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Ciordia S, Santos FM, Dias JML, Lamas JR, Paradela A, Alvarez-Sola G, Ávila MA, Corrales F. Refinement of paramagnetic bead-based digestion protocol for automatic sample preparation using an artificial neural network. Talanta 2024; 274:125988. [PMID: 38569368 DOI: 10.1016/j.talanta.2024.125988] [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: 01/25/2024] [Revised: 03/19/2024] [Accepted: 03/22/2024] [Indexed: 04/05/2024]
Abstract
Despite technological advances in the proteomics field, sample preparation still represents the main bottleneck in mass spectrometry (MS) analysis. Bead-based protein aggregation techniques have recently emerged as an efficient, reproducible, and high-throughput alternative for protein extraction and digestion. Here, a refined paramagnetic bead-based digestion protocol is described for Opentrons® OT-2 platform (OT-2) as a versatile, reproducible, and affordable alternative for the automatic sample preparation for MS analysis. For this purpose, an artificial neural network (ANN) was applied to maximize the number of peptides without missed cleavages identified in HeLa extract by combining factors such as the quantity (μg) of trypsin/Lys-C and beads (MagReSyn® Amine), % (w/v) SDS, % (v/v) acetonitrile, and time of digestion (h). ANN model predicted the optimal conditions for the digestion of 50 μg of HeLa extract, pointing to the use of 2.5% (w/v) SDS and 300 μg of beads for sample preparation and long-term digestion (16h) with 0.15 μg Lys-C and 2.5 μg trypsin (≈1:17 ratio). Based on the results of the ANN model, the manual protocol was automated in OT-2. The performance of the automatic protocol was evaluated with different sample types, including human plasma, Arabidopsis thaliana leaves, Escherichia coli cells, and mouse tissue cortex, showing great reproducibility and low sample-to-sample variability in all cases. In addition, we tested the performance of this method in the preparation of a challenging biological fluid such as rat bile, a proximal fluid that is rich in bile salts, bilirubin, cholesterol, and fatty acids, among other MS interferents. Compared to other protocols described in the literature for the extraction and digestion of bile proteins, the method described here allowed identify 385 unique proteins, thus contributing to improving the coverage of the bile proteome.
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Affiliation(s)
- Sergio Ciordia
- Functional Proteomics Laboratory, Centro Nacional de Biotecnología, CSIC, Calle Darwin 3, Campus de Cantoblanco, 28049, Madrid, Spain
| | - Fátima Milhano Santos
- Functional Proteomics Laboratory, Centro Nacional de Biotecnología, CSIC, Calle Darwin 3, Campus de Cantoblanco, 28049, Madrid, Spain
| | - João M L Dias
- Department of Medical Genetics, University of Cambridge, Cambridge, United Kingdom; Early Cancer Institute, University of Cambridge, Cambridge, United Kingdom
| | - José Ramón Lamas
- Functional Proteomics Laboratory, Centro Nacional de Biotecnología, CSIC, Calle Darwin 3, Campus de Cantoblanco, 28049, Madrid, Spain
| | - Alberto Paradela
- Functional Proteomics Laboratory, Centro Nacional de Biotecnología, CSIC, Calle Darwin 3, Campus de Cantoblanco, 28049, Madrid, Spain
| | - Gloria Alvarez-Sola
- Hepatology Laboratory, Solid Tumors Program, Center for Applied Medical Research (CIMA), University of Navarra, 31008, Pamplona, Spain; National Institute for the Study of Liver and Gastrointestinal Diseases (CIBERehd, Carlos III Health Institute), 28029, Madrid, Spain; IdiSNA, Navarra Institute for Health Research, 31008, Pamplona, Spain
| | - Matías A Ávila
- Hepatology Laboratory, Solid Tumors Program, Center for Applied Medical Research (CIMA), University of Navarra, 31008, Pamplona, Spain; National Institute for the Study of Liver and Gastrointestinal Diseases (CIBERehd, Carlos III Health Institute), 28029, Madrid, Spain; IdiSNA, Navarra Institute for Health Research, 31008, Pamplona, Spain
| | - Fernando Corrales
- Functional Proteomics Laboratory, Centro Nacional de Biotecnología, CSIC, Calle Darwin 3, Campus de Cantoblanco, 28049, Madrid, Spain.
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Influence of different sample preparation strategies on hypothesis-driven shotgun proteomic analysis of human saliva. OPEN CHEM 2022. [DOI: 10.1515/chem-2022-0216] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/03/2022] Open
Abstract
Abstract
This research aimed to find an efficient and repeatable bottom-up proteolytic strategy to process the unstimulated human saliva. The focus is on monitoring immune system activation via the cytokine and interleukin signaling pathways. Carbohydrate metabolism is also being studied as a possible trigger of inflammation and joint damage in the context of the diagnostic procedure of temporomandibular joint disorder. The preparation of clean peptide mixtures for liquid chromatography–mass spectrometry analysis was performed considering different aspects of sample preparation: the filter-aided sample preparation (FASP) with different loadings of salivary proteins, the unfractionated saliva, amylase-depleted, and amylase-enriched salivary fractions. To optimize the efficiency of the FASP method, the protocols with the digestion in the presence of 80% acetonitrile and one-step digestion in the presence of 80% acetonitrile were used, omitting protein reduction and alkylation. The digestion procedures were repeated in the standard in-solution mode. Alternatively, the temperature of 24 and 37°C was examined during the trypsin digestion. DyNet analysis of the hierarchical networks of Gene Ontology terms corresponding to each sample preparation method for the bottom-up assay revealed the wide variability in protein properties. The method can easily be tailored to the specific samples and groups of proteins to be examined.
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Chen Z, Gao Y, Zhong D. Technologies to improve the sensitivity of existing chromatographic methods used for bioanalytical studies. Biomed Chromatogr 2020; 34:e4798. [PMID: 31994210 DOI: 10.1002/bmc.4798] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2019] [Revised: 01/10/2020] [Accepted: 01/24/2020] [Indexed: 12/16/2022]
Abstract
Chromatographic method has long been recognized as the most widely used separation method in bioanalytical research. However, the relatively low sensitivity of existing chromatographic methods remains a significant challenge, as the requirements for experimental procedures become more demanding. This review discusses the main causes for the low sensitivity of chromatographic methods and aims to introduce different technologies for enhancing their sensitivity in the following aspects: (i) different pretreatment methods for improving clean-up efficiency and recovery; (ii) derivatization step for altering the chromatographic behavior of analytes and enhancing MS ionization efficiency; (iii) optimal LC-MS conditions and appropriate separation mechanism; and (iv) applications of other chromatographic methods, including miniaturized LC, 2D-LC, 2D-GC, and supercritical fluid chromatography. Altogether, this review is devoted to summarizing the recent technologies reported in the literature and providing new strategies for the detection of bioanalytes.
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Affiliation(s)
- Zhendong Chen
- State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, China.,University of Chinese Academy of Sciences, Beijing, China
| | - Yuxiong Gao
- State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, China.,University of Chinese Academy of Sciences, Beijing, China
| | - Dafang Zhong
- State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, China.,University of Chinese Academy of Sciences, Beijing, China
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