1
|
Hong H, Habib A, Bi L, Qais DS, Wen L. Hollow Cathode Discharge Ionization Mass Spectrometry: Detection, Quantification and Gas Phase Ion-Molecule Reactions of Explosives and Related Compounds. Crit Rev Anal Chem 2024; 54:148-174. [PMID: 35467991 DOI: 10.1080/10408347.2022.2067467] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Abstract
Mass spectrometry (MS) has become an essential analytical method in every sector of science and technology. Because of its unique ability to provide direct molecular structure information on analytes, an extra method is rarely required. This review describes fabrication of a variable-pressure hollow cathode discharge (HCD) ion source for MS in detection, quantification and investigation of gas-phase ion molecule reactions of explosives and related compounds using air as a carrier gas. The HCD ion source has been designed in such a way that by altering the ion source pressures, the system can generate both HCD and conventional GD. This design enables for the selective detection and quantification of explosives at trace to ultra-trace levels. The pressure-dependent HCD ion source has also been used to investigate ion-molecule reactions in the gas phase of explosives and related compounds. The mechanism of ion formation in explosive reactions is also discussed.
Collapse
Affiliation(s)
- Huanhuan Hong
- The Research Institute of Advanced Technologies, Ningbo University, Ningbo, Zhejiang, China
- China Innovation Instrument Co., Ltd, Ningbo, Zhejiang, China
| | - Ahsan Habib
- The Research Institute of Advanced Technologies, Ningbo University, Ningbo, Zhejiang, China
- Department of Chemistry, University of Dhaka, Dhaka, Bangladesh
| | - Lei Bi
- The Research Institute of Advanced Technologies, Ningbo University, Ningbo, Zhejiang, China
- China Innovation Instrument Co., Ltd, Ningbo, Zhejiang, China
| | | | - Luhong Wen
- The Research Institute of Advanced Technologies, Ningbo University, Ningbo, Zhejiang, China
- China Innovation Instrument Co., Ltd, Ningbo, Zhejiang, China
| |
Collapse
|
2
|
Chatterjee S, Zaia J. Proteomics-based mass spectrometry profiling of SARS-CoV-2 infection from human nasopharyngeal samples. MASS SPECTROMETRY REVIEWS 2024; 43:193-229. [PMID: 36177493 PMCID: PMC9538640 DOI: 10.1002/mas.21813] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/20/2022] [Revised: 09/07/2022] [Accepted: 09/09/2022] [Indexed: 05/12/2023]
Abstract
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the cause of the on-going global pandemic of coronavirus disease 2019 (COVID-19) that continues to pose a significant threat to public health worldwide. SARS-CoV-2 encodes four structural proteins namely membrane, nucleocapsid, spike, and envelope proteins that play essential roles in viral entry, fusion, and attachment to the host cell. Extensively glycosylated spike protein efficiently binds to the host angiotensin-converting enzyme 2 initiating viral entry and pathogenesis. Reverse transcriptase polymerase chain reaction on nasopharyngeal swab is the preferred method of sample collection and viral detection because it is a rapid, specific, and high-throughput technique. Alternate strategies such as proteomics and glycoproteomics-based mass spectrometry enable a more detailed and holistic view of the viral proteins and host-pathogen interactions and help in detection of potential disease markers. In this review, we highlight the use of mass spectrometry methods to profile the SARS-CoV-2 proteome from clinical nasopharyngeal swab samples. We also highlight the necessity for a comprehensive glycoproteomics mapping of SARS-CoV-2 from biological complex matrices to identify potential COVID-19 markers.
Collapse
Affiliation(s)
- Sayantani Chatterjee
- Department of Biochemistry, Center for Biomedical Mass SpectrometryBoston University School of MedicineBostonMassachusettsUSA
| | - Joseph Zaia
- Department of Biochemistry, Center for Biomedical Mass SpectrometryBoston University School of MedicineBostonMassachusettsUSA
- Bioinformatics ProgramBoston University School of MedicineBostonMassachusettsUSA
| |
Collapse
|
3
|
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.
Collapse
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.
| |
Collapse
|
4
|
Thakur A, Sharma V, Averbek S, Liang L, Pandya N, Kumar G, Cili A, Zhang K. Immune landscape and redox imbalance during neurological disorders in COVID-19. Cell Death Dis 2023; 14:593. [PMID: 37673862 PMCID: PMC10482955 DOI: 10.1038/s41419-023-06102-6] [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: 03/21/2023] [Revised: 08/13/2023] [Accepted: 08/22/2023] [Indexed: 09/08/2023]
Abstract
The outbreak of Coronavirus Disease 2019 (COVID-19) has prompted the scientific community to explore potential treatments or vaccines against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus that causes the illness. While SARS-CoV-2 is mostly considered a respiratory pathogen, several neurological complications have been reported, raising questions about how it may enter the Central Nervous System (CNS). Receptors such as ACE2, CD147, TMPRSS2, and NRP1 have been identified in brain cells and may be involved in facilitating SARS-CoV-2 entry into the CNS. Moreover, proteins like P2X7 and Panx-1 may contribute to the pathogenesis of COVID-19. Additionally, the role of the immune system in the gravity of COVID-19 has been investigated with respect to both innate and adaptive immune responses caused by SARS-CoV-2 infection, which can lead to a cytokine storm, tissue damage, and neurological manifestations. A redox imbalance has also been linked to the pathogenesis of COVID-19, potentially causing mitochondrial dysfunction, and generating proinflammatory cytokines. This review summarizes different mechanisms of reactive oxygen species and neuro-inflammation that may contribute to the development of severe COVID-19, and recent progress in the study of immunological events and redox imbalance in neurological complications of COVID-19, and the role of bioinformatics in the study of neurological implications of COVID-19.
Collapse
Affiliation(s)
- Abhimanyu Thakur
- Centre for Regenerative Medicine and Health, Hong Kong Institute of Science and Innovation-CAS Limited, Hong Kong SAR, Hong Kong.
| | - Vartika Sharma
- Department of Molecular and Human Genetics, Institute of Science, Banaras Hindu University, Varanasi, Uttar Pradesh, India
| | - Sera Averbek
- GSI Helmholtzzentrum für Schwerionenforschung GmbH, Darmstadt, Germany
- Technische Universität Darmstadt, Darmstadt, Germany
| | - Lifan Liang
- University of Pittsburgh, Pittsburgh, PA, USA
| | - Nirali Pandya
- Department of Chemistry, Faculty of Sciences, National University of Singapore, Singapore, Singapore
| | - Gaurav Kumar
- School of Biosciences and Biomedical Engineering, Department of Clinical Research, Galgotias University, Greater Noida, Uttar Pradesh, India
| | - Alma Cili
- Clinic of Hematology, University of Medicine, University Hospital center "Mother Teresa", Tirane, Albania
| | - Kui Zhang
- State Key Laboratory of Resource Insects, College of Sericulture, Textile and Biomass sciences, Southwest University, Chongqing, China.
- Cancer Centre, Medical Research Institute, Southwest University, Chongqing, China.
| |
Collapse
|
5
|
Moore JL, Patterson NH, Norris JL, Caprioli RM. Prospective on Imaging Mass Spectrometry in Clinical Diagnostics. Mol Cell Proteomics 2023; 22:100576. [PMID: 37209813 PMCID: PMC10545939 DOI: 10.1016/j.mcpro.2023.100576] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2023] [Revised: 05/10/2023] [Accepted: 05/12/2023] [Indexed: 05/22/2023] Open
Abstract
Imaging mass spectrometry (IMS) is a molecular technology utilized for spatially driven research, providing molecular maps from tissue sections. This article reviews matrix-assisted laser desorption ionization (MALDI) IMS and its progress as a primary tool in the clinical laboratory. MALDI mass spectrometry has been used to classify bacteria and perform other bulk analyses for plate-based assays for many years. However, the clinical application of spatial data within a tissue biopsy for diagnoses and prognoses is still an emerging opportunity in molecular diagnostics. This work considers spatially driven mass spectrometry approaches for clinical diagnostics and addresses aspects of new imaging-based assays that include analyte selection, quality control/assurance metrics, data reproducibility, data classification, and data scoring. It is necessary to implement these tasks for the rigorous translation of IMS to the clinical laboratory; however, this requires detailed standardized protocols for introducing IMS into the clinical laboratory to deliver reliable and reproducible results that inform and guide patient care.
Collapse
Affiliation(s)
| | - Nathan Heath Patterson
- Frontier Diagnostics, Nashville, Tennessee, USA; Vanderbilt University Mass Spectrometry Research Center, Vanderbilt University, Nashville, Tennessee, USA
| | - Jeremy L Norris
- Frontier Diagnostics, Nashville, Tennessee, USA; Vanderbilt University Mass Spectrometry Research Center, Vanderbilt University, Nashville, Tennessee, USA
| | - Richard M Caprioli
- Frontier Diagnostics, Nashville, Tennessee, USA; Vanderbilt University Mass Spectrometry Research Center, Vanderbilt University, Nashville, Tennessee, USA; Departments of Biochemistry, Pharmacology, Chemistry, and Medicine, Vanderbilt University, Nashville, Tennessee, USA.
| |
Collapse
|
6
|
di Flora DC, Dionizio A, Pereira HABS, Garbieri TF, Grizzo LT, Dionisio TJ, Leite ADL, Silva-Costa LC, Buzalaf NR, Reis FN, Pereira VBR, Rosa DMC, Dos Santos CF, Buzalaf MAR. Analysis of Plasma Proteins Involved in Inflammation, Immune Response/Complement System, and Blood Coagulation upon Admission of COVID-19 Patients to Hospital May Help to Predict the Prognosis of the Disease. Cells 2023; 12:1601. [PMID: 37371071 DOI: 10.3390/cells12121601] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2023] [Revised: 06/02/2023] [Accepted: 06/05/2023] [Indexed: 06/29/2023] Open
Abstract
The development of new approaches allowing for the early assessment of COVID-19 cases that are likely to become critical and the discovery of new therapeutic targets are urgently required. In this prospective cohort study, we performed proteomic and laboratory profiling of plasma from 163 COVID-19 patients admitted to Bauru State Hospital (Brazil) between 4 May 2020 and 4 July 2020. Plasma samples were collected upon admission for routine laboratory analyses and shotgun quantitative label-free proteomics. Based on the course of the disease, the patients were divided into three groups: (a) mild (n = 76) and (b) severe (n = 56) symptoms, whose patients were discharged without or with admission to an intensive care unit (ICU), respectively, and (c) critical (n = 31), a group consisting of patients who died after admission to an ICU. Based on our data, potential therapies for COVID-19 should target proteins involved in inflammation, the immune response and complement system, and blood coagulation. Other proteins that could potentially be employed in therapies against COVID-19 but that so far have not been associated with the disease are CD5L, VDBP, A1BG, C4BPA, PGLYRP2, SERPINC1, and APOH. Targeting these proteins' pathways might constitute potential new therapies or biomarkers of prognosis of the disease.
Collapse
Affiliation(s)
- Daniele Castro di Flora
- Department of Biological Sciences, Bauru School of Dentistry, University of São Paulo, Bauru 17012-901, Brazil
- Therapy and Diagnosis Unit, Bauru State Hospital, Bauru 17033-360, Brazil
| | - Aline Dionizio
- Department of Biological Sciences, Bauru School of Dentistry, University of São Paulo, Bauru 17012-901, Brazil
| | | | - Thais Francini Garbieri
- Department of Biological Sciences, Bauru School of Dentistry, University of São Paulo, Bauru 17012-901, Brazil
| | - Larissa Tercilia Grizzo
- Department of Biological Sciences, Bauru School of Dentistry, University of São Paulo, Bauru 17012-901, Brazil
| | - Thiago José Dionisio
- Department of Biological Sciences, Bauru School of Dentistry, University of São Paulo, Bauru 17012-901, Brazil
| | - Aline de Lima Leite
- Nebraska Center for Integrated Biomolecular Communication, University of Nebraska-Lincoln, Lincoln, NE 68503, USA
| | - Licia C Silva-Costa
- Laboratory of Neuroproteomics, Institute of Biology, Department of Biochemistry and Tissue Biology, University of Campinas, Campinas 13083-862, Brazil
| | - Nathalia Rabelo Buzalaf
- Department of Biological Sciences, Bauru School of Dentistry, University of São Paulo, Bauru 17012-901, Brazil
| | - Fernanda Navas Reis
- Department of Biological Sciences, Bauru School of Dentistry, University of São Paulo, Bauru 17012-901, Brazil
| | | | | | - Carlos Ferreira Dos Santos
- Department of Biological Sciences, Bauru School of Dentistry, University of São Paulo, Bauru 17012-901, Brazil
| | | |
Collapse
|
7
|
Guest PC, Hawkins SFC, Rahmoune H. Rapid Detection of SARS-CoV-2 Variants of Concern by Genomic Surveillance Techniques. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2023; 1412:491-509. [PMID: 37378785 DOI: 10.1007/978-3-031-28012-2_27] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/29/2023]
Abstract
This chapter describes the application of genomic, transcriptomic, proteomic, and metabolomic methods in the study of SARS-CoV-2 variants of concern. We also describe the important role of machine learning tools to identify the most significant biomarker signatures and discuss the latest point-of-care devices that can be used to translate these findings to the physician's office or to bedside care. The main emphasis is placed on increasing our diagnostic capacity and predictability of disease outcomes to guide the most appropriate treatment strategies.
Collapse
Affiliation(s)
- Paul C Guest
- Laboratory of Neuroproteomics, Department of Biochemistry and Tissue Biology, Institute of Biology, University of Campinas (UNICAMP), Campinas, Brazil
- Department of Psychiatry, Otto-von-Guericke-University Magdeburg, Magdeburg, Germany
- Laboratory of Translational Psychiatry, Otto-von-Guericke-University Magdeburg, Magdeburg, Germany
| | | | - Hassan Rahmoune
- Department of Chemical Engineering and Biotechnology, University of Cambridge, Cambridge, UK
| |
Collapse
|
8
|
Kistenev YV, Vrazhnov DA, Shnaider EE, Zuhayri H. Predictive models for COVID-19 detection using routine blood tests and machine learning. Heliyon 2022; 8:e11185. [PMID: 36311357 PMCID: PMC9595489 DOI: 10.1016/j.heliyon.2022.e11185] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2022] [Revised: 03/25/2022] [Accepted: 10/16/2022] [Indexed: 11/06/2022] Open
Abstract
The problem of accurate, fast, and inexpensive COVID-19 tests has been urgent till now. Standard COVID-19 tests need high-cost reagents and specialized laboratories with high safety requirements, are time-consuming. Data of routine blood tests as a base of SARS-CoV-2 invasion detection allows using the most practical medicine facilities. But blood tests give general information about a patient’s state, which is not directly associated with COVID-19. COVID-19-specific features should be selected from the list of standard blood characteristics, and decision-making software based on appropriate clinical data should be created. This review describes the abilities to develop predictive models for COVID-19 detection using routine blood tests and machine learning.
Collapse
|
9
|
Spectroscopic methods for COVID-19 detection and early diagnosis. Virol J 2022; 19:152. [PMID: 36138463 PMCID: PMC9502632 DOI: 10.1186/s12985-022-01867-2] [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: 04/16/2022] [Accepted: 08/16/2022] [Indexed: 11/10/2022] Open
Abstract
The coronavirus pandemic is a worldwide hazard that poses a threat to millions of individuals throughout the world. This pandemic is caused by the severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2), which was initially identified in Wuhan, China's Hubei provincial capital, and has since spread throughout the world. According to the World Health Organization's Weekly Epidemiological Update, there were more than 250 million documented cases of coronavirus infections globally, with five million fatalities. Early detection of coronavirus does not only reduce the spread of the virus, but it also increases the chance of curing the infection. Spectroscopic techniques have been widely used in the early detection and diagnosis of COVID-19 using Raman, Infrared, mass spectrometry and fluorescence spectroscopy. In this review, the reported spectroscopic methods for COVID-19 detection were discussed with emphasis on the practical aspects, limitations and applications.
Collapse
|
10
|
Zhang W, Li D, Xu B, Xu L, Lyu Q, Liu X, Li Z, Zhang J, Sun W, Ma Q, Qiao L, Liao P. Serum peptidome profiles immune response of COVID-19 Vaccine administration. Front Immunol 2022; 13:956369. [PMID: 36091008 PMCID: PMC9450691 DOI: 10.3389/fimmu.2022.956369] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2022] [Accepted: 08/01/2022] [Indexed: 11/13/2022] Open
Abstract
BackgroundCoronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused significant loss of life and property. In response to the serious pandemic, recently developed vaccines against SARS-CoV-2 have been administrated to the public. Nevertheless, the research on human immunization response against COVID-19 vaccines is insufficient. Although much information associated with vaccine efficacy, safety and immunogenicity has been reported by pharmaceutical companies based on laboratory studies and clinical trials, vaccine evaluation needs to be extended further to better understand the effect of COVID-19 vaccines on human beings.MethodsWe performed a comparative peptidome analysis on serum samples from 95 participants collected at four time points before and after receiving CoronaVac. The collected serum samples were analyzed by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) to profile the serum peptides, and also subjected to humoral and cellular immune response analyses to obtain typical immunogenicity information.ResultsSignificant difference in serum peptidome profiles by MALDI-TOF MS was observed after vaccination. By supervised statistical analysis, a total of 13 serum MALDI-TOF MS feature peaks were obtained on day 28 and day 42 of vaccination. The feature peaks were identified as component C1q receptor, CD59 glycoprotein, mannose-binding protein C, platelet basic protein, CD99 antigen, Leucine-rich alpha-2-glycoprotein, integral membrane protein 2B, platelet factor 4 and hemoglobin subunits. Combining with immunogenicity analysis, the study provided evidence for the humoral and cellular immune responses activated by CoronaVac. Furthermore, we found that it is possible to distinguish neutralizing antibody (NAbs)-positive from NAbs-negative individuals after complete vaccination using the serum peptidome profiles by MALDI-TOF MS together with machine learning methods, including random forest (RF), partial least squares-discriminant analysis (PLS-DA), linear support vector machine (SVM) and logistic regression (LR).ConclusionsThe study shows the promise of MALDI-TOF MS-based serum peptidome analysis for the assessment of immune responses activated by COVID-19 vaccination, and discovered a panel of serum peptides biomarkers for COVID-19 vaccination and for NAbs generation. The method developed in this study can help not only in the development of new vaccines, but also in the post-marketing evaluation of developed vaccines.
Collapse
Affiliation(s)
- Wenjia Zhang
- Department of Clinical Laboratory, Chongqing General Hospital, Chongqing, China
| | - Dandan Li
- Department of Chemistry, Fudan University, Shanghai, China
| | - Bin Xu
- Bioyong Technologics, Inc., Beijing, China
| | - Lanlan Xu
- Department of Clinical Laboratory, Chongqing General Hospital, Chongqing, China
| | - Qian Lyu
- Bioyong Technologics, Inc., Beijing, China
| | - Xiangyi Liu
- Department of Laboratory Medicine, Beijing Tongren Hospital, Capital Medical University, Beijing, China
| | - Zhijie Li
- Department of Clinical Laboratory, Chongqing General Hospital, Chongqing, China
| | - Jian Zhang
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, Beijing, China
| | - Wei Sun
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, Beijing, China
| | - Qingwei Ma
- Bioyong Technologics, Inc., Beijing, China
| | - Liang Qiao
- Department of Chemistry, Fudan University, Shanghai, China
- *Correspondence: Pu Liao, ; Liang Qiao,
| | - Pu Liao
- Department of Clinical Laboratory, Chongqing General Hospital, Chongqing, China
- *Correspondence: Pu Liao, ; Liang Qiao,
| |
Collapse
|
11
|
de Almeida C, Motta LC, Folli GS, Marcarini WD, Costa CA, Vilela ACS, Barauna VG, Martin FL, Singh MN, Campos LCG, Costa NL, Vassallo PF, Chaves AR, Endringer DC, Mill JG, Filgueiras PR, Romão W. MALDI(+) FT-ICR Mass Spectrometry (MS) Combined with Machine Learning toward Saliva-Based Diagnostic Screening for COVID-19. J Proteome Res 2022; 21:1868-1875. [PMID: 35880262 PMCID: PMC9344790 DOI: 10.1021/acs.jproteome.2c00148] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2022] [Indexed: 11/28/2022]
Abstract
Rapid identification of existing respiratory viruses in biological samples is of utmost importance in strategies to combat pandemics. Inputting MALDI FT-ICR MS (matrix-assisted laser desorption/ionization Fourier-transform ion cyclotron resonance mass spectrometry) data output into machine learning algorithms could hold promise in classifying positive samples for SARS-CoV-2. This study aimed to develop a fast and effective methodology to perform saliva-based screening of patients with suspected COVID-19, using the MALDI FT-ICR MS technique with a support vector machine (SVM). In the method optimization, the best sample preparation was obtained with the digestion of saliva in 10 μL of trypsin for 2 h and the MALDI analysis, which presented a satisfactory resolution for the analysis with 1 M. SVM models were created with data from the analysis of 97 samples that were designated as SARS-CoV-2 positives versus 52 negatives, confirmed by RT-PCR tests. SVM1 and SVM2 models showed the best results. The calibration group obtained 100% accuracy, and the test group 95.6% (SVM1) and 86.7% (SVM2). SVM1 selected 780 variables and has a false negative rate (FNR) of 0%, while SVM2 selected only two variables with a FNR of 3%. The proposed methodology suggests a promising tool to aid screening for COVID-19.
Collapse
Affiliation(s)
- Camila
M. de Almeida
- Chemistry
Department, Federal University of Espírito
Santo, Vitória, ES 29040-090, Brazil
| | - Larissa C. Motta
- Chemistry
Department, Federal University of Espírito
Santo, Vitória, ES 29040-090, Brazil
| | - Gabriely S. Folli
- Chemistry
Department, Federal University of Espírito
Santo, Vitória, ES 29040-090, Brazil
| | - Wena D. Marcarini
- Department
of Physiological Sciences, Federal University
of Espírito Santo, Vitória, ES 29040-090, Brazil
| | - Camila A. Costa
- School
of Dentistry, Department of Stomatology (Oral Pathology), Federal University of Goiás, Goiânia, GO 74000-000, Brazil
| | - Ana C. S. Vilela
- School
of Dentistry, Department of Stomatology (Oral Pathology), Federal University of Goiás, Goiânia, GO 74000-000, Brazil
| | - Valério G. Barauna
- Department
of Physiological Sciences, Federal University
of Espírito Santo, Vitória, ES 29040-090, Brazil
| | | | - Maneesh N. Singh
- Biocel
UK Ltd., 15 Riplingham
Road, West Ella, Hull HU10
6TS, U.K.
| | - Luciene C. G. Campos
- Department
of Biological Science, Santa Cruz State
University, Ilhéus, BA 45662-900, Brazil
| | - Nádia L. Costa
- School
of Dentistry, Department of Stomatology (Oral Pathology), Federal University of Goiás, Goiânia, GO 74000-000, Brazil
| | - Paula F. Vassallo
- Clinical
Hospital, Federal University of Minas Gerais, Belo Horizonte, MG 31270-901, Brazil
| | - Andrea R. Chaves
- Chromatography
and Mass Spectrometry Laboratory, Institute of Chemistry, Federal University of Goiás, Goiânia, GO 74690-900, Brazil
| | - Denise C. Endringer
- Pharmaceutical
Science Graduate Program, Universidade Vila
Velha, Vila Velha, ES 29106-010, Brazil
| | - José G. Mill
- Department
of Physiological Sciences, Federal University
of Espírito Santo, Vitória, ES 29040-090, Brazil
| | - Paulo R. Filgueiras
- Chemistry
Department, Federal University of Espírito
Santo, Vitória, ES 29040-090, Brazil
| | - Wanderson Romão
- Chemistry
Department, Federal University of Espírito
Santo, Vitória, ES 29040-090, Brazil
- Science
Department, Federal Institute of Education,
Science, and Technology of Espírito Santo, Vila Velha, ES 29106-010, Brazil
| |
Collapse
|
12
|
Tsai H, Phinney BS, Grigorean G, Salemi MR, Rashidi HH, Pepper J, Tran NK. Identification of Endogenous Peptides in Nasal Swab Transport Media used in MALDI-TOF-MS Based COVID-19 Screening. ACS OMEGA 2022; 7:17462-17471. [PMID: 35600141 PMCID: PMC9113002 DOI: 10.1021/acsomega.2c01864] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/28/2022] [Accepted: 04/18/2022] [Indexed: 06/15/2023]
Abstract
Mass spectrometry (MS) based diagnostic detection of 2019 novel coronavirus infectious disease (COVID-19) has been postulated to be a useful alternative to classical PCR based diagnostics. These MS based approaches have the potential to be both rapid and sensitive and can be done on-site without requiring a dedicated laboratory or depending on constrained supply chains (i.e., reagents and consumables). Matrix-assisted laser desorption ionization (MALDI)-time-of-flight (TOF) MS has a long and established history of microorganism detection and systemic disease assessment. Previously, we have shown that automated machine learning (ML) enhanced MALDI-TOF-MS screening of nasal swabs can be both sensitive and specific for COVID-19 detection. The underlying molecules responsible for this detection are generally unknown nor are they required for this automated ML platform to detect COVID-19. However, the identification of these molecules is important for understanding both the mechanism of detection and potentially the biology of the underlying infection. Here, we used nanoscale liquid chromatography tandem MS to identify endogenous peptides found in nasal swab saline transport media to identify peptides in the same the mass over charge (m/z) values observed by the MALDI-TOF-MS method. With our peptidomics workflow, we demonstrate that we can identify endogenous peptides and endogenous protease cut sites. Further, we show that SARS-CoV-2 viral peptides were not readily detected and are highly unlikely to be responsible for the accuracy of MALDI based SARS-CoV-2 diagnostics. Further analysis with more samples will be needed to validate our findings, but the methodology proves to be promising.
Collapse
Affiliation(s)
- Helen Tsai
- Proteomics
Core, University of California, Davis, 451 E. Health Sciences Dr., Davis, California 95616, United States
| | - Brett S. Phinney
- Proteomics
Core, University of California, Davis, 451 E. Health Sciences Dr., Davis, California 95616, United States
| | - Gabriela Grigorean
- Proteomics
Core, University of California, Davis, 451 E. Health Sciences Dr., Davis, California 95616, United States
| | - Michelle R. Salemi
- Proteomics
Core, University of California, Davis, 451 E. Health Sciences Dr., Davis, California 95616, United States
| | - Hooman H. Rashidi
- Department
of Pathology and Laboratory Medicine, University
of California, Davis, 4400 V St., Sacramento, California 95817, United States
| | - John Pepper
- SpectraPass,
LLC, 1980 Festival Plaza,
Suite 770, Las Vegas, Nevada 89135, United States
- Allegiant
Air, 1201 North Town
Center Drive, Las Vegas, Nevada 89144, United
States
| | - Nam K. Tran
- Department
of Pathology and Laboratory Medicine, University
of California, Davis, 4400 V St., Sacramento, California 95817, United States
| |
Collapse
|
13
|
Lazari LC, Zerbinati RM, Rosa-Fernandes L, Santiago VF, Rosa KF, Angeli CB, Schwab G, Palmieri M, Sarmento DJS, Marinho CRF, Almeida JD, To K, Giannecchini S, Wrenger C, Sabino EC, Martinho H, Lindoso JAL, Durigon EL, Braz-Silva PH, Palmisano G. MALDI-TOF mass spectrometry of saliva samples as a prognostic tool for COVID-19. J Oral Microbiol 2022; 14:2043651. [PMID: 35251522 PMCID: PMC8890567 DOI: 10.1080/20002297.2022.2043651] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/02/2022] Open
Abstract
Background Methods Results Conclusion
Collapse
Affiliation(s)
- Lucas C. Lazari
- GlycoProteomics Laboratory, Department of Parasitology, ICB, University of São Paulo, São Paulo, Brazil
| | - Rodrigo M. Zerbinati
- Laboratory of Virology (LIM-52-HC-FMUSP), Institute of Tropical Medicine of São Paulo, School of Medicine, University of São Paulo, São Paulo, Brazil
| | - Livia Rosa-Fernandes
- GlycoProteomics Laboratory, Department of Parasitology, ICB, University of São Paulo, São Paulo, Brazil
- Laboratory of Experimental Immunoparasitology, Department of Parasitology, ICB, University of São Paulo, São Paulo, Brazil
| | - Veronica Feijoli Santiago
- GlycoProteomics Laboratory, Department of Parasitology, ICB, University of São Paulo, São Paulo, Brazil
| | - Klaise F. Rosa
- GlycoProteomics Laboratory, Department of Parasitology, ICB, University of São Paulo, São Paulo, Brazil
| | - Claudia B. Angeli
- GlycoProteomics Laboratory, Department of Parasitology, ICB, University of São Paulo, São Paulo, Brazil
| | - Gabriela Schwab
- Laboratory of Virology (LIM-52-HC-FMUSP), Institute of Tropical Medicine of São Paulo, School of Medicine, University of São Paulo, São Paulo, Brazil
| | - Michelle Palmieri
- Department of Stomatology, School of Dentistry, University of São Paulo, São Paulo, Brazil
| | - Dmitry J. S. Sarmento
- Department of Stomatology, School of Dentistry, University of São Paulo, São Paulo, Brazil
| | - Claudio R. F. Marinho
- Laboratory of Experimental Immunoparasitology, Department of Parasitology, ICB, University of São Paulo, São Paulo, Brazil
| | - Janete Dias Almeida
- Department of Biosciences and Oral Diagnosis, Institute of Science and Technology, São Paulo State University, São José dos Campos, Brazil
| | - Kelvin To
- State Key Laboratory for Emerging Infectious Diseases, Department of Microbiology, Carol Yu Centre for Infection, Li KaShing Faculty of Medicine of the University of Hong Kong, Hong Kong, Special Administrative Region, China
| | - Simone Giannecchini
- Department of Experimental and Clinical Medicine, University of Florence, Florence, Italy
| | - Carsten Wrenger
- Unit for Drug Discovery, Department of Parasitology, ICB, University of São Paulo, São Paulo, Brazil
| | - Ester C. Sabino
- Institute of Tropical Medicine of São Paulo, School of Medicine, University of São Paulo, São Paulo, Brazil
| | - Herculano Martinho
- Centro de Ciencias Naturais e Humanas, Universidade Federal do ABC, Santo André, Brazil
| | - José A. L. Lindoso
- Institute of Infectious Diseases Emílio Ribas, São Paulo, Brazil
- Laboratory of Protozoology (LIM-49-HC-FMUSP), Institute of Tropical Medicine of São Paulo, School of Medicine, University of São Paulo, São Paulo, Brazil
- Department of Infectious Diseases, School of Medicine, University of São Paulo, São Paulo, Brazil
| | - Edison L. Durigon
- Laboratory of Clinical and Molecular Virology, Department of Microbiology, ICB, University of São Paulo, São Paulo, Brazil
| | - Paulo H. Braz-Silva
- Laboratory of Virology (LIM-52-HC-FMUSP), Institute of Tropical Medicine of São Paulo, School of Medicine, University of São Paulo, São Paulo, Brazil
- Department of Stomatology, School of Dentistry, University of São Paulo, São Paulo, Brazil
| | - Giuseppe Palmisano
- GlycoProteomics Laboratory, Department of Parasitology, ICB, University of São Paulo, São Paulo, Brazil
| |
Collapse
|
14
|
Costa MM, Martin H, Estellon B, Dupé FX, Saby F, Benoit N, Tissot-Dupont H, Million M, Pradines B, Granjeaud S, Almeras L. Exploratory Study on Application of MALDI-TOF-MS to Detect SARS-CoV-2 Infection in Human Saliva. J Clin Med 2022; 11:295. [PMID: 35053990 PMCID: PMC8781148 DOI: 10.3390/jcm11020295] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2021] [Revised: 12/16/2021] [Accepted: 12/31/2021] [Indexed: 12/24/2022] Open
Abstract
SARS-CoV-2 has caused a large outbreak since its emergence in December 2019. COVID-19 diagnosis became a priority so as to isolate and treat infected individuals in order to break the contamination chain. Currently, the reference test for COVID-19 diagnosis is the molecular detection (RT-qPCR) of the virus from nasopharyngeal swab (NPS) samples. Although this sensitive and specific test remains the gold standard, it has several limitations, such as the invasive collection method, the relative high cost and the duration of the test. Moreover, the material shortage to perform tests due to the discrepancy between the high demand for tests and the production capacities puts additional constraints on RT-qPCR. Here, we propose a PCR-free method for diagnosing SARS-CoV-2 based on matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) profiling and machine learning (ML) models from salivary samples. Kinetic saliva samples were collected at enrollment and ten and thirty days later (D0, D10 and D30), to assess the classification performance of the ML models compared to the molecular tests performed on NPS specimens. Spectra were generated using an optimized protocol of saliva collection and successive quality control steps were developed to ensure the reliability of spectra. A total of 360 averaged spectra were included in the study. At D0, the comparison of MS spectra from SARS-CoV-2 positive patients (n = 105) with healthy healthcare controls (n = 51) revealed nine peaks that significantly distinguished the two groups. Among the five ML models tested, support vector machine with linear kernel (SVM-LK) provided the best performance on the training dataset (accuracy = 85.2%, sensitivity = 85.1%, specificity = 85.3%, F1-Score = 85.1%). The application of the SVM-LK model on independent datasets confirmed its performances with 88.9% and 80.8% of correct classification for samples collected at D0 and D30, respectively. Conversely, at D10, the proportion of correct classification had fallen to 64.3%. The analysis of saliva samples by MALDI-TOF MS and ML appears as an interesting supplementary tool for COVID-19 diagnosis, despite the mitigated results obtained for convalescent patients (D10).
Collapse
Affiliation(s)
- Monique Melo Costa
- Unité Parasitologie et Entomologie, Département Microbiologie et Maladies Infectieuses, Institut de Recherche Biomédicale des Armées, 91220 Marseille, France; (M.M.C.); (H.M.); (F.S.); (N.B.); (B.P.)
- Aix-Marseille University, IRD, SSA, AP-HM, VITROME, 13005 Marseille, France
- IHU Méditerranée Infection, 13005 Marseille, France; (H.T.-D.); (M.M.)
| | - Hugo Martin
- Unité Parasitologie et Entomologie, Département Microbiologie et Maladies Infectieuses, Institut de Recherche Biomédicale des Armées, 91220 Marseille, France; (M.M.C.); (H.M.); (F.S.); (N.B.); (B.P.)
- Aix-Marseille University, IRD, SSA, AP-HM, VITROME, 13005 Marseille, France
- IHU Méditerranée Infection, 13005 Marseille, France; (H.T.-D.); (M.M.)
| | - Bertrand Estellon
- Laboratoire d’Informatique et Systèmes, Aix-Marseille University, CNRS, University de Toulon, 13013 Marseille, France; (B.E.); (F.-X.D.)
| | - François-Xavier Dupé
- Laboratoire d’Informatique et Systèmes, Aix-Marseille University, CNRS, University de Toulon, 13013 Marseille, France; (B.E.); (F.-X.D.)
| | - Florian Saby
- Unité Parasitologie et Entomologie, Département Microbiologie et Maladies Infectieuses, Institut de Recherche Biomédicale des Armées, 91220 Marseille, France; (M.M.C.); (H.M.); (F.S.); (N.B.); (B.P.)
- Aix-Marseille University, IRD, SSA, AP-HM, VITROME, 13005 Marseille, France
- IHU Méditerranée Infection, 13005 Marseille, France; (H.T.-D.); (M.M.)
| | - Nicolas Benoit
- Unité Parasitologie et Entomologie, Département Microbiologie et Maladies Infectieuses, Institut de Recherche Biomédicale des Armées, 91220 Marseille, France; (M.M.C.); (H.M.); (F.S.); (N.B.); (B.P.)
- Aix-Marseille University, IRD, SSA, AP-HM, VITROME, 13005 Marseille, France
- IHU Méditerranée Infection, 13005 Marseille, France; (H.T.-D.); (M.M.)
- Centre National de Référence du Paludisme, 13005 Marseille, France
| | - Hervé Tissot-Dupont
- IHU Méditerranée Infection, 13005 Marseille, France; (H.T.-D.); (M.M.)
- Aix-Marseille University, IRD, AP-HM, MEPHI, 13005 Marseille, France
| | - Matthieu Million
- IHU Méditerranée Infection, 13005 Marseille, France; (H.T.-D.); (M.M.)
- Aix-Marseille University, IRD, AP-HM, MEPHI, 13005 Marseille, France
| | - Bruno Pradines
- Unité Parasitologie et Entomologie, Département Microbiologie et Maladies Infectieuses, Institut de Recherche Biomédicale des Armées, 91220 Marseille, France; (M.M.C.); (H.M.); (F.S.); (N.B.); (B.P.)
- Aix-Marseille University, IRD, SSA, AP-HM, VITROME, 13005 Marseille, France
- IHU Méditerranée Infection, 13005 Marseille, France; (H.T.-D.); (M.M.)
- Centre National de Référence du Paludisme, 13005 Marseille, France
| | - Samuel Granjeaud
- CRCM Integrative Bioinformatics Platform, Centre de Recherche en Cancérologie de Marseille, INSERM, U1068, Institut Paoli-Calmettes, CNRS, UMR7258, Aix-Marseille Université UM 105, 13009 Marseille, France;
| | - Lionel Almeras
- Unité Parasitologie et Entomologie, Département Microbiologie et Maladies Infectieuses, Institut de Recherche Biomédicale des Armées, 91220 Marseille, France; (M.M.C.); (H.M.); (F.S.); (N.B.); (B.P.)
- Aix-Marseille University, IRD, SSA, AP-HM, VITROME, 13005 Marseille, France
- IHU Méditerranée Infection, 13005 Marseille, France; (H.T.-D.); (M.M.)
| |
Collapse
|
15
|
Guest PC, Rahmoune H. Antibody-Based Affinity Capture Combined with LC-MS Analysis for Identification of COVID-19 Disease Serum Biomarkers. Methods Mol Biol 2022; 2511:183-200. [PMID: 35838961 DOI: 10.1007/978-1-0716-2395-4_14] [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: 06/15/2023]
Abstract
Blood serum or plasma proteins are potentially useful in COVID-19 research as biomarkers for risk prediction, diagnosis, stratification, and treatment monitoring. However, serum protein-based biomarker identification and validation is complicated due to the wide concentration range of these proteins, which spans more than ten orders of magnitude. Here we present a combined affinity purification-liquid chromatography mass spectrometry approach which allows identification and quantitation of the most abundant serum proteins along with the nonspecifically bound and interaction proteins. This led to the reproducible identification of more than 100 proteins that were not specifically targeted by the affinity column. Many of these have already been implicated in COVID-19 disease.
Collapse
Affiliation(s)
- Paul C Guest
- Laboratory of Neuroproteomics, Department of Biochemistry and Tissue Biology, Institute of Biology, University of Campinas (UNICAMP), Campinas, Brazil.
| | - Hassan Rahmoune
- Department of Chemical Engineering & Biotechnology, University of Cambridge, Cambridge, UK
| |
Collapse
|
16
|
Do T, Guran R, Adam V, Zitka O. Use of MALDI-TOF mass spectrometry for virus identification: a review. Analyst 2022; 147:3131-3154. [DOI: 10.1039/d2an00431c] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
The possibilities of virus identification, including SARS-CoV-2, by MALDI-TOF mass spectrometry are discussed in this review.
Collapse
Affiliation(s)
- Tomas Do
- Department of Chemistry and Biochemistry, Faculty of AgriSciences, Mendel University in Brno, Zemedelska 1, CZ-613 00 Brno, Czech Republic
| | - Roman Guran
- Department of Chemistry and Biochemistry, Faculty of AgriSciences, Mendel University in Brno, Zemedelska 1, CZ-613 00 Brno, Czech Republic
- Central European Institute of Technology, Brno University of Technology, Purkynova 656/123, CZ-612 00 Brno, Czech Republic
| | - Vojtech Adam
- Department of Chemistry and Biochemistry, Faculty of AgriSciences, Mendel University in Brno, Zemedelska 1, CZ-613 00 Brno, Czech Republic
- Central European Institute of Technology, Brno University of Technology, Purkynova 656/123, CZ-612 00 Brno, Czech Republic
| | - Ondrej Zitka
- Department of Chemistry and Biochemistry, Faculty of AgriSciences, Mendel University in Brno, Zemedelska 1, CZ-613 00 Brno, Czech Republic
- Central European Institute of Technology, Brno University of Technology, Purkynova 656/123, CZ-612 00 Brno, Czech Republic
| |
Collapse
|
17
|
Lazari LC, Rosa-Fernandes L, Palmisano G. Machine Learning Approaches to Analyze MALDI-TOF Mass Spectrometry Protein Profiles. Methods Mol Biol 2022; 2511:375-394. [PMID: 35838976 DOI: 10.1007/978-1-0716-2395-4_29] [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: 06/15/2023]
Abstract
Machine learning is being employed for the development of diagnostic methods for several diseases, but prognostic techniques are still poorly explored. The development of such approaches is essential to assist healthcare workers to ensure the most appropriate treatment for patients. In this chapter, we demonstrate a detailed protocol for the application of machine learning to MALDI-TOF MS spectra of COVID-19-infected plasma samples for risk classification and biomarker identification.
Collapse
Affiliation(s)
- Lucas C Lazari
- GlycoProteomics Laboratory, Department of Parasitology, ICB, University of São Paulo, Sao Paulo, Brazil
| | - Livia Rosa-Fernandes
- GlycoProteomics Laboratory, Department of Parasitology, ICB, University of São Paulo, Sao Paulo, Brazil
| | - Giuseppe Palmisano
- GlycoProteomics Laboratory, Department of Parasitology, ICB, University of São Paulo, Sao Paulo, Brazil.
| |
Collapse
|
18
|
Exploring COVID-19 pathogenesis on command-line: A bioinformatics pipeline for handling and integrating omics data. ADVANCES IN PROTEIN CHEMISTRY AND STRUCTURAL BIOLOGY 2022; 131:311-339. [PMID: 35871895 PMCID: PMC9095070 DOI: 10.1016/bs.apcsb.2022.04.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Abstract
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was first identified in late 2019 in Wuhan, China, and has proven to be highly pathogenic, making it a global public health threat. The immediate need to understand the mechanisms and impact of the virus made omics techniques stand out, as they can offer a holistic and comprehensive view of thousands of molecules in a single experiment. Mastering bioinformatics tools to process, analyze, integrate, and interpret omics data is a powerful knowledge to enrich results. We present a robust and open access computational pipeline for extracting information from quantitative proteomics and transcriptomics public data. We present the entire pipeline from raw data to differentially expressed genes. We explore processes and pathways related to mapped transcripts and proteins. A pipeline is presented to integrate and compare proteomics and transcriptomics data using also packages available in the Bioconductor and providing the codes used. Cholesterol metabolism, immune system activity, ECM, and proteasomal degradation pathways increased in infected patients. Leukocyte activation profile was overrepresented in both proteomics and transcriptomics data. Finally, we found a panel of proteins and transcripts regulated in the same direction in the lung transcriptome and plasma proteome that distinguish healthy and infected individuals. This panel of markers was confirmed in another cohort of patients, thus validating the robustness and functionality of the tools presented.
Collapse
|
19
|
Lazari LC, Rosa-Fernandes L, Palmisano G. Identification of Circulating Biomarkers of COVID-19 Using MALDI-TOF Mass Spectrometry. Methods Mol Biol 2022; 2511:175-182. [PMID: 35838960 DOI: 10.1007/978-1-0716-2395-4_13] [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: 06/15/2023]
Abstract
Matrix-assisted laser desorption/ionization source coupled with time-of-flight mass analyzer mass spectrometry (MALDI-TOF MS) is being widely used to obtain proteomic profiles for clinical purposes, as a fast, low-cost, robust, and efficient technique. Here we describe a method for biofluid analysis using MALDI-TOF MS for rapid acquisition of proteomic signatures of COVID-19 infected patients. By using solid-phase extraction, the method allows the analysis of biofluids in less than 15 min.
Collapse
Affiliation(s)
- Lucas C Lazari
- GlycoProteomics Laboratory, Department of Parasitology, ICB, University of São Paulo, São Paulo, Brazil
| | - Livia Rosa-Fernandes
- GlycoProteomics Laboratory, Department of Parasitology, ICB, University of São Paulo, São Paulo, Brazil
| | - Giuseppe Palmisano
- GlycoProteomics Laboratory, Department of Parasitology, ICB, University of São Paulo, São Paulo, Brazil.
| |
Collapse
|
20
|
Guest PC, Popovic D, Steiner J. Challenges of Multiplex Assays for COVID-19 Research: A Machine Learning Perspective. Methods Mol Biol 2022; 2511:37-50. [PMID: 35838950 DOI: 10.1007/978-1-0716-2395-4_3] [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: 06/15/2023]
Abstract
Multiplex assays that provide simultaneous measurement of multiple analytes in biological samples have now developed into widely used technologies in the study of diseases, drug discovery, and other medical areas. These approaches span multiple assay systems and can provide readouts of specific assay components with similar accuracy as the respective single assay measurements. Multiplexing allows the consumption of lower sample volumes, lower costs, and higher throughput compared with carrying out single assays. A number of recent studies have demonstrated the impact of multiplex assays in the study of the SARS-CoV-2 virus, the infectious agent responsible for the current COVID-19 pandemic. In this respect, machine learning techniques have proven to be highly valuable in capturing complex disease phenotypes and converting these insights into models which can be applied in real-world settings. This chapter gives an overview of opportunities and challenges of multiplexed biomarker analysis, with a focus on the use of machine learning aimed at identification of biological signatures for increasing our understanding of COVID-19 disease, and for improved diagnostics and prediction of disease outcomes.
Collapse
Affiliation(s)
- Paul C Guest
- Laboratory of Neuroproteomics, Department of Biochemistry and Tissue Biology, Institute of Biology, University of Campinas (UNICAMP), Campinas, Brazil.
| | - David Popovic
- Section of Forensic Psychiatry, Department of Psychiatry and Psychotherapy, Ludwig-Maximilian-University, Munich, Germany
- International Max Planck Research School for Translational Psychiatry (IMPRS-TP), Munich, Germany
| | - Johann Steiner
- Laboratory of Translational Psychiatry, Otto-von-Guericke-University Magdeburg, Magdeburg, Germany
- Department of Psychiatry, Otto-von-Guericke-University Magdeburg, Magdeburg, Germany
- Center for Behavioral Brain Sciences, Magdeburg, Germany
- German Center for Mental Health (DZP), Center for Intervention and Research on adaptive and maladaptive brain Circuits underlying mental health (C-I-R-C), Site Jena-Magdeburg-Halle, Magdeburg, Germany
| |
Collapse
|
21
|
Shekhawat JK, Banerjee M. OUP accepted manuscript. J Appl Lab Med 2022; 7:1175-1188. [PMID: 35723351 PMCID: PMC9278167 DOI: 10.1093/jalm/jfac040] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2022] [Accepted: 04/21/2022] [Indexed: 12/04/2022]
Abstract
Background COVID-19 is a highly contagious respiratory disease that can be transmitted through human exhaled breath. It has caused immense loss and has challenged the healthcare sector. It has affected the economy of countries and thereby affected numerous sectors. Analysis of human breath samples is an attractive strategy for rapid diagnosis of COVID-19 by monitoring breath biomarkers. Content Breath collection is a noninvasive process. Various technologies are employed for detection of breath biomarkers like mass spectrometry, biosensors, artificial learning, and machine learning. These tools have low turnaround time, robustness, and provide onsite results. Also, MS-based approaches are promising tools with high speed, specificity, sensitivity, reproducibility, and broader coverage, as well as its coupling with various chromatographic separation techniques providing better clinical and biochemical understanding of COVID-19 using breath samples. Summary Herein, we have tried to review the MS-based approaches as well as other techniques used for the analysis of breath samples for COVID-19 diagnosis. We have also highlighted the different breath analyzers being developed for COVID-19 detection.
Collapse
Affiliation(s)
- Jyoti Kanwar Shekhawat
- Department of Biochemistry, All India Institute of Medical Sciences, Jodhpur-342005, Rajasthan, India
| | - Mithu Banerjee
- Address correspondence to this author at: AIIMS, Road, MI Phase-2, Basni, Jodhpur, Rajasthan, India—342005. E-mail:
| |
Collapse
|
22
|
Villar M, Urra JM, Rodríguez-Del-Río FJ, Artigas-Jerónimo S, Jiménez-Collados N, Ferreras-Colino E, Contreras M, de Mera IGF, Estrada-Peña A, Gortázar C, de la Fuente J. Characterization by Quantitative Serum Proteomics of Immune-Related Prognostic Biomarkers for COVID-19 Symptomatology. Front Immunol 2021; 12:730710. [PMID: 34566994 PMCID: PMC8457011 DOI: 10.3389/fimmu.2021.730710] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2021] [Accepted: 08/19/2021] [Indexed: 12/22/2022] Open
Abstract
The COVID-19 pandemic caused by SARS-CoV-2 challenges the understanding of factors affecting disease progression and severity. The identification of prognostic biomarkers and physiological processes associated with disease symptoms is relevant for the development of new diagnostic and therapeutic interventions to contribute to the control of this pandemic. To address this challenge, in this study, we used a quantitative proteomics together with multiple data analysis algorithms to characterize serum protein profiles in five cohorts from healthy to SARS-CoV-2-infected recovered (hospital discharge), nonsevere (hospitalized), and severe [at the intensive care unit (ICU)] cases with increasing systemic inflammation in comparison with healthy individuals sampled prior to the COVID-19 pandemic. The results showed significantly dysregulated proteins and associated biological processes and disorders associated to COVID-19. These results corroborated previous findings in COVID-19 studies and highlighted how the representation of dysregulated serum proteins and associated BPs increases with COVID-19 disease symptomatology from asymptomatic to severe cases. The analysis was then focused on novel disease processes and biomarkers that were correlated with disease symptomatology. To contribute to translational medicine, results corroborated the predictive value of selected immune-related biomarkers for disease recovery [Selenoprotein P (SELENOP) and Serum paraoxonase/arylesterase 1 (PON1)], severity [Carboxypeptidase B2 (CBP2)], and symptomatology [Pregnancy zone protein (PZP)] using protein-specific ELISA tests. Our results contributed to the characterization of SARS-CoV-2–host molecular interactions with potential contributions to the monitoring and control of this pandemic by using immune-related biomarkers associated with disease symptomatology.
Collapse
Affiliation(s)
- Margarita Villar
- SaBio, Instituto de Investigación en Recursos Cinegéticos IREC-CSIC-UCLM-JCCM, Ciudad Real, Spain.,Biochemistry Section, Faculty of Science and Chemical Technologies, and Regional Centre for Biomedical Research, University of Castilla-La Mancha, Ciudad Real, Spain
| | - José Miguel Urra
- Immunology, Hospital General Universitario de Ciudad Real, Ciudad Real, Spain.,Medicine School, Universidad de Castilla la Mancha, Ciudad Real, Spain
| | | | - Sara Artigas-Jerónimo
- SaBio, Instituto de Investigación en Recursos Cinegéticos IREC-CSIC-UCLM-JCCM, Ciudad Real, Spain
| | | | - Elisa Ferreras-Colino
- SaBio, Instituto de Investigación en Recursos Cinegéticos IREC-CSIC-UCLM-JCCM, Ciudad Real, Spain
| | - Marinela Contreras
- Interdisciplinary Laboratory of Clinical Analysis, Interlab-UMU, University of Murcia, Murcia, Spain
| | | | - Agustín Estrada-Peña
- Department of Animal Pathology, Faculty of Veterinary Medicine, University of Zaragoza, Zaragoza, Spain
| | - Christian Gortázar
- SaBio, Instituto de Investigación en Recursos Cinegéticos IREC-CSIC-UCLM-JCCM, Ciudad Real, Spain
| | - José de la Fuente
- SaBio, Instituto de Investigación en Recursos Cinegéticos IREC-CSIC-UCLM-JCCM, Ciudad Real, Spain.,Department of Veterinary Pathobiology, Center for Veterinary Health Sciences, Oklahoma State University, Stillwater, OK, United States
| |
Collapse
|
23
|
Yuan ZC, Hu B. Mass Spectrometry-Based Human Breath Analysis: Towards COVID-19 Diagnosis and Research. JOURNAL OF ANALYSIS AND TESTING 2021; 5:287-297. [PMID: 34422436 PMCID: PMC8364943 DOI: 10.1007/s41664-021-00194-9] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2021] [Accepted: 06/25/2021] [Indexed: 12/12/2022]
Abstract
COVID-19 is a highly contagious respiratory disease that can be infected through human exhaled breath. Human breath analysis is an attractive strategy for rapid diagnosis of COVID-19 in a non-invasive way by monitoring breath biomarkers. Mass spectrometry (MS)-based approaches offer a promising analytical platform for human breath analysis due to their high speed, specificity, sensitivity, reproducibility, and broad coverage, as well as its versatile coupling methods with different chromatographic separation, and thus can lead to a better understanding of the clinical and biochemical processes of COVID-19. Herein, we try to review the developments and applications of MS-based approaches for multidimensional analysis of COVID-19 breath samples, including metabolites, proteins, microorganisms, and elements. New features of breath sampling and analysis are highlighted. Prospects and challenges on MS-based breath analysis related to COVID-19 diagnosis and study are discussed.
Collapse
Affiliation(s)
- Zi-Cheng Yuan
- Guangdong Provincial Engineering Research Center for On-line Source Apportionment System of Air Pollution, Institute of Mass Spectrometry and Atmospheric Environment, Jinan University, Guangzhou, 510632 China
| | - Bin Hu
- Guangdong Provincial Engineering Research Center for On-line Source Apportionment System of Air Pollution, Institute of Mass Spectrometry and Atmospheric Environment, Jinan University, Guangzhou, 510632 China
| |
Collapse
|