | - Shaza B Zaghlool
- Department of Biophysics and Physiology, Weill Cornell Medicine - Qatar, Doha, Qatar
| | - Ingeborg Hers
- Physiology, Pharmacology & Neuroscience, University of Bristol, Biomedical Sciences Building, University Walk, Bristol, BS8 1TD, UK
| | - Nicholas J Timpson
- Population Health Sciences, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
- MRC Integrative Epidemiology Unit, Bristol, UK
| | - Laura J Corbin
- Population Health Sciences, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
- MRC Integrative Epidemiology Unit, Bristol, UK
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13
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Kitata RB, Yang JC, Chen YJ. Advances in data-independent acquisition mass spectrometry towards comprehensive digital proteome landscape. MASS SPECTROMETRY REVIEWS 2023; 42:2324-2348. [PMID: 35645145 DOI: 10.1002/mas.21781] [Citation(s) in RCA: 32] [Impact Index Per Article: 32.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/09/2021] [Revised: 12/17/2021] [Accepted: 01/21/2022] [Indexed: 06/15/2023]
Abstract
The data-independent acquisition mass spectrometry (DIA-MS) has rapidly evolved as a powerful alternative for highly reproducible proteome profiling with a unique strength of generating permanent digital maps for retrospective analysis of biological systems. Recent advancements in data analysis software tools for the complex DIA-MS/MS spectra coupled to fast MS scanning speed and high mass accuracy have greatly expanded the sensitivity and coverage of DIA-based proteomics profiling. Here, we review the evolution of the DIA-MS techniques, from earlier proof-of-principle of parallel fragmentation of all-ions or ions in selected m/z range, the sequential window acquisition of all theoretical mass spectra (SWATH-MS) to latest innovations, recent development in computation algorithms for data informatics, and auxiliary tools and advanced instrumentation to enhance the performance of DIA-MS. We further summarize recent applications of DIA-MS and experimentally-derived as well as in silico spectra library resources for large-scale profiling to facilitate biomarker discovery and drug development in human diseases with emphasis on the proteomic profiling coverage. Toward next-generation DIA-MS for clinical proteomics, we outline the challenges in processing multi-dimensional DIA data set and large-scale clinical proteomics, and continuing need in higher profiling coverage and sensitivity.
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Affiliation(s)
| | - Jhih-Ci Yang
- Institute of Chemistry, Academia Sinica, Taipei, Taiwan
- Sustainable Chemical Science and Technology, Taiwan International Graduate Program, Academia Sinica and National Yang Ming Chiao Tung University, Taipei, Taiwan
- Department of Applied Chemistry, National Yang Ming Chiao Tung University, Hsinchu, Taiwan
| | - Yu-Ju Chen
- Institute of Chemistry, Academia Sinica, Taipei, Taiwan
- Sustainable Chemical Science and Technology, Taiwan International Graduate Program, Academia Sinica and National Yang Ming Chiao Tung University, Taipei, Taiwan
- Department of Chemistry, National Taiwan University, Taipei, Taiwan
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14
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Gupta S, Sing JC, Röst HL. Achieving quantitative reproducibility in label-free multisite DIA experiments through multirun alignment. Commun Biol 2023; 6:1101. [PMID: 37903988 PMCID: PMC10616189 DOI: 10.1038/s42003-023-05437-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Accepted: 10/10/2023] [Indexed: 11/01/2023] Open
Abstract
DIA is a mainstream method for quantitative proteomics, but consistent quantification across multiple LC-MS/MS instruments remains a bottleneck in parallelizing data acquisition. One reason for this inconsistency and missing quantification is the retention time shift which current software does not adequately address for runs from multiple sites. We present multirun chromatogram alignment strategies to map peaks across columns, including the traditional reference-based Star method, and two novel approaches: MST and Progressive alignment. These reference-free strategies produce a quantitatively accurate data-matrix, even from heterogeneous multi-column studies. Progressive alignment also generates merged chromatograms from all runs which has not been previously achieved for LC-MS/MS data. First, we demonstrate the effectiveness of multirun alignment strategies on a gold-standard annotated dataset, resulting in a threefold reduction in quantitation error-rate compared to non-aligned DIA results. Subsequently, on a multi-species dataset that DIAlignR effectively controls the quantitative error rate, improves precision in protein measurements, and exhibits conservative peak alignment. We next show that the MST alignment reduces cross-site CV by 50% for highly abundant proteins when applied to a dataset from 11 different LC-MS/MS setups. Finally, the reanalysis of 949 plasma runs with multirun alignment revealed a more than 50% increase in insulin resistance (IR) and respiratory viral infection (RVI) proteins, identifying 11 and 13 proteins respectively, compared to prior analysis without it. The three strategies are implemented in our DIAlignR workflow (>2.3) and can be combined with linear, non-linear, or hybrid pairwise alignment.
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Affiliation(s)
- Shubham Gupta
- Terrence Donnelly Centre for Cellular & Biomolecular Research, University of Toronto, Toronto, ON, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada
| | - Justin C Sing
- Terrence Donnelly Centre for Cellular & Biomolecular Research, University of Toronto, Toronto, ON, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada
| | - Hannes L Röst
- Terrence Donnelly Centre for Cellular & Biomolecular Research, University of Toronto, Toronto, ON, Canada.
- Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada.
- Department of Computer Science, University of Toronto, Toronto, ON, Canada.
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15
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Han Y, Rovella V, Smirnov A, Buonomo OC, Mauriello A, Perretta T, Shi Y, Woodmsith J, Bischof J, Melino G, Candi E, Bernassola F. A BRCA2 germline mutation and high expression of immune checkpoints in a TNBC patient. Cell Death Discov 2023; 9:370. [PMID: 37813891 PMCID: PMC10562433 DOI: 10.1038/s41420-023-01651-3] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2023] [Revised: 08/23/2023] [Accepted: 09/13/2023] [Indexed: 10/11/2023] Open
Abstract
Triple-negative breast cancer (TNBC) is the most aggressive subtype of mammary carcinoma. Here, we describe a case of an 81-year-old female diagnosed with ductal triple negative breast cancer with a germline pathogenic variant in BReast CAncer gene2 (BRCA2). Genetic testing also revealed the presence of four somatic mutations in the ephrin type-A receptor 3 (EphA3), TP53, BRCA1-associated protein (BAP1), and MYB genes. The BRCA2, TP53, and BAP1 gene mutations are highly predictive of a defective homologous recombination repair system and subsequent chromosomal instability in this patient. Coherently, the patient displayed a strong homologous recombination deficiency signature and high tumor mutational burden status, which are generally associated with increased probability of immune neoantigens formation and presentation, and with tumor immunogenicity. Analysis of immune checkpoint revealed high expression of programmed cell death ligand 1 (PD-L1), programmed cell death ligand 2 (PD-L2), programmed death 1 (PD1), and cytotoxic T-lymphocyte-associated protein 4 (CTLA 4), suggesting that the patient might likely benefit from immunotherapies. Altogether, these findings support an unveiled link between BRCA2 inactivation, HR deficiency and increased expression of immune checkpoints in TNBC. This clinical case highlights the importance of screening TNBC patients for genetic mutations and TMB biomarkers in order to predict the potential efficacy of immunotherapy.
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Affiliation(s)
- Yuyi Han
- Department of Experimental Medicine, TOR, University of Rome Tor Vergata, 00133, Rome, Italy
- Department of Ophthalmology, The Affiliated Hospital of Jiangnan University, 214000, Wuxi, China
| | - Valentina Rovella
- Department of Experimental Medicine, TOR, University of Rome Tor Vergata, 00133, Rome, Italy
| | - Artem Smirnov
- Department of Experimental Medicine, TOR, University of Rome Tor Vergata, 00133, Rome, Italy
- Biochemistry Laboratory, Istituto Dermopatico Immacolata (IDI-IRCCS), 00100, Rome, Italy
| | - Oreste Claudio Buonomo
- Department of Experimental Medicine, TOR, University of Rome Tor Vergata, 00133, Rome, Italy
| | - Alessandro Mauriello
- Department of Experimental Medicine, TOR, University of Rome Tor Vergata, 00133, Rome, Italy
| | - Tommaso Perretta
- Department of Diagnostic Imaging and Interventional Radiology, Policlinico Tor Vergata University, Rome, 00133, Italy
| | - Yufang Shi
- The Third Affiliated Hospital of Soochow University, Institutes for Translational Medicine, Soochow University, Suzhou, 215000, China
| | | | - Julia Bischof
- Indivumed GmbH, Falkenried, 88 Building D, 20251, Hamburg, Germany
| | - Gerry Melino
- Department of Experimental Medicine, TOR, University of Rome Tor Vergata, 00133, Rome, Italy.
| | - Eleonora Candi
- Department of Experimental Medicine, TOR, University of Rome Tor Vergata, 00133, Rome, Italy.
- Biochemistry Laboratory, Istituto Dermopatico Immacolata (IDI-IRCCS), 00100, Rome, Italy.
| | - Francesca Bernassola
- Department of Experimental Medicine, TOR, University of Rome Tor Vergata, 00133, Rome, Italy.
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16
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Bennike TB. Advances in proteomics: characterization of the innate immune system after birth and during inflammation. Front Immunol 2023; 14:1254948. [PMID: 37868984 PMCID: PMC10587584 DOI: 10.3389/fimmu.2023.1254948] [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: 07/07/2023] [Accepted: 09/26/2023] [Indexed: 10/24/2023] Open
Abstract
Proteomics is the characterization of the protein composition, the proteome, of a biological sample. It involves the large-scale identification and quantification of proteins, peptides, and post-translational modifications. This review focuses on recent developments in mass spectrometry-based proteomics and provides an overview of available methods for sample preparation to study the innate immune system. Recent advancements in the proteomics workflows, including sample preparation, have significantly improved the sensitivity and proteome coverage of biological samples including the technically difficult blood plasma. Proteomics is often applied in immunology and has been used to characterize the levels of innate immune system components after perturbations such as birth or during chronic inflammatory diseases like rheumatoid arthritis (RA) and inflammatory bowel disease (IBD). In cancers, the tumor microenvironment may generate chronic inflammation and release cytokines to the circulation. In these situations, the innate immune system undergoes profound and long-lasting changes, the large-scale characterization of which may increase our biological understanding and help identify components with translational potential for guiding diagnosis and treatment decisions. With the ongoing technical development, proteomics will likely continue to provide increasing insights into complex biological processes and their implications for health and disease. Integrating proteomics with other omics data and utilizing multi-omics approaches have been demonstrated to give additional valuable insights into biological systems.
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Affiliation(s)
- Tue Bjerg Bennike
- Medical Microbiology and Immunology, Department of Health Science and Technology, Aalborg University, Aalborg, Denmark
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17
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Weckerle J, Mayr CH, Fundel-Clemens K, Lämmle B, Boryn L, Thomas MJ, Bretschneider T, Luippold AH, Huber HJ, Viollet C, Rist W, Veyel D, Ramirez F, Klee S, Kästle M. Transcriptomic and Proteomic Changes Driving Pulmonary Fibrosis Resolution in Young and Old Mice. Am J Respir Cell Mol Biol 2023; 69:422-440. [PMID: 37411041 DOI: 10.1165/rcmb.2023-0012oc] [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: 01/09/2023] [Accepted: 07/06/2023] [Indexed: 07/08/2023] Open
Abstract
Bleomycin-induced pulmonary fibrosis in mice mimics major hallmarks of idiopathic pulmonary fibrosis. Yet in this model, it spontaneously resolves over time. We studied molecular mechanisms of fibrosis resolution and lung repair, focusing on transcriptional and proteomic signatures and the effect of aging. Old mice showed incomplete and delayed lung function recovery 8 weeks after bleomycin instillation. This shift in structural and functional repair in old bleomycin-treated mice was reflected in a temporal shift in gene and protein expression. We reveal gene signatures and signaling pathways that underpin the lung repair process. Importantly, the downregulation of WNT, BMP, and TGFβ antagonists Frzb, Sfrp1, Dkk2, Grem1, Fst, Fstl1, and Inhba correlated with lung function improvement. Those genes constitute a network with functions in stem cell pathways, wound, and pulmonary healing. We suggest that insufficient and delayed downregulation of those antagonists during fibrosis resolution in old mice explains the impaired regenerative outcome. Together, we identified signaling pathway molecules with relevance to lung regeneration that should be tested in-depth experimentally as potential therapeutic targets for pulmonary fibrosis.
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Affiliation(s)
| | | | | | - Bärbel Lämmle
- Global Computational Biology and Digital Sciences, and
| | | | | | - Tom Bretschneider
- Department of Drug Discovery Sciences, Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach an der Riß, Germany; and
| | - Andreas H Luippold
- Department of Drug Discovery Sciences, Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach an der Riß, Germany; and
| | | | | | - Wolfgang Rist
- Department of Drug Discovery Sciences, Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach an der Riß, Germany; and
| | - Daniel Veyel
- Department of Drug Discovery Sciences, Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach an der Riß, Germany; and
| | - Fidel Ramirez
- Global Computational Biology and Digital Sciences, and
| | - Stephan Klee
- Department of Immunology and Respiratory Disease Research
| | - Marc Kästle
- Department of Immunology and Respiratory Disease Research
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18
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Kussmann M. Mass spectrometry as a lens into molecular human nutrition and health. EUROPEAN JOURNAL OF MASS SPECTROMETRY (CHICHESTER, ENGLAND) 2023; 29:370-379. [PMID: 37587732 DOI: 10.1177/14690667231193555] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/18/2023]
Abstract
Mass spectrometry (MS) has developed over the last decades into the most informative and versatile analytical technology in molecular and structural biology (). The platform enables discovery, identification, and characterisation of non-volatile biomolecules, such as proteins, peptides, DNA, RNA, nutrients, metabolites, and lipids at both speed and scale and can elucidate their interactions and effects. The versatility, robustness, and throughput have rendered MS a major research and development platform in molecular human health and biomedical science. More recently, MS has also been established as the central tool for 'Molecular Nutrition', enabling comprehensive and rapid identification and characterisation of macro- and micronutrients, bioactives, and other food compounds. 'Molecular Nutrition' thereby helps understand bioaccessibility, bioavailability, and bioefficacy of macro- and micronutrients and related health effects. Hence, MS provides a lens through which the fate of nutrients can be monitored along digestion via absorption to metabolism. This in turn provides the bioanalytical foundation for 'Personalised Nutrition' or 'Precision Nutrition' in which design and development of diets and nutritional products is tailored towards consumer and patient groups sharing similar genetic and environmental predisposition, health/disease conditions and lifestyles, and/or objectives of performance and wellbeing. The next level of integrated nutrition science is now being built as 'Systems Nutrition' where public and personal health data are correlated with life condition and lifestyle factors, to establish directional relationships between nutrition, lifestyle, environment, and health, eventually translating into science-based public and personal heath recommendations and actions. This account provides a condensed summary of the contributions of MS to a precise, quantitative, and comprehensive nutrition and health science and sketches an outlook on its future role in this fascinating and relevant field.
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Affiliation(s)
- Martin Kussmann
- Abteilung Wissenschaft, Kompetenzzentrum für Ernährung (KErn), Germany
- Kussmann Biotech GmbH, Germany
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19
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Wang J, Xie W, Sun L, Li J, Wu S, Li R, Zhao Y. Establishment and clinical application evaluations of a deep mining strategy of plasma proteomics based on nanomaterial protein coronas. Anal Chim Acta 2023; 1275:341569. [PMID: 37524462 DOI: 10.1016/j.aca.2023.341569] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2023] [Revised: 05/31/2023] [Accepted: 06/27/2023] [Indexed: 08/02/2023]
Abstract
Research on plasma proteomics has received extensive attention, because human plasma is an important sample for disease biomarker research due to its easy clinical accessibility and richness in biological information. Plasma samples contain a large number of leaked proteins from different tissues in the body, immune proteins and communication signal proteins. However, MS signal suppression from high-abundance proteins results in a large number of proteins that are present in low abundance in plasma not being detected by the LC-MS method. This situation makes it more difficult to study neurological diseases, where tissue sampling is difficult and body fluid samples such as plasma or cerebrospinal fluid are both affected by signal suppression. A large number of methods have been developed to deeply mine plasma proteomics information; however, their application limitations remain to some extent. Traditional immuno- or affinity-based depletion, fractionation and subproteome enrichment methods cannot meet the challenges of large clinical cohort applications due to limited time efficiency. In this study, a deep mining strategy of plasma proteomics was established by combing the protein corona formed by deep mining beads (DMB beads, hereafter referred to as magnetic covalent organic frameworks Fe3O4@TpPa-1), DIA-MS detection and the DIA-NN library searching method. By optimizing the enrichment step, mass spectrometry acquisition and data processing, the evaluation results of the deep mining strategy showed the following: depth, the strategy identified and quantified results of 2000+ proteins per plasma sample; stability, more than 87% of the enriched low-abundance proteins had CV < 20%; accuracy, good agreement between measured and theoretical values (1.81/2, 8.68/10, 38.36/50) for the gradient addition of E. coli proteins to a plasma sample; time efficiency, the processing time was reduced from >12h in the traditional method to <5h (incubation 30 min, washing 15 min, reductive/alkylation/digestion/desalting 4 h), and more importantly, 96 samples can be processed simultaneously in combination with the magnetic module of the automated device. The optimal strategy enables greater enrichment of neurological disease-related proteins, including SNCA and BDNF. Finally, the deep mining strategy was applied in a pilot study of multiple system atrophy (MSA) for biomarker discovery. The results showed that a total of 215 proteins were upregulated and 184 proteins were downregulated (p < 0.05) in the MSA group compared with the healthy control group. Eighteen proteins of these differentially expressed proteins were reported to be associated with neurological diseases or expressed specifically in brain tissue, 8 and 4 of which have reference concentrations of μg/L and ng/L, respectively. The alterations of ENPP2 and SLC2A1/Glut1 were reanalyzed by ELISA, further supporting the results of mass spectrometry. In conclusion, the results of the evaluation and application of the deep mining strategy showed promise for clinical research applications.
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Affiliation(s)
- Jianan Wang
- The First Medical Centre, Chinese PLA General Hospital, Beijing, 100853, PR China
| | - Wei Xie
- The First Medical Centre, Chinese PLA General Hospital, Beijing, 100853, PR China; Medical School of Chinese PLA, Beijing, 100853, PR China
| | - Longqin Sun
- Beijing Qinglian Biotech Co., Ltd, Beijing, 100094, PR China
| | - Jingli Li
- Beijing Qinglian Biotech Co., Ltd, Beijing, 100094, PR China
| | - Songfeng Wu
- Beijing Qinglian Biotech Co., Ltd, Beijing, 100094, PR China
| | - Ruibing Li
- The First Medical Centre, Chinese PLA General Hospital, Beijing, 100853, PR China.
| | - Yan Zhao
- Beijing Qinglian Biotech Co., Ltd, Beijing, 100094, PR China.
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20
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Cai X, Xue Z, Zeng FF, Tang J, Yue L, Wang B, Ge W, Xie Y, Miao Z, Gou W, Fu Y, Li S, Gao J, Shuai M, Zhang K, Xu F, Tian Y, Xiang N, Zhou Y, Shan PF, Zhu Y, Chen YM, Zheng JS, Guo T. Population serum proteomics uncovers a prognostic protein classifier for metabolic syndrome. Cell Rep Med 2023; 4:101172. [PMID: 37652016 PMCID: PMC10518601 DOI: 10.1016/j.xcrm.2023.101172] [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: 10/12/2022] [Revised: 07/31/2023] [Accepted: 08/03/2023] [Indexed: 09/02/2023]
Abstract
Metabolic syndrome (MetS) is a complex metabolic disorder with a global prevalence of 20%-25%. Early identification and intervention would help minimize the global burden on healthcare systems. Here, we measured over 400 proteins from ∼20,000 proteomes using data-independent acquisition mass spectrometry for 7,890 serum samples from a longitudinal cohort of 3,840 participants with two follow-up time points over 10 years. We then built a machine-learning model for predicting the risk of developing MetS within 10 years. Our model, composed of 11 proteins and the age of the individuals, achieved an area under the curve of 0.774 in the validation cohort (n = 242). Using linear mixed models, we found that apolipoproteins, immune-related proteins, and coagulation-related proteins best correlated with MetS development. This population-scale proteomics study broadens our understanding of MetS and may guide the development of prevention and targeted therapies for MetS.
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Affiliation(s)
- Xue Cai
- Center for Intelligent Proteomics, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang 310024, China
| | - Zhangzhi Xue
- Center for Intelligent Proteomics, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang 310024, China
| | - Fang-Fang Zeng
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 510080, China
| | - Jun Tang
- Center for Intelligent Proteomics, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang 310024, China; School of Life Sciences, Westlake University, Hangzhou, Zhejiang 310024, China; Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, Zhejiang 310024, China
| | - Liang Yue
- Center for Intelligent Proteomics, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang 310024, China; School of Life Sciences, Westlake University, Hangzhou, Zhejiang 310024, China; Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, Zhejiang 310024, China; Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, Zhejiang 310024, China
| | - Bo Wang
- Westlake Omics (Hangzhou) Biotechnology Co., Ltd., No. 1 Yunmeng Road, Cloud Town, Xihu District, Hangzhou, Zhejiang 310024, China
| | - Weigang Ge
- Westlake Omics (Hangzhou) Biotechnology Co., Ltd., No. 1 Yunmeng Road, Cloud Town, Xihu District, Hangzhou, Zhejiang 310024, China
| | - Yuting Xie
- Center for Intelligent Proteomics, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang 310024, China; School of Life Sciences, Westlake University, Hangzhou, Zhejiang 310024, China; Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, Zhejiang 310024, China; Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, Zhejiang 310024, China
| | - Zelei Miao
- Center for Intelligent Proteomics, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang 310024, China; School of Life Sciences, Westlake University, Hangzhou, Zhejiang 310024, China; Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, Zhejiang 310024, China
| | - Wanglong Gou
- Center for Intelligent Proteomics, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang 310024, China; School of Life Sciences, Westlake University, Hangzhou, Zhejiang 310024, China; Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, Zhejiang 310024, China
| | - Yuanqing Fu
- Center for Intelligent Proteomics, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang 310024, China; School of Life Sciences, Westlake University, Hangzhou, Zhejiang 310024, China; Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, Zhejiang 310024, China
| | - Sainan Li
- Center for Intelligent Proteomics, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang 310024, China; School of Life Sciences, Westlake University, Hangzhou, Zhejiang 310024, China; Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, Zhejiang 310024, China; Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, Zhejiang 310024, China
| | - Jinlong Gao
- Center for Intelligent Proteomics, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang 310024, China; School of Life Sciences, Westlake University, Hangzhou, Zhejiang 310024, China; Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, Zhejiang 310024, China; Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, Zhejiang 310024, China
| | - Menglei Shuai
- Center for Intelligent Proteomics, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang 310024, China; School of Life Sciences, Westlake University, Hangzhou, Zhejiang 310024, China; Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, Zhejiang 310024, China
| | - Ke Zhang
- Center for Intelligent Proteomics, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang 310024, China; School of Life Sciences, Westlake University, Hangzhou, Zhejiang 310024, China; Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, Zhejiang 310024, China
| | - Fengzhe Xu
- Center for Intelligent Proteomics, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang 310024, China; School of Life Sciences, Westlake University, Hangzhou, Zhejiang 310024, China; Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, Zhejiang 310024, China
| | - Yunyi Tian
- Center for Intelligent Proteomics, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang 310024, China; School of Life Sciences, Westlake University, Hangzhou, Zhejiang 310024, China; Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, Zhejiang 310024, China
| | - Nan Xiang
- Westlake Omics (Hangzhou) Biotechnology Co., Ltd., No. 1 Yunmeng Road, Cloud Town, Xihu District, Hangzhou, Zhejiang 310024, China
| | - Yan Zhou
- Center for Intelligent Proteomics, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang 310024, China; School of Life Sciences, Westlake University, Hangzhou, Zhejiang 310024, China; Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, Zhejiang 310024, China; Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, Zhejiang 310024, China
| | - Peng-Fei Shan
- Department of Endocrinology, the Second Affiliated Hospital of Zhejiang University School of Medicine, 88 Jiefang Road, Hangzhou, Zhejiang 310009, China
| | - Yi Zhu
- Center for Intelligent Proteomics, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang 310024, China; School of Life Sciences, Westlake University, Hangzhou, Zhejiang 310024, China; Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, Zhejiang 310024, China; Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, Zhejiang 310024, China.
| | - Yu-Ming Chen
- Guangdong Provincial Key Laboratory of Food, Nutrition and Health, Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China.
| | - Ju-Sheng Zheng
- Center for Intelligent Proteomics, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang 310024, China; School of Life Sciences, Westlake University, Hangzhou, Zhejiang 310024, China; Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, Zhejiang 310024, China.
| | - Tiannan Guo
- Center for Intelligent Proteomics, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang 310024, China; School of Life Sciences, Westlake University, Hangzhou, Zhejiang 310024, China; Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, Zhejiang 310024, China; Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, Zhejiang 310024, China.
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21
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Girish V, Lakhani AA, Thompson SL, Scaduto CM, Brown LM, Hagenson RA, Sausville EL, Mendelson BE, Kandikuppa PK, Lukow DA, Yuan ML, Stevens EC, Lee SN, Schukken KM, Akalu SM, Vasudevan A, Zou C, Salovska B, Li W, Smith JC, Taylor AM, Martienssen RA, Liu Y, Sun R, Sheltzer JM. Oncogene-like addiction to aneuploidy in human cancers. Science 2023; 381:eadg4521. [PMID: 37410869 PMCID: PMC10753973 DOI: 10.1126/science.adg4521] [Citation(s) in RCA: 18] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2023] [Accepted: 06/27/2023] [Indexed: 07/08/2023]
Abstract
Most cancers exhibit aneuploidy, but its functional significance in tumor development is controversial. Here, we describe ReDACT (Restoring Disomy in Aneuploid cells using CRISPR Targeting), a set of chromosome engineering tools that allow us to eliminate specific aneuploidies from cancer genomes. Using ReDACT, we created a panel of isogenic cells that have or lack common aneuploidies, and we demonstrate that trisomy of chromosome 1q is required for malignant growth in cancers harboring this alteration. Mechanistically, gaining chromosome 1q increases the expression of MDM4 and suppresses p53 signaling, and we show that TP53 mutations are mutually exclusive with 1q aneuploidy in human cancers. Thus, tumor cells can be dependent on specific aneuploidies, raising the possibility that these "aneuploidy addictions" could be targeted as a therapeutic strategy.
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Affiliation(s)
- Vishruth Girish
- Yale University School of Medicine, New Haven, CT 06511
- Johns Hopkins University School of Medicine, Baltimore, MD 21205
| | | | | | | | | | | | | | | | | | | | - Monet Lou Yuan
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724
| | | | - Sophia N. Lee
- Yale University School of Medicine, New Haven, CT 06511
| | | | | | | | - Charles Zou
- Yale University School of Medicine, New Haven, CT 06511
| | | | - Wenxue Li
- Yale University School of Medicine, New Haven, CT 06511
| | - Joan C. Smith
- Yale University School of Medicine, New Haven, CT 06511
| | | | - Robert A. Martienssen
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724
- Howard Hughes Medical Institute, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724
| | - Yansheng Liu
- Yale University School of Medicine, New Haven, CT 06511
| | - Ruping Sun
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN 55455
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22
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Vernardis SI, Demichev V, Lemke O, Grüning NM, Messner C, White M, Pietzner M, Peluso A, Collet TH, Henning E, Gille C, Campbell A, Hayward C, Porteous DJ, Marioni RE, Mülleder M, Zelezniak A, Wareham NJ, Langenberg C, Farooqi IS, Ralser M. The Impact of Acute Nutritional Interventions on the Plasma Proteome. J Clin Endocrinol Metab 2023; 108:2087-2098. [PMID: 36658456 PMCID: PMC10348471 DOI: 10.1210/clinem/dgad031] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/27/2022] [Revised: 01/14/2023] [Accepted: 01/17/2023] [Indexed: 01/21/2023]
Abstract
CONTEXT Humans respond profoundly to changes in diet, while nutrition and environment have a great impact on population health. It is therefore important to deeply characterize the human nutritional responses. OBJECTIVE Endocrine parameters and the metabolome of human plasma are rapidly responding to acute nutritional interventions such as caloric restriction or a glucose challenge. It is less well understood whether the plasma proteome would be equally dynamic, and whether it could be a source of corresponding biomarkers. METHODS We used high-throughput mass spectrometry to determine changes in the plasma proteome of i) 10 healthy, young, male individuals in response to 2 days of acute caloric restriction followed by refeeding; ii) 200 individuals of the Ely epidemiological study before and after a glucose tolerance test at 4 time points (0, 30, 60, 120 minutes); and iii) 200 random individuals from the Generation Scotland study. We compared the proteomic changes detected with metabolome data and endocrine parameters. RESULTS Both caloric restriction and the glucose challenge substantially impacted the plasma proteome. Proteins responded across individuals or in an individual-specific manner. We identified nutrient-responsive plasma proteins that correlate with changes in the metabolome, as well as with endocrine parameters. In particular, our study highlights the role of apolipoprotein C1 (APOC1), a small, understudied apolipoprotein that was affected by caloric restriction and dominated the response to glucose consumption and differed in abundance between individuals with and without type 2 diabetes. CONCLUSION Our study identifies APOC1 as a dominant nutritional responder in humans and highlights the interdependency of acute nutritional response proteins and the endocrine system.
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Affiliation(s)
- Spyros I Vernardis
- Molecular Biology of Metabolism Laboratory, The Francis Crick Institute, London, NW1 1HT, UK
| | - Vadim Demichev
- Department of Biochemistry, Charité—Universitätsmedizin Berlin, 10117 Berlin, Germany
| | - Oliver Lemke
- Department of Biochemistry, Charité—Universitätsmedizin Berlin, 10117 Berlin, Germany
| | - Nana-Maria Grüning
- Department of Biochemistry, Charité—Universitätsmedizin Berlin, 10117 Berlin, Germany
| | - Christoph Messner
- Molecular Biology of Metabolism Laboratory, The Francis Crick Institute, London, NW1 1HT, UK
| | - Matt White
- Molecular Biology of Metabolism Laboratory, The Francis Crick Institute, London, NW1 1HT, UK
| | - Maik Pietzner
- MRC Epidemiology Unit, University of Cambridge, Cambridge, CB2 0SL, UK
- Computational Medicine, Berlin Institute of Health at Charité—Universitätsmedizin Berlin, 10117 Berlin, Germany
| | - Alina Peluso
- Molecular Biology of Metabolism Laboratory, The Francis Crick Institute, London, NW1 1HT, UK
| | - Tinh-Hai Collet
- Metabolic Research Laboratories and National Institute for Health Research Cambridge Biomedical Research Centre, Wellcome-Medical Research Council Institute of Metabolic Science, Addenbrooke's Hospital, University of Cambridge, Cambridge, CB2 0QQ, UK
- Service of Endocrinology, Diabetology, Nutrition and Therapeutic Education, Department of Medicine, Geneva University Hospitals, 1211 Geneva, Switzerland
| | - Elana Henning
- Metabolic Research Laboratories and National Institute for Health Research Cambridge Biomedical Research Centre, Wellcome-Medical Research Council Institute of Metabolic Science, Addenbrooke's Hospital, University of Cambridge, Cambridge, CB2 0QQ, UK
| | - Christoph Gille
- Department of Biochemistry, Charité—Universitätsmedizin Berlin, 10117 Berlin, Germany
| | - Archie Campbell
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Caroline Hayward
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh EH4 2XU, UK
| | - David J Porteous
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Riccardo E Marioni
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Michael Mülleder
- Core Facility High Throughput Mass Spectrometry, Charité—Universitätsmedizin Berlin, 10117 Berlin, Germany
| | - Aleksej Zelezniak
- Molecular Biology of Metabolism Laboratory, The Francis Crick Institute, London, NW1 1HT, UK
- Department of Biology and Biological Engineering, Chalmers University of Technology, SE-412 96, Gothenburg, Sweden
- Institute of Biotechnology, Life Sciences Center, Vilnius University, Vilnius SE-412 96, Lithuania
- Randall Centre for Cell & Molecular Biophysics, King's College London, New Hunt's House, Guy's Campus, SE1 1UL London, UK
| | | | - Claudia Langenberg
- MRC Epidemiology Unit, University of Cambridge, Cambridge, CB2 0SL, UK
- Computational Medicine, Berlin Institute of Health at Charité—Universitätsmedizin Berlin, 10117 Berlin, Germany
- Precision Healthcare University Research Institute, Queen Mary University of London, London, E1 1HH, UK
| | - I Sadaf Farooqi
- Metabolic Research Laboratories and National Institute for Health Research Cambridge Biomedical Research Centre, Wellcome-Medical Research Council Institute of Metabolic Science, Addenbrooke's Hospital, University of Cambridge, Cambridge, CB2 0QQ, UK
| | - Markus Ralser
- Molecular Biology of Metabolism Laboratory, The Francis Crick Institute, London, NW1 1HT, UK
- Department of Biochemistry, Charité—Universitätsmedizin Berlin, 10117 Berlin, Germany
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23
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Midha MK, Kapil C, Maes M, Baxter DH, Morrone SR, Prokop TJ, Moritz RL. Vacuum Insulated Probe Heated Electrospray Ionization Source Enhances Microflow Rate Chromatography Signals in the Bruker timsTOF Mass Spectrometer. J Proteome Res 2023; 22:2525-2537. [PMID: 37294184 PMCID: PMC11060334 DOI: 10.1021/acs.jproteome.3c00305] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
By far the largest contribution to ion detectability in liquid chromatography-driven mass spectrometry-based proteomics is the efficient generation of peptide molecular ions by the electrospray source. To maximize the transfer of peptides from the liquid to gaseous phase and allow molecular ions to enter the mass spectrometer at microspray flow rates, an efficient electrospray process is required. Here we describe the superior performance of newly design vacuum insulated probe heated electrospray ionization (VIP-HESI) source coupled to a Bruker timsTOF PRO mass spectrometer operated in microspray mode. VIP-HESI significantly improves chromatography signals in comparison to electrospray ionization (ESI) and nanospray ionization using the captivespray (CS) source and provides increased protein detection with higher quantitative precision, enhancing reproducibility of sample injection amounts. Protein quantitation of human K562 lymphoblast samples displayed excellent chromatographic retention time reproducibility (<10% coefficient of variation (CV)) with no signal degradation over extended periods of time, and a mouse plasma proteome analysis identified 12% more plasma protein groups allowing large-scale analysis to proceed with confidence (1,267 proteins at 0.4% CV). We show that the Slice-PASEF VIP-HESI mode is sensitive in identifying low amounts of peptide without losing quantitative precision. We demonstrate that VIP-HESI coupled with microflow rate chromatography achieves a higher depth of coverage and run-to-run reproducibility for a broad range of proteomic applications. Data and spectral libraries are available via ProteomeXchange (PXD040497).
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Affiliation(s)
- Mukul K Midha
- Institute for Systems Biology, 401 Terry Avenue N, Seattle, Washington 98109, United States
| | - Charu Kapil
- Institute for Systems Biology, 401 Terry Avenue N, Seattle, Washington 98109, United States
| | - Michal Maes
- Institute for Systems Biology, 401 Terry Avenue N, Seattle, Washington 98109, United States
| | - David H Baxter
- Institute for Systems Biology, 401 Terry Avenue N, Seattle, Washington 98109, United States
| | - Seamus R Morrone
- Institute for Systems Biology, 401 Terry Avenue N, Seattle, Washington 98109, United States
| | - Timothy J Prokop
- Institute for Systems Biology, 401 Terry Avenue N, Seattle, Washington 98109, United States
| | - Robert L Moritz
- Institute for Systems Biology, 401 Terry Avenue N, Seattle, Washington 98109, United States
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24
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Kim SS, Shin H, Ahn KG, Park YM, Kwon MC, Lim JM, Oh EK, Kim Y, Han SM, Noh DY. Quantifiable peptide library bridges the gap for proteomics based biomarker discovery and validation on breast cancer. Sci Rep 2023; 13:8991. [PMID: 37268731 DOI: 10.1038/s41598-023-36159-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2023] [Accepted: 05/30/2023] [Indexed: 06/04/2023] Open
Abstract
Mass spectrometry (MS) based proteomics is widely used for biomarker discovery. However, often, most biomarker candidates from discovery are discarded during the validation processes. Such discrepancies between biomarker discovery and validation are caused by several factors, mainly due to the differences in analytical methodology and experimental conditions. Here, we generated a peptide library which allows discovery of biomarkers in the equal settings as the validation process, thereby making the transition from discovery to validation more robust and efficient. The peptide library initiated with a list of 3393 proteins detectable in the blood from public databases. For each protein, surrogate peptides favorable for detection in mass spectrometry was selected and synthesized. A total of 4683 synthesized peptides were spiked into neat serum and plasma samples to check their quantifiability in a 10 min liquid chromatography-MS/MS run time. This led to the PepQuant library, which is composed of 852 quantifiable peptides that cover 452 human blood proteins. Using the PepQuant library, we discovered 30 candidate biomarkers for breast cancer. Among the 30 candidates, nine biomarkers, FN1, VWF, PRG4, MMP9, CLU, PRDX6, PPBP, APOC1, and CHL1 were validated. By combining the quantification values of these markers, we generated a machine learning model predicting breast cancer, showing an average area under the curve of 0.9105 for the receiver operating characteristic curve.
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Affiliation(s)
- Sung-Soo Kim
- Manufacturing and Technology Division, Bertis Inc., Hungdeok 1-Ro, Giheung-Gu, Yongin-Si, Gyeonggi-Do, 16954, Republic of Korea
- Bio Convergence Research Institute, Bertis Inc., Heungdeok 1-Ro, Giheung-Gu, Yongin-Si, Gyeonggi-Do, 16954, Republic of Korea
| | - HyeonSeok Shin
- Bio Convergence Research Institute, Bertis Inc., Heungdeok 1-Ro, Giheung-Gu, Yongin-Si, Gyeonggi-Do, 16954, Republic of Korea
| | - Kyung-Geun Ahn
- Manufacturing and Technology Division, Bertis Inc., Hungdeok 1-Ro, Giheung-Gu, Yongin-Si, Gyeonggi-Do, 16954, Republic of Korea
| | - Young-Min Park
- Manufacturing and Technology Division, Bertis Inc., Hungdeok 1-Ro, Giheung-Gu, Yongin-Si, Gyeonggi-Do, 16954, Republic of Korea
| | - Min-Chul Kwon
- Manufacturing and Technology Division, Bertis Inc., Hungdeok 1-Ro, Giheung-Gu, Yongin-Si, Gyeonggi-Do, 16954, Republic of Korea
| | - Jae-Min Lim
- Manufacturing and Technology Division, Bertis Inc., Hungdeok 1-Ro, Giheung-Gu, Yongin-Si, Gyeonggi-Do, 16954, Republic of Korea
| | - Eun-Kyung Oh
- Manufacturing and Technology Division, Bertis Inc., Hungdeok 1-Ro, Giheung-Gu, Yongin-Si, Gyeonggi-Do, 16954, Republic of Korea
| | - Yumi Kim
- Department of Surgery, CHA Gangnam Medical Center, CHA University School of Medicine, 566, Nonhyeon-ro, Gangnam-gu, Seoul, 06135, Republic of Korea
| | - Seung-Man Han
- Bertis Inc., 172, Dolma-Ro, Bundang-Gu, Seongnam-Si, Gyeonggi-Do, 13605, Republic of Korea
| | - Dong-Young Noh
- Department of Surgery, CHA Gangnam Medical Center, CHA University School of Medicine, 566, Nonhyeon-ro, Gangnam-gu, Seoul, 06135, Republic of Korea.
- Bertis Inc., 172, Dolma-Ro, Bundang-Gu, Seongnam-Si, Gyeonggi-Do, 13605, Republic of Korea.
- Seoul National University College of Medicine, 103 Daehak-Ro, Seoul, 03080, Republic of Korea.
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25
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O'Rourke MB, Januszewski AS, Sullivan DR, Lengyel I, Stewart AJ, Arya S, Ma RC, Galande S, Hardikar AA, Joglekar MV, Keech AC, Jenkins AJ, Molloy MP. Optimised plasma sample preparation and LC-MS analysis to support large-scale proteomic analysis of clinical trial specimens: Application to the Fenofibrate Intervention and Event Lowering in Diabetes (FIELD) trial. Proteomics Clin Appl 2023; 17:e2200106. [PMID: 36891577 PMCID: PMC10909541 DOI: 10.1002/prca.202200106] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2022] [Revised: 02/10/2023] [Accepted: 02/28/2023] [Indexed: 03/10/2023]
Abstract
PURPOSE Robust, affordable plasma proteomic biomarker workflows are needed for large-scale clinical studies. We evaluated aspects of sample preparation to allow liquid chromatography-mass spectrometry (LC-MS) analysis of more than 1500 samples from the Fenofibrate Intervention and Event Lowering in Diabetes (FIELD) trial of adults with type 2 diabetes. METHODS Using LC-MS with data-independent acquisition we evaluated four variables: plasma protein depletion, EDTA or citrated anti-coagulant blood collection tubes, plasma lipid depletion strategies and plasma freeze-thaw cycles. Optimised methods were applied in a pilot study of FIELD participants. RESULTS LC-MS of undepleted plasma conducted over a 45 min gradient yielded 172 proteins after excluding immunoglobulin isoforms. Cibachrome-blue-based depletion yielded additional proteins but with cost and time expenses, while immunodepleting albumin and IgG provided few additional identifications. Only minor variations were associated with blood collection tube type, delipidation methods and freeze-thaw cycles. From 65 batches involving over 1500 injections, the median intra-batch quantitative differences in the top 100 proteins of the plasma external standard were less than 2%. Fenofibrate altered seven plasma proteins. CONCLUSIONS AND CLINICAL RELEVANCE A robust plasma handling and LC-MS proteomics workflow for abundant plasma proteins has been developed for large-scale biomarker studies that balance proteomic depth with time and resource costs.
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Affiliation(s)
- Matthew B. O'Rourke
- Bowel Cancer & Biomarker LabSchool of Medical SciencesFaculty of Medicine and HealthThe University of SydneySydneyAustralia
- Centre for InflammationCentenary InstituteSydneyAustralia
- School of Life SciencesFaculty of ScienceUniversity of Technology SydneySydneyAustralia
| | - Andrzej S. Januszewski
- NHMRC Clinical Trials CentreFaculty of Medicine and HealthThe University of SydneySydneyAustralia
| | - David R. Sullivan
- NHMRC Clinical Trials CentreFaculty of Medicine and HealthThe University of SydneySydneyAustralia
- Department of Chemical PathologyRoyal Prince Alfred HospitalNSW Health PathologyAustralia
| | - Imre Lengyel
- Wellcome‐Wolfson Institute for Experimental MedicineSchool of MedicineDentistry and Biomedical ScienceQueen's University BelfastBelfastBelfastUK
| | | | - Swati Arya
- School of MedicineUniversity of St AndrewsSt AndrewsFifeUK
| | - Ronald C. Ma
- Department of Medicine and TherapeuticsThe Chinese University of Hong KongHong KongChina
| | | | - Anandwardhan A. Hardikar
- NHMRC Clinical Trials CentreFaculty of Medicine and HealthThe University of SydneySydneyAustralia
- Present address:
Diabetes and Islet Biology groupSchool of MedicineWestern Sydney UniversityCampbelltownAustralia
| | - Mugdha V. Joglekar
- NHMRC Clinical Trials CentreFaculty of Medicine and HealthThe University of SydneySydneyAustralia
- Present address:
Diabetes and Islet Biology groupSchool of MedicineWestern Sydney UniversityCampbelltownAustralia
| | - Anthony C. Keech
- NHMRC Clinical Trials CentreFaculty of Medicine and HealthThe University of SydneySydneyAustralia
| | - Alicia J. Jenkins
- NHMRC Clinical Trials CentreFaculty of Medicine and HealthThe University of SydneySydneyAustralia
- Baker Heart and Diabetes InstituteMelbourneAustralia
| | - Mark P. Molloy
- Bowel Cancer & Biomarker LabSchool of Medical SciencesFaculty of Medicine and HealthThe University of SydneySydneyAustralia
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26
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Di Y, Li W, Salovska B, Ba Q, Hu Z, Wang S, Liu Y. A basic phosphoproteomic-DIA workflow integrating precise quantification of phosphosites in systems biology. BIOPHYSICS REPORTS 2023; 9:82-98. [PMID: 37753060 PMCID: PMC10518521 DOI: 10.52601/bpr.2023.230007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2023] [Accepted: 04/28/2023] [Indexed: 09/28/2023] Open
Abstract
Phosphorylation is one of the most important post-translational modifications (PTMs) of proteins, governing critical protein functions. Most human proteins have been shown to undergo phosphorylation, and phosphoproteomic studies have been widely applied due to recent advancements in high-resolution mass spectrometry technology. Although the experimental workflow for phosphoproteomics has been well-established, it would be useful to optimize and summarize a detailed, feasible protocol that combines phosphoproteomics and data-independent acquisition (DIA), along with follow-up data analysis procedures due to the recent instrumental and bioinformatic advances in measuring and understanding tens of thousands of site-specific phosphorylation events in a single experiment. Here, we describe an optimized Phos-DIA protocol, from sample preparation to bioinformatic analysis, along with practical considerations and experimental configurations for each step. The protocol is designed to be robust and applicable for both small-scale phosphoproteomic analysis and large-scale quantification of hundreds of samples for studies in systems biology and systems medicine.
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Affiliation(s)
- Yi Di
- Cancer Biology Institute, Yale University School of Medicine, West Haven, CT 06516, USA
| | - Wenxue Li
- Cancer Biology Institute, Yale University School of Medicine, West Haven, CT 06516, USA
| | - Barbora Salovska
- Cancer Biology Institute, Yale University School of Medicine, West Haven, CT 06516, USA
| | - Qian Ba
- Cancer Biology Institute, Yale University School of Medicine, West Haven, CT 06516, USA
- Current address: Laboratory Center, Shanghai Municipal Hospital of Traditional Chinese Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai 200071, China
| | - Zhenyi Hu
- Cancer Biology Institute, Yale University School of Medicine, West Haven, CT 06516, USA
| | - Shisheng Wang
- Department of Pulmonary and Critical Care Medicine, and Proteomics-Metabolomics Analysis Platform, West China Hospital, Sichuan University, Chengdu 610041, China
| | - Yansheng Liu
- Cancer Biology Institute, Yale University School of Medicine, West Haven, CT 06516, USA
- Department of Pharmacology, Yale University School of Medicine, New Haven, CT 06510, USA
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27
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Messner CB, Demichev V, Muenzner J, Aulakh SK, Barthel N, Röhl A, Herrera-Domínguez L, Egger AS, Kamrad S, Hou J, Tan G, Lemke O, Calvani E, Szyrwiel L, Mülleder M, Lilley KS, Boone C, Kustatscher G, Ralser M. The proteomic landscape of genome-wide genetic perturbations. Cell 2023; 186:2018-2034.e21. [PMID: 37080200 PMCID: PMC7615649 DOI: 10.1016/j.cell.2023.03.026] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2022] [Revised: 01/20/2023] [Accepted: 03/21/2023] [Indexed: 04/22/2023]
Abstract
Functional genomic strategies have become fundamental for annotating gene function and regulatory networks. Here, we combined functional genomics with proteomics by quantifying protein abundances in a genome-scale knockout library in Saccharomyces cerevisiae, using data-independent acquisition mass spectrometry. We find that global protein expression is driven by a complex interplay of (1) general biological properties, including translation rate, protein turnover, the formation of protein complexes, growth rate, and genome architecture, followed by (2) functional properties, such as the connectivity of a protein in genetic, metabolic, and physical interaction networks. Moreover, we show that functional proteomics complements current gene annotation strategies through the assessment of proteome profile similarity, protein covariation, and reverse proteome profiling. Thus, our study reveals principles that govern protein expression and provides a genome-spanning resource for functional annotation.
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Affiliation(s)
- Christoph B Messner
- The Francis Crick Institute, Molecular Biology of Metabolism Laboratory, London NW1 1AT, UK; Precision Proteomics Center, Swiss Institute of Allergy and Asthma Research (SIAF), University of Zurich, 7265 Davos, Switzerland
| | - Vadim Demichev
- The Francis Crick Institute, Molecular Biology of Metabolism Laboratory, London NW1 1AT, UK; Charité Universitätsmedizin Berlin, Department of Biochemistry, 10117 Berlin, Germany; Department of Biochemistry, Cambridge Centre for Proteomics, University of Cambridge, Cambridge CB2 1QW, UK
| | - Julia Muenzner
- Charité Universitätsmedizin Berlin, Department of Biochemistry, 10117 Berlin, Germany
| | - Simran K Aulakh
- The Francis Crick Institute, Molecular Biology of Metabolism Laboratory, London NW1 1AT, UK
| | - Natalie Barthel
- Charité Universitätsmedizin Berlin, Department of Biochemistry, 10117 Berlin, Germany
| | - Annika Röhl
- Charité Universitätsmedizin Berlin, Department of Biochemistry, 10117 Berlin, Germany
| | | | - Anna-Sophia Egger
- The Francis Crick Institute, Molecular Biology of Metabolism Laboratory, London NW1 1AT, UK
| | - Stephan Kamrad
- The Francis Crick Institute, Molecular Biology of Metabolism Laboratory, London NW1 1AT, UK
| | - Jing Hou
- The Donnelly Centre, University of Toronto, Toronto, ON M5S3E1, Canada
| | - Guihong Tan
- The Donnelly Centre, University of Toronto, Toronto, ON M5S3E1, Canada
| | - Oliver Lemke
- Charité Universitätsmedizin Berlin, Department of Biochemistry, 10117 Berlin, Germany
| | - Enrica Calvani
- The Francis Crick Institute, Molecular Biology of Metabolism Laboratory, London NW1 1AT, UK
| | - Lukasz Szyrwiel
- The Francis Crick Institute, Molecular Biology of Metabolism Laboratory, London NW1 1AT, UK; Charité Universitätsmedizin Berlin, Department of Biochemistry, 10117 Berlin, Germany
| | - Michael Mülleder
- Charité Universitätsmedizin, Core Facility - High Throughput Mass Spectrometry, 10117 Berlin, Germany
| | - Kathryn S Lilley
- Department of Biochemistry, Cambridge Centre for Proteomics, University of Cambridge, Cambridge CB2 1QW, UK
| | - Charles Boone
- Department of Molecular Genetics, University of Toronto, Toronto, ON M5S3E1, Canada; The Donnelly Centre, University of Toronto, Toronto, ON M5S3E1, Canada; RIKEN Center for Sustainable Resource Science, Wako, 351-0198 Saitama, Japan
| | - Georg Kustatscher
- Wellcome Centre for Cell Biology, University of Edinburgh, Max Born Crescent, Edinburgh EH9 3BF, Scotland, UK.
| | - Markus Ralser
- The Francis Crick Institute, Molecular Biology of Metabolism Laboratory, London NW1 1AT, UK; Charité Universitätsmedizin Berlin, Department of Biochemistry, 10117 Berlin, Germany; The Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford OX3 7BN, UK; Max Planck Institute for Molecular Genetics, 14195 Berlin, Germany.
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28
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Messner CB, Demichev V, Wang Z, Hartl J, Kustatscher G, Mülleder M, Ralser M. Mass spectrometry-based high-throughput proteomics and its role in biomedical studies and systems biology. Proteomics 2023; 23:e2200013. [PMID: 36349817 DOI: 10.1002/pmic.202200013] [Citation(s) in RCA: 18] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2022] [Revised: 10/13/2022] [Accepted: 10/13/2022] [Indexed: 11/11/2022]
Abstract
There are multiple reasons why the next generation of biological and medical studies require increasing numbers of samples. Biological systems are dynamic, and the effect of a perturbation depends on the genetic background and environment. As a consequence, many conditions need to be considered to reach generalizable conclusions. Moreover, human population and clinical studies only reach sufficient statistical power if conducted at scale and with precise measurement methods. Finally, many proteins remain without sufficient functional annotations, because they have not been systematically studied under a broad range of conditions. In this review, we discuss the latest technical developments in mass spectrometry (MS)-based proteomics that facilitate large-scale studies by fast and efficient chromatography, fast scanning mass spectrometers, data-independent acquisition (DIA), and new software. We further highlight recent studies which demonstrate how high-throughput (HT) proteomics can be applied to capture biological diversity, to annotate gene functions or to generate predictive and prognostic models for human diseases.
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Affiliation(s)
- Christoph B Messner
- Precision Proteomics Center, Swiss Institute of Allergy and Asthma Research (SIAF), University of Zurich, Davos, Switzerland
| | - Vadim Demichev
- Institute of Biochemistry, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Ziyue Wang
- Institute of Biochemistry, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Johannes Hartl
- Institute of Biochemistry, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Georg Kustatscher
- Wellcome Centre for Cell Biology, University of Edinburgh, Max Born Crescent, Edinburgh, Scotland, UK
| | - Michael Mülleder
- Core Facility High Throughput Mass Spectrometry, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Markus Ralser
- Institute of Biochemistry, Charité - Universitätsmedizin Berlin, Berlin, Germany
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK
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29
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Kreft IC, Hoogendijk AJ, van der Zwaan C, van Alphen FPJ, Boon-Spijker M, Prinsze F, Meijer AB, de Korte D, van den Hurk K, van den Biggelaar M. Mass spectrometry-based analysis on the impact of whole blood donation on the global plasma proteome. Transfusion 2023; 63:564-573. [PMID: 36722460 DOI: 10.1111/trf.17254] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2022] [Revised: 12/27/2022] [Accepted: 12/27/2022] [Indexed: 02/02/2023]
Abstract
BACKGROUND Biomonitoring may provide important insights into the impact of a whole blood donation for individual blood donors. STUDY DESIGN AND METHODS Here, we used unbiased mass spectrometry (MS)-based proteomics to assess longitudinal changes in the global plasma proteome, after a single blood donation for new and regular donors. Subsequently, we compared plasma proteomes of 76 male and female whole blood donors, that were grouped based on their ferritin and hemoglobin (Hb) levels. RESULTS The longitudinal analysis showed limited changes in the plasma proteomes of new and regular donors after a whole blood donation during a 180-day follow-up period, apart from a significant short-term decrease in fibronectin. No differences were observed in the plasma proteomes of donors with high versus low Hb and/or ferritin levels. Plasma proteins with the highest variation between and within donors included pregnancy zone protein, which was associated with sex, Alfa 1-antitrypsin which was associated with the allelic variation, and Immunoglobulin D. Coexpression analysis revealed clustering of proteins that are associated with platelet, red cell, and neutrophil signatures as well as with the complement system and immune responses, including a prominent correlating cluster of immunoglobulin M (IgM), immunoglobulin J chain (JCHAIN), and CD5 antigen-like (CD5L). DISCUSSION Overall, our proteomic approach shows that whole blood donation has a limited impact on the plasma proteins measured. Our findings suggest that plasma profiling can be successfully employed to consistently detect proteins and protein complexes that reflect the functionality and integrity of platelets, red blood cells, and immune cells in blood donors and thus highlights its potential use for donor health monitoring.
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Affiliation(s)
- Iris C Kreft
- Laboratory of Proteomics, Department of Molecular Hematology, Sanquin Research, Amsterdam, The Netherlands
| | - Arie J Hoogendijk
- Laboratory of Proteomics, Department of Molecular Hematology, Sanquin Research, Amsterdam, The Netherlands
| | - Carmen van der Zwaan
- Laboratory of Proteomics, Department of Molecular Hematology, Sanquin Research, Amsterdam, The Netherlands
| | - Floris P J van Alphen
- Laboratory of Proteomics, Department of Molecular Hematology, Sanquin Research, Amsterdam, The Netherlands
| | - Mariette Boon-Spijker
- Laboratory of Proteomics, Department of Molecular Hematology, Sanquin Research, Amsterdam, The Netherlands
| | - Femmeke Prinsze
- Donor Studies, Department of Donor Medicine Research, Sanquin Research, Amsterdam, The Netherlands
| | - Alexander B Meijer
- Laboratory of Proteomics, Department of Molecular Hematology, Sanquin Research, Amsterdam, The Netherlands
- Department of Biomolecular Mass Spectrometry and Proteomics, Utrecht Institute for Pharmaceutical Sciences (UIPS), Utrecht University, Utrecht, The Netherlands
| | - Dirk de Korte
- Department of Blood Cell Research, Sanquin Research, Amsterdam, The Netherlands
- Department of Product and Process Development, Sanquin Blood Bank, Amsterdam, The Netherlands
| | - Katja van den Hurk
- Donor Studies, Department of Donor Medicine Research, Sanquin Research, Amsterdam, The Netherlands
| | - Maartje van den Biggelaar
- Laboratory of Proteomics, Department of Molecular Hematology, Sanquin Research, Amsterdam, The Netherlands
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30
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Midha MK, Kapil C, Maes M, Baxter DH, Morrone SR, Prokop TJ, Moritz RL. Vacuum Insulated Probe Heated ElectroSpray Ionization source (VIP-HESI) enhances micro flow rate chromatography signals in the Bruker timsTOF mass spectrometer. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.02.15.528699. [PMID: 36824828 PMCID: PMC9949110 DOI: 10.1101/2023.02.15.528699] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/17/2023]
Abstract
By far the largest contribution to ion detectability in liquid chromatography-driven mass spectrometry-based proteomics is the efficient generation of peptide ions by the electrospray source. To maximize the transfer of peptides from liquid to a gaseous phase to allow molecular ions to enter the mass spectrometer at micro-spray flow rates, an efficient electrospray process is required. Here we describe superior performance of new Vacuum-Insulated-Probe-Heated-ElectroSpray-Ionization source (VIP-HESI) coupled with micro-spray flow rate chromatography and Bruker timsTOF PRO mass spectrometer. VIP-HESI significantly improves chromatography signals in comparison to nano-spray ionization using the CaptiveSpray source and provides increased protein detection with higher quantitative precision, enhancing reproducibility of sample injection amounts. Protein quantitation of human K562 lymphoblast samples displayed excellent chromatographic retention time reproducibility (<10% coefficient-of-variation (CV)) with no signal degradation over extended periods of time, and a mouse plasma proteome analysis identified 12% more plasma protein groups allowing large-scale analysis to proceed with confidence (1,267 proteins at 0.4% CV). We show that Slice-PASEF mode with VIP-HESI setup is sensitive in identifying low amounts of peptide without losing quantitative precision. We demonstrate that VIP-HESI coupled with micro-flow-rate chromatography achieves higher depth of coverage and run-to-run reproducibility for a broad range of proteomic applications.
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31
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Salovska B, Gao E, Müller‐Dott S, Li W, Cordon CC, Wang S, Dugourd A, Rosenberger G, Saez‐Rodriguez J, Liu Y. Phosphoproteomic analysis of metformin signaling in colorectal cancer cells elucidates mechanism of action and potential therapeutic opportunities. Clin Transl Med 2023; 13:e1179. [PMID: 36781298 PMCID: PMC9925373 DOI: 10.1002/ctm2.1179] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Revised: 12/30/2022] [Accepted: 01/05/2023] [Indexed: 02/15/2023] Open
Abstract
BACKGROUND The biguanide drug metformin is a safe and widely prescribed drug for type 2 diabetes. Interestingly, hundreds of clinical trials have been set to evaluate the potential role of metformin in the prevention and treatment of cancer including colorectal cancer (CRC). However, the "metformin signaling" remains controversial. AIMS AND METHODS To interrogate cell signaling induced by metformin in CRC and explore the druggability of the metformin-rewired phosphorylation network, we performed integrative analysis of phosphoproteomics, bioinformatics, and cell proliferation assays on a panel of 12 molecularly heterogeneous CRC cell lines. Using the high-resolute data-independent analysis mass spectrometry (DIA-MS), we monitored a total of 10,142 proteins and 56,080 phosphosites (P-sites) in CRC cells upon a short- and a long-term metformin treatment. RESULTS AND CONCLUSIONS We found that metformin tended to primarily remodel cell signaling in the long-term and only minimally regulated the total proteome expression levels. Strikingly, the phosphorylation signaling response to metformin was highly heterogeneous in the CRC panel, based on a network analysis inferring kinase/phosphatase activities and cell signaling reconstruction. A "MetScore" was determined to assign the metformin relevance of each P-site, revealing new and robust phosphorylation nodes and pathways in metformin signaling. Finally, we leveraged the metformin P-site signature to identify pharmacodynamic interactions and confirmed a number of candidate metformin-interacting drugs, including navitoclax, a BCL-2/BCL-xL inhibitor. Together, we provide a comprehensive phosphoproteomic resource to explore the metformin-induced cell signaling for potential cancer therapeutics. This resource can be accessed at https://yslproteomics.shinyapps.io/Metformin/.
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Affiliation(s)
- Barbora Salovska
- Yale Cancer Biology InstituteYale UniversityWest HavenConnecticutUSA
| | - Erli Gao
- Yale Cancer Biology InstituteYale UniversityWest HavenConnecticutUSA
| | - Sophia Müller‐Dott
- Institute for Computational BiomedicineFaculty of MedicineHeidelberg University HospitalBioquant, Heidelberg UniversityHeidelbergGermany
| | - Wenxue Li
- Yale Cancer Biology InstituteYale UniversityWest HavenConnecticutUSA
| | | | - Shisheng Wang
- West China‐Washington Mitochondria and Metabolism Research CenterWest China HospitalSichuan UniversityChengduChina
| | - Aurelien Dugourd
- Institute for Computational BiomedicineFaculty of MedicineHeidelberg University HospitalBioquant, Heidelberg UniversityHeidelbergGermany
| | | | - Julio Saez‐Rodriguez
- Institute for Computational BiomedicineFaculty of MedicineHeidelberg University HospitalBioquant, Heidelberg UniversityHeidelbergGermany
| | - Yansheng Liu
- Yale Cancer Biology InstituteYale UniversityWest HavenConnecticutUSA
- Department of PharmacologyYale University School of MedicineNew HavenConnecticutUSA
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32
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Girish V, Lakhani AA, Scaduto CM, Thompson SL, Brown LM, Hagenson RA, Sausville EL, Mendelson BE, Lukow DA, Yuan ML, Kandikuppa PK, Stevens EC, Lee SN, Salovska B, Li W, Smith JC, Taylor AM, Martienssen RA, Liu Y, Sun R, Sheltzer JM. Oncogene-like addiction to aneuploidy in human cancers. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.01.09.523344. [PMID: 36711674 PMCID: PMC9882055 DOI: 10.1101/2023.01.09.523344] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Abstract
Most cancers exhibit aneuploidy, but its functional significance in tumor development is controversial. Here, we describe ReDACT (Restoring Disomy in Aneuploid cells using CRISPR Targeting), a set of chromosome engineering tools that allow us to eliminate specific aneuploidies from cancer genomes. Using ReDACT, we created a panel of isogenic cells that have or lack common aneuploidies, and we demonstrate that trisomy of chromosome 1q is required for malignant growth in cancers harboring this alteration. Mechanistically, gaining chromosome 1q increases the expression of MDM4 and suppresses TP53 signaling, and we show that TP53 mutations are mutually-exclusive with 1q aneuploidy in human cancers. Thus, specific aneuploidies play essential roles in tumorigenesis, raising the possibility that targeting these "aneuploidy addictions" could represent a novel approach for cancer treatment.
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Affiliation(s)
- Vishruth Girish
- Yale University School of Medicine, New Haven, CT 06511
- Johns Hopkins University School of Medicine, Baltimore, MD 21205
| | | | | | | | | | | | | | | | | | - Monet Lou Yuan
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724
| | | | | | - Sophia N. Lee
- Yale University School of Medicine, New Haven, CT 06511
| | | | - Wenxue Li
- Yale University School of Medicine, New Haven, CT 06511
| | - Joan C. Smith
- Yale University School of Medicine, New Haven, CT 06511
| | | | - Robert A. Martienssen
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724
- Howard Hughes Medical Institute, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
| | - Yansheng Liu
- Yale University School of Medicine, New Haven, CT 06511
| | - Ruping Sun
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN 55455
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33
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Liang Y, Zhang L, Zhang Y. Chromatographic separation of peptides and proteins for characterization of proteomes. Chem Commun (Camb) 2023; 59:270-281. [PMID: 36504223 DOI: 10.1039/d2cc05568f] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/03/2022]
Abstract
Characterization of proteomes aims to comprehensively characterize proteins in cells or tissues via two main strategies: (1) bottom-up strategy based on the separation and identification of enzymatic peptides; (2) top-down strategy based on the separation and identification of intact proteins. However, it is challenged by the high complexity of proteomes. Consequently, the improvements in peptide and protein separation technologies for simplifying the sample should be critical. In this feature article, separation columns for peptide and protein separation were introduced, and peptide separation technologies for bottom-up proteomic analysis as well as protein separation technologies for top-down proteomic analysis were summarized. The achievement, recent development, limitation and future trends are discussed. Besides, the outlook on challenges and future directions of chromatographic separation in the field of proteomics was also presented.
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Affiliation(s)
- Yu Liang
- CAS Key Lab of Separation Sciences for Analytical Chemistry, National Chromatographic Research and Analysis Center, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, 116023, China.
| | - Lihua Zhang
- CAS Key Lab of Separation Sciences for Analytical Chemistry, National Chromatographic Research and Analysis Center, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, 116023, China.
| | - Yukui Zhang
- CAS Key Lab of Separation Sciences for Analytical Chemistry, National Chromatographic Research and Analysis Center, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, 116023, China.
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34
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Zhou Y, Sun R, Li S, Liang X, Qian L, Yue L, Guo T. High-Throughput and In-Depth Proteomic Profiling of 5 μL Plasma and Serum Using TMTpro 16-Plex. Methods Mol Biol 2023; 2628:81-92. [PMID: 36781780 DOI: 10.1007/978-1-0716-2978-9_6] [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] [Indexed: 04/25/2023]
Abstract
High-throughput and in-depth proteomic analysis of plasma and serum samples remains challenging due to the presence of multiple high-abundance proteins. Here, we provide a detailed protocol for proteomic analysis of serum and plasma specimens using a high-abundance protein depletion kit and TMTpro 16-plex reagents. This method requires only 5 μL serum or plasma, identifying and quantifying about 1000 proteins. A batch of 16 samples can be processed in 36 h. On average, each sample consumes about 1.5 h of mass spectrometer instrument time. Overall, our method can identify proteins across six orders of magnitude with high reproducibility (CV < 20%) using a shorter instrument time and less sample volume compared to existing methods. Thus, the method is suitable to be applied to large-scale proteomic studies.
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Affiliation(s)
- Yan Zhou
- iMarker lab, Westlake Laboratory of Life Sciences and Biomedicine, Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, Zhejiang, China
- Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, Zhejiang, China
- Research Center for Industries of the Future, Westlake University, Hangzhou, Zhejiang, China
| | - Rui Sun
- iMarker lab, Westlake Laboratory of Life Sciences and Biomedicine, Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, Zhejiang, China
- Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, Zhejiang, China
- Research Center for Industries of the Future, Westlake University, Hangzhou, Zhejiang, China
| | - Sainan Li
- iMarker lab, Westlake Laboratory of Life Sciences and Biomedicine, Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, Zhejiang, China
- Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, Zhejiang, China
- Research Center for Industries of the Future, Westlake University, Hangzhou, Zhejiang, China
| | - Xiao Liang
- iMarker lab, Westlake Laboratory of Life Sciences and Biomedicine, Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, Zhejiang, China
- Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, Zhejiang, China
- Research Center for Industries of the Future, Westlake University, Hangzhou, Zhejiang, China
| | - Liujia Qian
- iMarker lab, Westlake Laboratory of Life Sciences and Biomedicine, Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, Zhejiang, China
- Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, Zhejiang, China
- Research Center for Industries of the Future, Westlake University, Hangzhou, Zhejiang, China
| | - Liang Yue
- iMarker lab, Westlake Laboratory of Life Sciences and Biomedicine, Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, Zhejiang, China
- Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, Zhejiang, China
- Research Center for Industries of the Future, Westlake University, Hangzhou, Zhejiang, China
| | - Tiannan Guo
- iMarker lab, Westlake Laboratory of Life Sciences and Biomedicine, Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, Zhejiang, China.
- Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, Zhejiang, China.
- Research Center for Industries of the Future, Westlake University, Hangzhou, Zhejiang, China.
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35
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Li C, Yue L, Ju Y, Wang J, Chen M, Lu H, Liu S, Liu T, Wang J, Hu X, Tuohetaerbaike B, Wen H, Zhang W, Xu S, Jiang C, Chen F. Serum Proteomic Analysis for New Types of Long-Term Persistent COVID-19 Patients in Wuhan. Microbiol Spectr 2022; 10:e0127022. [PMID: 36314975 PMCID: PMC9784772 DOI: 10.1128/spectrum.01270-22] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2022] [Accepted: 10/07/2022] [Indexed: 12/24/2022] Open
Abstract
The emergence of a new type of COVID-19 patients, who were retested positive after hospital discharge with long-term persistent SARS-CoV-2 infection but without COVID-19 clinical symptoms (hereinafter, LTPPs), poses novel challenges to COVID-19 treatment and prevention. Why was there such a contradictory phenomenon in LTPPs? To explore the mechanism underlying this phenomenon, we performed quantitative proteomic analyses using the sera of 12 LTPPs (Wuhan Pulmonary Hospital), with the longest carrying history of 132 days, and mainly focused on 7 LTPPs without hypertension (LTPPs-NH). The results showed differential serum protein profiles between LTPPs/LTPPs-NH and health controls. Further analysis identified 174 differentially-expressed-proteins (DEPs) for LTPPs, and 165 DEPs for LTPPs-NH, most of which were shared. GO and KEGG analyses for these DEPs revealed significant enrichment of "coagulation" and "immune response" in both LTPPs and LTPPs-NH. A unity of contradictory genotypes in the 2 aspects were then observed: some DEPs showed the same dysregulated expressed trend as that previously reported for patients in the acute phase of COVID-19, which might be caused by long-term stimulation of persistent SARS-CoV-2 infection in LTPPs, further preventing them from complete elimination; in contrast, some DEPs showed the opposite expression trend in expression, so as to retain control of COVID-19 clinical symptoms in LTPPs. Overall, the contrary effects of these DEPs worked together to maintain the balance of LTPPs, further endowing their contradictory steady-state with long-term persistent SARS-CoV-2 infection but without symptoms. Additionally, our study revealed some potential therapeutic targets of COVID-19. Further studies on these are warranted. IMPORTANCE This study reported a new type of COVID-19 patients and explored the underlying molecular mechanism by quantitative proteomic analyses. DEPs were significantly enriched in "coagulation" and "immune response". Importantly, we identified 7 "coagulation system"- and 9 "immune response"-related DEPs, the expression levels of which were consistent with those previously reported for patients in the acute phase of COVID-19, which appeared to play a role in avoiding the complete elimination of SARS-CoV-2 in LTPPs. On the contrary, 6 "coagulation system"- and 5 "immune response"-related DEPs showed the opposite trend in expression. The 11 inconsistent serum proteins seem to play a key role in the fight against long-term persistent SARS-CoV-2 infection, further retaining control of COVID-19 clinical symptom of LTPPs. The 26 proteins can serve as potential therapeutic targets and are thus valuable for the treatment of LTPPs; further studies on them are warranted.
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Affiliation(s)
- Cuidan Li
- Beijing Institute of Genomics, Chinese Academy of Sciences, China National Center for Bioinformation, Beijing, China
| | - Liya Yue
- Beijing Institute of Genomics, Chinese Academy of Sciences, China National Center for Bioinformation, Beijing, China
| | - Yingjiao Ju
- Beijing Institute of Genomics, Chinese Academy of Sciences, China National Center for Bioinformation, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Jie Wang
- Beijing Institute of Genomics, Chinese Academy of Sciences, China National Center for Bioinformation, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Mengfan Chen
- Beijing Institute of Genomics, Chinese Academy of Sciences, China National Center for Bioinformation, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Hao Lu
- Beijing Institute of Genomics, Chinese Academy of Sciences, China National Center for Bioinformation, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Sitong Liu
- Beijing Institute of Genomics, Chinese Academy of Sciences, China National Center for Bioinformation, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Tao Liu
- Beijing Institute of Genomics, Chinese Academy of Sciences, China National Center for Bioinformation, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Jing Wang
- State Key Laboratory of Pathogenesis, Prevention and Treatment of High Incidence Diseases in Central Asia, Urumqi, Xinjiang, China
| | - Xin Hu
- State Key Laboratory of Pathogenesis, Prevention and Treatment of High Incidence Diseases in Central Asia, Urumqi, Xinjiang, China
| | - Bahetibieke Tuohetaerbaike
- State Key Laboratory of Pathogenesis, Prevention and Treatment of High Incidence Diseases in Central Asia, Urumqi, Xinjiang, China
| | - Hao Wen
- State Key Laboratory of Pathogenesis, Prevention and Treatment of High Incidence Diseases in Central Asia, Urumqi, Xinjiang, China
| | - Wenbao Zhang
- State Key Laboratory of Pathogenesis, Prevention and Treatment of High Incidence Diseases in Central Asia, Urumqi, Xinjiang, China
| | - Sihong Xu
- Division II of In Vitro Diagnostics for Infectious Diseases, Institute for In Vitro Diagnostics Control, National Institutes for Food and Drug Control, Beijing, China
| | - Chunlai Jiang
- National Engineering Laboratory for AIDS Vaccine, School of Life Science, Jilin University, Changchun, China
| | - Fei Chen
- Beijing Institute of Genomics, Chinese Academy of Sciences, China National Center for Bioinformation, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
- State Key Laboratory of Pathogenesis, Prevention and Treatment of High Incidence Diseases in Central Asia, Urumqi, Xinjiang, China
- Beijing Key Laboratory of Genome and Precision Medicine Technologies, Beijing, China
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36
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Gerdle B, Wåhlén K, Gordh T, Bäckryd E, Carlsson A, Ghafouri B. Plasma proteins from several components of the immune system differentiate chronic widespread pain patients from healthy controls - an exploratory case-control study combining targeted and non-targeted protein identification. Medicine (Baltimore) 2022; 101:e31013. [PMID: 36401429 PMCID: PMC9678582 DOI: 10.1097/md.0000000000031013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/02/2022] Open
Abstract
Chronic widespread pain (CWP), including fibromyalgia (FM), is characterized by generalized musculoskeletal pain and hyperalgesia. Plasma proteins from proteomics (non-targeted) and from targeted inflammatory panels (cytokines/chemokines) differentiate CWP/FM from controls. The importance of proteins obtained from these two sources, the protein-protein association network, and the biological processes involved were investigated. Plasma proteins from women with CWP (n = 15) and CON (n = 23) were analyzed using two-dimensional gel electrophoresis analysis and a multiplex proximity extension assay for analysis of cytokines/chemokines. Associations between the proteins and group were multivarietly analyzed. The protein-protein association network and the biological processes according to the Gene Ontology were investigated. Proteins from both sources were important for group differentiation; the majority from the two-dimensional gel electrophoresis analysis. 58 proteins significantly differentiated the two groups (R2 = 0.83). A significantly enriched network was found; biological processes were acute phase response, complement activation, and innate immune response. As with other studies, this study shows that plasma proteins can differentiate CWP from healthy subjects. Focusing on cytokines/chemokines is not sufficient to grasp the peripheral biological processes that maintain CWP/FM since our results show that other components of the immune and inflammation systems are also highly significant.
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Affiliation(s)
- Björn Gerdle
- Pain and Rehabilitation Centre, and Department of Health, Medicine, and Caring Sciences, Linköping University, Linköping, Sweden
- *Correspondence: Björn Gerdle, Pain and Rehabilitation Centre and Department of Health, Medicine and Caring Sciences, Linköping University, SE-581 85 Linköping, Sweden (e-mail: )
| | - Karin Wåhlén
- Pain and Rehabilitation Centre, and Department of Health, Medicine, and Caring Sciences, Linköping University, Linköping, Sweden
| | - Torsten Gordh
- Department of Surgical Sciences, Uppsala University, Uppsala, Sweden
| | - Emmanuel Bäckryd
- Pain and Rehabilitation Centre, and Department of Health, Medicine, and Caring Sciences, Linköping University, Linköping, Sweden
| | - Anders Carlsson
- Pain and Rehabilitation Centre, and Department of Health, Medicine, and Caring Sciences, Linköping University, Linköping, Sweden
| | - Bijar Ghafouri
- Pain and Rehabilitation Centre, and Department of Health, Medicine, and Caring Sciences, Linköping University, Linköping, Sweden
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Hill EB, Siebert JC, Yazza DN, Ostendorf DM, Bing K, Wayland L, Scorsone JJ, Bessesen DH, MacLean PS, Melanson EL, Catenacci VA, Borengasser SJ. Proteomics, dietary intake, and changes in cardiometabolic health within a behavioral weight-loss intervention: A pilot study. Obesity (Silver Spring) 2022; 30:2134-2145. [PMID: 36321274 PMCID: PMC9634672 DOI: 10.1002/oby.23574] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/15/2022] [Revised: 08/15/2022] [Accepted: 08/24/2022] [Indexed: 11/29/2022]
Abstract
OBJECTIVE Identifying associations among circulating proteins, dietary intakes, and clinically relevant indicators of cardiometabolic health during weight loss may elucidate biologically relevant pathways affected by diet, allowing for an incorporation of precision nutrition approaches when designing future interventions. This study hypothesized that plasma proteins would be associated with diet and cardiometabolic health indicators within a behavioral weight-loss intervention. METHODS This secondary data analysis included participants (n = 20, mean [SD], age: 40.1 [9.5] years, BMI: 34.2 [4.0] kg/m2 ) who completed a 1-year behavioral weight-loss intervention. Cardiovascular disease-related plasma proteins, diet, and cardiometabolic health indicators were evaluated at baseline and 3 months. Associations were determined via linear regression and integrated networks created using Visualization Of LineAr Regression Elements (VOLARE). RESULTS A total of 16 plasma proteins were associated with ≥1 diet or health indicator at baseline (p < 0.001); changes in 42 proteins were associated with changes in diet or health indicators from baseline to 3 months (p < 0.005). Baseline tumor necrosis factor receptor superfamily member 10C (TNFRSF10C) was associated with intakes of dark green vegetables (r = -0.712), and fatty acid-binding protein 4 (FABP4) was associated with intakes of unsweetened coffee (r = -0.689). Changes in refined-grain intakes were associated with changes in scavenger receptor cysteine-rich type 1 protein M130 (CD163; r = 0.725), interleukin-1 receptor type 1 (IL1R-T1; r = 0.624), insulin (r = 0.656), and triglycerides (r = 0.648). CONCLUSIONS Circulating cardiovascular disease-related proteins were associated with diet and cardiometabolic health indicators prior to and in response to weight loss.
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Affiliation(s)
- Emily B. Hill
- Department of Pediatrics, Section of Nutrition, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | | | - Deaunabah N. Yazza
- Department of Pediatrics, Section of Nutrition, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Danielle M. Ostendorf
- Department of Medicine, Division of Endocrinology, Metabolism, and Diabetes, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
- Department of Medicine, Anschutz Health and Wellness Center, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Kristen Bing
- Department of Medicine, Division of Endocrinology, Metabolism, and Diabetes, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
- Department of Medicine, Anschutz Health and Wellness Center, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Liza Wayland
- Department of Medicine, Division of Endocrinology, Metabolism, and Diabetes, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
- Department of Medicine, Anschutz Health and Wellness Center, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Jared J. Scorsone
- Department of Medicine, Anschutz Health and Wellness Center, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Daniel H. Bessesen
- Department of Medicine, Division of Endocrinology, Metabolism, and Diabetes, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Paul S. MacLean
- Department of Medicine, Division of Endocrinology, Metabolism, and Diabetes, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Edward L. Melanson
- Department of Medicine, Division of Endocrinology, Metabolism, and Diabetes, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
- Department of Medicine, Division of Geriatric Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
- Eastern Colorado Veterans Affairs Geriatric Research, Education, and Clinical Center, Denver, CO, USA
| | - Victoria A. Catenacci
- Department of Medicine, Division of Endocrinology, Metabolism, and Diabetes, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
- Department of Medicine, Anschutz Health and Wellness Center, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Sarah J. Borengasser
- Department of Pediatrics, Section of Nutrition, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
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Liu Y, Yang Q, Du Z, Liu J, Zhang Y, Zhang W, Qin W. Synthesis of Surface-Functionalized Molybdenum Disulfide Nanomaterials for Efficient Adsorption and Deep Profiling of the Human Plasma Proteome by Data-Independent Acquisition. Anal Chem 2022; 94:14956-14964. [PMID: 36264706 DOI: 10.1021/acs.analchem.2c02736] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Blood is one of the most important clinical samples for protein biomarker discovery, as it provides rich physiological and pathological information and is easy to obtain with low invasiveness. However, the discovery of protein biomarkers in the blood by mass spectrometry (MS)-based proteomic strategies has been shown to be highly challenging due to the particularly large concentration range of proteins and the strong interference by the high-abundant proteins in the blood. Therefore, developing sensitive methods for low-abundant biomarker protein identification is a key issue that has received great attention. Here, we report the synthesis and characterization of surface-functionalized magnetic molybdenum disulfide (MoS2) for the large-scale adsorption of low-abundant plasma proteins and deep profiling by MS. MoS2 nanomaterials resulted in the coverage of more than 3400 proteins (including a single-peptide hit) in a single LC-MS analysis without peptide prefractionation using pooled plasma samples, which were five times more than those obtained by the direct analysis of the plasma proteome. A detection limit in the low ng L-1 range was obtained, which is rare compared with previous reports.
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Affiliation(s)
- Yuanyuan Liu
- State Key Laboratory of Proteomics, National Center for Protein Sciences Beijing, Beijing Proteome Research Center, Beijing Institute of Lifeomics, Beijing 102206, P.R. China
| | - Qianying Yang
- State Key Laboratory of Proteomics, National Center for Protein Sciences Beijing, Beijing Proteome Research Center, Beijing Institute of Lifeomics, Beijing 102206, P.R. China.,School of Basic Medical Science, Anhui Medical University, Hefei 230032, China
| | - Zhuokun Du
- State Key Laboratory of Proteomics, National Center for Protein Sciences Beijing, Beijing Proteome Research Center, Beijing Institute of Lifeomics, Beijing 102206, P.R. China.,School of Basic Medical Science, Anhui Medical University, Hefei 230032, China
| | - Jiayu Liu
- Department of Laboratory Medicine, the First Medical Centre, Chinese PLA General Hospital, Beijing 100853, P. R. China
| | - Yangjun Zhang
- State Key Laboratory of Proteomics, National Center for Protein Sciences Beijing, Beijing Proteome Research Center, Beijing Institute of Lifeomics, Beijing 102206, P.R. China.,School of Basic Medical Science, Anhui Medical University, Hefei 230032, China
| | - Wanjun Zhang
- State Key Laboratory of Proteomics, National Center for Protein Sciences Beijing, Beijing Proteome Research Center, Beijing Institute of Lifeomics, Beijing 102206, P.R. China.,School of Basic Medical Science, Anhui Medical University, Hefei 230032, China
| | - Weijie Qin
- State Key Laboratory of Proteomics, National Center for Protein Sciences Beijing, Beijing Proteome Research Center, Beijing Institute of Lifeomics, Beijing 102206, P.R. China.,School of Basic Medical Science, Anhui Medical University, Hefei 230032, China
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39
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Wang Z, Tober-Lau P, Farztdinov V, Lemke O, Schwecke T, Steinbrecher S, Muenzner J, Kriedemann H, Sander LE, Hartl J, Mülleder M, Ralser M, Kurth F. The human host response to monkeypox infection: a proteomic case series study. EMBO Mol Med 2022; 14:e16643. [PMID: 36169042 PMCID: PMC9641420 DOI: 10.15252/emmm.202216643] [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: 07/25/2022] [Revised: 09/09/2022] [Accepted: 09/09/2022] [Indexed: 11/23/2022] Open
Abstract
The rapid rise of monkeypox (MPX) cases outside previously endemic areas prompts for a better understanding of the disease. We studied the plasma proteome of a group of MPX patients with a similar infection history and clinical manifestation typical for the current outbreak. We report that MPX in this case series is associated with a strong plasma proteomic response among nutritional and acute phase response proteins. Moreover, we report a correlation between plasma proteins and disease severity. Contrasting the MPX host response with that of COVID‐19, we find a range of similarities, but also important differences. For instance, CFHR1 is induced in COVID‐19, but suppressed in MPX, reflecting the different roles of the complement system in the two infectious diseases. Of note, the spatial overlap in response proteins suggested that a COVID‐19 biomarker panel assay could be repurposed for MPX. Applying a targeted protein panel assay provided encouraging results and distinguished MPX cases from healthy controls. Hence, our results provide a first proteomic characterization of the MPX human host response and encourage further research on protein‐panel assays in emerging infectious diseases.
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Affiliation(s)
- Ziyue Wang
- Department of Biochemistry, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Pinkus Tober-Lau
- Department of Infectious Diseases and Respiratory Medicine, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Vadim Farztdinov
- Core Facility High Throughput Mass Spectrometry, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Oliver Lemke
- Department of Biochemistry, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Torsten Schwecke
- Department of Biochemistry, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Sarah Steinbrecher
- Department of Infectious Diseases and Respiratory Medicine, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Julia Muenzner
- Department of Biochemistry, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Helene Kriedemann
- Department of Infectious Diseases and Respiratory Medicine, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Leif Erik Sander
- Department of Infectious Diseases and Respiratory Medicine, Charité - Universitätsmedizin Berlin, Berlin, Germany.,Berlin Institute of Health, Berlin, Germany
| | - Johannes Hartl
- Department of Biochemistry, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Michael Mülleder
- Core Facility High Throughput Mass Spectrometry, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Markus Ralser
- Department of Biochemistry, Charité - Universitätsmedizin Berlin, Berlin, Germany.,Berlin Institute of Health, Berlin, Germany.,The Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Florian Kurth
- Department of Infectious Diseases and Respiratory Medicine, Charité - Universitätsmedizin Berlin, Berlin, Germany
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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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41
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Sui X, Wu Q, Cui X, Wang X, Zhang L, Deng N, Bian Y, Xu R, Tian R. Robust Capillary- and Micro-Flow Liquid Chromatography-Tandem Mass Spectrometry Methods for High-Throughput Proteome Profiling. J Proteome Res 2022; 21:2472-2480. [PMID: 36040778 DOI: 10.1021/acs.jproteome.2c00405] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Capillary- and micro-flow liquid chromatography-tandem mass spectrometry (capLC-MS/MS and μLC-MS/MS) is becoming a valuable alternative to nano-flow LC-MS/MS due to its high robustness and throughput. The systematic comparison of capLC-MS/MS and μLC-MS/MS systems for global proteome profiling has not been reported yet. Here, the capLC-MS/MS (150 μm i.d. column, 1 μL/min) and μLC-MS/MS (1 mm i.d. column, 50 μL/min) systems were both established based on UltiMate 3000 RSLCnano coupled to an Orbitrap Exploris 240 by integrating with different flowmeters. We evaluated both systems in terms of sensitivity, analysis throughput, separation efficiency, and robustness. capLC-MS/MS was about 10 times more sensitive than μLC-MS/MS at different gradient lengths. Compared with capLC-MS/MS, μLC-MS/MS was able to achieve higher analysis throughput and separation efficiency. During the 7 days' long-term performance test, both systems showed good reproducibility of chromatographic full width (RSD < 3%), retention time (RSD < 0.4%), and protein identification (RSD < 3%). These results demonstrate that capLC-MS/MS is more suitable for high-throughput analysis of clinical samples with a limited starting material. When enough samples are available, μLC-MS/MS is preferred. Together, capLC and μLC coupled to Orbitrap Exploris 240 with moderate sensitivity should well meet the needs of large-cohort clinical proteomic analysis.
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Affiliation(s)
- Xintong Sui
- Department of Chemistry, Southern University of Science and Technology, Shenzhen 518055, China
| | - Qiong Wu
- Department of Chemistry, Southern University of Science and Technology, Shenzhen 518055, China
| | - Xiaozhen Cui
- Department of Chemistry, Southern University of Science and Technology, Shenzhen 518055, China
| | - Xi Wang
- Department of Oncology, The Second Clinical Medical College, Jinan University (Shenzhen People's Hospital), Shenzhen 518020, China
| | - Luobin Zhang
- Department of Oncology, The Second Clinical Medical College, Jinan University (Shenzhen People's Hospital), Shenzhen 518020, China
| | - Nan Deng
- Instrumental Analysis Center, Xi'an Jiaotong University, Xi'an 710049, China
| | - Yangyang Bian
- The College of Life Sciences, Northwest University, Xi'an 710069, China
| | - Ruilian Xu
- Department of Oncology, The Second Clinical Medical College, Jinan University (Shenzhen People's Hospital), Shenzhen 518020, China
| | - Ruijun Tian
- Department of Chemistry, Southern University of Science and Technology, Shenzhen 518055, China
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42
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Circulating proteins as predictive and prognostic biomarkers in breast cancer. Clin Proteomics 2022; 19:25. [PMID: 35818030 PMCID: PMC9275040 DOI: 10.1186/s12014-022-09362-0] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2022] [Accepted: 06/28/2022] [Indexed: 11/22/2022] Open
Abstract
Breast cancer (BC) is the most common cancer and among the leading causes of cancer death in women. It is a heterogeneous group of tumours with numerous morphological and molecular subtypes, making predictions of disease evolution and patient outcomes difficult. Therefore, biomarkers are needed to help clinicians choose the best treatment for each patient. For the last years, studies have increasingly focused on biomarkers obtainable by liquid biopsy. Circulating proteins (from serum or plasma) can be used for inexpensive and minimally invasive determination of disease risk, early diagnosis, treatment adjusting, prognostication and disease progression monitoring. We provide here a review of the main published studies on serum proteins in breast cancer and elaborate on the potential of circulating proteins to be predictive and/or prognostic biomarkers in breast cancer.
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43
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Mendes ML, Dittmar G. Targeted proteomics on its way to discovery. Proteomics 2022; 22:e2100330. [PMID: 35816345 DOI: 10.1002/pmic.202100330] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Revised: 06/20/2022] [Accepted: 06/27/2022] [Indexed: 11/06/2022]
Abstract
For a long time, targeted and discovery proteomics covered different corners of the detection spectrum, with targeted proteomics focused on small target sets. This changed with the recent advances in highly multiplexed analysis. While discovery proteomics still pushes higher numbers of identified and quantified proteins, the advances in targeted proteomics rose to cover large parts of less complex proteomes or proteomes with low protein detection counts due to dynamic range restrictions, like the blood proteome. These new developments will impact, especially on the field of biomarker discovery and the possibility of using targeted proteomics for diagnostic purposes. This article is protected by copyright. All rights reserved.
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Affiliation(s)
- Marta L Mendes
- Proteomics of cellular signalling, Department of Infection and Immunity, Luxembourg Institute of Health, L-1445, Strassen, Luxembourg
| | - Gunnar Dittmar
- Proteomics of cellular signalling, Department of Infection and Immunity, Luxembourg Institute of Health, L-1445, Strassen, Luxembourg.,Department of Life Sciences and Medicine, University of Luxembourg, L-4367, Belvaux, Luxembourg
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44
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Li W, Li M, Zhang X, Yue S, Xu Y, Jian W, Qin Y, Lin L, Liu W. Improved profiling of low molecular weight serum proteome for gastric carcinoma by data-independent acquisition. Anal Bioanal Chem 2022; 414:6403-6417. [PMID: 35773495 DOI: 10.1007/s00216-022-04196-z] [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: 04/14/2022] [Revised: 06/06/2022] [Accepted: 06/22/2022] [Indexed: 11/27/2022]
Abstract
Low molecular weight proteins (LMWPs) in the bloodstream participate in various biological processes and are closely associated with disease status, whereas identification of serous LMWPs remains a great technical challenge due to the wide dynamic range of protein components. In this study, we constructed an integrated LMWP library by combining the LMWPs obtained by three enrichment methods (50% ACN, 20% ACN + 20 mM ABC, and 30 kDa) and their fractions identified by the data-dependent acquisition method. With this newly constructed library, we comprehensively profiled LMWPs in serum using data-independent acquisition and reliably achieved quantitative results for 75% serous LMWPs. When applying this strategy to quantify LMWPs in human serum samples, we could identify 405 proteins on average per sample, of which 136 proteins were with a MW less than 30 kDa and 293 proteins were with a MW less than 65 kDa. Of note, pre- and post-operative gastric carcinoma (GC) patients showed differentially expressed serous LWMPs, which was also different from the pattern of LWMP expression in healthy controls. In conclusion, our results showed that LMWPs could efficiently distinguish GC patients from healthy controls as well as between pre- and post-operative statuses, and more importantly, our newly developed LMWP profiling platform could be used to discover candidate LMWP biomarkers for disease diagnosis and status monitoring.
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Affiliation(s)
- Weifeng Li
- The Central Laboratory, Shenzhen Second People's Hospital/the First Affiliated Hospital of Shenzhen University, Shenzhen, 518035, China
| | - Mengna Li
- The Central Laboratory, Shenzhen Second People's Hospital/the First Affiliated Hospital of Shenzhen University, Shenzhen, 518035, China
| | - Xiaoli Zhang
- The Central Laboratory, Shenzhen Second People's Hospital/the First Affiliated Hospital of Shenzhen University, Shenzhen, 518035, China
| | - Siqin Yue
- The Central Laboratory, Shenzhen Second People's Hospital/the First Affiliated Hospital of Shenzhen University, Shenzhen, 518035, China
| | - Yun Xu
- The Central Laboratory, Shenzhen Second People's Hospital/the First Affiliated Hospital of Shenzhen University, Shenzhen, 518035, China
| | - Wenjing Jian
- The Central Laboratory, Shenzhen Second People's Hospital/the First Affiliated Hospital of Shenzhen University, Shenzhen, 518035, China
| | - Yin Qin
- Department of Gastrointestinal Surgery, Shenzhen Second People's Hospital/the First Affiliated Hospital of Shenzhen University, Shenzhen, 518035, China.
| | - Lin Lin
- Sustech Core Research Facilities, Southern University of Science and Technology, Shenzhen, 518055, China.
| | - Wenlan Liu
- The Central Laboratory, Shenzhen Second People's Hospital/the First Affiliated Hospital of Shenzhen University, Shenzhen, 518035, China.
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Tognetti M, Sklodowski K, Müller S, Kamber D, Muntel J, Bruderer R, Reiter L. Biomarker Candidates for Tumors Identified from Deep-Profiled Plasma Stem Predominantly from the Low Abundant Area. J Proteome Res 2022; 21:1718-1735. [PMID: 35605973 PMCID: PMC9251764 DOI: 10.1021/acs.jproteome.2c00122] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
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The plasma proteome
has the potential to enable a holistic analysis
of the health state of an individual. However, plasma biomarker discovery
is difficult due to its high dynamic range and variability. Here,
we present a novel automated analytical approach for deep plasma profiling
and applied it to a 180-sample cohort of human plasma from lung, breast,
colorectal, pancreatic, and prostate cancers. Using a controlled quantitative
experiment, we demonstrate a 257% increase in protein identification
and a 263% increase in significantly differentially abundant proteins
over neat plasma. In the cohort, we identified 2732 proteins. Using
machine learning, we discovered biomarker candidates such as STAT3
in colorectal cancer and developed models that classify the diseased
state. For pancreatic cancer, a separation by stage was achieved.
Importantly, biomarker candidates came predominantly from the low
abundance region, demonstrating the necessity to deeply profile because
they would have been missed by shallow profiling.
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Affiliation(s)
| | | | | | | | - Jan Muntel
- Biognosys, Schlieren, Zurich 8952, Switzerland
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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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47
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Mc Ardle A, Binek A, Moradian A, Chazarin Orgel B, Rivas A, Washington KE, Phebus C, Manalo DM, Go J, Venkatraman V, Coutelin Johnson CW, Fu Q, Cheng S, Raedschelders K, Fert-Bober J, Pennington SR, Murray CI, Van Eyk JE. Standardized Workflow for Precise Mid- and High-Throughput Proteomics of Blood Biofluids. Clin Chem 2022; 68:450-460. [PMID: 34687543 DOI: 10.1093/clinchem/hvab202] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2021] [Accepted: 08/30/2021] [Indexed: 01/04/2023]
Abstract
BACKGROUND Accurate discovery assay workflows are critical for identifying authentic circulating protein biomarkers in diverse blood matrices. Maximizing the commonalities in the proteomic workflows between different biofluids simplifies the approach and increases the likelihood for reproducibility. We developed a workflow that can accommodate 3 blood-based proteomes: naive plasma, depleted plasma and dried blood. METHODS Optimal conditions for sample preparation and data independent acquisition-mass spectrometry analysis were established in plasma then automated for depleted plasma and dried blood. The mass spectrometry workflow was modified to facilitate sensitive high-throughput analysis or deeper profiling with mid-throughput analysis. Analytical performance was evaluated by the linear response of peptides and proteins to a 6- or 7-point dilution curve and the reproducibility of the relative peptide and protein intensity for 5 digestion replicates per day on 3 different days for each biofluid. RESULTS Using the high-throughput workflow, 74% (plasma), 93% (depleted), and 87% (dried blood) displayed an inter-day CV <30%. The mid-throughput workflow had 67% (plasma), 90% (depleted), and 78% (dried blood) of peptides display an inter-day CV <30%. Lower limits of detection and quantification were determined for peptides and proteins observed in each biofluid and workflow. Based on each protein and peptide's analytical performance, we could describe the observable, reliable, reproducible, and quantifiable proteomes for each biofluid and workflow. CONCLUSION The standardized workflows established here allows for reproducible and quantifiable detection of proteins covering a broad dynamic range. We envisage that implementation of this standard workflow should simplify discovery approaches and facilitate the translation of candidate markers into clinical use.
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Affiliation(s)
- Angela Mc Ardle
- Smidt Heart Institute, Advanced Clinical Biosystems Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Aleksandra Binek
- Smidt Heart Institute, Advanced Clinical Biosystems Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Annie Moradian
- Precision Biomarker Laboratories, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Blandine Chazarin Orgel
- Smidt Heart Institute, Advanced Clinical Biosystems Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Alejandro Rivas
- Smidt Heart Institute, Advanced Clinical Biosystems Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Kirstin E Washington
- Smidt Heart Institute, Advanced Clinical Biosystems Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Conor Phebus
- Smidt Heart Institute, Advanced Clinical Biosystems Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Danica-Mae Manalo
- Smidt Heart Institute, Advanced Clinical Biosystems Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - James Go
- Smidt Heart Institute, Advanced Clinical Biosystems Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Vidya Venkatraman
- Precision Biomarker Laboratories, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | | | - Qin Fu
- Smidt Heart Institute, Advanced Clinical Biosystems Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Susan Cheng
- Smidt Heart Institute, Barbra Streisand Women's Heart Center, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Koen Raedschelders
- Smidt Heart Institute, Advanced Clinical Biosystems Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Justyna Fert-Bober
- Smidt Heart Institute, Advanced Clinical Biosystems Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Stephen R Pennington
- School of Medicine and Medical Sciences, UCD Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Dublin 4, Ireland
| | - Christopher I Murray
- Smidt Heart Institute, Advanced Clinical Biosystems Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Jennifer E Van Eyk
- Smidt Heart Institute, Advanced Clinical Biosystems Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
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Abstract
INTRODUCTION Due to its excellent sensitivity, nano-flow liquid chromatography tandem mass spectrometry (LC-MS/MS) is the mainstay in proteome research; however, this comes at the expense of limited throughput and robustness. In contrast, micro-flow LC-MS/MS enables high-throughput, robustness, quantitative reproducibility, and precision while retaining a moderate degree of sensitivity. Such features make it an attractive technology for a wide range of proteomic applications. In particular, large-scale projects involving the analysis of hundreds to thousands of samples. AREAS COVERED This review summarizes the history of chromatographic separation in discovery proteomics with a focus on micro-flow LC-MS/MS, discusses the current state-of-the-art, highlights advances in column development and instrumentation, and provides guidance on which LC flow best supports different types of proteomic applications. EXPERT OPINION Micro-flow LC-MS/MS will replace nano-flow LC-MS/MS in many proteomic applications, particularly when sample quantities are not limited and sample cohorts are large. Examples include clinical analyses of body fluids, tissues, drug discovery and chemical biology investigations, plus systems biology projects across all kingdoms of life. When combined with rapid and sensitive MS, intelligent data acquisition, and informatics approaches, it will soon become possible to analyze large cohorts of more than 10,000 samples in a comprehensive and fully quantitative fashion.
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Affiliation(s)
- Yangyang Bian
- The College of Life Science, Northwest University, Xi'an, P.R. China
| | - Chunli Gao
- The College of Life Science, Northwest University, Xi'an, P.R. China
| | - Bernhard Kuster
- Chair of Proteomics and Bioanalytics, Technical University of Munich, Freising, Germany
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49
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Harney DJ, Larance M. Annotated Protein Database Using Known Cleavage Sites for Rapid Detection of Secreted Proteins. J Proteome Res 2022; 21:965-974. [DOI: 10.1021/acs.jproteome.1c00806] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- Dylan J. Harney
- Charles Perkins Centre and School of Life and Environmental Sciences, University of Sydney, 2006 Sydney, Australia
| | - Mark Larance
- Charles Perkins Centre and School of Life and Environmental Sciences, University of Sydney, 2006 Sydney, Australia
- Charles Perkins Centre and School of Medical Sciences, University of Sydney, 2006 Sydney, Australia
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50
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Marshall JL, Peshkin BN, Yoshino T, Vowinckel J, Danielsen HE, Melino G, Tsamardinos I, Haudenschild C, Kerr DJ, Sampaio C, Rha SY, FitzGerald KT, Holland EC, Gallagher D, Garcia-Foncillas J, Juhl H. OUP accepted manuscript. Oncologist 2022; 27:272-284. [PMID: 35380712 PMCID: PMC8982374 DOI: 10.1093/oncolo/oyab048] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2021] [Accepted: 11/05/2021] [Indexed: 11/13/2022] Open
Affiliation(s)
- John L Marshall
- Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington, DC, USA
- Corresponding author: John L. Marshall, MD, The Ruesch Center for the Cure of Gastrointestinal Cancers, Frederick P. Smith Endowed Chair, Chief, Hematology and Oncology, Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, 3800 Reservoir Road, Washington, DC 20007, USA. Tel: +1 202 444 2223;
| | - Beth N Peshkin
- Georgetown University, Lombardi Comprehensive Cancer Center, Washington, DC, USA
| | | | | | - Håvard E Danielsen
- Institute for Cancer Genetics and Informatics, Oslo University Hospital, Radiumhospitalet, Montebello, Oslo, Norway
| | - Gerry Melino
- Department of Experimental Medicine, TOR, University of Rome Tor Vergata, Rome, Italy
| | - Ioannis Tsamardinos
- JADBio Gnosis DA, N. Plastira 100, Science and Technology Park of Crete and Institute of Applied and Computational Mathematics, Foundation for Research and Technology Hellas, Heraklion, GR, Greece
| | | | - David J Kerr
- Nuffield Division of Clinical and Laboratory Sciences, Level 4, Academic Block, John Radcliffe Infirmary, Headington, Oxford, UK
| | | | - Sun Young Rha
- Yonsei Cancer Center, Yonsei University College of Medicine, Seodaemun-Ku, Seoul, Korea
| | - Kevin T FitzGerald
- Department of Medical Humanities in the School of Medicine, Creighton University, Omaha, NE, USA
| | - Eric C Holland
- Division of Human Biology, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - David Gallagher
- St. James’s Hospital/Trinity College Dublin, St. Raphael’s House, Dublin, Ireland
| | - Jesus Garcia-Foncillas
- Cancer Institute, Fundacion Jimenez Diaz University Hospital, Autonomous University, Madrid, Spain
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