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Takis PG, Vučković I, Kowalka AM, Tan T, Šuvakov M, Meloche R, Lanza IR, Macura S. Toward Absolute Quantification of Soluble Proteins via Proton Nuclear Magnetic Resonance Spectroscopy: Total Protein Concentration in Blood Plasma. Anal Chem 2024; 96:16162-16169. [PMID: 39365892 DOI: 10.1021/acs.analchem.4c02711] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/06/2024]
Abstract
For absolute protein quantification using nuclear magnetic resonance (NMR) spectroscopy, we considered proteins as homopolymers and effective amino acid (AA) residues (AAREff) as monomer units. For diverse classes of proteins, we determined the AAREff molecular weight as 111.5 ± 3.2 Da and the number of hydrogens per AA as 7.8 ± 0.2. Their ratio of 14.3 ± 0.3 (g/LP)/(mol/LH) remains constant across various protein classes and is equivalent to Kjeldahl's nitrogen-to-protein conversion constant of 5.78 ± 0.29 gN/gP. By analogy to the Kjeldahl method, we suggest that the total integral of a 1H NMR solution protein spectrum could be used for total protein quantification. We synthesized low-resolution protein spectra from the weighted sums of individual AA spectra and compared them with experimental spectra. In the methyl region, the ratio of the protein mass to the total number of protons in the synthetic spectra (corrected for the chemical shift mismatch) was ∼1 (mg/mL)/mM, which agrees with an earlier reported experimental ratio for urine (1.05 ± 0.06 (mg/mL)/mM). For human blood plasma, in the methyl region, we found empirical ratios of 1.115 ± 0.006 (mg/mL)/mM (using 96 patient samples) and 1.121 ± 0.011 (mg/mL)/mM for the NIST plasma standard. This numerical agreement points to universal conversion constants, i.e., protein mixtures with unknown compositions could be quantified without the need for calibration standards by measuring the millimolar proton concentration within the methyl region of the NMR spectrum using the same conversion constant.
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Affiliation(s)
- Panteleimon G Takis
- Section of Bioanalytical Chemistry, Division of Systems Medicine, Department of Metabolism, Digestion, and Reproduction, Imperial College London, London SW7 2AZ, U.K
- National Phenome Center, Department of Metabolism, Digestion, and Reproduction, Imperial College London, London W12 0NN, U.K
- Section of Analytical Chemistry, Department of Chemistry, University of Ioannina, Ioannina 45110, Greece
| | - Ivan Vučković
- Metabolomics Core, Mayo Clinic, Rochester, Minnesota 55905, United States
| | - Anna M Kowalka
- Section of Endocrinology and Investigative Medicine, Division of Diabetes, Endocrinology, and Metabolism, Department of Metabolism, Digestion, and Reproduction, Imperial College London, London SW7 2AZ, U.K
| | - Tricia Tan
- Section of Endocrinology and Investigative Medicine, Division of Diabetes, Endocrinology, and Metabolism, Department of Metabolism, Digestion, and Reproduction, Imperial College London, London SW7 2AZ, U.K
| | - Milovan Šuvakov
- Department of Quantitative Health Sciences, Center for Individualized Medicine, Mayo Clinic, Rochester, Minnesota 55905, United States
| | - Ryan Meloche
- Metabolomics Core, Mayo Clinic, Rochester, Minnesota 55905, United States
| | - Ian R Lanza
- Metabolomics Core, Mayo Clinic, Rochester, Minnesota 55905, United States
- Division of Endocrinology and Metabolism, Mayo Clinic College of Medicine, Rochester, Minnesota 55905, United States
| | - Slobodan Macura
- Department of Biochemistry and Molecular Biology, Mayo Clinic, Rochester, Minnesota 55905, United States
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Theillet FX, Luchinat E. In-cell NMR: Why and how? PROGRESS IN NUCLEAR MAGNETIC RESONANCE SPECTROSCOPY 2022; 132-133:1-112. [PMID: 36496255 DOI: 10.1016/j.pnmrs.2022.04.002] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/15/2021] [Revised: 04/19/2022] [Accepted: 04/27/2022] [Indexed: 06/17/2023]
Abstract
NMR spectroscopy has been applied to cells and tissues analysis since its beginnings, as early as 1950. We have attempted to gather here in a didactic fashion the broad diversity of data and ideas that emerged from NMR investigations on living cells. Covering a large proportion of the periodic table, NMR spectroscopy permits scrutiny of a great variety of atomic nuclei in all living organisms non-invasively. It has thus provided quantitative information on cellular atoms and their chemical environment, dynamics, or interactions. We will show that NMR studies have generated valuable knowledge on a vast array of cellular molecules and events, from water, salts, metabolites, cell walls, proteins, nucleic acids, drugs and drug targets, to pH, redox equilibria and chemical reactions. The characterization of such a multitude of objects at the atomic scale has thus shaped our mental representation of cellular life at multiple levels, together with major techniques like mass-spectrometry or microscopies. NMR studies on cells has accompanied the developments of MRI and metabolomics, and various subfields have flourished, coined with appealing names: fluxomics, foodomics, MRI and MRS (i.e. imaging and localized spectroscopy of living tissues, respectively), whole-cell NMR, on-cell ligand-based NMR, systems NMR, cellular structural biology, in-cell NMR… All these have not grown separately, but rather by reinforcing each other like a braided trunk. Hence, we try here to provide an analytical account of a large ensemble of intricately linked approaches, whose integration has been and will be key to their success. We present extensive overviews, firstly on the various types of information provided by NMR in a cellular environment (the "why", oriented towards a broad readership), and secondly on the employed NMR techniques and setups (the "how", where we discuss the past, current and future methods). Each subsection is constructed as a historical anthology, showing how the intrinsic properties of NMR spectroscopy and its developments structured the accessible knowledge on cellular phenomena. Using this systematic approach, we sought i) to make this review accessible to the broadest audience and ii) to highlight some early techniques that may find renewed interest. Finally, we present a brief discussion on what may be potential and desirable developments in the context of integrative studies in biology.
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Affiliation(s)
- Francois-Xavier Theillet
- Université Paris-Saclay, CEA, CNRS, Institute for Integrative Biology of the Cell (I2BC), 91198 Gif-sur-Yvette, France.
| | - Enrico Luchinat
- Dipartimento di Scienze e Tecnologie Agro-Alimentari, Alma Mater Studiorum - Università di Bologna, Piazza Goidanich 60, 47521 Cesena, Italy; CERM - Magnetic Resonance Center, and Neurofarba Department, Università degli Studi di Firenze, 50019 Sesto Fiorentino, Italy
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Vuckovic I, Denic A, Charlesworth MC, Šuvakov M, Bobart S, Lieske JC, Fervenza FC, Macura S. 1H Nuclear Magnetic Resonance Spectroscopy-Based Methods for the Quantification of Proteins in Urine. Anal Chem 2021; 93:13177-13186. [PMID: 34546699 DOI: 10.1021/acs.analchem.1c01618] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Abstract
We described several postprocessing methods to measure protein concentrations in human urine from existing 1H nuclear magnetic resonance (NMR) metabolomic spectra: (1) direct spectral integration, (2) integration of NCD spectra (NCD = 1D NOESY-CPMG), (3) integration of SMolESY-filtered 1D NOESY spectra (SMolESY = Small Molecule Enhancement SpectroscopY), (4) matching protein patterns, and (5) TSP line integral and TSP linewidth. Postprocessing consists of (a) removal of the metabolite signals (demetabolization) and (b) extraction of the protein integral from the demetabolized spectra. For demetabolization, we tested subtraction of the spin-echo 1D spectrum (CPMG) from the regular 1D spectrum and low-pass filtering of 1D NOESY by its derivatives (c-SMolESY). Because of imperfections in the demetabolization, in addition to direct integration, we extracted protein integrals by the piecewise comparison of demetabolized spectra with the reference spectrum of albumin. We analyzed 42 urine samples with protein content known from the bicinchoninic acid (BCA) assay. We found excellent correlation between the BCA assay and the demetabolized NMR integrals. We have provided conversion factors for calculating protein concentrations in mg/mL from spectral integrals in mM. Additionally, we found the trimethylsilyl propionate (TSP, NMR standard) spectral linewidth and the TSP integral to be good indicators of protein concentration. The described methods increase the information content of urine NMR metabolomics spectra by informing clinical studies of protein concentration.
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Affiliation(s)
- Ivan Vuckovic
- Metabolomics Core, Mayo Clinic, Rochester, Minnesota 55905, United States
| | - Aleksandar Denic
- Division of Nephrology and Hypertension, Mayo Clinic, Rochester, Minnesota 55905, United States
| | | | - Milovan Šuvakov
- Department of Quantitative Health Sciences, Center for Individualized Medicine, Mayo Clinic, Rochester, Minnesota 55905, United States
| | - Shane Bobart
- Division of Nephrology and Hypertension, Mayo Clinic, Rochester, Minnesota 55905, United States
| | - John C Lieske
- Division of Nephrology and Hypertension, Mayo Clinic, Rochester, Minnesota 55905, United States
| | - Fernando C Fervenza
- Division of Nephrology and Hypertension, Mayo Clinic, Rochester, Minnesota 55905, United States
| | - Slobodan Macura
- Metabolomics Core, Mayo Clinic, Rochester, Minnesota 55905, United States.,Department of Biochemistry and Molecular Biology, Mayo Clinic, Rochester, Minnesota 55905, United States
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Ranjan R, Sinha N. Nuclear magnetic resonance (NMR)-based metabolomics for cancer research. NMR IN BIOMEDICINE 2019; 32:e3916. [PMID: 29733484 DOI: 10.1002/nbm.3916] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/03/2017] [Revised: 02/01/2018] [Accepted: 02/12/2018] [Indexed: 06/08/2023]
Abstract
Nuclear magnetic resonance (NMR) has emerged as an effective tool in various spheres of biomedical research, amongst which metabolomics is an important method for the study of various types of disease. Metabolomics has proved its stronghold in cancer research by the development of different NMR methods over time for the study of metabolites, thus identifying key players in the aetiology of cancer. A plethora of one-dimensional and two-dimensional NMR experiments (in solids, semi-solids and solution phases) are utilized to obtain metabolic profiles of biofluids, cell extracts and tissue biopsy samples, which can further be subjected to statistical analysis. Any alteration in the assigned metabolite peaks gives an indication of changes in metabolic pathways. These defined changes demonstrate the utility of NMR in the early diagnosis of cancer and provide further measures to combat malignancy and its progression. This review provides a snapshot of the trending NMR techniques and the statistical analysis involved in the metabolomics of diseases, with emphasis on advances in NMR methodology developed for cancer research.
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Affiliation(s)
- Renuka Ranjan
- Centre of Biomedical Research, SGPGIMS Campus, Raebarelly Road, Lucknow, India
- School of Biotechnology, Institute of Science Banaras Hindu University, Varanasi, India
| | - Neeraj Sinha
- Centre of Biomedical Research, SGPGIMS Campus, Raebarelly Road, Lucknow, India
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Zhu Y, Zhang R, Zhang B, Zhao T, Wang P, Liang G, Cheng G. Blood meal acquisition enhances arbovirus replication in mosquitoes through activation of the GABAergic system. Nat Commun 2017; 8:1262. [PMID: 29093445 PMCID: PMC5665997 DOI: 10.1038/s41467-017-01244-6] [Citation(s) in RCA: 44] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2017] [Accepted: 08/30/2017] [Indexed: 11/13/2022] Open
Abstract
Mosquitoes are hematophagous insects that carry-on and transmit many human viruses. However, little information is available regarding the common mechanisms underlying the infection of mosquitoes by these viruses. In this study, we reveal that the hematophagous nature of mosquitoes contributes to arboviral infection after a blood meal, which suppresses antiviral innate immunity by activating the GABAergic pathway. dsRNA-mediated interruption of the GABA signaling and blockage of the GABAA receptor by the specific inhibitors both significantly impaired arbovirus replication. Consistently, inoculation of GABA enhanced arboviral infection, indicating that GABA signaling facilitates the arboviral infection of mosquitoes. The ingestion of blood by mosquitoes resulted in robust GABA production from glutamic acid derived from blood protein digestion. The oral introduction of glutamic acid increased virus acquisition by mosquitoes via activation of the GABAergic system. Our study reveals that blood meals enhance arbovirus replication in mosquitoes through activation of the GABAergic system. Transmission of many human viruses depends on replication in their mosquito vectors. Here, Zhu et al. show that glutamic acid digested from the blood meal activates GABA signaling, resulting in suppression of antiviral innate immunity and increased virus replication in mosquitoes.
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Affiliation(s)
- Yibin Zhu
- Tsinghua-Peking Center for Life Sciences, School of Medicine, Tsinghua University, Beijing, 100084, China.,Institute of pathogenic organisms, Shenzhen Center for Disease Control and Prevention, Shenzhen, Guangdong, 518055, China.,School of Life Science, Tsinghua University, Beijing, 100084, China
| | - Rudian Zhang
- Tsinghua-Peking Center for Life Sciences, School of Medicine, Tsinghua University, Beijing, 100084, China.,School of Life Science, Tsinghua University, Beijing, 100084, China
| | - Bei Zhang
- Tsinghua-Peking Center for Life Sciences, School of Medicine, Tsinghua University, Beijing, 100084, China
| | - Tongyan Zhao
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, 100071, China
| | - Penghua Wang
- Department of Microbiology and Immunology, School of Medicine, New York Medical College, Valhalla, NY, 10595, USA
| | - Guodong Liang
- State Key Laboratory of Infectious Disease Prevention and Control, National Institute for Viral Disease Control and Prevention, Chinese Center for Viral Disease Control and Prevention, Beijing, 102206, China.,Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Hangzhou, 310000, China
| | - Gong Cheng
- Tsinghua-Peking Center for Life Sciences, School of Medicine, Tsinghua University, Beijing, 100084, China. .,Institute of pathogenic organisms, Shenzhen Center for Disease Control and Prevention, Shenzhen, Guangdong, 518055, China.
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Affiliation(s)
- G. A. Nagana Gowda
- Northwest Metabolomics Research Center, Department of Anesthesiology and Pain Medicine and
| | - Daniel Raftery
- Northwest Metabolomics Research Center, Department of Anesthesiology and Pain Medicine and
- Department of Chemistry, University of Washington, Seattle, Washington 98109, United States
- Fred Hutchinson Cancer Research Center, Seattle, Washington 98109, United States
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Software-assisted serum metabolite quantification using NMR. Anal Chim Acta 2016; 934:194-202. [PMID: 27506360 DOI: 10.1016/j.aca.2016.04.054] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2016] [Revised: 04/27/2016] [Accepted: 04/29/2016] [Indexed: 01/12/2023]
Abstract
The goal of metabolomics is to analyze a whole metabolome under a given set of conditions, and accurate and reliable quantitation of metabolites is crucial. Absolute concentration is more valuable than relative concentration; however, the most commonly used method in NMR-based serum metabolic profiling, bin-based and full data point peak quantification, provides relative concentration levels of metabolites and are not reliable when metabolite peaks overlap in a spectrum. In this study, we present the software-assisted serum metabolite quantification (SASMeQ) method, which allows us to identify and quantify metabolites in NMR spectra using Chenomx software. This software uses the ERETIC2 utility from TopSpin to add a digitally synthesized peak to a spectrum. The SASMeQ method will advance NMR-based serum metabolic profiling by providing an accurate and reliable method for absolute quantification that is superior to bin-based quantification.
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