1
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Purohit K, Reddy N, Sunna A. Exploring the Potential of Bioactive Peptides: From Natural Sources to Therapeutics. Int J Mol Sci 2024; 25:1391. [PMID: 38338676 PMCID: PMC10855437 DOI: 10.3390/ijms25031391] [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: 12/01/2023] [Revised: 01/18/2024] [Accepted: 01/21/2024] [Indexed: 02/12/2024] Open
Abstract
Bioactive peptides, specific protein fragments with positive health effects, are gaining traction in drug development for advantages like enhanced penetration, low toxicity, and rapid clearance. This comprehensive review navigates the intricate landscape of peptide science, covering discovery to functional characterization. Beginning with a peptidomic exploration of natural sources, the review emphasizes the search for novel peptides. Extraction approaches, including enzymatic hydrolysis, microbial fermentation, and specialized methods for disulfide-linked peptides, are extensively covered. Mass spectrometric analysis techniques for data acquisition and identification, such as liquid chromatography, capillary electrophoresis, untargeted peptide analysis, and bioinformatics, are thoroughly outlined. The exploration of peptide bioactivity incorporates various methodologies, from in vitro assays to in silico techniques, including advanced approaches like phage display and cell-based assays. The review also discusses the structure-activity relationship in the context of antimicrobial peptides (AMPs), ACE-inhibitory peptides (ACEs), and antioxidative peptides (AOPs). Concluding with key findings and future research directions, this interdisciplinary review serves as a comprehensive reference, offering a holistic understanding of peptides and their potential therapeutic applications.
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Affiliation(s)
- Kruttika Purohit
- School of Natural Sciences, Macquarie University, Sydney, NSW 2109, Australia;
- Australian Research Council Industrial Transformation Training Centre for Facilitated Advancement of Australia’s Bioactives (FAAB), Sydney, NSW 2109, Australia;
| | - Narsimha Reddy
- Australian Research Council Industrial Transformation Training Centre for Facilitated Advancement of Australia’s Bioactives (FAAB), Sydney, NSW 2109, Australia;
- School of Science, Parramatta Campus, Western Sydney University, Penrith, NSW 2751, Australia
| | - Anwar Sunna
- School of Natural Sciences, Macquarie University, Sydney, NSW 2109, Australia;
- Australian Research Council Industrial Transformation Training Centre for Facilitated Advancement of Australia’s Bioactives (FAAB), Sydney, NSW 2109, Australia;
- Biomolecular Discovery Research Centre, Macquarie University, Sydney, NSW 2109, Australia
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2
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Schrader M, Fricker LD. Current Challenges and Future Directions in Peptidomics. Methods Mol Biol 2024; 2758:485-498. [PMID: 38549031 DOI: 10.1007/978-1-0716-3646-6_26] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/02/2024]
Abstract
The field of peptidomics has been under development since its start more than 20 years ago. In this chapter we provide a personal outlook for future directions in this field. The applications of peptidomics technologies are spreading more and more from classical research of peptide hormones and neuropeptides towards commercial applications in plant and food-science. Many clinical applications have been developed to analyze the complexity of biofluids, which are being addressed with new instrumentation, automization, and data processing. Additionally, the newly developed field of immunopeptidomics is showing promise for cancer therapies. In conclusion, peptidomics will continue delivering important information in classical fields like neuropeptides and peptide hormones, benefiting from improvements in state-of-the-art technologies. Moreover, new directions of research such as immunopeptidomics will further complement classical omics technologies and may become routine clinical procedures. Taken together, discoveries of new substances, networks, and applications of peptides can be expected in different disciplines.
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Affiliation(s)
- Michael Schrader
- Department of Bioengineering Sciences, Weihenstephan-Tr. University of Applied Sciences, Freising, Germany.
| | - Lloyd D Fricker
- Departments of Molecular Pharmacology and Neuroscience, Albert Einstein College of Medicine, Bronx, NY, USA
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3
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Bichmann L, Gupta S, Röst H. Data-Independent Acquisition Peptidomics. Methods Mol Biol 2024; 2758:77-88. [PMID: 38549009 DOI: 10.1007/978-1-0716-3646-6_4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/02/2024]
Abstract
In recent years, data-independent acquisition (DIA) has emerged as a powerful analysis method in biological mass spectrometry (MS). Compared to the previously predominant data-dependent acquisition (DDA), it offers a way to achieve greater reproducibility, sensitivity, and dynamic range in MS measurements. To make DIA accessible to non-expert users, a multifunctional, automated high-throughput pipeline DIAproteomics was implemented in the computational workflow framework "Nextflow" ( https://nextflow.io ). This allows high-throughput processing of proteomics and peptidomics DIA datasets on diverse computing infrastructures. This chapter provides a short summary and usage protocol guide for the most important modes of operation of this pipeline regarding the analysis of peptidomics datasets using the command line. In brief, DIAproteomics is a wrapper around the OpenSwathWorkflow and relies on either existing or ad-hoc generated spectral libraries from matching DDA runs. The OpenSwathWorkflow extracts chromatograms from the DIA runs and performs chromatographic peak-picking. Further downstream of the pipeline, these peaks are scored, aligned, and statistically evaluated for qualitative and quantitative differences across conditions depending on the user's interest. DIAproteomics is open-source and available under a permissive license. We encourage the scientific community to use or modify the pipeline to meet their specific requirements.
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Affiliation(s)
- Leon Bichmann
- Department of Computer Science, Applied Bioinformatics, University of Tübingen, Tübingen, Germany
| | - Shubham Gupta
- Donnelly Center for Cellular and Biomolecular Research, University of Toronto, Toronto, ON, Canada
| | - Hannes Röst
- Donnelly Center for Cellular and Biomolecular Research, University of Toronto, Toronto, ON, Canada
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4
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Smith JW, O'Meally RN, Burke SM, Ng DK, Chen JG, Kensler TW, Groopman JD, Cole RN. Global Discovery and Temporal Changes of Human Albumin Modifications by Pan-Protein Adductomics: Initial Application to Air Pollution Exposure. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2023; 34:595-607. [PMID: 36939690 DOI: 10.1021/jasms.2c00314] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/18/2023]
Abstract
Assessing personal exposure to environmental toxicants is a critical challenge for predicting disease risk. Previously, using human serum albumin (HSA)-based biomonitoring, we reported dosimetric relationships between adducts at HSA Cys34 and ambient air pollutant levels (Smith et al., Chem. Res. Toxicol. 2021, 34, 1183). These results provided the foundation to explore modifications at other sites in HSA to reveal novel adducts of complex exposures. Thus, the Pan-Protein Adductomics (PPA) technology reported here is the next step toward an unbiased, comprehensive characterization of the HSA adductome. The PPA workflow requires <2 μL serum/plasma and uses nanoflow-liquid chromatography, gas-phase fractionation, and overlapping-window data-independent acquisition high-resolution tandem mass spectrometry. PPA analysis of albumin from nonsmoking women exposed to high levels of air pollution uncovered 68 unique location-specific modifications (LSMs) across 21 HSA residues. While nearly half were located at Cys34 (33 LSMs), 35 were detected on other residues, including Lys, His, Tyr, Ser, Met, and Arg. HSA adduct relative abundances spanned a ∼400 000-fold range and included putative products of exogenous (SO2, benzene, phycoerythrobilin) and endogenous (oxidation, lipid peroxidation, glycation, carbamylation) origin, as well as 24 modifications without annotations. PPA quantification revealed statistically significant changes in LSM levels across the 84 days of monitoring (∼3 HSA lifetimes) in the following putative adducts: Cys34 trioxidation, β-methylthiolation, benzaldehyde, and benzene diol epoxide; Met329 oxidation; Arg145 dioxidation; and unannotated Cys34 and His146 adducts. Notably, the PPA workflow can be extended to any protein. Pan-Protein Adductomics is a novel and powerful strategy for untargeted global exploration of protein modifications.
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Affiliation(s)
- Joshua W Smith
- Department of Environmental Health and Engineering, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland 21205, United States
| | - Robert N O'Meally
- Department of Biological Chemistry, School of Medicine, Johns Hopkins University, Baltimore, Maryland 21205, United States
| | - Sean M Burke
- Department of Environmental Health and Engineering, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland 21205, United States
| | - Derek K Ng
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland 21205, United States
| | - Jian-Guo Chen
- Qidong Liver Cancer Institute, Qidong People's Hospital, Affiliated Qidong Hospital of Nantong University, Qidong, Jiangsu 226200, P. R. China
| | - Thomas W Kensler
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, Washington 98109, United States
| | - John D Groopman
- Department of Environmental Health and Engineering, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland 21205, United States
| | - Robert N Cole
- Department of Biological Chemistry, School of Medicine, Johns Hopkins University, Baltimore, Maryland 21205, United States
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5
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Caira S, Picariello G, Renzone G, Arena S, Troise AD, De Pascale S, Ciaravolo V, Pinto G, Addeo F, Scaloni A. Recent developments in peptidomics for the quali-quantitative analysis of food-derived peptides in human body fluids and tissues. Trends Food Sci Technol 2022. [DOI: 10.1016/j.tifs.2022.06.014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/17/2022]
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6
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Li W, Li M, Zhang X, Yue S, Xu Y, Jian W, Qin Y, Lin L, Liu W. Improved profiling of low molecular weight serum proteome for gastric carcinoma by data-independent acquisition. Anal Bioanal Chem 2022; 414:6403-6417. [PMID: 35773495 DOI: 10.1007/s00216-022-04196-z] [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: 04/14/2022] [Revised: 06/06/2022] [Accepted: 06/22/2022] [Indexed: 11/27/2022]
Abstract
Low molecular weight proteins (LMWPs) in the bloodstream participate in various biological processes and are closely associated with disease status, whereas identification of serous LMWPs remains a great technical challenge due to the wide dynamic range of protein components. In this study, we constructed an integrated LMWP library by combining the LMWPs obtained by three enrichment methods (50% ACN, 20% ACN + 20 mM ABC, and 30 kDa) and their fractions identified by the data-dependent acquisition method. With this newly constructed library, we comprehensively profiled LMWPs in serum using data-independent acquisition and reliably achieved quantitative results for 75% serous LMWPs. When applying this strategy to quantify LMWPs in human serum samples, we could identify 405 proteins on average per sample, of which 136 proteins were with a MW less than 30 kDa and 293 proteins were with a MW less than 65 kDa. Of note, pre- and post-operative gastric carcinoma (GC) patients showed differentially expressed serous LWMPs, which was also different from the pattern of LWMP expression in healthy controls. In conclusion, our results showed that LMWPs could efficiently distinguish GC patients from healthy controls as well as between pre- and post-operative statuses, and more importantly, our newly developed LMWP profiling platform could be used to discover candidate LMWP biomarkers for disease diagnosis and status monitoring.
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Affiliation(s)
- Weifeng Li
- The Central Laboratory, Shenzhen Second People's Hospital/the First Affiliated Hospital of Shenzhen University, Shenzhen, 518035, China
| | - Mengna Li
- The Central Laboratory, Shenzhen Second People's Hospital/the First Affiliated Hospital of Shenzhen University, Shenzhen, 518035, China
| | - Xiaoli Zhang
- The Central Laboratory, Shenzhen Second People's Hospital/the First Affiliated Hospital of Shenzhen University, Shenzhen, 518035, China
| | - Siqin Yue
- The Central Laboratory, Shenzhen Second People's Hospital/the First Affiliated Hospital of Shenzhen University, Shenzhen, 518035, China
| | - Yun Xu
- The Central Laboratory, Shenzhen Second People's Hospital/the First Affiliated Hospital of Shenzhen University, Shenzhen, 518035, China
| | - Wenjing Jian
- The Central Laboratory, Shenzhen Second People's Hospital/the First Affiliated Hospital of Shenzhen University, Shenzhen, 518035, China
| | - Yin Qin
- Department of Gastrointestinal Surgery, Shenzhen Second People's Hospital/the First Affiliated Hospital of Shenzhen University, Shenzhen, 518035, China.
| | - Lin Lin
- Sustech Core Research Facilities, Southern University of Science and Technology, Shenzhen, 518055, China.
| | - Wenlan Liu
- The Central Laboratory, Shenzhen Second People's Hospital/the First Affiliated Hospital of Shenzhen University, Shenzhen, 518035, China.
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7
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Vitorino R, Choudhury M, Guedes S, Ferreira R, Thongboonkerd V, Sharma L, Amado F, Srivastava S. Peptidomics and proteogenomics: background, challenges and future needs. Expert Rev Proteomics 2021; 18:643-659. [PMID: 34517741 DOI: 10.1080/14789450.2021.1980388] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Abstract
INTRODUCTION With available genomic data and related information, it is becoming possible to better highlight mutations or genomic alterations associated with a particular disease or disorder. The advent of high-throughput sequencing technologies has greatly advanced diagnostics, prognostics, and drug development. AREAS COVERED Peptidomics and proteogenomics are the two post-genomic technologies that enable the simultaneous study of peptides and proteins/transcripts/genes. Both technologies add a remarkably large amount of data to the pool of information on various peptides associated with gene mutations or genome remodeling. Literature search was performed in the PubMed database and is up to date. EXPERT OPINION This article lists various techniques used for peptidomic and proteogenomic analyses. It also explains various bioinformatics workflows developed to understand differentially expressed peptides/proteins and their role in disease pathogenesis. Their role in deciphering disease pathways, cancer research, and biomarker discovery using biofluids is highlighted. Finally, the challenges and future requirements to overcome the current limitations for their effective clinical use are also discussed.
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Affiliation(s)
- Rui Vitorino
- Faculdade de Medicina da Universidade do Porto, Porto, Portugal.,iBiMED, Department of Medical Sciences, University of Aveiro, Aveiro, Portugal.,Laqv/requimte, Department of Chemistry, University of Aveiro, Aveiro, Portugal
| | - Manisha Choudhury
- Department of Biosciences and Bioengineering, Indian Institute of Technology Bombay, Mumbai, Powai, India
| | - Sofia Guedes
- Laqv/requimte, Department of Chemistry, University of Aveiro, Aveiro, Portugal
| | - Rita Ferreira
- Laqv/requimte, Department of Chemistry, University of Aveiro, Aveiro, Portugal
| | - Visith Thongboonkerd
- Medical Proteomics Unit, Office for Research and Development, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand
| | | | - Francisco Amado
- Laqv/requimte, Department of Chemistry, University of Aveiro, Aveiro, Portugal
| | - Sanjeeva Srivastava
- Department of Biosciences and Bioengineering, Indian Institute of Technology Bombay, Mumbai, Powai, India
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8
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Foreman RE, George AL, Reimann F, Gribble FM, Kay RG. Peptidomics: A Review of Clinical Applications and Methodologies. J Proteome Res 2021; 20:3782-3797. [PMID: 34270237 DOI: 10.1021/acs.jproteome.1c00295] [Citation(s) in RCA: 34] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Improvements in both liquid chromatography (LC) and mass spectrometry (MS) instrumentation have greatly enhanced proteomic and small molecule metabolomic analysis in recent years. Less focus has been on the improved capability to detect and quantify small bioactive peptides, even though the exact sequences of the peptide species produced can have important biological consequences. Endogenous bioactive peptide hormones, for example, are generated by the targeted and regulated cleavage of peptides from their prohormone sequence. This process may include organ specific variants, as proglucagon is converted to glucagon in the pancreas but glucagon-like peptide-1 (GLP-1) in the small intestine, with glucagon raising, whereas GLP-1, as an incretin, lowering blood glucose. Therefore, peptidomics workflows must preserve the structure of the processed peptide products to prevent the misidentification of ambiguous peptide species. The poor in vivo and in vitro stability of peptides in biological matrices is a major factor that needs to be considered when developing methods to study them. The bioinformatic analysis of peptidomics data sets requires the inclusion of specific post-translational modifications, which are critical for the function of many bioactive peptides. This review aims to discuss and contrast the various extraction, analytical, and bioinformatics approaches used for human peptidomics studies in a multitude of matrices.
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Affiliation(s)
- Rachel E Foreman
- University of Cambridge Metabolic Research Laboratories, Level 4, Wellcome Trust-MRC Institute of Metabolic Science, Box 289, Addenbrooke's Hospital, Cambridge CB2 0QQ, U.K
| | - Amy L George
- University of Cambridge Metabolic Research Laboratories, Level 4, Wellcome Trust-MRC Institute of Metabolic Science, Box 289, Addenbrooke's Hospital, Cambridge CB2 0QQ, U.K
| | - Frank Reimann
- University of Cambridge Metabolic Research Laboratories, Level 4, Wellcome Trust-MRC Institute of Metabolic Science, Box 289, Addenbrooke's Hospital, Cambridge CB2 0QQ, U.K
| | - Fiona M Gribble
- University of Cambridge Metabolic Research Laboratories, Level 4, Wellcome Trust-MRC Institute of Metabolic Science, Box 289, Addenbrooke's Hospital, Cambridge CB2 0QQ, U.K
| | - Richard G Kay
- University of Cambridge Metabolic Research Laboratories, Level 4, Wellcome Trust-MRC Institute of Metabolic Science, Box 289, Addenbrooke's Hospital, Cambridge CB2 0QQ, U.K
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9
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Bichmann L, Gupta S, Rosenberger G, Kuchenbecker L, Sachsenberg T, Ewels P, Alka O, Pfeuffer J, Kohlbacher O, Röst H. DIAproteomics: A Multifunctional Data Analysis Pipeline for Data-Independent Acquisition Proteomics and Peptidomics. J Proteome Res 2021; 20:3758-3766. [PMID: 34153189 DOI: 10.1021/acs.jproteome.1c00123] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Data-independent acquisition (DIA) is becoming a leading analysis method in biomedical mass spectrometry. The main advantages include greater reproducibility and sensitivity and a greater dynamic range compared with data-dependent acquisition (DDA). However, the data analysis is complex and often requires expert knowledge when dealing with large-scale data sets. Here we present DIAproteomics, a multifunctional, automated, high-throughput pipeline implemented in the Nextflow workflow management system that allows one to easily process proteomics and peptidomics DIA data sets on diverse compute infrastructures. The central components are well-established tools such as the OpenSwathWorkflow for the DIA spectral library search and PyProphet for the false discovery rate assessment. In addition, it provides options to generate spectral libraries from existing DDA data and to carry out the retention time and chromatogram alignment. The output includes annotated tables and diagnostic visualizations from the statistical postprocessing and computation of fold-changes across pairwise conditions, predefined in an experimental design. DIAproteomics is well documented open-source software and is available under a permissive license to the scientific community at https://www.openms.de/diaproteomics/.
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Affiliation(s)
- Leon Bichmann
- Department of Computer Science, Applied Bioinformatics, University of Tübingen, Tübingen 72076, Germany.,Institute for Cell Biology, Department of Immunology, University of Tübingen, Tübingen 72076, Germany
| | - Shubham Gupta
- Donnelly Center for Biomolecular Research, University of Toronto, Toronto, Ontario ON M5S 3E1, Canada
| | - George Rosenberger
- Department of Systems Biology, Columbia University, New York, New York 10032, United States
| | - Leon Kuchenbecker
- Department of Computer Science, Applied Bioinformatics, University of Tübingen, Tübingen 72076, Germany
| | - Timo Sachsenberg
- Department of Computer Science, Applied Bioinformatics, University of Tübingen, Tübingen 72076, Germany
| | - Phil Ewels
- Science for Life Laboratory (SciLifeLab), Department of Biochemistry and Biophysics, Stockholm University, Stockholm, Sweden
| | - Oliver Alka
- Department of Computer Science, Applied Bioinformatics, University of Tübingen, Tübingen 72076, Germany
| | - Julianus Pfeuffer
- Department of Computer Science, Applied Bioinformatics, University of Tübingen, Tübingen 72076, Germany.,Institute for Informatics, Freie Universität Berlin, Berlin 14195, Germany.,Zuse Institute Berlin, Berlin 14195, Germany
| | - Oliver Kohlbacher
- Department of Computer Science, Applied Bioinformatics, University of Tübingen, Tübingen 72076, Germany.,Institute for Biological and Medical Informatics, University of Tübingen, Tübingen 72076, Germany.,Institute for Translational Bioinformatics, University Hospital Tübingen, Tübingen 72076, Germany
| | - Hannes Röst
- Donnelly Center for Biomolecular Research, University of Toronto, Toronto, Ontario ON M5S 3E1, Canada
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10
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Hanas JS, Hocker JRS, Vannarath CA, Lerner MR, Blair SG, Lightfoot SA, Hanas RJ, Couch JR, Hershey LA. Distinguishing Alzheimer's Disease Patients and Biochemical Phenotype Analysis Using a Novel Serum Profiling Platform: Potential Involvement of the VWF/ADAMTS13 Axis. Brain Sci 2021; 11:brainsci11050583. [PMID: 33946285 PMCID: PMC8145311 DOI: 10.3390/brainsci11050583] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2021] [Revised: 04/25/2021] [Accepted: 04/27/2021] [Indexed: 11/16/2022] Open
Abstract
It is important to develop minimally invasive biomarker platforms to help in the identification and monitoring of patients with Alzheimer's disease (AD). Assisting in the understanding of biochemical mechanisms as well as identifying potential novel biomarkers and therapeutic targets would be an added benefit of such platforms. This study utilizes a simplified and novel serum profiling platform, using mass spectrometry (MS), to help distinguish AD patient groups (mild and moderate) and controls, as well as to aid in understanding of biochemical phenotypes and possible disease development. A comparison of discriminating sera mass peaks between AD patients and control individuals was performed using leave one [serum sample] out cross validation (LOOCV) combined with a novel peak classification valuation (PCV) procedure. LOOCV/PCV was able to distinguish significant sera mass peak differences between a group of mild AD patients and control individuals with a p value of 10-13. This value became non-significant (p = 0.09) when the same sera samples were randomly allocated between the two groups and reanalyzed by LOOCV/PCV. This is indicative of physiological group differences in the original true-pathology binary group comparison. Similarities and differences between AD patients and traumatic brain injury (TBI) patients were also discernable using this novel LOOCV/PCV platform. MS/MS peptide analysis was performed on serum mass peaks comparing mild AD patients with control individuals. Bioinformatics analysis suggested that cell pathways/biochemical phenotypes affected in AD include those involving neuronal cell death, vasculature, neurogenesis, and AD/dementia/amyloidosis. Inflammation, autoimmunity, autophagy, and blood-brain barrier pathways also appear to be relevant to AD. An impaired VWF/ADAMTS13 vasculature axis with connections to F8 (factor VIII) and LRP1 and NOTCH1 was indicated and is proposed to be important in AD development.
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Affiliation(s)
- Jay S. Hanas
- Department of Biochemistry, University of Oklahoma Health Sciences Center, Oklahoma City, OK 73104, USA; (J.R.S.H.); (C.A.V.); (R.J.H.)
- Department of Surgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK 73104, USA; (M.R.L.); (S.G.B.)
- Veterans Administration Hospital, Oklahoma City, OK 73104, USA;
- Correspondence:
| | - James R. S. Hocker
- Department of Biochemistry, University of Oklahoma Health Sciences Center, Oklahoma City, OK 73104, USA; (J.R.S.H.); (C.A.V.); (R.J.H.)
| | - Christian A. Vannarath
- Department of Biochemistry, University of Oklahoma Health Sciences Center, Oklahoma City, OK 73104, USA; (J.R.S.H.); (C.A.V.); (R.J.H.)
| | - Megan R. Lerner
- Department of Surgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK 73104, USA; (M.R.L.); (S.G.B.)
| | - Scott G. Blair
- Department of Surgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK 73104, USA; (M.R.L.); (S.G.B.)
| | | | - Rushie J. Hanas
- Department of Biochemistry, University of Oklahoma Health Sciences Center, Oklahoma City, OK 73104, USA; (J.R.S.H.); (C.A.V.); (R.J.H.)
| | - James R. Couch
- Department of Neurology, University of Oklahoma Health Sciences Center, Oklahoma City, OK 73104, USA; (J.R.C.); (L.A.H.)
| | - Linda A. Hershey
- Department of Neurology, University of Oklahoma Health Sciences Center, Oklahoma City, OK 73104, USA; (J.R.C.); (L.A.H.)
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11
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Gao W, Zhang Q, Su Y, Huang P, Lu X, Gong Q, Chen W, Xu R, Tian R. Multiomic analysis of a dried single-drop plasma sample using an integrated mass spectrometry approach. Analyst 2020; 145:6441-6446. [PMID: 32785396 DOI: 10.1039/d0an01149e] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
An easy-to-use and fast approach was developed for integrated proteomic and metabolic profiling in a dried single-drop plasma sample. Plasma collection, room temperature storage, and sample preparation for both proteins and metabolites were seamlessly integrated in one spintip device. MS-based multiomic profiling using the same nano LC-MS system identified more than 150 proteins and 160 metabolites from the 1 μL plasma sample in 6 hours. Further combination with micro-flow LC and targeted MS made it a promising approach for the fast profiling of molecular biomarkers with high sensitivity and accuracy.
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Affiliation(s)
- Weina Gao
- Department of Chemistry, Southern University of Science and Technology, Shenzhen 518055, China.
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12
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Mellinger AL, Griffith EH, Bereman MS. Peptide variability and signatures associated with disease progression in CSF collected longitudinally from ALS patients. Anal Bioanal Chem 2020; 412:5465-5475. [PMID: 32591871 DOI: 10.1007/s00216-020-02765-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2020] [Revised: 05/20/2020] [Accepted: 06/09/2020] [Indexed: 01/06/2023]
Abstract
We employ shotgun proteomics and data-independent acquisition (DIA) mass spectrometry to analyze cerebrospinal fluid longitudinally collected from 14 amyotrophic lateral sclerosis (ALS) patients (8 males and 6 females). We perform three main analyses of these data: (1) examine the intra- and inter-patient protein variability in CSF; (2) explore the association of inflammation with rate of disease progression; and (3) develop a mixed-effects model to best explain the decrease in ALS-Functional Rating Scale (ALS-FRS) score. Overall, the CSF protein abundances are tightly regulated with the intra-individual variability contributing just 4% to the overall variance. In four patients, a moderately significant correlation (p < 0.1) was observed between inflammation and rate of disease progression. Using a least absolute shrinkage and selection operator (LASSO) variable selection, we selected 55 viable peptides for mathematical modeling via a linear mixed-effects regression. We then employed forward selection to generate a final model by minimizing Akaike's information criterion (AIC). The final model utilized changes in abundance from 28 peptides as fixed effects to model progression of the disease in these patients. These peptides were from proteins involved in stress response and innate immunity. Graphical abstract.
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Affiliation(s)
- Allyson L Mellinger
- Department of Chemistry, North Carolina State University, Raleigh, NC, 27695, USA
| | - Emily H Griffith
- Department of Statistics, North Carolina State University, Raleigh, NC, 27695, USA
| | - Michael S Bereman
- Department of Chemistry, North Carolina State University, Raleigh, NC, 27695, USA. .,Department of Biological Sciences, North Carolina State University, Raleigh, NC, 27695, USA. .,Center for Human Health and the Environment, North Carolina State University, Raleigh, NC, 27695, USA.
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13
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Raimondo F, Pitto M. Prognostic significance of proteomics and multi-omics studies in renal carcinoma. Expert Rev Proteomics 2020; 17:323-334. [PMID: 32428425 DOI: 10.1080/14789450.2020.1772058] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
Abstract
INTRODUCTION Renal carcinoma, and in particular its most common variant, the clear cell subtype, is often diagnosed incidentally through abdominal imaging and frequently, the tumor is discovered at an early stage. However, 20% to 40% of patients undergoing nephrectomy for clinically localized renal cancer, even after accurate histological and clinical classification, will develop metastasis or recurrence, justifying the associated mortality rate. Therefore, even if renal carcinoma is not among the most frequent nor deadly cancers, a better prognostication is needed. AREAS COVERED Recently proteomics or other omics combinations have been applied to both cancer tissues, on the neoplasia itself and surrounding microenvironment, cultured cells, and biological fluids (so-called liquid biopsy) generating a list of prognostic molecular tools that will be reviewed in the present paper. EXPERT OPINION Although promising, none of the approaches listed above has been yet translated in clinics. This is likely due to the peculiar genetic and phenotypic heterogeneity of this cancer, which makes nearly each tumor different from all the others. Attempts to overcome this issue will be also revised. In particular, we will discuss how the application of omics-integrated approaches could provide the determinants of response to the different targeted drugs.
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Affiliation(s)
- Francesca Raimondo
- Clinical Proteomics and Metabolomics Unit, School of Medicine and Surgery, University of Milano - Bicocca , Vedano al Lambro, Italy
| | - Marina Pitto
- Clinical Proteomics and Metabolomics Unit, School of Medicine and Surgery, University of Milano - Bicocca , Vedano al Lambro, Italy
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