1
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Palstrøm NB, Campbell AJ, Lindegaard CA, Cakar S, Matthiesen R, Beck HC. Spectral library search for improved TMTpro labelled peptide assignment in human plasma proteomics. Proteomics 2024; 24:e2300236. [PMID: 37706597 DOI: 10.1002/pmic.202300236] [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: 06/01/2023] [Revised: 06/21/2023] [Accepted: 06/22/2023] [Indexed: 09/15/2023]
Abstract
Clinical biomarker discovery is often based on the analysis of human plasma samples. However, the high dynamic range and complexity of plasma pose significant challenges to mass spectrometry-based proteomics. Current methods for improving protein identifications require laborious pre-analytical sample preparation. In this study, we developed and evaluated a TMTpro-specific spectral library for improved protein identification in human plasma proteomics. The library was constructed by LC-MS/MS analysis of highly fractionated TMTpro-tagged human plasma, human cell lysates, and relevant arterial tissues. The library was curated using several quality filters to ensure reliable peptide identifications. Our results show that spectral library searching using the TMTpro spectral library improves the identification of proteins in plasma samples compared to conventional sequence database searching. Protein identifications made by the spectral library search engine demonstrated a high degree of complementarity with the sequence database search engine, indicating the feasibility of increasing the number of protein identifications without additional pre-analytical sample preparation. The TMTpro-specific spectral library provides a resource for future plasma proteomics research and optimization of search algorithms for greater accuracy and speed in protein identifications in human plasma proteomics, and is made publicly available to the research community via ProteomeXchange with identifier PXD042546.
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Affiliation(s)
- Nicolai B Palstrøm
- Department of Clinical Biochemistry, Odense University Hospital, Odense, Denmark
| | - Amanda J Campbell
- Department of Clinical Biochemistry, Odense University Hospital, Odense, Denmark
| | | | - Samir Cakar
- Department of Clinical Biochemistry, Odense University Hospital, Odense, Denmark
| | - Rune Matthiesen
- Computational and Experimental Biology Group, CEDOC, Chronic Diseases Research Centre, NOVA Medical School, Faculdade de Ciências Médicas, Universidade NOVA de Lisboa, Lisbon, Portugal
| | - Hans C Beck
- Department of Clinical Biochemistry, Odense University Hospital, Odense, Denmark
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2
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Radke J, Meinhardt J, Aschman T, Chua RL, Farztdinov V, Lukassen S, Ten FW, Friebel E, Ishaque N, Franz J, Huhle VH, Mothes R, Peters K, Thomas C, Schneeberger S, Schumann E, Kawelke L, Jünger J, Horst V, Streit S, von Manitius R, Körtvélyessy P, Vielhaber S, Reinhold D, Hauser AE, Osterloh A, Enghard P, Ihlow J, Elezkurtaj S, Horst D, Kurth F, Müller MA, Gassen NC, Melchert J, Jechow K, Timmermann B, Fernandez-Zapata C, Böttcher C, Stenzel W, Krüger E, Landthaler M, Wyler E, Corman V, Stadelmann C, Ralser M, Eils R, Heppner FL, Mülleder M, Conrad C, Radbruch H. Proteomic and transcriptomic profiling of brainstem, cerebellum and olfactory tissues in early- and late-phase COVID-19. Nat Neurosci 2024; 27:409-420. [PMID: 38366144 DOI: 10.1038/s41593-024-01573-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2023] [Accepted: 01/08/2024] [Indexed: 02/18/2024]
Abstract
Neurological symptoms, including cognitive impairment and fatigue, can occur in both the acute infection phase of coronavirus disease 2019 (COVID-19) and at later stages, yet the mechanisms that contribute to this remain unclear. Here we profiled single-nucleus transcriptomes and proteomes of brainstem tissue from deceased individuals at various stages of COVID-19. We detected an inflammatory type I interferon response in acute COVID-19 cases, which resolves in the late disease phase. Integrating single-nucleus RNA sequencing and spatial transcriptomics, we could localize two patterns of reaction to severe systemic inflammation, one neuronal with a direct focus on cranial nerve nuclei and a separate diffuse pattern affecting the whole brainstem. The latter reflects a bystander effect of the respiratory infection that spreads throughout the vascular unit and alters the transcriptional state of mainly oligodendrocytes, microglia and astrocytes, while alterations of the brainstem nuclei could reflect the connection of the immune system and the central nervous system via, for example, the vagus nerve. Our results indicate that even without persistence of severe acute respiratory syndrome coronavirus 2 in the central nervous system, local immune reactions are prevailing, potentially causing functional disturbances that contribute to neurological complications of COVID-19.
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Affiliation(s)
- Josefine Radke
- Institute of Pathology, Universitätsmedizin Greifswald, Greifswald, Germany.
- Department of Neuropathology, Charité - Universitätsmedizin Berlin, Berlin, Germany.
| | - Jenny Meinhardt
- Department of Neuropathology, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Tom Aschman
- Department of Neuropathology, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Robert Lorenz Chua
- Center of Digital Health, Berlin Institute of Health at Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Vadim Farztdinov
- Core Facility High Throughput Mass Spectrometry, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Sören Lukassen
- Center of Digital Health, Berlin Institute of Health at Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Foo Wei Ten
- Center of Digital Health, Berlin Institute of Health at Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Ekaterina Friebel
- Department of Neuropathology, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Naveed Ishaque
- Center of Digital Health, Berlin Institute of Health at Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Jonas Franz
- Department of Neuropathology, University Medical Center Göttingen, Göttingen, Germany
| | - Valerie Helena Huhle
- Department of Neuropathology, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Ronja Mothes
- Department of Neuropathology, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Kristin Peters
- Institute of Pathology, Universitätsmedizin Greifswald, Greifswald, Germany
| | - Carolina Thomas
- Department of Neuropathology, University Medical Center Göttingen, Göttingen, Germany
| | - Shirin Schneeberger
- Department of Neuropathology, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Elisa Schumann
- Department of Neuropathology, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Leona Kawelke
- Department of Neuropathology, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Julia Jünger
- Department of Neuropathology, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Viktor Horst
- Department of Neuropathology, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Simon Streit
- Department of Neuropathology, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Regina von Manitius
- Department of Neuropathology, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Péter Körtvélyessy
- Department of Neurology, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Stefan Vielhaber
- Department of Neurology, Otto von Guerike University Magdeburg, Magdeburg, Germany
| | - Dirk Reinhold
- Institute of Molecular and Clinical Immunology, Otto von Guerike University Magdeburg, Magdeburg, Germany
| | - Anja E Hauser
- Department of Rheumatology and Clinical Immunology, Charité - Universitätsmedizin Berlin, Berlin, Germany
- Immune Dynamics, Deutsches Rheuma-Forschungszentrum, a Leibniz Institute, Berlin, Germany
| | - Anja Osterloh
- Department of Pathology, University Medical Center Ulm, Ulm, Germany
| | - Philipp Enghard
- Department of Nephrology and Medical Intensive Care, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Jana Ihlow
- Department of Pathology, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Sefer Elezkurtaj
- Department of Pathology, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - David Horst
- Department of Pathology, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Florian Kurth
- Department of Infectious Diseases and Respiratory Medicine, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Marcel A Müller
- Institute of Virology, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Nils C Gassen
- Department of Psychiatry and Psychotherapy, University Hospital Bonn, Bonn, Germany
| | - Julia Melchert
- Institute of Virology, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Katharina Jechow
- Center of Digital Health, Berlin Institute of Health at Charité - Universitätsmedizin Berlin, Berlin, Germany
| | | | - Camila Fernandez-Zapata
- Experimental and Clinical Research Center, a cooperation between the Max Delbrück Center for Molecular Medicine in the Helmholtz Association and Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Chotima Böttcher
- Experimental and Clinical Research Center, a cooperation between the Max Delbrück Center for Molecular Medicine in the Helmholtz Association and Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Werner Stenzel
- Department of Neuropathology, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Elke Krüger
- Institute of Medical Biochemistry and Molecular Biology, Universitätsmedizin Greifswald, Greifswald, Germany
| | - Markus Landthaler
- Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
- Institut für Biologie, Humboldt Universität, Berlin, Germany
| | - Emanuel Wyler
- Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
| | - Victor Corman
- Department of Infectious Diseases and Respiratory Medicine, Charité - Universitätsmedizin Berlin, Berlin, Germany
- German Centre for Infection Research (DZIF), associated partner, Berlin, Germany
| | - Christine Stadelmann
- Department of Neuropathology, University Medical Center Göttingen, Göttingen, Germany
| | - Markus Ralser
- Core Facility High Throughput Mass Spectrometry, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Roland Eils
- Center of Digital Health, Berlin Institute of Health at Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Frank L Heppner
- Department of Neuropathology, Charité - Universitätsmedizin Berlin, Berlin, Germany
- German Center for Neurodegenerative Diseases (DZNE) Berlin, Berlin, Germany
- Cluster of Excellence NeuroCure, Berlin, Germany
- German Cancer Consortium (DKTK), Partner Site Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Michael Mülleder
- Core Facility High Throughput Mass Spectrometry, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Christian Conrad
- Center of Digital Health, Berlin Institute of Health at Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Helena Radbruch
- Department of Neuropathology, Charité - Universitätsmedizin Berlin, Berlin, Germany.
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Jia W, Peng J, Zhang Y, Zhu J, Qiang X, Zhang R, Shi L. Exploring novel ANGICon-EIPs through ameliorated peptidomics techniques: Can deep learning strategies as a core breakthrough in peptide structure and function prediction? Food Res Int 2023; 174:113640. [PMID: 37986483 DOI: 10.1016/j.foodres.2023.113640] [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: 09/05/2023] [Revised: 10/23/2023] [Accepted: 10/24/2023] [Indexed: 11/22/2023]
Abstract
Dairy-derived angiotensin-I-converting enzyme inhibitory peptides (ANGICon-EIPs) have been regarded as a relatively safe supplementary diet-therapy strategy for individuals with hypertension, and short-chain peptides may have more relevant antihypertensive benefits due to their direct intestinal absorption. Our previous explorations have confirmed that endogenous goat milk short-chain peptides are also an essential source of ANGICon-EIPs. Nonetheless, there are limited explorations on endogenous ANGICon-EIPs owing to the limitations of the extraction and enrichment of endogenous peptides, currently. This review outlined ameliorated pre-treatment strategies, data acquisition methods, and tools for the prediction of peptide structure and function, aiming to provide creative ideas for discovering novel ANGICon-EIPs. Currently, deep learning-based peptide structure and function prediction algorithms have achieved significant advancements. The convolutional neural network (CNN) and peptide sequence-based multi-label deep learning approach for determining the multi-functionalities of bioactive peptides (MLBP) can predict multiple peptide functions with absolute true value and accuracy of 0.699 and 0.708, respectively. Utilizing peptide sequence input, torsion angles, and inter-residue distance to train neural networks, APPTEST predicted the average backbone root mean square deviation (RMSD) value of peptide (5-40 aa) structures as low as 1.96 Å. Overall, with the exploration of more neural network architectures, deep learning could be considered a critical research tool to reduce the cost and improve the efficiency of identifying novel endogenous ANGICon-EIPs.
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Affiliation(s)
- Wei Jia
- School of Food and Bioengineering, Shaanxi University of Science and Technology, Xi'an 710021, China; Inspection and Testing Center of Fuping County (Shaanxi goat milk product quality supervision and Inspection Center), Weinan 711700, China; Shaanxi Research Institute of Agricultural Products Processing Technology, Xi'an 710021, China.
| | - Jian Peng
- School of Food and Bioengineering, Shaanxi University of Science and Technology, Xi'an 710021, China
| | - Yan Zhang
- Inspection and Testing Center of Fuping County (Shaanxi goat milk product quality supervision and Inspection Center), Weinan 711700, China
| | - Jiying Zhu
- School of Food and Bioengineering, Shaanxi University of Science and Technology, Xi'an 710021, China
| | - Xin Qiang
- Inspection and Testing Center of Fuping County (Shaanxi goat milk product quality supervision and Inspection Center), Weinan 711700, China
| | - Rong Zhang
- School of Food and Bioengineering, Shaanxi University of Science and Technology, Xi'an 710021, China
| | - Lin Shi
- School of Food and Bioengineering, Shaanxi University of Science and Technology, Xi'an 710021, China
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McGann CD, Barshop WD, Canterbury JD, Lin C, Gabriel W, Huang J, Bergen D, Zabrouskov V, Melani RD, Wilhelm M, McAlister GC, Schweppe DK. Real-Time Spectral Library Matching for Sample Multiplexed Quantitative Proteomics. J Proteome Res 2023; 22:2836-2846. [PMID: 37557900 DOI: 10.1021/acs.jproteome.3c00085] [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: 08/11/2023]
Abstract
Sample multiplexed quantitative proteomics assays have proved to be a highly versatile means to assay molecular phenotypes. Yet, stochastic precursor selection and precursor coisolation can dramatically reduce the efficiency of data acquisition and quantitative accuracy. To address this, intelligent data acquisition (IDA) strategies have recently been developed to improve instrument efficiency and quantitative accuracy for both discovery and targeted methods. Toward this end, we sought to develop and implement a new real-time spectral library searching (RTLS) workflow that could enable intelligent scan triggering and peak selection within milliseconds of scan acquisition. To ensure ease of use and general applicability, we built an application to read in diverse spectral libraries and file types from both empirical and predicted spectral libraries. We demonstrate that RTLS methods enable improved quantitation of multiplexed samples, particularly with consideration for quantitation from chimeric fragment spectra. We used RTLS to profile proteome responses to small molecule perturbations and were able to quantify up to 15% more significantly regulated proteins in half the gradient time compared to traditional methods. Taken together, the development of RTLS expands the IDA toolbox to improve instrument efficiency and quantitative accuracy for sample multiplexed analyses.
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Affiliation(s)
- Chris D McGann
- University of Washington, Seattle, Washington 98105, United States
| | | | | | - Chuwei Lin
- University of Washington, Seattle, Washington 98105, United States
| | | | - Jingjing Huang
- Thermo Fisher Scientific, San Jose, California 95134, United States
| | - David Bergen
- Thermo Fisher Scientific, San Jose, California 95134, United States
| | - Vlad Zabrouskov
- Thermo Fisher Scientific, San Jose, California 95134, United States
| | - Rafael D Melani
- Thermo Fisher Scientific, San Jose, California 95134, United States
| | | | | | - Devin K Schweppe
- University of Washington, Seattle, Washington 98105, United States
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