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Wang Y, Liu Y, Liu S, Cheng L, Liu X. Recent advances in N-glycan biomarker discovery among human diseases. Acta Biochim Biophys Sin (Shanghai) 2024. [PMID: 38910518 DOI: 10.3724/abbs.2024101] [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: 06/25/2024] Open
Abstract
N-glycans play important roles in a variety of biological processes. In recent years, analytical technologies with high resolution and sensitivity have advanced exponentially, enabling analysts to investigate N-glycomic changes in different states. Specific glycan and glycosylation signatures have been identified in multiple diseases, including cancer, autoimmune diseases, nervous system disorders, and metabolic and cardiovascular diseases. These glycans demonstrate comparable or superior indicating capability in disease diagnosis and prognosis over routine biomarkers. Moreover, synchronous glycan alterations concurrent with disease initiation and progression provide novel insights into pathogenetic mechanisms and potential treatment targets. This review elucidates the biological significance of N-glycans, compares the existing glycomic technologies, and delineates the clinical performance of N-glycans across a range of diseases.
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Affiliation(s)
- Yi Wang
- Department of Laboratory Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Yuanyuan Liu
- The Key Laboratory for Biomedical Photonics of MOE at Wuhan National Laboratory for Optoelectronics-Hubei Bioinformatics & Molecular Imaging Key Laboratory, Systems Biology Theme, Department of Biomedical Engineering, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Si Liu
- Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fuzhou 350122, China
| | - Liming Cheng
- Department of Laboratory Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Xin Liu
- The Key Laboratory for Biomedical Photonics of MOE at Wuhan National Laboratory for Optoelectronics-Hubei Bioinformatics & Molecular Imaging Key Laboratory, Systems Biology Theme, Department of Biomedical Engineering, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan 430074, China
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Yamada CAO, de Paula Oliveira Santos B, Lemos RP, Batista ACS, da Conceição IMCA, de Paula Sabino A, E Lima LMTDR, de Magalhães MTQ. Applications of Mass Spectrometry in the Characterization, Screening, Diagnosis, and Prognosis of COVID-19. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2024; 1443:33-61. [PMID: 38409415 DOI: 10.1007/978-3-031-50624-6_3] [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: 02/28/2024]
Abstract
Mass spectrometry (MS) is a powerful analytical technique that plays a central role in modern protein analysis and the study of proteostasis. In the field of advanced molecular technologies, MS-based proteomics has become a cornerstone that is making a significant impact in the post-genomic era and as precision medicine moves from the research laboratory to clinical practice. The global dissemination of COVID-19 has spurred collective efforts to develop effective diagnostics, vaccines, and therapeutic interventions. This chapter highlights how MS seamlessly integrates with established methods such as RT-PCR and ELISA to improve viral identification and disease progression assessment. In particular, matrix-assisted laser desorption/ionization time of flight mass spectrometry (MALDI-TOF-MS) takes the center stage, unraveling intricate details of SARS-CoV-2 proteins, revealing modifications such as glycosylation, and providing insights critical to formulating therapies and assessing prognosis. However, high-throughput analysis of MALDI data presents challenges in manual interpretation, which has driven the development of programmatic pipelines and specialized packages such as MALDIquant. As we move forward, it becomes clear that integrating proteomic data with various omic findings is an effective strategy to gain a comprehensive understanding of the intricate biology of COVID-19 and ultimately develop targeted therapeutic paradigms.
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Affiliation(s)
- Camila Akemi Oliveira Yamada
- Laboratory for Macromolecular Biophysics - LBM, Department of Biochemistry and Immunology, Federal University of Minas Gerais, Belo Horizonte, Minas Gerais, Brazil
- Interunit Postgraduate Program in Bioinformatics, Federal University of Minas Gerais, Belo Horizonte, Minas Gerais, Brazil
| | - Bruno de Paula Oliveira Santos
- Laboratory for Macromolecular Biophysics - LBM, Department of Biochemistry and Immunology, Federal University of Minas Gerais, Belo Horizonte, Minas Gerais, Brazil
| | - Rafael Pereira Lemos
- Laboratory for Macromolecular Biophysics - LBM, Department of Biochemistry and Immunology, Federal University of Minas Gerais, Belo Horizonte, Minas Gerais, Brazil
- Interunit Postgraduate Program in Bioinformatics, Federal University of Minas Gerais, Belo Horizonte, Minas Gerais, Brazil
| | - Ana Carolina Silva Batista
- Laboratory for Macromolecular Biophysics - LBM, Department of Biochemistry and Immunology, Federal University of Minas Gerais, Belo Horizonte, Minas Gerais, Brazil
- Interunit Postgraduate Program in Bioinformatics, Federal University of Minas Gerais, Belo Horizonte, Minas Gerais, Brazil
| | | | - Adriano de Paula Sabino
- Interunit Postgraduate Program in Bioinformatics, Federal University of Minas Gerais, Belo Horizonte, Minas Gerais, Brazil
- Laboratory of Clinical and Molecular Hematology - Faculty of Pharmacy, Federal University of Minas Gerais, Belo Horizonte, Minas Gerais, Brazil
| | | | - Mariana T Q de Magalhães
- Laboratory for Macromolecular Biophysics - LBM, Department of Biochemistry and Immunology, Federal University of Minas Gerais, Belo Horizonte, Minas Gerais, Brazil.
- Interunit Postgraduate Program in Bioinformatics, Federal University of Minas Gerais, Belo Horizonte, Minas Gerais, Brazil.
- Biochemistry and Immunology Postgraduate Program, Federal University of Minas Gerais, Belo Horizonte, Minas Gerais, Brazil.
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Cattaneo C, Givonetti A, Cavaletto M. Protein Mass Fingerprinting and Antioxidant Power of Hemp Seeds in Relation to Plant Cultivar and Environment. PLANTS (BASEL, SWITZERLAND) 2023; 12:782. [PMID: 36840130 PMCID: PMC9966504 DOI: 10.3390/plants12040782] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/17/2023] [Revised: 02/06/2023] [Accepted: 02/07/2023] [Indexed: 06/18/2023]
Abstract
Cannabis sativa (hemp) seeds are considered a functional food for their favorable contents of essential fatty acids, proteins and antioxidants. Beyond phenolics and carotenoids, the bioactivity of proteins has recently been investigated. However, plant genotype and environmental conditions can affect quantity and quality of macronutrients and phytochemicals in seeds, influencing their nutraceutical properties. In this study, the effects of plant variety and seed origin on the protein profile and antioxidant activity of hemp seeds were evaluated. Seeds from two cultivars, Secuieni Jubileu and Finola, were harvested from a mountain field located in Italy and compared with reference seeds used for sowing. Albumin and globulin extracts were obtained using the Osborne method and their antioxidant power was assayed (DPPH and ABTS methods). A matrix-assisted laser desorption ionization time-of-flight (MALDI-TOF) mass spectrometry method was developed for protein fingerprinting analysis. Albumins from seeds of the mountain site showed higher radical scavenging activity and compounds of lower molecular weight than reference seeds, suggesting a role of proteins in the observed bioactivity. The MALDI-TOF method discriminated samples according to origin and variety, highlighting changes in the protein profile and identifying signals which could be used as markers of hemp cultivars.
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Affiliation(s)
- Chiara Cattaneo
- Department of Science and Technological Innovation, DiSIT, University of Eastern Piedmont, 13100 Vercelli, Italy
| | - Annalisa Givonetti
- Department for Sustainable Development and Ecological Transition, DiSSTE, University of Eastern Piedmont, 13100 Vercelli, Italy
| | - Maria Cavaletto
- Department for Sustainable Development and Ecological Transition, DiSSTE, University of Eastern Piedmont, 13100 Vercelli, Italy
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Trbojević-Akmačić I, Lageveen-Kammeijer GSM, Heijs B, Petrović T, Deriš H, Wuhrer M, Lauc G. High-Throughput Glycomic Methods. Chem Rev 2022; 122:15865-15913. [PMID: 35797639 PMCID: PMC9614987 DOI: 10.1021/acs.chemrev.1c01031] [Citation(s) in RCA: 21] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
Glycomics aims to identify the structure and function of the glycome, the complete set of oligosaccharides (glycans), produced in a given cell or organism, as well as to identify genes and other factors that govern glycosylation. This challenging endeavor requires highly robust, sensitive, and potentially automatable analytical technologies for the analysis of hundreds or thousands of glycomes in a timely manner (termed high-throughput glycomics). This review provides a historic overview as well as highlights recent developments and challenges of glycomic profiling by the most prominent high-throughput glycomic approaches, with N-glycosylation analysis as the focal point. It describes the current state-of-the-art regarding levels of characterization and most widely used technologies, selected applications of high-throughput glycomics in deciphering glycosylation process in healthy and disease states, as well as future perspectives.
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Affiliation(s)
| | | | - Bram Heijs
- Center
for Proteomics and Metabolomics, Leiden
University Medical Center, PO Box 9600, 2300 RC Leiden, The Netherlands
| | - Tea Petrović
- Genos,
Glycoscience Research Laboratory, Borongajska cesta 83H, 10 000 Zagreb, Croatia
| | - Helena Deriš
- Genos,
Glycoscience Research Laboratory, Borongajska cesta 83H, 10 000 Zagreb, Croatia
| | - Manfred Wuhrer
- Center
for Proteomics and Metabolomics, Leiden
University Medical Center, PO Box 9600, 2300 RC Leiden, The Netherlands
| | - Gordan Lauc
- Genos,
Glycoscience Research Laboratory, Borongajska cesta 83H, 10 000 Zagreb, Croatia
- Faculty
of Pharmacy and Biochemistry, University
of Zagreb, A. Kovačića 1, 10 000 Zagreb, Croatia
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Wang HJ, Xie YB, Zhang PJ, Jiang T. Evaluation of the diagnostic value of serum-based proteomics for colorectal cancer. World J Gastrointest Oncol 2022; 14:1562-1573. [PMID: 36160749 PMCID: PMC9412932 DOI: 10.4251/wjgo.v14.i8.1562] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/08/2022] [Revised: 04/13/2022] [Accepted: 07/18/2022] [Indexed: 02/05/2023] Open
Abstract
BACKGROUND Colorectal cancer (CRC) is a highly malignant cancer with a high incidence and mortality in China. It is urgent to find a diagnostic marker with higher sensitivity and specificity than the traditional approaches for CRC diagnosis.
AIM To provide new ideas for the diagnosis of CRC based on serum proteomics.
METHODS Specimens from 83 healthy people, 62 colon polyp (CRP) patients, and 101 CRC patients were analyzed by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. The diagnostic value of the profiles of differentially expressed proteins was then analyzed.
RESULTS Compared with the healthy control group, CRC patients had elevated expression of 5 proteins and reduced expression of 14 proteins. The area under the curve (AUC) for a differentially expressed protein with a mass-to-charge ratio of 2022.34 was the largest; the AUC was 0.843, which was higher than the AUC of 0.717 observed with carcinoembryonic antigen (CEA), and the sensitivity and specificity of this identified marker were 75.3% and 79.5%, respectively. After cross-validation, the accuracy of diagnosis using levels of this differentially expressed protein was 82.37%. Compared with the CRP group, the expression of 3 proteins in the serum of CRC patients was elevated and 11 proteins were expressed at reduced levels. Proteins possessing mass-to-charge ratio values of 2899.38 and 877.3 were selected to establish a classification tree model. The results showed that the accuracy of CRC diagnosis was 89.5%, the accuracy of CRP diagnosis was 81.6%, and the overall accuracy of this approach was 86.3%. The overall sensitivity and specificity of diagnosis using the proteomics approach were 81.8% and 66.75%, respectively. The sensitivities and specificities of diagnoses based on CEA and carbohydrate antigen 19-9 expression were 55.6% and 91.3% and 65.4% and 65.2%, respectively.
CONCLUSION We demonstrated that serum proteomics may be helpful for the detection of CRC, and it may assist clinical practice for CRC diagnosis.
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Affiliation(s)
- Hui-Juan Wang
- Department of Respiratory and Critical Care Medicine, Beijing Chao-Yang Hospital, Beijing Institute of Respiratory Medicine, Capital Medical University, Beijing 100020, China
| | - Yi-Bin Xie
- Department of Pancreatic and Gastric Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Peng-Jun Zhang
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Interventional Therapy Department, Peking University Cancer Hospital and Institute, Beijing 100142, China
| | - Tao Jiang
- Medical Innovation Research Division of Chinese PLA General Hospital, Beijing 100853, China
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