1
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Qin T, Lv Y, Xi X, Wu Z. PLK-3-mediated phosphorylation of BAP1 prevents diabetic retinopathy. Biochem Pharmacol 2024; 226:116374. [PMID: 38906226 DOI: 10.1016/j.bcp.2024.116374] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2024] [Revised: 06/01/2024] [Accepted: 06/18/2024] [Indexed: 06/23/2024]
Abstract
Diabetic retinopathy (DR) is a microvascular complication of diabetes mellitus, and its main clinical manifestation is retinal vascular dysfunction. DR causes blindness and is a problem with significant global health implications. However, treating DR is still challenging. In this study, we aimed to explore the role of polo-like kinase-3 (PLK-3) and the potential regulatory mechanism in DR. Sprague-Dawley rats were injected intraperitoneally with streptozotocin (STZ, 60 mg/kg) to induce a rat model of DR, and rat retinal microvascular endothelial cells (RRMECs) were treated with high glucose (HG, 25 mmol/L glucose) to develop a cell model of DR. We found that PLK-3 was significantly downregulated in the retinal tissues of STZ-induced diabetic rats and HG-induced RRMECs. Lentivirus-mediated PLK-3 overexpression alleviated the histological damages in DR rats. After HG stimulation, cell proliferation, migration, and angiogenesis in RRMECs were inhibited after PLK-3 upregulation. By using label-free proteomics, we identified 82 differentially expressed proteins downstream of PLK-3, including BRCA1-associated protein 1 (BAP1), which was significantly upregulated in PLK-3-overexpressed RRMECs compared to control cells under the HG condition. In vivo and in vitro assays indicated that the forced expression of PLK-3 increased the phosphorylation of BAP1 at serine 592 and caspase-8 expression. Detailed evidence showed that BAP1-shRNA-mediated knockdown restored the cell function in HG-treated RRMECs when PLK-3 was overexpressed. Collectively, this study shows that PLK-3 alleviates retinal vascular dysfunction in DR by inhibiting the phosphorylation of BAP1. Thus, PLK-3 may develop as a promising target for the therapy of DR.
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Affiliation(s)
- Tingyu Qin
- Department of Ophthalmology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China.
| | - Yingnan Lv
- Department of Ophthalmology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
| | - Xiangying Xi
- Department of Ophthalmology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
| | - Zhipeng Wu
- Department of Ophthalmology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
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2
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Kohler D, Staniak M, Yu F, Nesvizhskii AI, Vitek O. An MSstats workflow for detecting differentially abundant proteins in large-scale data-independent acquisition mass spectrometry experiments with FragPipe processing. Nat Protoc 2024:10.1038/s41596-024-01000-3. [PMID: 38769142 DOI: 10.1038/s41596-024-01000-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2023] [Accepted: 03/11/2024] [Indexed: 05/22/2024]
Abstract
Technological advances in mass spectrometry and proteomics have made it possible to perform larger-scale and more-complex experiments. The volume and complexity of the resulting data create major challenges for downstream analysis. In particular, next-generation data-independent acquisition (DIA) experiments enable wider proteome coverage than more traditional targeted approaches but require computational workflows that can manage much larger datasets and identify peptide sequences from complex and overlapping spectral features. Data-processing tools such as FragPipe, DIA-NN and Spectronaut have undergone substantial improvements to process spectral features in a reasonable time. Statistical analysis tools are needed to draw meaningful comparisons between experimental samples, but these tools were also originally designed with smaller datasets in mind. This protocol describes an updated version of MSstats that has been adapted to be compatible with large-scale DIA experiments. A very large DIA experiment, processed with FragPipe, is used as an example to demonstrate different MSstats workflows. The choice of workflow depends on the user's computational resources. For datasets that are too large to fit into a standard computer's memory, we demonstrate the use of MSstatsBig, a companion R package to MSstats. The protocol also highlights key decisions that have a major effect on both the results and the processing time of the analysis. The MSstats processing can be expected to take 1-3 h depending on the usage of MSstatsBig. The protocol can be run in the point-and-click graphical user interface MSstatsShiny or implemented with minimal coding expertise in R.
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Affiliation(s)
- Devon Kohler
- Khoury College of Computer Sciences, Northeastern University, Boston, MA, USA
- Barnett Institute for Chemical and Biological Analysis, Northeastern University, Boston, MA, USA
| | | | - Fengchao Yu
- Department of Pathology, University of Michigan, Ann Arbor, MI, USA
| | - Alexey I Nesvizhskii
- Department of Pathology, University of Michigan, Ann Arbor, MI, USA
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Olga Vitek
- Khoury College of Computer Sciences, Northeastern University, Boston, MA, USA.
- Barnett Institute for Chemical and Biological Analysis, Northeastern University, Boston, MA, USA.
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3
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Richard V, Mitsa G, Eshghi A, Chaplygina D, Mohammed Y, Goodlett DR, Zahedi RP, Thevis M, Borchers CH. Establishing Personalized Blood Protein Reference Ranges Using Noninvasive Microsampling and Targeted Proteomics: Implications for Antidoping Strategies. J Proteome Res 2024; 23:1779-1787. [PMID: 38655860 PMCID: PMC11077581 DOI: 10.1021/acs.jproteome.4c00020] [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: 01/11/2024] [Revised: 03/28/2024] [Accepted: 04/05/2024] [Indexed: 04/26/2024]
Abstract
To prevent doping practices in sports, the World Anti-Doping Agency implemented the Athlete Biological Passport (ABP) program, monitoring biological variables over time to indirectly reveal the effects of doping rather than detect the doping substance or the method itself. In the context of this program, a highly multiplexed mass spectrometry-based proteomics assay for 319 peptides corresponding to 250 proteins was developed, including proteins associated with blood-doping practices. "Baseline" expression profiles of these potential biomarkers in capillary blood (dried blood spots (DBS)) were established using multiple reaction monitoring (MRM). Combining DBS microsampling with highly multiplexed MRM assays is the best-suited technology to enhance the effectiveness of the ABP program, as it represents a cost-effective and robust alternative analytical method with high specificity and selectivity of targets in the attomole range. DBS data were collected from 10 healthy athlete volunteers over a period of 140 days (28 time points per participant). These comprehensive findings provide a personalized targeted blood proteome "fingerprint" showcasing that the targeted proteome is unique to an individual and likely comparable to a DNA fingerprint. The results can serve as a baseline for future studies investigating doping-related perturbations.
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Affiliation(s)
- Vincent
R. Richard
- Segal
Cancer Proteomics Centre, Lady Davis Institute
for Medical Research, Jewish General Hospital, Montréal, Quebec H3T 1E2, Canada
| | - Georgia Mitsa
- Segal
Cancer Proteomics Centre, Lady Davis Institute
for Medical Research, Jewish General Hospital, Montréal, Quebec H3T 1E2, Canada
- Division
of Experimental Medicine, McGill University, Montréal, Quebec H4A 3J1, Canada
| | - Azad Eshghi
- University
of Victoria-Genome BC Proteomics Centre, Victoria, British Columbia V8Z 7X8, Canada
| | - Daria Chaplygina
- Segal
Cancer Proteomics Centre, Lady Davis Institute
for Medical Research, Jewish General Hospital, Montréal, Quebec H3T 1E2, Canada
| | - Yassene Mohammed
- Center
for Proteomics and Metabolomics, Leiden
University Medical Center, Leiden 2333 ZC, The Netherlands
| | - David R. Goodlett
- University
of Victoria-Genome BC Proteomics Centre, Victoria, British Columbia V8Z 7X8, Canada
| | - Rene P. Zahedi
- Manitoba
Centre for Proteomics and Systems Biology, Winnipeg, Manitoba R3E 3P4, Canada
- Department
of Internal Medicine, University of Manitoba, Winnipeg, Manitoba R3E 3P4, Canada
- Department
of Biochemistry and Medical Genetics, University
of Manitoba, Winnipeg, Manitoba R3E 0J9, Canada
- CancerCare
Manitoba Research Institute, Winnipeg, Manitoba R3E 0V9, Canada
| | - Mario Thevis
- Institute
of Biochemistry, Center for Preventive Doping Research, German Sport University Cologne, Cologne 50933, Germany
- European
Monitoring Center for Emerging Doping Agents (EuMoCEDA), Cologne/Bonn 50933, Germany
| | - Christoph H. Borchers
- Segal
Cancer Proteomics Centre, Lady Davis Institute
for Medical Research, Jewish General Hospital, Montréal, Quebec H3T 1E2, Canada
- Division
of Experimental Medicine, McGill University, Montréal, Quebec H4A 3J1, Canada
- Gerald
Bronfman Department of Oncology, McGill
University, Montréal, Quebec H4A 3T2, Canada
- Department
of Pathology, McGill University, Montréal, Quebec H4A 3J1, Canada
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4
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Zhang F, Zhang Y, Zhou Q, Shi Y, Gao X, Zhai S, Zhang H. Using machine learning to identify proteomic and metabolomic signatures of stroke in atrial fibrillation. Comput Biol Med 2024; 173:108375. [PMID: 38569232 DOI: 10.1016/j.compbiomed.2024.108375] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2023] [Revised: 03/18/2024] [Accepted: 03/24/2024] [Indexed: 04/05/2024]
Abstract
Atrial fibrillation (AF) is a common cardiac arrhythmia, with stroke being its most detrimental comorbidity. The exact mechanism of AF related stroke (AFS) still needs to be explored. In this study, we integrated proteomics and metabolomics platform to explore disordered plasma proteins and metabolites between AF patients and AFS patients. There were 22 up-regulated and 31 down-regulated differentially expressed proteins (DEPs) in AFS plasma samples. Moreover, 63 up-regulated and 51 down-regulated differentially expressed metabolites (DEMs) were discovered in AFS plasma samples. We integrated proteomics and metabolomics based on the topological interactions of DEPs and DEMs, which yielded revealed several related pathways such as arachidonic acid metabolism, serotonergic synapse, purine metabolism, tyrosine metabolism and steroid hormone biosynthesis. We then performed a machine learning model to identify potential biomarkers of stroke in AF. Finally, we selected 6 proteins and 6 metabolites as candidate biomarkers for predicting stroke in AF by random forest, the area under the curve being 0.976. In conclusion, this study provides new perspectives for understanding the progressive mechanisms of AF related stroke and discovering innovative biomarkers for determining the prognosis of stroke in AF.
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Affiliation(s)
- Fan Zhang
- NHC Key Laboratory of Cell Transplantation, The First Affiliated Hospital of Harbin Medical University, Harbin, 150001, China
| | - Ying Zhang
- Beidahuang Industry Group General Hospital, Harbin, 150001, China
| | - Qi Zhou
- Research Management Office, The First Affiliated Hospital of Harbin Medical University, Harbin, 150001, China
| | - Yuanqi Shi
- Key Laboratory of Cardiovascular Disease Acousto-Optic Electromagnetic Diagnosis and Treatment in Heilongjiang Province, The First Affiliated Hospital of Harbin Medical University, Harbin, 150001, China
| | - Xiangyuan Gao
- NHC Key Laboratory of Cell Transplantation, The First Affiliated Hospital of Harbin Medical University, Harbin, 150001, China
| | - Siqi Zhai
- NHC Key Laboratory of Cell Transplantation, The First Affiliated Hospital of Harbin Medical University, Harbin, 150001, China
| | - Haiyu Zhang
- Key Laboratory of Cardiovascular Disease Acousto-Optic Electromagnetic Diagnosis and Treatment in Heilongjiang Province, The First Affiliated Hospital of Harbin Medical University, Harbin, 150001, China.
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5
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Wang M, Gu Y, Li Q, Feng B, Lv X, Zhang H, Kong Q, Dong Z, Tian X, Zhang Y. The Traf2 and NcK interacting kinase inhibitor NCB-0846 suppresses seizure activity involving the decrease of GRIA1. Genes Dis 2024; 11:100997. [PMID: 38292191 PMCID: PMC10826163 DOI: 10.1016/j.gendis.2023.03.036] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2023] [Revised: 03/09/2023] [Accepted: 03/29/2023] [Indexed: 02/01/2024] Open
Abstract
Epilepsy, one of the most common neurological disorders, is characterized by spontaneous recurrent seizures. Temporal lobe epilepsy (TLE) is one of the most common medically intractable seizure disorders. Traf2-and NcK-interacting kinase (TNIK) has recently attracted attention as a critical modulation target of many neurological and psychiatric disorders, but its role in epilepsy remains unclear. In this study, we hypothesized the involvement of TNIK in epilepsy and investigated TNIK expression in patients with intractable TLE and in a pilocarpine-induced rat model of epilepsy by western blotting, immunofluorescence, and immunohistochemistry. A pentylenetetrazole (PTZ)-induced epilepsy rat model was used to determine the effect of the TNIK inhibitor NCB-0846 on behavioral manifestations of epilepsy. Coimmunoprecipitation (Co-IP)/mass spectrometry (MS) was used to identify the potential mechanism. Through Co-IP, we detected and confirmed the main potential TNIK interactors. Subcellular fractionation was used to establish the effect of NCB-0846 on the expression of the main interactors in postsynaptic density (PSD) fractions. We found that TNIK was primarily located in neurons and decreased significantly in epilepsy model rats and TLE patients compared with controls. NCB-0846 delayed kindling progression and decreased seizure severity. Co-IP/MS identified 63 candidate TNIK interactors in rat hippocampi, notably CaMKII. Co-IP showed that TNIK might correlate with endogenous GRIA1, SYN2, PSD-95, CaMKIV, GABRG1, and GABRG2. In addition, the significant decrease in GRIA1 in hippocampal total lysate and PSDs after NCB-0846 treatment might help modify the progression of PTZ kindling. Our results suggest that TNIK contributes to epileptic pathology and is a potential antiepileptic drug target.
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Affiliation(s)
- Min Wang
- Department of Neurology, Affiliated Hospital of Jining Medical University, Jining, Shandong 272000, China
| | - Yixue Gu
- Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing Key Laboratory of Neurology, Chongqing 400016, China
| | - Qiubo Li
- Department of Pediatrics, Affiliated Hospital of Jining Medical University, Jining, Shandong 272000, China
| | - Bangzhe Feng
- Department of Neurology, Affiliated Hospital of Jining Medical University, Jining, Shandong 272000, China
| | - Xinke Lv
- Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing Key Laboratory of Neurology, Chongqing 400016, China
| | - Hao Zhang
- Department of Neurosurgery, Affiliated Hospital of Jining Medical University, Jining, Shandong 272000, China
| | - Qingxia Kong
- Department of Neurology, Affiliated Hospital of Jining Medical University, Jining, Shandong 272000, China
| | - Zhifang Dong
- Pediatric Research Institute, Ministry of Education Key Laboratory of Child Development and Disorders, National Clinical Research Center for Child Health and Disorders, Chongqing Key Laboratory of Translational Medical Research in Cognitive Development and Learning and Memory Disorders, Children's Hospital of Chongqing Medical University, Chongqing 400014, China
| | - Xin Tian
- Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing Key Laboratory of Neurology, Chongqing 400016, China
| | - Yanke Zhang
- Department of Neurology, Affiliated Hospital of Jining Medical University, Jining, Shandong 272000, China
- Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai 200031, China
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6
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Vialaret J, Vignon M, Hirtz C, Badiou S, Baptista G, Fichter L, Dupuy AM, Maceski AM, Fayolle M, Brousse M, Cristol JP, Jeandel C, Lehmann S. Use of dried blood spots for monitoring inflammatory and nutritional biomarkers in the elderly. Clin Chem Lab Med 2024; 62:881-890. [PMID: 37999931 DOI: 10.1515/cclm-2023-0312] [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: 03/27/2023] [Accepted: 11/01/2023] [Indexed: 11/25/2023]
Abstract
OBJECTIVES Blood microsampling, particularly dried blood spots (DBSs), is an attractive minimally-invasive approach that is well suited for home sampling and predictive medicine associated with longitudinal follow-up of the elderly. However, in vitro diagnostic quantification of biomarkers from DBS poses a major challenge. Clinical mass spectrometry can reliably quantify blood proteins in various research projects. Our goal here was to use mass spectrometry of DBS in a real-world clinical setting and compared it to the standard immunoassay method. We also sought to correlate DBS mass spectrometry measurements with clinical indices. METHODS A clinical trial of diagnostic equivalence was conducted to compare conventional venous samples quantified by immunoassay and DBSs quantified by mass spectrometry in an elderly population. We assayed three protein biomarkers of nutritional and inflammatory status: prealbumin (transthyretin), C-reactive protein, and transferrin. RESULTS The analysis of DBSs showed satisfactory variability and low detection limits. Statistical analysis confirmed that the two methods give comparable results at clinical levels of accuracy. In conclusion, we demonstrated, in a real-life setting, that DBSs can be used to measure prealbumin, CRP and transferrin, which are commonly used markers of nutritional status and inflammation in the elderly. However, there was no correlation with patient frailty for these proteins. CONCLUSIONS Early detection and regular monitoring of nutritional and inflammatory problems using DBS appear to be clinically feasible. This could help resolve major public health challenges in the elderly for whom frailty leads to serious risks of health complications.
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Affiliation(s)
- Jérôme Vialaret
- LBPC-PPC, Univ Montpellier, CHU Montpellier, INM INSERM, Montpellier, France
| | - Margaux Vignon
- LBPC-PPC, Univ Montpellier, CHU Montpellier, INM INSERM, Montpellier, France
| | - Christophe Hirtz
- LBPC-PPC, Univ Montpellier, CHU Montpellier, INM INSERM, Montpellier, France
| | - Stéphanie Badiou
- Department of Biochemistry and Hormonology, Univ Montpellier, CHU Montpellier, INSERM, Montpellier, France
| | - Gregory Baptista
- Centre de gérontologie clinique Antonin-Balmès, Univ Montpellier, CHU Montpellier, Montpellier, France
| | - Laura Fichter
- LBPC-PPC, Univ Montpellier, CHU Montpellier, INM INSERM, Montpellier, France
| | - Anne-Marie Dupuy
- Department of Biochemistry and Hormonology, Univ Montpellier, CHU Montpellier, INSERM, Montpellier, France
| | | | - Martin Fayolle
- LBPC-PPC, Univ Montpellier, CHU Montpellier, INM INSERM, Montpellier, France
- Department of Biochemistry and Hormonology, Univ Montpellier, CHU Montpellier, INSERM, Montpellier, France
| | - Mehdi Brousse
- LBPC-PPC, Univ Montpellier, CHU Montpellier, INM INSERM, Montpellier, France
- Department of Biochemistry and Hormonology, Univ Montpellier, CHU Montpellier, INSERM, Montpellier, France
| | - Jean-Paul Cristol
- Department of Biochemistry and Hormonology, Univ Montpellier, CHU Montpellier, INSERM, Montpellier, France
| | - Claude Jeandel
- Centre de gérontologie clinique Antonin-Balmès, Univ Montpellier, CHU Montpellier, Montpellier, France
| | - Sylvain Lehmann
- LBPC-PPC, Univ Montpellier, CHU Montpellier, INM INSERM, Montpellier, France
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7
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Mayr AL, Hummel K, Leitsch D, Razzazi-Fazeli E. A Comparison of Bottom-Up Proteomic Sample Preparation Methods for the Human Parasite Trichomonas vaginalis. ACS OMEGA 2024; 9:9782-9791. [PMID: 38434803 PMCID: PMC10905575 DOI: 10.1021/acsomega.3c10040] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/15/2023] [Revised: 01/25/2024] [Accepted: 01/31/2024] [Indexed: 03/05/2024]
Abstract
Bottom-up proteomic approaches depend on the efficient digestion of proteins into peptides for mass spectrometric analysis. Sample preparation strategies, based on magnetic beads, filter-aided systems, or in-solution digests, are commonly used for proteomic analysis. Time-intensive methods like filter-aided sample preparation (FASP) have led to the development of new, more time-efficient filter-based strategies like suspension trappings (S-Traps) or magnetic bead-based strategies like SP3. S-Traps have been reported as an alternative proteomic sample preparation method as they allow for high sodium dodecyl sulfate (SDS) concentrations to be present in the sample. In this study, we compare the efficiency of different protocols for FASP, SP3, and S-Trap-based digestion of proteins after extraction from Trichomonas vaginalis. Overall, we found a high number of protein IDs for all tested methods and a high degree of reproducibility within each method type. However, FASP with a 3 kDa cutoff filter unit outperformed the other methods analyzed, referring to the number of protein IDs. This is the first work providing the direct comparison of four different bottom-up proteomic approaches regarding the most efficient proteomic sample preparation protocol for the human parasite T. vaginalis.
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Affiliation(s)
- Anna-Lena Mayr
- VetCore
Facility, University of Veterinary Medicine, Veterinärplatz 1, 1210 Vienna, Austria
| | - Karin Hummel
- VetCore
Facility, University of Veterinary Medicine, Veterinärplatz 1, 1210 Vienna, Austria
| | - David Leitsch
- ISPTM, Medical
University of Vienna, Kinderspitalgasse 15, 1090 Vienna, Austria
| | - Ebrahim Razzazi-Fazeli
- VetCore
Facility, University of Veterinary Medicine, Veterinärplatz 1, 1210 Vienna, Austria
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8
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Gobena S, Admassu B, Kinde MZ, Gessese AT. Proteomics and Its Current Application in Biomedical Area: Concise Review. ScientificWorldJournal 2024; 2024:4454744. [PMID: 38404932 PMCID: PMC10894052 DOI: 10.1155/2024/4454744] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Revised: 02/09/2024] [Accepted: 02/13/2024] [Indexed: 02/27/2024] Open
Abstract
Biomedical researchers tirelessly seek cutting-edge technologies to advance disease diagnosis, drug discovery, and therapeutic interventions, all aimed at enhancing human and animal well-being. Within this realm, proteomics stands out as a pivotal technology, focusing on extensive studies of protein composition, structure, function, and interactions. Proteomics, with its subdivisions of expression, structural, and functional proteomics, plays a crucial role in unraveling the complexities of biological systems. Various sophisticated techniques are employed in proteomics, including polyacrylamide gel electrophoresis, mass spectrometry analysis, NMR spectroscopy, protein microarray, X-ray crystallography, and Edman sequencing. These methods collectively contribute to the comprehensive understanding of proteins and their roles in health and disease. In the biomedical field, proteomics finds widespread application in cancer research and diagnosis, stem cell studies, and the diagnosis and research of both infectious and noninfectious diseases. In addition, it plays a pivotal role in drug discovery and the emerging frontier of personalized medicine. The versatility of proteomics allows researchers to delve into the intricacies of molecular mechanisms, paving the way for innovative therapeutic approaches. As infectious and noninfectious diseases continue to emerge and the field of biomedical research expands, the significance of proteomics becomes increasingly evident. Keeping abreast of the latest developments in proteomics applications becomes paramount for the development of therapeutics, translational research, and study of diverse diseases. This review aims to provide a comprehensive overview of proteomics, offering a concise outline of its current applications in the biomedical domain. By doing so, it seeks to contribute to the understanding and advancement of proteomics, emphasizing its pivotal role in shaping the future of biomedical research and therapeutic interventions.
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Affiliation(s)
- Semira Gobena
- College of Veterinary Medicine and Animal Sciences, University of Gondar, Gondar, Ethiopia
| | - Bemrew Admassu
- Department of Veterinary Biomedical Sciences, College of Veterinary Medicine and Animal Sciences, University of Gondar, Gondar, Ethiopia
| | - Mebrie Zemene Kinde
- Department of Veterinary Biomedical Sciences, College of Veterinary Medicine and Animal Sciences, University of Gondar, Gondar, Ethiopia
| | - Abebe Tesfaye Gessese
- Department of Veterinary Biomedical Sciences, College of Veterinary Medicine and Animal Sciences, University of Gondar, Gondar, Ethiopia
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9
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Contini C, Fadda L, Lai G, Masala C, Olianas A, Castagnola M, Messana I, Iavarone F, Bizzarro A, Masullo C, Solla P, Defazio G, Manconi B, Diaz G, Cabras T. A top-down proteomic approach reveals a salivary protein profile able to classify Parkinson's disease with respect to Alzheimer's disease patients and to healthy controls. Proteomics 2024; 24:e2300202. [PMID: 37541286 DOI: 10.1002/pmic.202300202] [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: 04/29/2023] [Revised: 07/25/2023] [Accepted: 07/26/2023] [Indexed: 08/06/2023]
Abstract
Parkinson's disease (PD) is a complex neurodegenerative disease with motor and non-motor symptoms. Diagnosis is complicated by lack of reliable biomarkers. To individuate peptides and/or proteins with diagnostic potential for early diagnosis, severity and discrimination from similar pathologies, the salivary proteome in 36 PD patients was investigated in comparison with 36 healthy controls (HC) and 35 Alzheimer's disease (AD) patients. A top-down platform based on HPLC-ESI-IT-MS allowed characterizing and quantifying intact peptides, small proteins and their PTMs (overall 51). The three groups showed significantly different protein profiles, PD showed the highest levels of cystatin SA and antileukoproteinase and the lowest of cystatin SN and some statherin proteoforms. HC exhibited the lowest abundance of thymosin β4, short S100A9, cystatin A, and dimeric cystatin B. AD patients showed the highest abundance of α-defensins and short oxidized S100A9. Moreover, different proteoforms of the same protein, as S-cysteinylated and S-glutathionylated cystatin B, showed opposite trends in the two pathological groups. Statherin, cystatins SA and SN classified accurately PD from HC and AD subjects. α-defensins, histatin 1, oxidized S100A9, and P-B fragments were the best classifying factors between PD and AD patients. Interestingly statherin and thymosin β4 correlated with defective olfactory functions in PD patients. All these outcomes highlighted implications of specific proteoforms involved in the innate-immune response and inflammation regulation at oral and systemic level, suggesting a possible panel of molecular and clinical markers suitable to recognize subjects affected by PD.
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Affiliation(s)
- Cristina Contini
- Department of Life and Environmental Sciences, University of Cagliari, Cittadella Universitaria Monserrato, Monserrato, CA, Italy
| | - Laura Fadda
- Department of Medical Sciences and Public Health, Institute of Neurology, Cagliari, Italy
| | - Greca Lai
- Department of Life and Environmental Sciences, University of Cagliari, Cittadella Universitaria Monserrato, Monserrato, CA, Italy
| | - Carla Masala
- Department of Biomedical Sciences University of Cagliari, Cittadella Univ. Monserrato, Monserrato, Italy
| | - Alessandra Olianas
- Department of Life and Environmental Sciences, University of Cagliari, Cittadella Universitaria Monserrato, Monserrato, CA, Italy
| | - Massimo Castagnola
- Proteomics Laboratory. European Center for Brain Research, (IRCCS) Santa Lucia Foundation, Rome, Italy
| | - Irene Messana
- Consiglio Nazionale delle Ricerche, Istituto di Scienze e Tecnologie Chimiche "Giulio Natta", Rome, Italy
| | - Federica Iavarone
- Department of Basic Biotechnological Sciences, Intensive and Perioperative Clinics, Rome, Italy
- Fondazione Policlinico Universitario "A. Gemelli", IRCCS, Rome, Italy
| | - Alessandra Bizzarro
- Fondazione Policlinico Universitario "A. Gemelli", IRCCS, Rome, Italy
- Department of Geriatrics, Orthopaedics and Rheumatology, Rome, Italy
| | - Carlo Masullo
- Department of Neuroscience, Neurology Section, Università Cattolica del Sacro Cuore Rome, Rome, Italy
| | - Paolo Solla
- Neurological Unit, Department of Medicine, Surgery and Pharmacy, University of Sassari, Sassari, Italy
| | - Giovanni Defazio
- Department of Medical Sciences and Public Health, Institute of Neurology, Cagliari, Italy
| | - Barbara Manconi
- Department of Life and Environmental Sciences, University of Cagliari, Cittadella Universitaria Monserrato, Monserrato, CA, Italy
| | - Giacomo Diaz
- Department of Biomedical Sciences University of Cagliari, Cittadella Univ. Monserrato, Monserrato, Italy
| | - Tiziana Cabras
- Department of Life and Environmental Sciences, University of Cagliari, Cittadella Universitaria Monserrato, Monserrato, CA, Italy
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10
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Rebak AS, Hendriks IA, Nielsen ML. Characterizing citrullination by mass spectrometry-based proteomics. Philos Trans R Soc Lond B Biol Sci 2023; 378:20220237. [PMID: 37778389 PMCID: PMC10542455 DOI: 10.1098/rstb.2022.0237] [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: 03/15/2023] [Accepted: 05/25/2023] [Indexed: 10/03/2023] Open
Abstract
Citrullination is an important post-translational modification (PTM) of arginine, known to play a role in autoimmune disorders, innate immunity response and maintenance of stem cell potency. However, citrullination remains poorly characterized and not as comprehensively understood compared to other PTMs, such as phosphorylation and ubiquitylation. High-resolution mass spectrometry (MS)-based proteomics offers a valuable approach for studying citrullination in an unbiased manner, allowing confident identification of citrullination modification sites and distinction from deamidation events on asparagine and glutamine. MS efforts have already provided valuable insights into peptidyl arginine deaminase targeting along with site-specific information of citrullination in for example synovial fluids derived from rheumatoid arthritis patients. Still, there is unrealized potential for the wider citrullination field by applying MS-based mass spectrometry approaches for proteome-wide investigations. Here we will outline contemporary methods and current challenges for studying citrullination by MS, and discuss how the development of neoteric citrullination-specific proteomics approaches still may improve our understanding of citrullination networks. This article is part of the Theo Murphy meeting issue 'The virtues and vices of protein citrullination'.
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Affiliation(s)
- A. S. Rebak
- Proteomics Program, Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Blegdamsvej 3B, 2200 Copenhagen, Denmark
| | - I. A. Hendriks
- Proteomics Program, Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Blegdamsvej 3B, 2200 Copenhagen, Denmark
| | - M. L. Nielsen
- Proteomics Program, Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Blegdamsvej 3B, 2200 Copenhagen, Denmark
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11
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Lai YH, Wang YS. Advances in high-resolution mass spectrometry techniques for analysis of high mass-to-charge ions. MASS SPECTROMETRY REVIEWS 2023; 42:2426-2445. [PMID: 35686331 DOI: 10.1002/mas.21790] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/06/2021] [Revised: 01/27/2022] [Accepted: 04/07/2022] [Indexed: 06/15/2023]
Abstract
A major challenge in modern mass spectrometry (MS) is achieving high mass resolving power and accuracy for precision analyses in high mass-to-charge (m/z) regions. To advance the capability of MS for increasingly demanding applications, understanding limitations of state-of-the-art techniques and their status in applied sciences is essential. This review summarizes important instruments in high-resolution mass spectrometry (HRMS) and related advances to extend their working range to high m/z regions. It starts with an overview of HRMS techniques that provide adequate performance for macromolecular analysis, including Fourier-transform, time-of-flight (TOF), quadrupole-TOF, and related data-processing techniques. Methodologies and applications of HRMS for characterizing macromolecules in biochemistry and material sciences are summarized, such as top-down proteomics, native MS, drug discovery, structural virology, and polymer analyses.
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Affiliation(s)
- Yin-Hung Lai
- Genomics Research Center, Academia Sinica, Taipei, Taiwan, R.O.C
- Department of Chemical Engineering, National United University, Miaoli, Taiwan, R.O.C
- Institute of Food Safety and Health Risk Assessment, National Yang Ming Chiao Tung University, Taipei, Taiwan, R.O.C
| | - Yi-Sheng Wang
- Genomics Research Center, Academia Sinica, Taipei, Taiwan, R.O.C
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12
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Li X. Recent applications of quantitative mass spectrometry in biopharmaceutical process development and manufacturing. J Pharm Biomed Anal 2023; 234:115581. [PMID: 37494866 DOI: 10.1016/j.jpba.2023.115581] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2023] [Revised: 06/27/2023] [Accepted: 07/12/2023] [Indexed: 07/28/2023]
Abstract
Biopharmaceutical products have seen rapid growth over the past few decades and continue to dominate the global pharmaceutical market. Aligning with the quality by design (QbD) framework and realization, recent advances in liquid chromatography-mass spectrometry (LC-MS) instrumentation and related techniques have enhanced biopharmaceutical characterization capabilities and have supported an increased development of biopharmaceutical products. Beyond its routine qualitative characterization, the quantitative feature of LC-MS has unique applications in biopharmaceutical process development and manufacturing. This review describes the recent applications and implications of the advancement of quantitative MS methods in biopharmaceutical process development, and characterization of biopharmaceutical product, product-related variants, and process-related impurities. We also provide insights on the emerging applications of quantitative MS in the lifecycle of biopharmaceutical product development including quality control in the Good Manufacturing Practice (GMP) environment and process analytical technology (PAT) practices during process development and manufacturing. Through collaboration with instrument and software vendors and regulatory agencies, we envision broader adoption of phase-appropriate quantitative MS-based methods for the analysis of biopharmaceutical products, which in turn has the potential to enable manufacture of higher quality products for patients.
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Affiliation(s)
- Xuanwen Li
- Analytical Research and Development, MRL, Merck & Co., Inc., 126 E. Lincoln Avenue, Rahway, NJ 07065, USA.
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13
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Huang T, Wang J, Stukalov A, Donovan MKR, Ferdosi S, Williamson L, Just S, Castro G, Cantrell LS, Elgierari E, Benz RW, Huang Y, Motamedchaboki K, Hakimi A, Arrey T, Damoc E, Kreimer S, Farokhzad OC, Batzoglou S, Siddiqui A, Van Eyk JE, Hornburg D. Protein Coronas on Functionalized Nanoparticles Enable Quantitative and Precise Large-Scale Deep Plasma Proteomics. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.08.28.555225. [PMID: 37693476 PMCID: PMC10491250 DOI: 10.1101/2023.08.28.555225] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/12/2023]
Abstract
Background The wide dynamic range of circulating proteins coupled with the diversity of proteoforms present in plasma has historically impeded comprehensive and quantitative characterization of the plasma proteome at scale. Automated nanoparticle (NP) protein corona-based proteomics workflows can efficiently compress the dynamic range of protein abundances into a mass spectrometry (MS)-accessible detection range. This enhances the depth and scalability of quantitative MS-based methods, which can elucidate the molecular mechanisms of biological processes, discover new protein biomarkers, and improve comprehensiveness of MS-based diagnostics. Methods Investigating multi-species spike-in experiments and a cohort, we investigated fold-change accuracy, linearity, precision, and statistical power for the using the Proteograph™ Product Suite, a deep plasma proteomics workflow, in conjunction with multiple MS instruments. Results We show that NP-based workflows enable accurate identification (false discovery rate of 1%) of more than 6,000 proteins from plasma (Orbitrap Astral) and, compared to a gold standard neat plasma workflow that is limited to the detection of hundreds of plasma proteins, facilitate quantification of more proteins with accurate fold-changes, high linearity, and precision. Furthermore, we demonstrate high statistical power for the discovery of biomarkers in small- and large-scale cohorts. Conclusions The automated NP workflow enables high-throughput, deep, and quantitative plasma proteomics investigation with sufficient power to discover new biomarker signatures with a peptide level resolution.
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Affiliation(s)
| | - Jian Wang
- Seer, Inc., Redwood City, CA, 94065 USA
| | | | | | | | | | - Seth Just
- Seer, Inc., Redwood City, CA, 94065 USA
| | | | | | | | | | | | | | | | | | - Eugen Damoc
- Thermo Fisher Scientific, (Bremen) GmbH, Germany
| | - Simion Kreimer
- Advanced Clinical Biosystems Research Institute, Precision Health, Barbra Streisand Women’s Heart Center at the Smidt Heart Institute, Cedars-Sinai Medical Center, 127 S. San Vicente Blvd., Los Angeles, CA, 90048, USA
| | | | | | | | - Jennifer E. Van Eyk
- Advanced Clinical Biosystems Research Institute, Precision Health, Barbra Streisand Women’s Heart Center at the Smidt Heart Institute, Cedars-Sinai Medical Center, 127 S. San Vicente Blvd., Los Angeles, CA, 90048, USA
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14
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Timechko EE, Yakimov AM, Paramonova AI, Usoltseva AA, Utyashev NP, Ivin NO, Utyasheva AA, Yakunina AV, Kalinin VA, Dmitrenko DV. Mass Spectrometry as a Quantitative Proteomic Analysis Tool for the Search for Temporal Lobe Epilepsy Biomarkers: A Systematic Review. Int J Mol Sci 2023; 24:11130. [PMID: 37446307 DOI: 10.3390/ijms241311130] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Revised: 06/25/2023] [Accepted: 07/04/2023] [Indexed: 07/15/2023] Open
Abstract
Temporal lobe epilepsy (TLE) is the most common form of epilepsy in adults. Tissue reorganization at the site of the epileptogenic focus is accompanied by changes in the expression patterns of protein molecules. The study of mRNA and its corresponding proteins is crucial for understanding the pathogenesis of the disease. Protein expression profiles do not always directly correlate with the levels of their transcripts; therefore, it is protein profiling that is no less important for understanding the molecular mechanisms and biological processes of TLE. The study and annotation of proteins that are statistically significantly different in patients with TLE is an approach to search for biomarkers of this disease, various stages of its development, as well as a method for searching for specific targets for the development of a further therapeutic strategy. When writing a systematic review, the following aggregators of scientific journals were used: MDPI, PubMed, ScienceDirect, Springer, and Web of Science. Scientific articles were searched using the following keywords: "proteomic", "mass-spectrometry", "protein expression", "temporal lobe epilepsy", and "biomarkers". Publications from 2003 to the present have been analyzed. Studies of brain tissues, experimental models of epilepsy, as well as biological fluids, were analyzed. For each of the groups, aberrantly expressed proteins found in various studies were isolated. Most of the studies omitted important characteristics of the studied patients, such as: duration of illness, type and response to therapy, gender, etc. Proteins that overlap across different tissue types and different studies have been highlighted: DPYSL, SYT1, STMN1, APOE, NME1, and others. The most common biological processes for them were the positive regulation of neurofibrillary tangle assembly, the regulation of amyloid fibril formation, lipoprotein catabolic process, the positive regulation of vesicle fusion, the positive regulation of oxidative stress-induced intrinsic apoptotic signaling pathway, removal of superoxide radicals, axon extension, and the regulation of actin filament depolymerization. MS-based proteomic profiling for a relevant study must accept a number of limitations, the most important of which is the need to compare different types of neurological and, in particular, epileptic disorders. Such a criterion could increase the specificity of the search work and, in the future, lead to the discovery of biomarkers for a particular disease.
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Affiliation(s)
- Elena E Timechko
- Department of Medical Genetics and Clinical Neurophysiology of Postgraduate Education, V.F. Voino-Yasenetsky Krasnoyarsk State Medical University, 660022 Krasnoyarsk, Russia
| | - Alexey M Yakimov
- Department of Medical Genetics and Clinical Neurophysiology of Postgraduate Education, V.F. Voino-Yasenetsky Krasnoyarsk State Medical University, 660022 Krasnoyarsk, Russia
| | - Anastasia I Paramonova
- Department of Medical Genetics and Clinical Neurophysiology of Postgraduate Education, V.F. Voino-Yasenetsky Krasnoyarsk State Medical University, 660022 Krasnoyarsk, Russia
| | - Anna A Usoltseva
- Department of Medical Genetics and Clinical Neurophysiology of Postgraduate Education, V.F. Voino-Yasenetsky Krasnoyarsk State Medical University, 660022 Krasnoyarsk, Russia
| | - Nikita P Utyashev
- Federal State Budgetary Institution "National Medical and Surgical Center Named after N.I. Pirogov", 105203 Moscow, Russia
| | - Nikita O Ivin
- Federal State Budgetary Institution "National Medical and Surgical Center Named after N.I. Pirogov", 105203 Moscow, Russia
| | - Anna A Utyasheva
- Federal State Budgetary Institution "National Medical and Surgical Center Named after N.I. Pirogov", 105203 Moscow, Russia
| | - Albina V Yakunina
- Department of Neurology and Neurobiology of Postgraduate Education, Samara State Medical University, 443079 Samara, Russia
| | - Vladimir A Kalinin
- Department of Neurology and Neurobiology of Postgraduate Education, Samara State Medical University, 443079 Samara, Russia
| | - Diana V Dmitrenko
- Department of Medical Genetics and Clinical Neurophysiology of Postgraduate Education, V.F. Voino-Yasenetsky Krasnoyarsk State Medical University, 660022 Krasnoyarsk, Russia
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15
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Gurdo N, Taylor Parkins SK, Fricano M, Wulff T, Nielsen LK, Nikel PI. Protocol for absolute quantification of proteins in Gram-negative bacteria based on QconCAT-based labeled peptides. STAR Protoc 2023; 4:102060. [PMID: 36853682 PMCID: PMC9881405 DOI: 10.1016/j.xpro.2023.102060] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2022] [Revised: 10/02/2022] [Accepted: 01/05/2023] [Indexed: 01/26/2023] Open
Abstract
Mass-spectrometry-based absolute protein quantification uses labeled quantification concatamer (QconCAT) as internal standards (ISs). To calculate the amount of protein(s), the ion intensity ratio between the analyte and its cognate IS is compared in each biological sample. The present protocol describes a systematic workflow to design, produce, and purify QconCATs and to quantify soluble proteins in Pseudomonas putida KT2440. Our methodology enables the quantification of detectable peptide and serves as a versatile platform to produce ISs for different biological systems.
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Affiliation(s)
- Nicolás Gurdo
- The Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, 2800 Kongens Lyngby, Denmark
| | | | - Martina Fricano
- The Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, 2800 Kongens Lyngby, Denmark
| | - Tune Wulff
- The Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, 2800 Kongens Lyngby, Denmark
| | - Lars Keld Nielsen
- The Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, 2800 Kongens Lyngby, Denmark; Australian Institute for Bioengineering and Nanotechnology, The University of Queensland, Brisbane, QLD 4072, Australia
| | - Pablo Iván Nikel
- The Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, 2800 Kongens Lyngby, Denmark.
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16
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ProInfer: An interpretable protein inference tool leveraging on biological networks. PLoS Comput Biol 2023; 19:e1010961. [PMID: 36930671 PMCID: PMC10057851 DOI: 10.1371/journal.pcbi.1010961] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2022] [Revised: 03/29/2023] [Accepted: 02/20/2023] [Indexed: 03/18/2023] Open
Abstract
In mass spectrometry (MS)-based proteomics, protein inference from identified peptides (protein fragments) is a critical step. We present ProInfer (Protein Inference), a novel protein assembly method that takes advantage of information in biological networks. ProInfer assists recovery of proteins supported only by ambiguous peptides (a peptide which maps to more than one candidate protein) and enhances the statistical confidence for proteins supported by both unique and ambiguous peptides. Consequently, ProInfer rescues weakly supported proteins thereby improving proteome coverage. Evaluated across THP1 cell line, lung cancer and RAW267.4 datasets, ProInfer always infers the most numbers of true positives, in comparison to mainstream protein inference tools Fido, EPIFANY and PIA. ProInfer is also adept at retrieving differentially expressed proteins, signifying its usefulness for functional analysis and phenotype profiling. Source codes of ProInfer are available at https://github.com/PennHui2016/ProInfer.
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17
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Kim J, Seo S, Kim TY. Metabolic deuterium oxide (D 2O) labeling in quantitative omics studies: A tutorial review. Anal Chim Acta 2023; 1242:340722. [PMID: 36657897 DOI: 10.1016/j.aca.2022.340722] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2022] [Revised: 11/25/2022] [Accepted: 12/13/2022] [Indexed: 12/15/2022]
Abstract
Mass spectrometry (MS) is an invaluable tool for sensitive detection and characterization of individual biomolecules in omics studies. MS combined with stable isotope labeling enables the accurate and precise determination of quantitative changes occurring in biological samples. Metabolic isotope labeling, wherein isotopes are introduced into biomolecules through biosynthetic metabolism, is one of the main labeling strategies. Among the precursors employed in metabolic isotope labeling, deuterium oxide (D2O) is cost-effective and easy to implement in any biological systems. This tutorial review aims to explain the basic principle of D2O labeling and its applications in omics research. D2O labeling incorporates D into stable C-H bonds in various biomolecules, including nucleotides, proteins, lipids, and carbohydrates. Typically, D2O labeling is performed at low enrichment of 1%-10% D2O, which causes subtle changes in the isotopic distribution of a biomolecule, instead of the complete separation between labeled and unlabeled samples in a mass spectrum. D2O labeling has been employed in various omics studies to determine the metabolic flux, turnover rate, and relative quantification. Moreover, the advantages and challenges of D2O labeling and its future prospects in quantitative omics are discussed. The economy, versatility, and convenience of D2O labeling will be beneficial for the long-term omics studies for higher organisms.
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Affiliation(s)
- Jonghyun Kim
- School of Earth Sciences and Environmental Engineering, Gwangju Institute of Science and Technology, Gwangju, 61005, South Korea
| | - Seungwoo Seo
- School of Earth Sciences and Environmental Engineering, Gwangju Institute of Science and Technology, Gwangju, 61005, South Korea
| | - Tae-Young Kim
- School of Earth Sciences and Environmental Engineering, Gwangju Institute of Science and Technology, Gwangju, 61005, South Korea.
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18
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Shen Q, Dai H, Wen L, Zheng W, Li B, Dai J, Li B, Chen Y. Effects of pH-shifting treatments on the emulsifying properties of rice protein isolates: Quantitative analysis of interfacial protein layer. Food Res Int 2023; 164:112306. [PMID: 36737901 DOI: 10.1016/j.foodres.2022.112306] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2022] [Revised: 11/29/2022] [Accepted: 12/03/2022] [Indexed: 12/12/2022]
Abstract
For the limitation of poor solubility and interfacial adsorption capacity of rice protein isolates (RPI), in this work the effects of pH-shifting treatments on the emulsifying properties of RPI were investigated. The results showed that the particle size of the emulsion stabilized by alkaline pH-shifting treated RPI was smaller than that stabilized by acid pH-shifting treated RPI. In addition, the RPI-10 stabilized emulsion showed a more uniform particle size distribution, which was explained by its high emulsifying activity and stability (EAI: 49.5 m2/g, ESI: 59.5 min). The interface rheology results showed that the alkaline pH-shifting treatment could promote the protein rearrangement and subsequently formed interface film with higher rate of protein penetration and rearrangement. The quantitative analysis of adsorbed proteins in the RPI-10 stabilized emulsion showed that glutelin-type isoforms as major proteins in RPI were increased at the oil-water interface for their balanced distribution of the hydrophilic and hydrophobic amino acid group. These quantitative and interfacial rheology analysis could improve deep understanding of the interfacial properties of pH-shifting treated RPI, and promote the development of application in grain protein stabilized emulsion.
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Affiliation(s)
- Qian Shen
- College of Food Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
| | - Hongmin Dai
- College of Food Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
| | - Luming Wen
- College of Food Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
| | - Wei Zheng
- College of Food Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
| | - Beixi Li
- College of Food Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
| | - Jun Dai
- Key Laboratory of Fermentation Engineering (Ministry of Education), College of Bioengineering, Hubei University of Technology, Wuhan 430068, China
| | - Bin Li
- College of Food Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
| | - Yijie Chen
- College of Food Science and Technology, Huazhong Agricultural University, Wuhan 430070, China; Shenzhen Institute of Nutrition and Health, Huazhong Agricultural University, Wuhan 430070, China; Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518124, China.
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19
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Top-Down Proteomics Detection of Potential Salivary Biomarkers for Autoimmune Liver Diseases Classification. Int J Mol Sci 2023; 24:ijms24020959. [PMID: 36674470 PMCID: PMC9866740 DOI: 10.3390/ijms24020959] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2022] [Revised: 12/23/2022] [Accepted: 12/27/2022] [Indexed: 01/06/2023] Open
Abstract
(1) Autoimmune hepatitis (AIH) and primary biliary cholangitis (PBC) are autoimmune liver diseases characterized by chronic hepatic inflammation and progressive liver fibrosis. The possible use of saliva as a diagnostic tool has been explored in several oral and systemic diseases. The use of proteomics for personalized medicine is a rapidly emerging field. (2) Salivary proteomic data of 36 healthy controls (HCs), 36 AIH and 36 PBC patients, obtained by liquid chromatography/mass spectrometry top-down pipeline, were analyzed by multiple Mann-Whitney test, Kendall correlation, Random Forest (RF) analysis and Linear Discriminant Analysis (LDA); (3) Mann-Whitney tests provided indications on the panel of differentially expressed salivary proteins and peptides, namely cystatin A, statherin, histatin 3, histatin 5 and histatin 6, which were elevated in AIH patients with respect to both HCs and PBC patients, while S100A12, S100A9 short, cystatin S1, S2, SN and C showed varied levels in PBC with respect to HCs and/or AIH patients. RF analysis evidenced a panel of salivary proteins/peptides able to classify with good accuracy PBC vs. HCs (83.3%), AIH vs. HCs (79.9%) and PBC vs. AIH (80.2%); (4) RF appears to be an attractive machine-learning tool suited for classification of AIH and PBC based on their different salivary proteomic profiles.
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20
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Duda JM, Thomas SN. Combination of Stable Isotope Labeling by Amino Acids in Cell Culture (SILAC) and Substrate Trapping for the Detection of Transient Protein Interactions. Methods Mol Biol 2023; 2603:219-234. [PMID: 36370283 PMCID: PMC10567058 DOI: 10.1007/978-1-0716-2863-8_18] [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] [Indexed: 06/16/2023]
Abstract
Antibody-based affinity purification is a recognized method for use in studying protein-protein interactions. There are four different classes of proteins that are typically identified with such affinity purification workflows: bait protein, proteins that specifically interact with the bait protein, proteins nonspecifically associated with the antibody, and proteins that cross-react with the antibody. Mass spectrometry can be used to differentiate these classes of proteins in affinity-purified mixtures. Here we describe the use of stable isotope labeling by amino acids in cell culture, substrate trapping, and mass spectrometry to enable the objective identification of the components of affinity-purified protein complexes.
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Affiliation(s)
- Jolene M Duda
- Department of Biochemistry, Molecular Biology and Biophysics, University of Minnesota College of Biological Sciences, Minneapolis, MN, USA
| | - Stefani N Thomas
- Department of Laboratory Medicine and Pathology, University of Minnesota School of Medicine, Minneapolis, MN, USA.
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21
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Wei B, Zenaidee MA, Lantz C, Williams BJ, Totten S, Ogorzalek Loo RR, Loo JA. Top-down mass spectrometry and assigning internal fragments for determining disulfide bond positions in proteins. Analyst 2022; 148:26-37. [PMID: 36399030 PMCID: PMC9772244 DOI: 10.1039/d2an01517j] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Disulfide bonds in proteins have a substantial impact on protein structure, stability, and biological activity. Localizing disulfide bonds is critical for understanding protein folding and higher-order structure. Conventional top-down mass spectrometry (TD-MS), where only terminal fragments are assigned for disulfide-intact proteins, can access disulfide information, but suffers from low fragmentation efficiency, thereby limiting sequence coverage. Here, we show that assigning internal fragments generated from TD-MS enhances the sequence coverage of disulfide-intact proteins by 20-60% by returning information from the interior of the protein sequence, which cannot be obtained by terminal fragments alone. The inclusion of internal fragments can extend the sequence information of disulfide-intact proteins to near complete sequence coverage. Importantly, the enhanced sequence information that arise from the assignment of internal fragments can be used to determine the relative position of disulfide bonds and the exact disulfide connectivity between cysteines. The data presented here demonstrates the benefits of incorporating internal fragment analysis into the TD-MS workflow for analyzing disulfide-intact proteins, which would be valuable for characterizing biotherapeutic proteins such as monoclonal antibodies and antibody-drug conjugates.
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Affiliation(s)
- Benqian Wei
- Department of Chemistry and Biochemistry, University of California Los Angeles, Los Angeles, CA, USA.
| | - Muhammad A Zenaidee
- Department of Chemistry and Biochemistry, University of California Los Angeles, Los Angeles, CA, USA.
- Australian Proteome Analysis Facility, Macquarie University, Macquarie Park, NSW, Australia
| | - Carter Lantz
- Department of Chemistry and Biochemistry, University of California Los Angeles, Los Angeles, CA, USA.
| | | | | | - Rachel R Ogorzalek Loo
- Department of Chemistry and Biochemistry, University of California Los Angeles, Los Angeles, CA, USA.
| | - Joseph A Loo
- Department of Chemistry and Biochemistry, University of California Los Angeles, Los Angeles, CA, USA.
- Department of Biological Chemistry, University of California Los Angeles, Los Angeles, CA, USA
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22
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Staudt DE, Murray HC, Skerrett-Byrne DA, Smith ND, Jamaluddin MFB, Kahl RGS, Duchatel RJ, Germon ZP, McLachlan T, Jackson ER, Findlay IJ, Kearney PS, Mannan A, McEwen HP, Douglas AM, Nixon B, Verrills NM, Dun MD. Phospho-heavy-labeled-spiketide FAIMS stepped-CV DDA (pHASED) provides real-time phosphoproteomics data to aid in cancer drug selection. Clin Proteomics 2022; 19:48. [PMID: 36536316 PMCID: PMC9762002 DOI: 10.1186/s12014-022-09385-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2022] [Accepted: 12/07/2022] [Indexed: 12/23/2022] Open
Abstract
Global high-throughput phosphoproteomic profiling is increasingly being applied to cancer specimens to identify the oncogenic signaling cascades responsible for promoting disease initiation and disease progression; pathways that are often invisible to genomics analysis. Hence, phosphoproteomic profiling has enormous potential to inform and improve individualized anti-cancer treatment strategies. However, to achieve the adequate phosphoproteomic depth and coverage necessary to identify the activated, and hence, targetable kinases responsible for driving oncogenic signaling pathways, affinity phosphopeptide enrichment techniques are required and often coupled with offline high-pressure liquid chromatographic (HPLC) separation prior to nanoflow liquid chromatography-tandem mass spectrometry (nLC-MS/MS). These complex and time-consuming procedures, limit the utility of phosphoproteomics for the analysis of individual cancer patient specimens in real-time, and restrict phosphoproteomics to specialized laboratories often outside of the clinical setting. To address these limitations, here we have optimized a new protocol, phospho-heavy-labeled-spiketide FAIMS Stepped-CV DDA (pHASED), that employs online phosphoproteome deconvolution using high-field asymmetric waveform ion mobility spectrometry (FAIMS) and internal phosphopeptide standards to provide accurate label-free quantitation (LFQ) data in real-time. Compared with traditional single-shot LFQ phosphoproteomics workflows, pHASED provided increased phosphoproteomic depth and coverage (phosphopeptides = 4617 pHASED, 2789 LFQ), whilst eliminating the variability associated with offline prefractionation. pHASED was optimized using tyrosine kinase inhibitor (sorafenib) resistant isogenic FLT3-mutant acute myeloid leukemia (AML) cell line models. Bioinformatic analysis identified differential activation of the serine/threonine protein kinase ataxia-telangiectasia mutated (ATM) pathway, responsible for sensing and repairing DNA damage in sorafenib-resistant AML cell line models, thereby uncovering a potential therapeutic opportunity. Herein, we have optimized a rapid, reproducible, and flexible protocol for the characterization of complex cancer phosphoproteomes in real-time, a step towards the implementation of phosphoproteomics in the clinic to aid in the selection of anti-cancer therapies for patients.
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Affiliation(s)
- Dilana E. Staudt
- grid.266842.c0000 0000 8831 109XSchool of Biomedical Sciences and Pharmacy, College of Health, Medicine and Wellbeing, University of Newcastle, Callaghan, NSW 2308 Australia ,grid.413648.cPrecision Medicine Research Program, Hunter Medical Research Institute, New Lambton Heights, NSW 2305 Australia
| | - Heather C. Murray
- grid.266842.c0000 0000 8831 109XSchool of Biomedical Sciences and Pharmacy, College of Health, Medicine and Wellbeing, University of Newcastle, Callaghan, NSW 2308 Australia ,grid.413648.cPrecision Medicine Research Program, Hunter Medical Research Institute, New Lambton Heights, NSW 2305 Australia
| | - David A. Skerrett-Byrne
- grid.266842.c0000 0000 8831 109XSchool of Environmental and Life Sciences, College of Engineering, Science and Environment, University of Newcastle, Callaghan, NSW 2308 Australia ,grid.413648.cInfertility and Reproduction Research Program, Hunter Medical Research Institute, New Lambton Heights, NSW 2305 Australia
| | - Nathan D. Smith
- grid.266842.c0000 0000 8831 109XAnalytical and Biomolecular Research Facility (ABRF), Research Services, University of Newcastle, NSW, Callaghan, 2308 Australia
| | - M. Fairuz B. Jamaluddin
- grid.266842.c0000 0000 8831 109XSchool of Biomedical Sciences and Pharmacy, College of Health, Medicine and Wellbeing, University of Newcastle, Callaghan, NSW 2308 Australia
| | - Richard G. S. Kahl
- grid.266842.c0000 0000 8831 109XSchool of Biomedical Sciences and Pharmacy, College of Health, Medicine and Wellbeing, University of Newcastle, Callaghan, NSW 2308 Australia
| | - Ryan J. Duchatel
- grid.266842.c0000 0000 8831 109XSchool of Biomedical Sciences and Pharmacy, College of Health, Medicine and Wellbeing, University of Newcastle, Callaghan, NSW 2308 Australia ,grid.413648.cPrecision Medicine Research Program, Hunter Medical Research Institute, New Lambton Heights, NSW 2305 Australia
| | - Zacary P. Germon
- grid.266842.c0000 0000 8831 109XSchool of Biomedical Sciences and Pharmacy, College of Health, Medicine and Wellbeing, University of Newcastle, Callaghan, NSW 2308 Australia ,grid.413648.cPrecision Medicine Research Program, Hunter Medical Research Institute, New Lambton Heights, NSW 2305 Australia
| | - Tabitha McLachlan
- grid.266842.c0000 0000 8831 109XSchool of Biomedical Sciences and Pharmacy, College of Health, Medicine and Wellbeing, University of Newcastle, Callaghan, NSW 2308 Australia ,grid.413648.cPrecision Medicine Research Program, Hunter Medical Research Institute, New Lambton Heights, NSW 2305 Australia
| | - Evangeline R. Jackson
- grid.266842.c0000 0000 8831 109XSchool of Biomedical Sciences and Pharmacy, College of Health, Medicine and Wellbeing, University of Newcastle, Callaghan, NSW 2308 Australia ,grid.413648.cPrecision Medicine Research Program, Hunter Medical Research Institute, New Lambton Heights, NSW 2305 Australia
| | - Izac J. Findlay
- grid.266842.c0000 0000 8831 109XSchool of Biomedical Sciences and Pharmacy, College of Health, Medicine and Wellbeing, University of Newcastle, Callaghan, NSW 2308 Australia ,grid.413648.cPrecision Medicine Research Program, Hunter Medical Research Institute, New Lambton Heights, NSW 2305 Australia
| | - Padraic S. Kearney
- grid.266842.c0000 0000 8831 109XSchool of Biomedical Sciences and Pharmacy, College of Health, Medicine and Wellbeing, University of Newcastle, Callaghan, NSW 2308 Australia ,grid.413648.cPrecision Medicine Research Program, Hunter Medical Research Institute, New Lambton Heights, NSW 2305 Australia
| | - Abdul Mannan
- grid.266842.c0000 0000 8831 109XSchool of Biomedical Sciences and Pharmacy, College of Health, Medicine and Wellbeing, University of Newcastle, Callaghan, NSW 2308 Australia ,grid.413648.cPrecision Medicine Research Program, Hunter Medical Research Institute, New Lambton Heights, NSW 2305 Australia
| | - Holly P. McEwen
- grid.266842.c0000 0000 8831 109XSchool of Biomedical Sciences and Pharmacy, College of Health, Medicine and Wellbeing, University of Newcastle, Callaghan, NSW 2308 Australia ,grid.413648.cPrecision Medicine Research Program, Hunter Medical Research Institute, New Lambton Heights, NSW 2305 Australia
| | - Alicia M. Douglas
- grid.266842.c0000 0000 8831 109XSchool of Biomedical Sciences and Pharmacy, College of Health, Medicine and Wellbeing, University of Newcastle, Callaghan, NSW 2308 Australia
| | - Brett Nixon
- grid.266842.c0000 0000 8831 109XSchool of Environmental and Life Sciences, College of Engineering, Science and Environment, University of Newcastle, Callaghan, NSW 2308 Australia ,grid.413648.cInfertility and Reproduction Research Program, Hunter Medical Research Institute, New Lambton Heights, NSW 2305 Australia
| | - Nicole M. Verrills
- grid.266842.c0000 0000 8831 109XSchool of Biomedical Sciences and Pharmacy, College of Health, Medicine and Wellbeing, University of Newcastle, Callaghan, NSW 2308 Australia ,grid.413648.cPrecision Medicine Research Program, Hunter Medical Research Institute, New Lambton Heights, NSW 2305 Australia
| | - Matthew D. Dun
- grid.266842.c0000 0000 8831 109XSchool of Biomedical Sciences and Pharmacy, College of Health, Medicine and Wellbeing, University of Newcastle, Callaghan, NSW 2308 Australia ,grid.413648.cPrecision Medicine Research Program, Hunter Medical Research Institute, New Lambton Heights, NSW 2305 Australia
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Zhang H, Wang L, Yin D, Zhou Q, Lv L, Dong Z, Shi Y. Integration of proteomic and metabolomic characterization in atrial fibrillation-induced heart failure. BMC Genomics 2022; 23:789. [PMID: 36456901 PMCID: PMC9714089 DOI: 10.1186/s12864-022-09044-z] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2022] [Accepted: 11/24/2022] [Indexed: 12/02/2022] Open
Abstract
BACKGROUND The exact mechanism of atrial fibrillation (AF)-induced heart failure (HF) remains unclear. Proteomics and metabolomics were integrated to in this study, as to describe AF patients' dysregulated proteins and metabolites, comparing patients without HF to patients with HF. METHODS Plasma samples of 20 AF patients without HF and another 20 with HF were analyzed by multi-omics platforms. Proteomics was performed with data independent acquisition-based liquid chromatography-tandem mass spectrometry (LC-MS/MS), as metabolomics was performed with LC-MS/MS platform. Proteomic and metabolomic results were analyzed separately and integrated using univariate statistical methods, multivariate statistical methods or machine learning model. RESULTS We found 35 up-regulated and 15 down-regulated differentially expressed proteins (DEPs) in AF patients with HF compared to AF patients without HF. Moreover, 121 up-regulated and 14 down-regulated differentially expressed metabolites (DEMs) were discovered in HF patients compared to AF patients without HF. An integrated analysis of proteomics and metabolomics revealed several significantly enriched pathways, including Glycolysis or Gluconeogenesis, Tyrosine metabolism and Pentose phosphate pathway. A total of 10 DEPs and DEMs selected as potential biomarkers provided excellent predictive performance, with an AUC of 0.94. In addition, subgroup analysis of HF classification was performed based on metabolomics, which yielded 9 DEMs that can distinguish between AF and HF for HF classification. CONCLUSIONS This study provides novel insights to understanding the mechanisms of AF-induced HF progression and identifying novel biomarkers for prognosis of AF with HF by using metabolomics and proteomics analyses.
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Affiliation(s)
- Haiyu Zhang
- grid.410736.70000 0001 2204 9268Key Laboratory of Cardiovascular Disease Acousto-Optic Electromagnetic Diagnosis and Treatment in Heilongjiang Province, the First Affiliated Hospital, Harbin Medical University, 23 Youzheng Street, Nangang District, Harbin, 150001 China
| | - Lu Wang
- grid.410736.70000 0001 2204 9268Key Laboratory of Cardiovascular Disease Acousto-Optic Electromagnetic Diagnosis and Treatment in Heilongjiang Province, the First Affiliated Hospital, Harbin Medical University, 23 Youzheng Street, Nangang District, Harbin, 150001 China
| | - Dechun Yin
- grid.410736.70000 0001 2204 9268Department of Cardiology, the First Affiliated Hospital, Harbin Medical University, 23 Youzheng Street, Nangang District, Harbin, 150001 China
| | - Qi Zhou
- grid.410736.70000 0001 2204 9268Research Management Office, the First Affiliated Hospital, Harbin Medical University, 23 Youzheng Street, Nangang District, Harbin, 150001 China
| | - Lin Lv
- grid.410736.70000 0001 2204 9268Key Laboratory of Cardiovascular Disease Acousto-Optic Electromagnetic Diagnosis and Treatment in Heilongjiang Province, the First Affiliated Hospital, Harbin Medical University, 23 Youzheng Street, Nangang District, Harbin, 150001 China
| | - Zengxiang Dong
- grid.410736.70000 0001 2204 9268Key Laboratory of Cardiovascular Disease Acousto-Optic Electromagnetic Diagnosis and Treatment in Heilongjiang Province, the First Affiliated Hospital, Harbin Medical University, 23 Youzheng Street, Nangang District, Harbin, 150001 China
| | - Yuanqi Shi
- grid.410736.70000 0001 2204 9268Key Laboratory of Cardiovascular Disease Acousto-Optic Electromagnetic Diagnosis and Treatment in Heilongjiang Province, the First Affiliated Hospital, Harbin Medical University, 23 Youzheng Street, Nangang District, Harbin, 150001 China
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24
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Shen Q, Xiong T, Dai J, Chen X, Wang L, Li Y, Li J, Li B, Chen Y. Effects of pH-shifting treatments on oil-water interfacial properties of pea protein isolates: Identification and quantification of proteins at interfacial protein layer. Food Hydrocoll 2022. [DOI: 10.1016/j.foodhyd.2022.107937] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2022]
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25
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Barrett K, Zhao H, Hao P, Bacic A, Lange L, Holck J, Meyer AS. Discovery of novel secretome CAZymes from Penicillium sclerotigenum by bioinformatics and explorative proteomics analyses during sweet potato pectin digestion. Front Bioeng Biotechnol 2022; 10:950259. [PMID: 36185449 PMCID: PMC9523869 DOI: 10.3389/fbioe.2022.950259] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2022] [Accepted: 08/08/2022] [Indexed: 11/13/2022] Open
Abstract
Novel selective enzymatic refining of sweet potato processing residues requires judicious enzyme selection and enzyme discovery. We prepared a pectinaceous cell wall polysaccharide fraction from sweet potato using an enzymatic a treatment to preserve the natural linkages and substitutions. Polysaccharide composition and linkage analysis data confirmed the pectinaceous polysaccharide fraction to be a rhamnogalacturonan I-rich fraction with a high content of arabinogalactan Type I. We hypothesized that the post-harvest tuber pathogenic fungus Penicillium sclerotigenum would harbor novel enzymes targeting selective sweet potato pectin modification. As part of the study, we also report the first genome sequence of P. sclerotigenum. We incubated the sweet potato pectinaceous fraction with P. sclerotigenum. Using proteomics accompanied by CUPP-bioinformatics analysis, we observed induced expression of 23 pectin-associated degradative enzymes. We also identified six abundantly secreted, induced proteins that do not correspond to known CAZymes, but which we suggest as novel enzymes involved in pectin degradation. For validation, the predicted CUPP grouping of putative CAZymes and the exo-proteome data obtained for P. sclerotigenum during growth on sweet potato pectin were compared with proteomics and transcriptomics data reported previously for pectin-associated CAZymes from Aspergillus niger strain NRRL3. The data infer that P. sclerotigenum has the capacity to express several novel enzymes that may provide novel opportunities for sweet potato pectin modification and valorization of sweet potato starch processing residues. In addition, the methodological approach employed represents an integrative systematic strategy for enzyme discovery.
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Affiliation(s)
- Kristian Barrett
- Department of Biotechnology and Biomedicine, Technical University of Denmark, Kgs. Lyngby, Denmark
| | - Hai Zhao
- Chengdu Institute of Biology, Chinese Academy of Science, Chengdu, China
| | - Pengfei Hao
- La Trobe Institute for Agriculture and Food, La Trobe University, Melbourne, VIC, Australia
| | - Antony Bacic
- La Trobe Institute for Agriculture and Food, La Trobe University, Melbourne, VIC, Australia
| | - Lene Lange
- LLa BioEconomy, Research & Advisory, Valby, Denmark
| | - Jesper Holck
- Department of Biotechnology and Biomedicine, Technical University of Denmark, Kgs. Lyngby, Denmark
| | - Anne S. Meyer
- Department of Biotechnology and Biomedicine, Technical University of Denmark, Kgs. Lyngby, Denmark
- *Correspondence: Anne S. Meyer,
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26
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Su J, Chen T, Liao D, Wang Y, Su Y, Liu S, Chen X, Ruifang Q, Jiang L, Liu Z. Novel peptides extracted from Muraenesox cinereus bone promote calcium transport, osteoblast differentiation, and calcium absorption. J Funct Foods 2022. [DOI: 10.1016/j.jff.2022.105157] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022] Open
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27
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Contini C, Serrao S, Manconi B, Olianas A, Iavarone F, Bizzarro A, Masullo C, Castagnola M, Messana I, Diaz G, Cabras T. Salivary Proteomics Reveals Significant Changes in Relation to Alzheimer's Disease and Aging. J Alzheimers Dis 2022; 89:605-622. [PMID: 35912740 DOI: 10.3233/jad-220246] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
BACKGROUND Aging is a risk factor for several pathologies as Alzheimer's disease (AD). Great interest exists, therefore, in discovering diagnostic biomarkers and indicators discriminating biological aging and health status. To this aim, omic investigations of biological matrices, as saliva, whose sampling is easy and non-invasive, offer great potential. OBJECTIVE Investigate the salivary proteome through a statistical comparison of the proteomic data by several approaches to highlight quali-/quantitative variations associated specifically either to aging or to AD occurrence, and, thus, able to classify the subjects. METHODS Salivary proteomic data of healthy controls under-70 (adults) and over-70 (elderly) years old, and over-70 AD patients, obtained by liquid chromatography/mass spectrometry, were analyzed by multiple Mann-Whitney test, Kendall correlation, and Random-Forest (RF) analysis. RESULTS Almost all the investigated proteins/peptides significantly decreased in relation to aging in elderly subjects, with or without AD, in comparison with adults. AD subjects exhibited the highest levels of α-defensins, thymosin β4, cystatin B, S100A8 and A9. Correlation tests also highlighted age/disease associated differences. RF analysis individuated quali-/quantitative variations in 20 components, as oxidized S100A8 and S100A9, α-defensin 3, P-B peptide, able to classify with great accuracy the subjects into the three groups. CONCLUSION The findings demonstrated a strong change of the salivary protein profile in relation to the aging. Potential biomarkers candidates of AD were individuated in peptides/proteins involved in antimicrobial defense, innate immune system, inflammation, and in oxidative stress. RF analysis revealed the feasibility of the salivary proteome to discriminate groups of subjects based on age and health status.
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Affiliation(s)
- Cristina Contini
- Department of Life and Environmental Sciences, University of Cagliari, Cagliari, Italy
| | - Simone Serrao
- Department of Life and Environmental Sciences, University of Cagliari, Cagliari, Italy
| | - Barbara Manconi
- Department of Life and Environmental Sciences, University of Cagliari, Cagliari, Italy
| | - Alessandra Olianas
- Department of Life and Environmental Sciences, University of Cagliari, Cagliari, Italy
| | - Federica Iavarone
- Department of Basic Biotechnological Sciences, Intensive and Perioperative Clinics, Catholic University of the Sacred Heart, Rome, Italy.,Policlinico Universitario "A. Gemelli" Foundation -IRCCS, Rome, Italy
| | | | - Carlo Masullo
- Department of Neuroscience, Section Neurology, Catholic University of the Sacred Heart, Rome, Italy
| | - Massimo Castagnola
- Proteomics laboratory, European Centre for Research on the Brain, "Santa Lucia" Foundation -IRCCS, Rome, Italy
| | - Irene Messana
- Institute of Chemical Sciences and Technologies "Giulio Natta", National Research Council, Rome, Italy
| | - Giacomo Diaz
- Department of Biomedical Sciences University of Cagliari Cagliari, Italy
| | - Tiziana Cabras
- Department of Life and Environmental Sciences, University of Cagliari, Cagliari, Italy
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28
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Dar MA, Arafah A, Bhat KA, Khan A, Khan MS, Ali A, Ahmad SM, Rashid SM, Rehman MU. Multiomics technologies: role in disease biomarker discoveries and therapeutics. Brief Funct Genomics 2022; 22:76-96. [PMID: 35809340 DOI: 10.1093/bfgp/elac017] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2022] [Revised: 05/21/2022] [Accepted: 06/14/2022] [Indexed: 11/13/2022] Open
Abstract
Medical research has been revolutionized after the publication of the full human genome. This was the major landmark that paved the way for understanding the biological functions of different macro and micro molecules. With the advent of different high-throughput technologies, biomedical research was further revolutionized. These technologies constitute genomics, transcriptomics, proteomics, metabolomics, etc. Collectively, these high-throughputs are referred to as multi-omics technologies. In the biomedical field, these omics technologies act as efficient and effective tools for disease diagnosis, management, monitoring, treatment and discovery of certain novel disease biomarkers. Genotyping arrays and other transcriptomic studies have helped us to elucidate the gene expression patterns in different biological states, i.e. healthy and diseased states. Further omics technologies such as proteomics and metabolomics have an important role in predicting the role of different biological molecules in an organism. It is because of these high throughput omics technologies that we have been able to fully understand the role of different genes, proteins, metabolites and biological pathways in a diseased condition. To understand a complex biological process, it is important to apply an integrative approach that analyses the multi-omics data in order to highlight the possible interrelationships of the involved biomolecules and their functions. Furthermore, these omics technologies offer an important opportunity to understand the information that underlies disease. In the current review, we will discuss the importance of omics technologies as promising tools to understand the role of different biomolecules in diseases such as cancer, cardiovascular diseases, neurodegenerative diseases and diabetes. SUMMARY POINTS
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29
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Yeung D, Anderson G, Spicer V, Krokhin OV. Chromatographic behaviour of peptides modified with amine-reacting tags for relative protein quantitation in proteomic applications. J Chromatogr A 2022; 1679:463391. [DOI: 10.1016/j.chroma.2022.463391] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2022] [Revised: 07/27/2022] [Accepted: 07/29/2022] [Indexed: 10/16/2022]
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30
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Artificial intelligence in cancer target identification and drug discovery. Signal Transduct Target Ther 2022; 7:156. [PMID: 35538061 PMCID: PMC9090746 DOI: 10.1038/s41392-022-00994-0] [Citation(s) in RCA: 58] [Impact Index Per Article: 29.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2021] [Revised: 03/14/2022] [Accepted: 04/05/2022] [Indexed: 02/08/2023] Open
Abstract
Artificial intelligence is an advanced method to identify novel anticancer targets and discover novel drugs from biology networks because the networks can effectively preserve and quantify the interaction between components of cell systems underlying human diseases such as cancer. Here, we review and discuss how to employ artificial intelligence approaches to identify novel anticancer targets and discover drugs. First, we describe the scope of artificial intelligence biology analysis for novel anticancer target investigations. Second, we review and discuss the basic principles and theory of commonly used network-based and machine learning-based artificial intelligence algorithms. Finally, we showcase the applications of artificial intelligence approaches in cancer target identification and drug discovery. Taken together, the artificial intelligence models have provided us with a quantitative framework to study the relationship between network characteristics and cancer, thereby leading to the identification of potential anticancer targets and the discovery of novel drug candidates.
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31
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The potential of emerging sub-omics technologies for CHO cell engineering. Biotechnol Adv 2022; 59:107978. [DOI: 10.1016/j.biotechadv.2022.107978] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2022] [Revised: 04/25/2022] [Accepted: 05/07/2022] [Indexed: 11/23/2022]
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32
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Cao Z, Yu LR. Mass Spectrometry-Based Proteomics for Biomarker Discovery. METHODS IN MOLECULAR BIOLOGY (CLIFTON, N.J.) 2022; 2486:3-17. [PMID: 35437715 DOI: 10.1007/978-1-0716-2265-0_1] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Abstract
Proteomics plays a pivotal role in systems medicine, in which pharmacoproteomics and toxicoproteomics have been developed to address questions related to efficacy and toxicity of drugs. Mass spectrometry is the core technology for quantitative proteomics, providing the capabilities of identification and quantitation of thousands of proteins. The technology has been applied to biomarker discovery and understanding the mechanisms of drug action. Both stable isotope labeling of proteins or peptides and label-free approaches have been incorporated with multidimensional LC separation and tandem mass spectrometry (LC-MS/MS) to increase the coverage and depth of proteome analysis. A protocol of such an approach exemplified by dimethyl labeling in combination with 2D-LC-MS/MS is described. With further development of novel proteomic tools and increase in sample throughput, the full spectrum of mass spectrometry-based proteomic research will greatly advance systems medicine.
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Affiliation(s)
- Zhijun Cao
- Division of Systems Biology, National Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, AR, USA
| | - Li-Rong Yu
- Division of Systems Biology, National Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, AR, USA.
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33
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Na S, Choi H, Paek E. Deephos: Predicted spectral database search for TMT-labeled phosphopeptides and its false discovery rate estimation. Bioinformatics 2022; 38:2980-2987. [PMID: 35441674 DOI: 10.1093/bioinformatics/btac280] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2021] [Revised: 03/26/2022] [Accepted: 04/14/2022] [Indexed: 11/14/2022] Open
Abstract
MOTIVATION Tandem mass tag (TMT)-based tandem mass spectrometry (MS/MS) has become the method of choice for the quantification of post-translational modifications in complex mixtures. Many cancer proteogenomic studies have highlighted the importance of large-scale phosphopeptide quantification coupled with TMT labeling. Herein, we propose a predicted Spectral DataBase (pSDB) search strategy called Deephos that can improve both sensitivity and specificity in identifying MS/MS spectra of TMT-labeled phosphopeptides. RESULTS With deep learning-based fragment ion prediction, we compiled a pSDB of TMT-labeled phosphopeptides generated from ∼8,000 human phosphoproteins annotated in UniProt. Deep learning could successfully recognize the fragmentation patterns altered by both TMT labeling and phosphorylation. In addition, we discuss the decoy spectra for false discovery rate (FDR) estimation in the pSDB search. We show that FDR could be inaccurately estimated by the existing decoy spectra generation methods and propose an innovative method to generate decoy spectra for more accurate FDR estimation. The utilities of Deephos were demonstrated in multi-stage analyses (coupled with database searches) of glioblastoma, acute myeloid leukemia, and breast cancer phosphoproteomes. AVAILABILITY Deephos pSDB and the search software are available at https://github.com/seungjinna/deephos.
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Affiliation(s)
- Seungjin Na
- Institute for Artificial Intelligence Research, Hanyang University, Seoul, 04763, Republic of Korea
| | - Hyunjin Choi
- Department of Automotive Engineering, Hanyang University, Seoul, 04763, Republic of Korea
| | - Eunok Paek
- Institute for Artificial Intelligence Research, Hanyang University, Seoul, 04763, Republic of Korea.,Department of Computer Science, Hanyang University, Seoul, 04763, Republic of Korea
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Mizero B, Villacrés C, Spicer V, Viner R, Saba J, Patel B, Snovida S, Jensen P, Huhmer A, Krokhin OV. Retention Time Prediction for TMT-Labeled Peptides in Proteomic LC-MS Experiments. J Proteome Res 2022; 21:1218-1228. [PMID: 35363494 DOI: 10.1021/acs.jproteome.1c00833] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
We present the first detailed study of chromatographic behavior of peptides labeled with tandem mass tags (TMT and TMTpro) in 2D LC for proteomic applications. Carefully designed experimental procedures have permitted generating data sets of over 100,000 nonlabeled and TMT-labeled peptide pairs for the low pH RP in the second separation dimension and data sets of over 10,000 peptide pairs for high-pH RP, HILIC (amide and silica), and SCX separations in the first separation dimension. The average increase in peptide RPLC (0.1% formic acid) retention upon TMT labeling was found to be 3.3% acetonitrile (linear water/acetonitrile gradients), spanning a range of -4 to 10.3%. In addition to the bulk peptide properties such as length, hydrophobicity, and the number of labeled residues, we found several sequence-dependent features mostly associated with differences in N-terminal chemistry. The behavior of TMTpro-labeled peptides was found to be very similar except for a slightly higher hydrophobicity: an average retention shift of 3.7% acetonitrile. The respective versions of the sequence-specific retention calculator (SSRCalc) model have been developed to accommodate both TMT chemistries, showing identical prediction accuracy (R2 ∼ 0.98) for labeled and nonlabeled peptides. Higher retention for TMT-labeled peptides was observed for high-pH RP and HILIC separations, while SCX selectivity remained virtually unchanged.
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Affiliation(s)
- Benilde Mizero
- Department of Chemistry, University of Manitoba, Winnipeg R3T 2N2, Canada
| | - Carina Villacrés
- Manitoba Centre for Proteomics and Systems Biology, Winnipeg R3E 3P4, Canada
| | - Victor Spicer
- Manitoba Centre for Proteomics and Systems Biology, Winnipeg R3E 3P4, Canada
| | - Rosa Viner
- Thermo Fisher Scientific, San Jose, California 95134, United States
| | - Julian Saba
- Thermo Fisher Scientific, San Jose, California 95134, United States
| | | | - Sergei Snovida
- Thermo Fisher Scientific, Rockford, Illinois 61101, United States
| | - Penny Jensen
- Thermo Fisher Scientific, Rockford, Illinois 61101, United States
| | - Andreas Huhmer
- Thermo Fisher Scientific, San Jose, California 95134, United States
| | - Oleg V Krokhin
- Department of Chemistry, University of Manitoba, Winnipeg R3T 2N2, Canada.,Manitoba Centre for Proteomics and Systems Biology, Winnipeg R3E 3P4, Canada.,Department of Internal Medicine, University of Manitoba, Winnipeg R3E 3P4, Canada
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35
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Zakharova NV, Kononikhin AS, Indeykina MI, Bugrova AE, Strelnikova P, Pekov S, Kozin SA, Popov IA, Mitkevich V, Makarov AA, Nikolaev EN. Mass spectrometric studies of the variety of beta-amyloid proteoforms in Alzheimer's disease. MASS SPECTROMETRY REVIEWS 2022:e21775. [PMID: 35347731 DOI: 10.1002/mas.21775] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/28/2021] [Revised: 03/03/2022] [Accepted: 03/12/2022] [Indexed: 06/14/2023]
Abstract
This review covers the results of the application of mass spectrometric (MS) techniques to study the diversity of beta-amyloid (Aβ) peptides in human samples. Since Aβ is an important hallmark of Alzheimer's disease (AD), which is a socially significant neurodegenerative disorder of the elderly worldwide, analysis of its endogenous variations is of particular importance for elucidating the pathogenesis of AD, predicting increased risks of the disease onset, and developing effective therapy. MS approaches have no alternative for the study of complex samples, including a wide variety of Aβ proteoforms, differing in length and modifications. Approaches based on matrix-assisted laser desorption/ionization time-of-flight and liquid chromatography with electrospray ionization tandem MS are most common in Aβ studies. However, Aβ forms with isomerized and/or racemized Asp and Ser residues require the use of special methods for separation and extra sensitive and selective methods for detection. Overall, this review summarizes current knowledge of Aβ species found in human brain, cerebrospinal fluid, and blood plasma; focuses on application of different MS approaches for Aβ studies; and considers the potential of MS techniques for further studies of Aβ-peptides.
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Affiliation(s)
- Natalia V Zakharova
- Emanuel Institute of Biochemical Physics, Russian Academy of Sciences, Moscow, Russia
| | - Alexey S Kononikhin
- CMCB, Skolkovo Institute of Science and Technology, Moscow, Russia
- Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, Moscow, Russia
| | - Maria I Indeykina
- Emanuel Institute of Biochemical Physics, Russian Academy of Sciences, Moscow, Russia
- Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, Moscow, Russia
| | - Anna E Bugrova
- Emanuel Institute of Biochemical Physics, Russian Academy of Sciences, Moscow, Russia
- CMCB, Skolkovo Institute of Science and Technology, Moscow, Russia
| | - Polina Strelnikova
- Emanuel Institute of Biochemical Physics, Russian Academy of Sciences, Moscow, Russia
- Laboratory of ion and molecular physics, Moscow Institute of Physics and Technology, Dolgoprudny, Russia
| | - Stanislav Pekov
- CMCB, Skolkovo Institute of Science and Technology, Moscow, Russia
- Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, Moscow, Russia
- Laboratory of ion and molecular physics, Moscow Institute of Physics and Technology, Dolgoprudny, Russia
| | - Sergey A Kozin
- Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, Moscow, Russia
| | - Igor A Popov
- Laboratory of ion and molecular physics, Moscow Institute of Physics and Technology, Dolgoprudny, Russia
- N.N. Semenov Federal Center of Chemical Physics, V.L. Talrose Institute for Energy Problems of Chemical Physics, Russian Academy of Sciences, Moscow, Russia
| | - Vladimir Mitkevich
- Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, Moscow, Russia
| | - Alexander A Makarov
- Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, Moscow, Russia
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36
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Dong J, Duchesne A, Bayne AN, Mohamed NV, Yi W, Mathur M, Chen CXQ, You Z, Abdian N, Taylor L, Fon EA, Durcan TM, Trempe JF. An Approach to Measuring Protein Turnover in Human Induced Pluripotent Stem Cell Organoids by Mass Spectrometry. Methods 2022; 203:17-27. [PMID: 35331912 DOI: 10.1016/j.ymeth.2022.03.011] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2021] [Revised: 03/15/2022] [Accepted: 03/19/2022] [Indexed: 02/06/2023] Open
Abstract
Patient-derived organoids from induced pluripotent stem cells have emerged as a model for studying human diseases beyond conventional two-dimensional (2D) cell culture. Briefly, these three-dimensional organoids are highly complex, capable of self-organizing, recapitulate cellular architecture, and have the potential to model diseases in complex organs, such as the brain. For example, the hallmark of Parkinson's disease (PD) - proteostatic dysfunction leading to the selective death of neurons in the substantia nigra - present a subtle distinction in cell type specificity that is lost in 2D cell culture models. As such, the development of robust methods to study global proteostasis and protein turnover in organoids will remain essential as organoid models evolve. To solve this problem, we have designed a workflow to reproducibly extract proteins from brain organoids, measure global turnover using mass spectrometry, and statistically investigate turnover differences between genotypes. We also provide robust methodology for data filtering and statistical treatment of turnover data. Using human midbrain organoids (hMO) as a model system, our method accurately characterized the half-lives of 773 midbrain proteins. We compared these half-lives both to Parkin knockout hMOs and to previously reported data from primary cell cultures and in vivo models. Overall, this method will facilitate the study of proteostasis in organoid models of human disease and will provide an analytical and statistical framework to measure protein turnover in organoids of all cell types.
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Affiliation(s)
- Jing Dong
- Department of Pharmacology & Therapeutics and Centre de Recherche en Biologie Structurale, McGill University, 3655 Promenade Sir William Osler, Montreal, Quebec, H3G 1Y6, Canada
| | - Anthony Duchesne
- Department of Pharmacology & Therapeutics and Centre de Recherche en Biologie Structurale, McGill University, 3655 Promenade Sir William Osler, Montreal, Quebec, H3G 1Y6, Canada
| | - Andrew N Bayne
- Department of Pharmacology & Therapeutics and Centre de Recherche en Biologie Structurale, McGill University, 3655 Promenade Sir William Osler, Montreal, Quebec, H3G 1Y6, Canada
| | - Nguyen-Vi Mohamed
- Early Drug Discovery Unit (EDDU), Montreal Neurological Institute-Hospital, Department of Neurology and Neurosurgery, McGill University, 3801 University Street, Montreal, Quebec, H3A 2B4, Canada
| | - Wei Yi
- Early Drug Discovery Unit (EDDU), Montreal Neurological Institute-Hospital, Department of Neurology and Neurosurgery, McGill University, 3801 University Street, Montreal, Quebec, H3A 2B4, Canada
| | - Meghna Mathur
- Early Drug Discovery Unit (EDDU), Montreal Neurological Institute-Hospital, Department of Neurology and Neurosurgery, McGill University, 3801 University Street, Montreal, Quebec, H3A 2B4, Canada
| | - Carol X Q Chen
- Early Drug Discovery Unit (EDDU), Montreal Neurological Institute-Hospital, Department of Neurology and Neurosurgery, McGill University, 3801 University Street, Montreal, Quebec, H3A 2B4, Canada
| | - Zhipeng You
- Early Drug Discovery Unit (EDDU), Montreal Neurological Institute-Hospital, Department of Neurology and Neurosurgery, McGill University, 3801 University Street, Montreal, Quebec, H3A 2B4, Canada
| | - Narges Abdian
- Early Drug Discovery Unit (EDDU), Montreal Neurological Institute-Hospital, Department of Neurology and Neurosurgery, McGill University, 3801 University Street, Montreal, Quebec, H3A 2B4, Canada
| | - Lorne Taylor
- Proteomics Platform, Centre for Translational Biology, Research Institute of the McGill University Health Centre, 1001 Bd Décarie, Montréal, Quebec, H4A 3J1, Canada
| | - Edward A Fon
- Early Drug Discovery Unit (EDDU), Montreal Neurological Institute-Hospital, Department of Neurology and Neurosurgery, McGill University, 3801 University Street, Montreal, Quebec, H3A 2B4, Canada
| | - Thomas M Durcan
- Early Drug Discovery Unit (EDDU), Montreal Neurological Institute-Hospital, Department of Neurology and Neurosurgery, McGill University, 3801 University Street, Montreal, Quebec, H3A 2B4, Canada
| | - Jean-François Trempe
- Department of Pharmacology & Therapeutics and Centre de Recherche en Biologie Structurale, McGill University, 3655 Promenade Sir William Osler, Montreal, Quebec, H3G 1Y6, Canada; Proteomics Platform, Centre for Translational Biology, Research Institute of the McGill University Health Centre, 1001 Bd Décarie, Montréal, Quebec, H4A 3J1, Canada; Brain Repair and Integrative Neuroscience (BRaIN) Program, Centre for Translational Biology, Research Institute of the McGill University Health Centre, 1001 Bd Décarie, Montréal, Quebec, H4A 3J1, Canada.
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37
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Towards understanding the formation of internal fragments generated by collisionally activated dissociation for top-down mass spectrometry. Anal Chim Acta 2022; 1194:339400. [PMID: 35063165 PMCID: PMC9088748 DOI: 10.1016/j.aca.2021.339400] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2021] [Revised: 11/30/2021] [Accepted: 12/23/2021] [Indexed: 12/15/2022]
Abstract
Top-down mass spectrometry (TD-MS) generates fragment ions that returns information on the polypeptide amino acid sequence. In addition to terminal fragments, internal fragments that result from multiple cleavage events can also be formed. Traditionally, internal fragments are largely ignored due to a lack of available software to reliably assign them, mainly caused by a poor understanding of their formation mechanism. To accurately assign internal fragments, their formation process needs to be better understood. Here, we applied a statistical method to compare fragmentation patterns of internal and terminal fragments of peptides and proteins generated by collisionally activated dissociation (CAD). Internal fragments share similar fragmentation propensities with terminal fragments (e.g., enhanced cleavages N-terminal to proline and C-terminal to acidic residues), suggesting that their formation follows conventional CAD pathways. Internal fragments should be generated by subsequent cleavages of terminal fragments and their formation can be explained by the well-known mobile proton model. In addition, internal fragments can be coupled with terminal fragments to form complementary product ions that span the entire protein sequence. These enhance our understanding of internal fragment formation and can help improve sequencing algorithms to accurately assign internal fragments, which will ultimately lead to more efficient and comprehensive TD-MS analysis of proteins and proteoforms.
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38
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Sharafeldin M, Fleschhut F, James T, Davis JJ. A Quantification of Target Protein Biomarkers in Complex Media by Faradaic Shotgun Tagging. Anal Chem 2022; 94:2375-2382. [PMID: 35083913 PMCID: PMC9082491 DOI: 10.1021/acs.analchem.1c03695] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
![]()
The
progressive emergence of protein biomarkers promises a revolution
in the healthcare industry and a shift of focus from disease management
to much earlier intervention. Here, we introduce a facile shotgun
tagging of ensemble proteins in clinically relevant media prior to
specific target capture at antibody-modified electrodes. This facilitates
a convenient voltammetric quantification of markers down to sub-pg/mL
levels and across several orders of concentration. A translation of
the methodology to an automated microfluidic platform enables marker
quantification from 25 μL of sample in less than 15 min, demonstrated
here with a simultaneous assaying of CRP and cardiac troponin I (cTnI).
The assays show a good correlation with a standard immunoassay when
applied to real patient serum samples. The platform is simple, generic,
highly sensitive and requires no secondary labeling/binding or amplification.
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Affiliation(s)
- Mohamed Sharafeldin
- Department of Chemistry, University of Oxford South Parks Road, Oxford OX1 3QZ, U.K
| | - Felix Fleschhut
- Department of Chemistry, University of Oxford South Parks Road, Oxford OX1 3QZ, U.K
| | - Timothy James
- Department of Clinical Biochemistry, John Radcliffe Hospital Oxford University Hospitals NHS Foundation Trust, Oxford OX3 9DU, U.K
| | - Jason J Davis
- Department of Chemistry, University of Oxford South Parks Road, Oxford OX1 3QZ, U.K
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39
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Brzhozovskiy A, Kononikhin A, Bugrova AE, Kovalev GI, Schmit PO, Kruppa G, Nikolaev EN, Borchers CH. The Parallel Reaction Monitoring-Parallel Accumulation-Serial Fragmentation (prm-PASEF) Approach for Multiplexed Absolute Quantitation of Proteins in Human Plasma. Anal Chem 2022; 94:2016-2022. [PMID: 35040635 DOI: 10.1021/acs.analchem.1c03782] [Citation(s) in RCA: 21] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Mass spectrometry (MS)-based quantitative proteomic methods have become some of the major tools for protein biomarker discovery and validation. The recently developed parallel reaction monitoring-parallel accumulation-serial fragmentation (prm-PASEF) approach on a Bruker timsTOF Pro mass spectrometer allows the addition of ion mobility as a new dimension to LC-MS-based proteomics and increases proteome coverage at a reduced analysis time. In this study, a prm-PASEF approach was used for the multiplexed absolute quantitation of proteins in human plasma using isotope-labeled peptide standards for 125 plasma proteins, over a broad (104-106) dynamic range. Optimization of LC and MS parameters, such as accumulation time and collision energy, resulted in improved sensitivity for more than half of the targets (73 out of 125 peptides) by increasing the signal-to-noise ratio by a factor of up to 10. Overall, 41 peptides showed up to a 2-fold increase in sensitivity, 25 peptides showed up to a 5-fold increase in sensitivity, and 7 peptides showed up to a 10-fold increase in sensitivity. Implementation of the prm-PASEF method allowed absolute protein quantitation (down to 1.13 fmol) in human plasma samples. A comparison of the concentration values of plasma proteins determined by MRM on a QTRAP instrument and by prm-PASEF on a timsTOF Pro revealed an excellent correlation (R2 = 0.97) with a slope of close to 1 (0.99), demonstrating that prm-PASEF is well suited for "absolute" quantitative proteomics.
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Affiliation(s)
- Alexander Brzhozovskiy
- Center for Computational and Data-Intensive Science and Engineering, Skolkovo Institute of Science and Technology, Moscow 121205, Russia
| | - Alexey Kononikhin
- Center for Computational and Data-Intensive Science and Engineering, Skolkovo Institute of Science and Technology, Moscow 121205, Russia
| | - Anna E Bugrova
- Center for Computational and Data-Intensive Science and Engineering, Skolkovo Institute of Science and Technology, Moscow 121205, Russia.,Emanuel Institute for Biochemical Physics, Russian Academy of Sciences, Moscow 119334, Russia
| | - Grigoriy I Kovalev
- Center for Computational and Data-Intensive Science and Engineering, Skolkovo Institute of Science and Technology, Moscow 121205, Russia
| | | | - Gary Kruppa
- Bruker Daltonics, Inc. Billerica, Massachusetts 018215, United States
| | - Evgeny N Nikolaev
- Center for Computational and Data-Intensive Science and Engineering, Skolkovo Institute of Science and Technology, Moscow 121205, Russia
| | - Christoph H Borchers
- Center for Computational and Data-Intensive Science and Engineering, Skolkovo Institute of Science and Technology, Moscow 121205, Russia.,Segal Cancer Proteomics Centre, Lady Davis Institute, Jewish General Hospital, McGill University, Montreal, Quebec H3T 1E2, Canada.,Gerald Bronfman Department of Oncology, Jewish General Hospital, McGill University, Montreal, Quebec H3T 1E2, Canada
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40
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Vincent D, Bui A, Ram D, Ezernieks V, Bedon F, Panozzo J, Maharjan P, Rochfort S, Daetwyler H, Hayden M. Mining the Wheat Grain Proteome. Int J Mol Sci 2022; 23:ijms23020713. [PMID: 35054899 PMCID: PMC8775872 DOI: 10.3390/ijms23020713] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2021] [Revised: 12/23/2021] [Accepted: 12/30/2021] [Indexed: 12/10/2022] Open
Abstract
Bread wheat is the most widely cultivated crop worldwide, used in the production of food products and a feed source for animals. Selection tools that can be applied early in the breeding cycle are needed to accelerate genetic gain for increased wheat production while maintaining or improving grain quality if demand from human population growth is to be fulfilled. Proteomics screening assays of wheat flour can assist breeders to select the best performing breeding lines and discard the worst lines. In this study, we optimised a robust LC–MS shotgun quantitative proteomics method to screen thousands of wheat genotypes. Using 6 cultivars and 4 replicates, we tested 3 resuspension ratios (50, 25, and 17 µL/mg), 2 extraction buffers (with urea or guanidine-hydrochloride), 3 sets of proteases (chymotrypsin, Glu-C, and trypsin/Lys-C), and multiple LC settings. Protein identifications by LC–MS/MS were used to select the best parameters. A total 8738 wheat proteins were identified. The best method was validated on an independent set of 96 cultivars and peptides quantities were normalised using sample weights, an internal standard, and quality controls. Data mining tools found particularly useful to explore the flour proteome are presented (UniProt Retrieve/ID mapping tool, KEGG, AgriGO, REVIGO, and Pathway Tools).
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Affiliation(s)
- Delphine Vincent
- Agriculture Victoria, AgriBio, Centre for AgriBioscience, 5 Ring Road, Bundoora, VIC 3083, Australia; (A.B.); (D.R.); (V.E.); (S.R.); (H.D.); (M.H.)
- Correspondence:
| | - AnhDuyen Bui
- Agriculture Victoria, AgriBio, Centre for AgriBioscience, 5 Ring Road, Bundoora, VIC 3083, Australia; (A.B.); (D.R.); (V.E.); (S.R.); (H.D.); (M.H.)
| | - Doris Ram
- Agriculture Victoria, AgriBio, Centre for AgriBioscience, 5 Ring Road, Bundoora, VIC 3083, Australia; (A.B.); (D.R.); (V.E.); (S.R.); (H.D.); (M.H.)
| | - Vilnis Ezernieks
- Agriculture Victoria, AgriBio, Centre for AgriBioscience, 5 Ring Road, Bundoora, VIC 3083, Australia; (A.B.); (D.R.); (V.E.); (S.R.); (H.D.); (M.H.)
| | - Frank Bedon
- Department of Animal, Plant and Soil Sciences, School of Life Sciences, La Trobe University, Bundoora, VIC 3083, Australia;
| | - Joe Panozzo
- Agriculture Research Victoria, 110 Natimuk Road, Horsham, VIC 3400, Australia; (J.P.); (P.M.)
- Centre for Agricultural Innovation, University of Melbourne, Parkville, VIC 3010, Australia
| | - Pankaj Maharjan
- Agriculture Research Victoria, 110 Natimuk Road, Horsham, VIC 3400, Australia; (J.P.); (P.M.)
| | - Simone Rochfort
- Agriculture Victoria, AgriBio, Centre for AgriBioscience, 5 Ring Road, Bundoora, VIC 3083, Australia; (A.B.); (D.R.); (V.E.); (S.R.); (H.D.); (M.H.)
- School of Applied Systems Biology, La Trobe University, Bundoora, VIC 3083, Australia
| | - Hans Daetwyler
- Agriculture Victoria, AgriBio, Centre for AgriBioscience, 5 Ring Road, Bundoora, VIC 3083, Australia; (A.B.); (D.R.); (V.E.); (S.R.); (H.D.); (M.H.)
- School of Applied Systems Biology, La Trobe University, Bundoora, VIC 3083, Australia
| | - Matthew Hayden
- Agriculture Victoria, AgriBio, Centre for AgriBioscience, 5 Ring Road, Bundoora, VIC 3083, Australia; (A.B.); (D.R.); (V.E.); (S.R.); (H.D.); (M.H.)
- School of Applied Systems Biology, La Trobe University, Bundoora, VIC 3083, Australia
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41
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Targeted proteomics for the analysis of cultural heritage: application of broadband collision-induced dissociation mass spectrometry. Anal Bioanal Chem 2022; 414:1723-1737. [DOI: 10.1007/s00216-021-03805-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2021] [Revised: 11/19/2021] [Accepted: 11/24/2021] [Indexed: 11/01/2022]
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42
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Boroumand M, Manconi B, Serrao S, Iavarone F, Olianas A, Cabras T, Contini C, Pieroni L, Sanna MT, Vento G, Tirone C, Desiderio C, Fiorita A, Faa G, Messana I, Castagnola M. Investigation by top‐down high‐performance liquid chromatography–mass spectrometry of glutathionylation and cysteinylation of salivary S100A9 and cystatin B in preterm newborns. SEPARATION SCIENCE PLUS 2022. [DOI: 10.1002/sscp.202100049] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Affiliation(s)
- Mozghan Boroumand
- Laboratorio di Proteomica, Centro Europeo di Ricerca sul Cervello IRCCS Fondazione Santa Lucia Via Ardeatina, 306/354 Roma 00179 Italy
| | - Barbara Manconi
- Dipartimento di Scienze della Vita e dell'Ambiente Università di Cagliari Cagliari Italy
| | - Simone Serrao
- Dipartimento di Scienze della Vita e dell'Ambiente Università di Cagliari Cagliari Italy
| | - Federica Iavarone
- Fondazione Policlinico Universitario “A. Gemelli” ‐ IRCCS Roma Italy
- Dipartimento di Scienze Biotecnologiche di Base Cliniche Intensivologiche e Perioperatorie Facoltà di Medicina e Chirurgia Università Cattolica Sacro Cuore Roma Italy
| | - Alessandra Olianas
- Dipartimento di Scienze della Vita e dell'Ambiente Università di Cagliari Cagliari Italy
| | - Tiziana Cabras
- Dipartimento di Scienze della Vita e dell'Ambiente Università di Cagliari Cagliari Italy
| | - Cristina Contini
- Dipartimento di Scienze della Vita e dell'Ambiente Università di Cagliari Cagliari Italy
| | - Luisa Pieroni
- Laboratorio di Proteomica, Centro Europeo di Ricerca sul Cervello IRCCS Fondazione Santa Lucia Via Ardeatina, 306/354 Roma 00179 Italy
| | - Maria Teresa Sanna
- Dipartimento di Scienze della Vita e dell'Ambiente Università di Cagliari Cagliari Italy
| | - Giovanni Vento
- Fondazione Policlinico Universitario “A. Gemelli” ‐ IRCCS Roma Italy
- Divisione di Neonatologia Dipartimento per la Salute della Donna e del Bambino Università Cattolica del Sacro Cuore Roma Italy
| | - Chiara Tirone
- Fondazione Policlinico Universitario “A. Gemelli” ‐ IRCCS Roma Italy
- Divisione di Neonatologia Dipartimento per la Salute della Donna e del Bambino Università Cattolica del Sacro Cuore Roma Italy
| | - Claudia Desiderio
- Istituto di Scienze e Tecnologie Chimiche “Giulio Natta” Consiglio Nazionale delle Ricerche Roma Italy
| | - Antonella Fiorita
- Fondazione Policlinico Universitario “A. Gemelli” ‐ IRCCS Roma Italy
- Dipartimento di Scienze dell'Invecchiamento Neurologiche Ortopediche e della Testa e del Collo Università Cattolica del Sacro Cuore Roma Italy
| | - Gavino Faa
- Sezione di Anatomia Patologica Dipartimento di Scienze Mediche e Sanità Pubblica Università di Cagliari Cagliari Italy
- Temple University Philadelphia USA
| | - Irene Messana
- Istituto di Scienze e Tecnologie Chimiche “Giulio Natta” Consiglio Nazionale delle Ricerche Roma Italy
| | - Massimo Castagnola
- Laboratorio di Proteomica, Centro Europeo di Ricerca sul Cervello IRCCS Fondazione Santa Lucia Via Ardeatina, 306/354 Roma 00179 Italy
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43
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Nosti AJ, Barrio LC, Calderón-Celis F, Soldado A, Encinar JR. Absolute quantification of proteins using element mass spectrometry and generic standards. J Proteomics 2022; 256:104499. [DOI: 10.1016/j.jprot.2022.104499] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2021] [Accepted: 01/21/2022] [Indexed: 10/19/2022]
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44
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Li W, Li F, Zhang X, Lin HK, Xu C. Insights into the post-translational modification and its emerging role in shaping the tumor microenvironment. Signal Transduct Target Ther 2021; 6:422. [PMID: 34924561 PMCID: PMC8685280 DOI: 10.1038/s41392-021-00825-8] [Citation(s) in RCA: 57] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2021] [Revised: 11/02/2021] [Accepted: 11/05/2021] [Indexed: 12/11/2022] Open
Abstract
More and more in-depth studies have revealed that the occurrence and development of tumors depend on gene mutation and tumor heterogeneity. The most important manifestation of tumor heterogeneity is the dynamic change of tumor microenvironment (TME) heterogeneity. This depends not only on the tumor cells themselves in the microenvironment where the infiltrating immune cells and matrix together forming an antitumor and/or pro-tumor network. TME has resulted in novel therapeutic interventions as a place beyond tumor beds. The malignant cancer cells, tumor infiltrate immune cells, angiogenic vascular cells, lymphatic endothelial cells, cancer-associated fibroblastic cells, and the released factors including intracellular metabolites, hormonal signals and inflammatory mediators all contribute actively to cancer progression. Protein post-translational modification (PTM) is often regarded as a degradative mechanism in protein destruction or turnover to maintain physiological homeostasis. Advances in quantitative transcriptomics, proteomics, and nuclease-based gene editing are now paving the global ways for exploring PTMs. In this review, we focus on recent developments in the PTM area and speculate on their importance as a critical functional readout for the regulation of TME. A wealth of information has been emerging to prove useful in the search for conventional therapies and the development of global therapeutic strategies.
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Affiliation(s)
- Wen Li
- grid.54549.390000 0004 0369 4060Integrative Cancer Center & Cancer Clinical Research Center, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, 610042 Chengdu, P. R. China
| | - Feifei Li
- grid.54549.390000 0004 0369 4060Integrative Cancer Center & Cancer Clinical Research Center, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, 610042 Chengdu, P. R. China ,grid.256607.00000 0004 1798 2653Guangxi Collaborative Innovation Center for Biomedicine (Guangxi-ASEAN Collaborative Innovation Center for Major Disease Prevention and Treatment), Guangxi Medical University, 530021 Nanning, Guangxi China
| | - Xia Zhang
- grid.410570.70000 0004 1760 6682Institute of Pathology and Southwest Cancer Center, Southwest Hospital, Third Military Medical University (Army Medical University), 400038 Chongqing, China
| | - Hui-Kuan Lin
- grid.241167.70000 0001 2185 3318Department of Cancer Biology, Wake Forest Baptist Medical Center, Wake Forest University, Winston Salem, NC 27101 USA
| | - Chuan Xu
- Integrative Cancer Center & Cancer Clinical Research Center, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, 610042, Chengdu, P. R. China. .,Department of Cancer Biology, Wake Forest Baptist Medical Center, Wake Forest University, Winston Salem, NC, 27101, USA.
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45
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Gaudelet T, Day B, Jamasb AR, Soman J, Regep C, Liu G, Hayter JBR, Vickers R, Roberts C, Tang J, Roblin D, Blundell TL, Bronstein MM, Taylor-King JP. Utilizing graph machine learning within drug discovery and development. Brief Bioinform 2021; 22:bbab159. [PMID: 34013350 PMCID: PMC8574649 DOI: 10.1093/bib/bbab159] [Citation(s) in RCA: 48] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2020] [Revised: 04/01/2021] [Accepted: 04/05/2021] [Indexed: 12/15/2022] Open
Abstract
Graph machine learning (GML) is receiving growing interest within the pharmaceutical and biotechnology industries for its ability to model biomolecular structures, the functional relationships between them, and integrate multi-omic datasets - amongst other data types. Herein, we present a multidisciplinary academic-industrial review of the topic within the context of drug discovery and development. After introducing key terms and modelling approaches, we move chronologically through the drug development pipeline to identify and summarize work incorporating: target identification, design of small molecules and biologics, and drug repurposing. Whilst the field is still emerging, key milestones including repurposed drugs entering in vivo studies, suggest GML will become a modelling framework of choice within biomedical machine learning.
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Affiliation(s)
| | - Ben Day
- Relation Therapeutics, London, UK
- The Computer Laboratory, University of Cambridge, UK
| | - Arian R Jamasb
- Relation Therapeutics, London, UK
- The Computer Laboratory, University of Cambridge, UK
- Department of Biochemistry, University of Cambridge, UK
| | | | | | | | | | | | | | - Jian Tang
- Mila, the Quebec AI Institute, Canada
- HEC Montreal, Canada
| | - David Roblin
- Relation Therapeutics, London, UK
- Juvenescence, London, UK
- The Francis Crick Institute, London, UK
| | | | - Michael M Bronstein
- Relation Therapeutics, London, UK
- Department of Computing, Imperial College London, UK
- Twitter, UK
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46
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Chepyala SR, Liu X, Yang K, Wu Z, Breuer AM, Cho JH, Li Y, Mancieri A, Jiao Y, Zhang H, Peng J. JUMPt: Comprehensive Protein Turnover Modeling of In Vivo Pulse SILAC Data by Ordinary Differential Equations. Anal Chem 2021; 93:13495-13504. [PMID: 34587451 DOI: 10.1021/acs.analchem.1c02309] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Recent advances in mass spectrometry (MS)-based proteomics allow the measurement of turnover rates of thousands of proteins using dynamic labeling methods, such as pulse stable isotope labeling by amino acids in cell culture (pSILAC). However, when applying the pSILAC strategy to multicellular animals (e.g., mice), the labeling process is significantly delayed by native amino acids recycled from protein degradation in vivo, raising a challenge of defining accurate protein turnover rates. Here, we report JUMPt, a software package using a novel ordinary differential equation (ODE)-based mathematical model to determine reliable rates of protein degradation. The uniqueness of JUMPt is to consider amino acid recycling and fit the kinetics of the labeling amino acid (e.g., Lys) and whole proteome simultaneously to derive half-lives of individual proteins. Multiple settings in the software are designed to enable simple to comprehensive data inputs for precise analysis of half-lives with flexibility. We examined the software by studying the turnover of thousands of proteins in the pSILAC brain and liver tissues. The results were largely consistent with the proteome turnover measurements from previous studies. The long-lived proteins are enriched in the integral membrane, myelin sheath, and mitochondrion in the brain. In summary, the ODE-based JUMPt software is an effective proteomics tool for analyzing large-scale protein turnover, and the software is publicly available on GitHub (https://github.com/JUMPSuite/JUMPt) to the research community.
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Affiliation(s)
- Surendhar Reddy Chepyala
- Department of Structural Biology, St. Jude Children's Research Hospital, Memphis, Tennessee 38105, United States.,Department of Developmental Neurobiology, St. Jude Children's Research Hospital, Memphis, Tennessee 38105, United States
| | - Xueyan Liu
- Department of Biostatistics, St. Jude Children's Research Hospital, Memphis, Tennessee 38105, United States
| | - Ka Yang
- Department of Structural Biology, St. Jude Children's Research Hospital, Memphis, Tennessee 38105, United States.,Department of Developmental Neurobiology, St. Jude Children's Research Hospital, Memphis, Tennessee 38105, United States
| | - Zhiping Wu
- Department of Structural Biology, St. Jude Children's Research Hospital, Memphis, Tennessee 38105, United States.,Department of Developmental Neurobiology, St. Jude Children's Research Hospital, Memphis, Tennessee 38105, United States
| | - Alex M Breuer
- Department of Information Services, St. Jude Children's Research Hospital, Memphis, Tennessee 38105, United States
| | - Ji-Hoon Cho
- Center for Proteomics and Metabolomics, St. Jude Children's Research Hospital, Memphis, Tennessee 38105, United States
| | - Yuxin Li
- Center for Proteomics and Metabolomics, St. Jude Children's Research Hospital, Memphis, Tennessee 38105, United States
| | - Ariana Mancieri
- Department of Structural Biology, St. Jude Children's Research Hospital, Memphis, Tennessee 38105, United States.,Department of Developmental Neurobiology, St. Jude Children's Research Hospital, Memphis, Tennessee 38105, United States
| | - Yun Jiao
- Department of Structural Biology, St. Jude Children's Research Hospital, Memphis, Tennessee 38105, United States.,Department of Developmental Neurobiology, St. Jude Children's Research Hospital, Memphis, Tennessee 38105, United States
| | - Hui Zhang
- Department of Biostatistics, St. Jude Children's Research Hospital, Memphis, Tennessee 38105, United States
| | - Junmin Peng
- Department of Structural Biology, St. Jude Children's Research Hospital, Memphis, Tennessee 38105, United States.,Department of Developmental Neurobiology, St. Jude Children's Research Hospital, Memphis, Tennessee 38105, United States.,Center for Proteomics and Metabolomics, St. Jude Children's Research Hospital, Memphis, Tennessee 38105, United States
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47
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Serrano-Blesa E, Porter A, Lendrem DW, Pitzalis C, Barton A, Treumann A, Isaacs JD. Robust optimization of SWATH-MS workflow for human blood serum proteome analysis using a quality by design approach. Clin Proteomics 2021; 18:20. [PMID: 34384350 PMCID: PMC8359389 DOI: 10.1186/s12014-021-09323-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2021] [Accepted: 07/21/2021] [Indexed: 11/13/2022] Open
Abstract
Background It is not enough to optimize proteomics assays. It is critical those assays are robust to operating conditions. Without robust assays, proteomic biomarkers are unlikely to translate readily into the clinic. This study outlines a structured approach to the identification of a robust operating window for proteomics assays and applies that method to Sequential Window Acquisition of all Theoretical Spectra Mass Spectroscopy (SWATH-MS). Methods We used a sequential quality by design approach exploiting a fractional screening design to first identify critical SWATH-MS parameters, then using response surface methods to identify a robust operating window with good reproducibility, before validating those settings in a separate validation study. Results The screening experiment identified two critical SWATH-MS parameters. We modelled the number of proteins and reproducibility as a function of those parameters identifying an operating window permitting robust maximization of the number of proteins quantified in human serum. In a separate validation study, these settings were shown to give good proteome-wide coverage and high quantification reproducibility. Conclusions Using design of experiments permits identification of a robust operating window for SWATH-MS. The method gives a good understanding of proteomics assays and greater data-driven confidence in SWATH-MS performance. Supplementary Information The online version contains supplementary material available at 10.1186/s12014-021-09323-z.
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Affiliation(s)
- Edith Serrano-Blesa
- National Institute of Health Research Newcastle Biomedical Research Centre and the Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, UK
| | - Andrew Porter
- Newcastle University Protein and Proteome Facility, Newcastle upon Tyne, UK
| | - Dennis W Lendrem
- National Institute of Health Research Newcastle Biomedical Research Centre and the Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, UK
| | - Costantino Pitzalis
- Centre for Experimental Medicine and Rheumatology, Queen Mary University of London, London, UK
| | - Anne Barton
- Versus Arthritis Centre for Genetics and Genomics, Centre for Musculoskeletal Research, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre,, The University of Manchester, Manchester, UK
| | - Achim Treumann
- Newcastle University Protein and Proteome Facility, Newcastle upon Tyne, UK
| | - John D Isaacs
- National Institute of Health Research Newcastle Biomedical Research Centre and the Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, UK. .,Musculoskeletal Unit, Freeman Hospital, Newcastle upon Tyne NHS Foundation Trust, Newcastle upon Tyne, UK.
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48
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Miles HN, Delafield DG, Li L. Recent Developments and Applications of Quantitative Proteomics Strategies for High-Throughput Biomolecular Analyses in Cancer Research. RSC Chem Biol 2021; 4:1050-1072. [PMID: 34430874 PMCID: PMC8341969 DOI: 10.1039/d1cb00039j] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2021] [Accepted: 05/18/2021] [Indexed: 12/28/2022] Open
Abstract
Innovations in medical technology and dedicated focus from the scientific community have inspired numerous treatment strategies for benign and invasive cancers. While these improvements often lend themselves to more positive prognoses and greater patient longevity, means for early detection and severity stratification have failed to keep pace. Detection and validation of cancer-specific biomarkers hinges on the ability to identify subtype-specific phenotypic and proteomic alterations and the systematic screening of diverse patient groups. For this reason, clinical and scientific research settings rely on high throughput and high sensitivity mass spectrometry methods to discover and quantify unique molecular perturbations in cancer patients. Discussed within is an overview of quantitative proteomics strategies and a summary of recent applications that enable revealing potential biomarkers and treatment targets in prostate, ovarian, breast, and pancreatic cancer in a high throughput manner.
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Affiliation(s)
- Hannah N. Miles
- School of Pharmacy, University of Wisconsin-Madison777 Highland AvenueMadisonWI53705-2222USA+1-608-262-5345+1-608-265-8491
| | | | - Lingjun Li
- School of Pharmacy, University of Wisconsin-Madison777 Highland AvenueMadisonWI53705-2222USA+1-608-262-5345+1-608-265-8491
- Department of Chemistry, University of Wisconsin-MadisonMadisonWI53706USA
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49
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López-López V, Pérez-Sánz F, de Torre-Minguela C, Marco-Abenza J, Robles-Campos R, Sánchez-Bueno F, Pons JA, Ramírez P, Baroja-Mazo A. Proteomics in Liver Transplantation: A Systematic Review. Front Immunol 2021; 12:672829. [PMID: 34381445 PMCID: PMC8350337 DOI: 10.3389/fimmu.2021.672829] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2021] [Accepted: 07/12/2021] [Indexed: 01/10/2023] Open
Abstract
Background Although proteomics has been employed in the study of several models of liver injury, proteomic methods have only recently been applied not only to biomarker discovery and validation but also to improve understanding of the molecular mechanisms involved in transplantation. Methods The study was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology and the guidelines for performing systematic literature reviews in bioinformatics (BiSLR). The PubMed, ScienceDirect, and Scopus databases were searched for publications through April 2020. Proteomics studies designed to understand liver transplant outcomes, including ischemia-reperfusion injury (IRI), rejection, or operational tolerance in human or rat samples that applied methodologies for differential expression analysis were considered. Results The analysis included 22 studies after application of the inclusion and exclusion criteria. Among the 497 proteins annotated, 68 were shared between species and 10 were shared between sample sources. Among the types of studies analyzed, IRI and rejection shared a higher number of proteins. The most enriched pathway for liver biopsy samples, IRI, and rejection was metabolism, compared to cytokine-cytokine receptor interactions for tolerance. Conclusions Proteomics is a promising technique to detect large numbers of proteins. However, our study shows that several technical issues such as the identification of proteoforms or the dynamic range of protein concentration in clinical samples hinder the successful identification of biomarkers in liver transplantation. In addition, there is a need to minimize the experimental variability between studies, increase the sample size and remove high-abundance plasma proteins.
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Affiliation(s)
- Victor López-López
- Department of Surgery, Hospital Clínico Universitario Virgen de la Arrixaca, Murcia, Spain.,Digestive and Endocrine Surgery and Transplantation of Abdominal Organs, Biomedical Research Institute of Murcia (IMIB-Arrixaca), Murcia, Spain
| | - Fernando Pérez-Sánz
- Biomedical Informatic and Bioinformatic Platform, Biomedical Research Institute of Murcia (IMIB-Arrixaca), Murcia, Spain
| | - Carlos de Torre-Minguela
- Digestive and Endocrine Surgery and Transplantation of Abdominal Organs, Biomedical Research Institute of Murcia (IMIB-Arrixaca), Murcia, Spain
| | | | - Ricardo Robles-Campos
- Department of Surgery, Hospital Clínico Universitario Virgen de la Arrixaca, Murcia, Spain.,Digestive and Endocrine Surgery and Transplantation of Abdominal Organs, Biomedical Research Institute of Murcia (IMIB-Arrixaca), Murcia, Spain
| | - Francisco Sánchez-Bueno
- Department of Surgery, Hospital Clínico Universitario Virgen de la Arrixaca, Murcia, Spain.,Digestive and Endocrine Surgery and Transplantation of Abdominal Organs, Biomedical Research Institute of Murcia (IMIB-Arrixaca), Murcia, Spain
| | - José A Pons
- Digestive and Endocrine Surgery and Transplantation of Abdominal Organs, Biomedical Research Institute of Murcia (IMIB-Arrixaca), Murcia, Spain.,Department of Gastroenterology, Unit of Hepatology, Hospital Clínico Universitario Virgen de la Arrixaca, Murcia, Spain
| | - Pablo Ramírez
- Department of Surgery, Hospital Clínico Universitario Virgen de la Arrixaca, Murcia, Spain.,Digestive and Endocrine Surgery and Transplantation of Abdominal Organs, Biomedical Research Institute of Murcia (IMIB-Arrixaca), Murcia, Spain
| | - Alberto Baroja-Mazo
- Digestive and Endocrine Surgery and Transplantation of Abdominal Organs, Biomedical Research Institute of Murcia (IMIB-Arrixaca), Murcia, Spain
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50
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Ai Y, Zhao P, FNU PIJ, Chen H. Absolute Quantitation of Tryptophan-Containing Peptides and Amyloid β-Peptide Fragments by Coulometric Mass Spectrometry. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2021; 32:1771-1779. [PMID: 34101439 PMCID: PMC8925997 DOI: 10.1021/jasms.1c00121] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/13/2023]
Abstract
Isotope-labeled internal standards are routinely used for mass spectrometry (MS)-based absolute quantitation. However, syntheses of isotope-labeled peptides are time-consuming and costly. To tackle this issue, we recently developed a coulometric mass spectrometric (CMS) approach for absolute quantitation without the use of standards, based on the electrochemical oxidation of cysteine or tyrosine-containing peptides followed by mass spectrometric measurement of the oxidation yield. To further expand the utility of this method, herein we present the CMS method for absolute quantitation of peptides based on tryptophan electrochemical oxidation. Several tryptophan-containing peptides, such as WGG, WQPPRARI, WAGGDASGE, RTRPLWVRME, and KVPRNQDWL, were successfully quantified with a quantification error ranging from -4.5 to +4.3%. Furthermore, this quantitation approach is also applicable to protein, in which protein can be digested and a surrogate peptide can be selected for quantification to reflect the amount of the parent protein, as exemplified by CMS analysis of peptide GITWK from cytochrome c. The CMS result agreed well with the traditional isotope dilution method, with only a small difference of 3.5%. In addition, CMS was used to successfully quantify amyloid beta (Aβ) peptide fragments (up to 28 amino acid residues) based on tyrosine oxidation. The validity of the CMS method for peptide and protein absolute quantitation without using isotope-labeled peptide standards would greatly facilitate proteomics research.
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Affiliation(s)
| | | | | | - Hao Chen
- Corresponding Author: Hao Chen - Department of Chemistry and Environmental Science, New Jersey Institute of Technology, Newark, New Jersey, USA 07102
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