1
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Bruce ER, Kibbe RR, Hector EC, Muddiman DC. Absolute Quantification of Glutathione Using Top-Hat Optics for IR-MALDESI Mass Spectrometry Imaging. JOURNAL OF MASS SPECTROMETRY : JMS 2024; 59:e5091. [PMID: 39291925 DOI: 10.1002/jms.5091] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/28/2024] [Revised: 08/26/2024] [Accepted: 09/02/2024] [Indexed: 09/19/2024]
Abstract
Infrared matrix-assisted laser desorption electrospray ionization (IR-MALDESI) uses an infrared laser to desorb neutral biomolecules with postionization via ESI at atmospheric pressure. The Gaussian profile of the laser with conventional optics results in the heating of adjacent nonablated tissue due to the energy profile being circular. A diffractive optical element (DOE) was incorporated into the optical train to correct for this disadvantage. The DOE produces a top-hat beam profile and square ablation spots, which have uniform energy distributions. Although beneficial to mass spectrometry imaging (MSI), it is unknown how the DOE affects the ability to perform quantitative MSI (qMSI). In this work, we evaluate the performance of the DOE optical train against our conventional optics to define the potential advantages of the top-hat beam profile. Absolute quantification of glutathione (GSH) was achieved by normalizing the analyte of interest to homoglutathione (hGSH), spotting a dilution series of stable isotope labeled glutathione (SIL-GSH), and analyzing by IR-MALDESI MSI with either the conventional optical train or with the DOE incorporated. Statistical comparison indicates that there was no significant difference between the quantification of GSH by the two optical trains as evidenced by similar calibration curves. Results support that both optical trains can be used for qMSI without a change in the ability to carry out absolute quantification but providing the benefits of the top-hat optical train (i.e., flat energy profile and square ablation spots)-for future qMSI studies.
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Affiliation(s)
- Emily R Bruce
- FTMS Laboratory for Human Health Research, Department of Chemistry, North Carolina State University, Raleigh, North Carolina, USA
| | - Russell R Kibbe
- FTMS Laboratory for Human Health Research, Department of Chemistry, North Carolina State University, Raleigh, North Carolina, USA
| | - Emily C Hector
- Department of Statistics, North Carolina State University, Raleigh, North Carolina, USA
| | - David C Muddiman
- FTMS Laboratory for Human Health Research, Department of Chemistry, North Carolina State University, Raleigh, North Carolina, USA
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2
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Kibbe RR, Muddiman DC. Quantitative mass spectrometry imaging (qMSI): A tutorial. JOURNAL OF MASS SPECTROMETRY : JMS 2024; 59:e5009. [PMID: 38488849 DOI: 10.1002/jms.5009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/16/2023] [Accepted: 01/29/2024] [Indexed: 03/19/2024]
Abstract
Mass spectrometry imaging (MSI) is an analytical technique that enables the simultaneous detection of hundreds to thousands of chemical species while retaining their spatial information; usually, MSI is applied to biological tissues. Combining these elements can create ion images, which allows for the identification and localization of multiple chemical species within the sample. Being able to produce molecular images of biological tissues has already impacted the study of health and disease; however, the next logical step is being able to combine MSI with quantitative mass spectrometry methods to both quantify and determine the localization of disease progression or drug action. In this tutorial, we will detail the main factors to consider when designing a qMSI experiment and highlight the methods that have been developed to overcome these added complexities, specifically for those newer to the field of MSI.
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Affiliation(s)
- Russell R Kibbe
- Department of Chemistry, FTMS Laboratory for Human Health Research, North Carolina State University, Raleigh, North Carolina, USA
| | - David C Muddiman
- Department of Chemistry, FTMS Laboratory for Human Health Research, North Carolina State University, Raleigh, North Carolina, USA
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3
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Macdonald JK, Mehta AS, Drake RR, Angel PM. Molecular analysis of the extracellular microenvironment: from form to function. FEBS Lett 2024; 598:602-620. [PMID: 38509768 PMCID: PMC11049795 DOI: 10.1002/1873-3468.14852] [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: 11/29/2023] [Revised: 02/26/2024] [Accepted: 02/28/2024] [Indexed: 03/22/2024]
Abstract
The extracellular matrix (ECM) proteome represents an important component of the tissue microenvironment that controls chemical flux and induces cell signaling through encoded structure. The analysis of the ECM represents an analytical challenge through high levels of post-translational modifications, protease-resistant structures, and crosslinked, insoluble proteins. This review provides a comprehensive overview of the analytical challenges involved in addressing the complexities of spatially profiling the extracellular matrix proteome. A synopsis of the process of synthesizing the ECM structure, detailing inherent chemical complexity, is included to present the scope of the analytical challenge. Current chromatographic and spatial techniques addressing these challenges are detailed. Capabilities for multimodal multiplexing with cellular populations are discussed with a perspective on developing a holistic view of disease processes that includes both the cellular and extracellular microenvironment.
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Affiliation(s)
- Jade K Macdonald
- Department of Cell and Molecular Pharmacology & Experimental Therapeutics, Medical University of South Carolina, Charleston, SC
| | - Anand S Mehta
- Department of Cell and Molecular Pharmacology & Experimental Therapeutics, Medical University of South Carolina, Charleston, SC
| | - Richard R Drake
- Department of Cell and Molecular Pharmacology & Experimental Therapeutics, Medical University of South Carolina, Charleston, SC
| | - Peggi M. Angel
- Department of Cell and Molecular Pharmacology & Experimental Therapeutics, Medical University of South Carolina, Charleston, SC
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4
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Knizner KT, Kibbe RR, Garrard KP, Nuñez JR, Anderton CR, Muddiman DC. On the importance of color in mass spectrometry imaging. JOURNAL OF MASS SPECTROMETRY : JMS 2022; 57:e4898. [PMID: 36463891 PMCID: PMC9944061 DOI: 10.1002/jms.4898] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/27/2022] [Revised: 11/07/2022] [Accepted: 11/17/2022] [Indexed: 05/12/2023]
Abstract
Mass spectrometry imaging (MSI) data visualization relies on heatmaps to show the spatial distribution and measured abundances of molecules within a sample. Nonuniform color gradients such as jet are still commonly used to visualize MSI data, increasing the probability of data misinterpretation and false conclusions. Also, the use of nonuniform color gradients and the combination of hues used in common colormaps make it challenging for people with color vision deficiencies (CVDs) to visualize and accurately interpret data. Here we present best practices for choosing a colormap to accurately display MSI data, improve readability, and accommodate all CVDs. We also provide other resources on the misuse of color in the scientific field and resources on scientifically derived colormaps presented herein.
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Affiliation(s)
- Kevan T. Knizner
- FTMS Laboratory for Human Health Research, Department of ChemistryNorth Carolina State UniversityRaleighNorth CarolinaUSA
| | - Russell R. Kibbe
- FTMS Laboratory for Human Health Research, Department of ChemistryNorth Carolina State UniversityRaleighNorth CarolinaUSA
| | - Kenneth P. Garrard
- FTMS Laboratory for Human Health Research, Department of ChemistryNorth Carolina State UniversityRaleighNorth CarolinaUSA
- Molecular Education, Technology and Research Innovation Center (METRIC)North Carolina State UniversityRaleighNorth CarolinaUSA
- Precision Engineering ConsortiumNorth Carolina State UniversityRaleighNorth CarolinaUSA
| | - Jamie R. Nuñez
- Earth and Biological Sciences DirectoratePacific Northwest National LaboratoryRichlandWashingtonUSA
| | - Christopher R. Anderton
- Earth and Biological Sciences DirectoratePacific Northwest National LaboratoryRichlandWashingtonUSA
| | - David C. Muddiman
- FTMS Laboratory for Human Health Research, Department of ChemistryNorth Carolina State UniversityRaleighNorth CarolinaUSA
- Molecular Education, Technology and Research Innovation Center (METRIC)North Carolina State UniversityRaleighNorth CarolinaUSA
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5
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Mellinger AL, Kibbe RR, Rabbani ZN, Meritet D, Muddiman DC, Gamcsik MP. Mapping glycine uptake and its metabolic conversion to glutathione in mouse mammary tumors using functional mass spectrometry imaging. Free Radic Biol Med 2022; 193:677-684. [PMID: 36402437 PMCID: PMC9737053 DOI: 10.1016/j.freeradbiomed.2022.11.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/28/2022] [Revised: 11/08/2022] [Accepted: 11/08/2022] [Indexed: 11/18/2022]
Abstract
Although glutathione plays a key role in cancer cell viability and therapy response there is no clear trend in relating the level of this antioxidant to clinical stage, histological grade, or therapy response in patient tumors. The likely reason is that static levels of glutathione are not a good indicator of how a tissue deals with oxidative stress. A better indicator is the functional capacity of the tissue to maintain glutathione levels in response to this stress. However, there are few methods to assess glutathione metabolic function in tissue. We have developed a novel functional mass spectrometry imaging (fMSI) method that can map the variations in the conversion of glycine to glutathione metabolic activity across tumor tissue sections by tracking the fate of three glycine isotopologues administered in a timed sequence to tumor-bearing anesthetized mice. This fMSI method generates multiple time point kinetic data for substrate uptake and glutathione production from each spatial location in the tissue. As expected, the fMSI data shows glutathione metabolic activity varies across the murine 4T1 mammary tumor. Although glutathione levels are highest at the tumor periphery there are regions of high content but low metabolic activity. The timed infusion method also detects variations in delivery of the glycine isotopologues thereby providing a measure of tissue perfusion, including evidence of intermittent perfusion, that contributes to the observed differences in metabolic activity. We believe this new approach will be an asset to linking molecular content to tissue function.
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Affiliation(s)
- Allyson L Mellinger
- FTMS Laboratory for Human Health Research, Department of Chemistry, NC State University, 2700 Stinson Dr., Raleigh, NC, 27607, USA
| | - Russell R Kibbe
- FTMS Laboratory for Human Health Research, Department of Chemistry, NC State University, 2700 Stinson Dr., Raleigh, NC, 27607, USA
| | - Zahid N Rabbani
- UNC/NCSU Joint Department of Biomedical Engineering, 1840 Entrepreneur Drive, Raleigh, NC, 27695, USA
| | - Danielle Meritet
- Department of Population Health and Pathobiology, College of Veterinary Medicine, NC State University, Raleigh, NC, 27607, USA
| | - David C Muddiman
- FTMS Laboratory for Human Health Research, Department of Chemistry, NC State University, 2700 Stinson Dr., Raleigh, NC, 27607, USA; Molecular Education, Technology and Research Innovation Center (METRIC), Raleigh, NC, 27695, USA
| | - Michael P Gamcsik
- UNC/NCSU Joint Department of Biomedical Engineering, 1840 Entrepreneur Drive, Raleigh, NC, 27695, USA.
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Sohn AL, Ping L, Glass JD, Seyfried NT, Hector EC, Muddiman DC. Interrogating the Metabolomic Profile of Amyotrophic Lateral Sclerosis in the Post-Mortem Human Brain by Infrared Matrix-Assisted Laser Desorption Electrospray Ionization (IR-MALDESI) Mass Spectrometry Imaging (MSI). Metabolites 2022; 12:1096. [PMID: 36355179 PMCID: PMC9696666 DOI: 10.3390/metabo12111096] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2022] [Revised: 10/26/2022] [Accepted: 11/07/2022] [Indexed: 01/03/2024] Open
Abstract
Amyotrophic lateral sclerosis (ALS) is an idiopathic, fatal neurodegenerative disease characterized by progressive loss of motor function with an average survival time of 2-5 years after diagnosis. Due to the lack of signature biomarkers and heterogenous disease phenotypes, a definitive diagnosis of ALS can be challenging. Comprehensive investigation of this disease is imperative to discovering unique features to expedite the diagnostic process and improve diagnostic accuracy. Here, we present untargeted metabolomics by mass spectrometry imaging (MSI) for comparing sporadic ALS (sALS) and C9orf72 positive (C9Pos) post-mortem frontal cortex human brain tissues against a control cohort. The spatial distribution and relative abundance of metabolites were measured by infrared matrix-assisted laser desorption electrospray ionization (IR-MALDESI) MSI for association to biological pathways. Proteomic studies on the same patients were completed via LC-MS/MS in a previous study, and results were integrated with imaging metabolomics results to enhance the breadth of molecular coverage. Utilizing METASPACE annotation platform and MSiPeakfinder, nearly 300 metabolites were identified across the sixteen samples, where 25 were identified as dysregulated between disease cohorts. The dysregulated metabolites were further examined for their relevance to alanine, aspartate, and glutamate metabolism, glutathione metabolism, and arginine and proline metabolism. The dysregulated pathways discussed are consistent with reports from other ALS studies. To our knowledge, this work is the first of its kind, reporting on the investigation of ALS post-mortem human brain tissue analyzed by multiomic MSI.
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Affiliation(s)
- Alexandria L. Sohn
- FTMS Laboratory for Human Health Research, Department of Chemistry, North Carolina State University, Raleigh, NC 27695, USA
| | - Lingyan Ping
- Goizueta Alzheimer’s Disease Research Center, Emory University School of Medicine, Atlanta, GA 30322, USA
- Department of Neurology, Emory University School of Medicine, Atlanta, GA 30322, USA
- Department of Biochemistry, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Jonathan D. Glass
- Department of Neurology, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Nicholas T. Seyfried
- Goizueta Alzheimer’s Disease Research Center, Emory University School of Medicine, Atlanta, GA 30322, USA
- Department of Neurology, Emory University School of Medicine, Atlanta, GA 30322, USA
- Department of Biochemistry, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Emily C. Hector
- Department of Statistics, North Carolina State University, Raleigh, NC 27695, USA
| | - David C. Muddiman
- FTMS Laboratory for Human Health Research, Department of Chemistry, North Carolina State University, Raleigh, NC 27695, USA
- Molecular Education, Technology and Research Innovation Center (METRIC), North Carolina State University, Raleigh, NC 27695, USA
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7
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Wu Y, Wong CW, Chiles EN, Mellinger AL, Bae H, Jung S, Peterson T, Wang J, Negrete M, Huang Q, Wang L, Jang C, Muddiman DC, Su X, Williamson I, Shen X. Glycerate from intestinal fructose metabolism induces islet cell damage and glucose intolerance. Cell Metab 2022; 34:1042-1053.e6. [PMID: 35688154 PMCID: PMC9897509 DOI: 10.1016/j.cmet.2022.05.007] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/20/2021] [Revised: 12/21/2021] [Accepted: 05/18/2022] [Indexed: 02/06/2023]
Abstract
Dietary fructose, especially in the context of a high-fat western diet, has been linked to type 2 diabetes. Although the effect of fructose on liver metabolism has been extensively studied, a significant portion of the fructose is first metabolized in the small intestine. Here, we report that dietary fat enhances intestinal fructose metabolism, which releases glycerate into the blood. Chronic high systemic glycerate levels induce glucose intolerance by slowly damaging pancreatic islet cells and reducing islet sizes. Our findings provide a link between dietary fructose and diabetes that is modulated by dietary fat.
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Affiliation(s)
- Yanru Wu
- Department of Prosthodontics, School and Hospital of Stomatology, Wuhan University, Wuhan, Hubei 430079, China; Department of Biomedical Engineering, Pratt School of Engineering, Duke University, Durham, NC 27708, USA
| | - Chi Wut Wong
- Department of Biomedical Engineering, Pratt School of Engineering, Duke University, Durham, NC 27708, USA; Department of Pharmacology & Cancer Biology, Duke University Medical Center, Durham, NC 27710, USA
| | - Eric N Chiles
- Metabolomics Shared Resource, Rutgers Cancer Institute of New Jersey, Rutgers University, New Brunswick, NJ 08903, USA
| | - Allyson L Mellinger
- FTMS Laboratory for Human Health Research, Department of Chemistry, North Carolina State University, Raleigh, NC 27695, USA
| | - Hosung Bae
- Department of Biological Chemistry, University of California, Irvine, Irvine, CA 92697, USA
| | - Sunhee Jung
- Department of Biological Chemistry, University of California, Irvine, Irvine, CA 92697, USA
| | - Ted Peterson
- Department of Biomedical Engineering, Pratt School of Engineering, Duke University, Durham, NC 27708, USA
| | - Jamie Wang
- Department of Biomedical Engineering, Pratt School of Engineering, Duke University, Durham, NC 27708, USA
| | - Marcos Negrete
- Department of Biomedical Engineering, Pratt School of Engineering, Duke University, Durham, NC 27708, USA
| | - Qiang Huang
- Department of Biomedical Engineering, Pratt School of Engineering, Duke University, Durham, NC 27708, USA; Department of Pediatric Surgery, Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shanxi 710004, China
| | - Lihua Wang
- Department of Biomedical Engineering, Pratt School of Engineering, Duke University, Durham, NC 27708, USA
| | - Cholsoon Jang
- Department of Biological Chemistry, University of California, Irvine, Irvine, CA 92697, USA
| | - David C Muddiman
- FTMS Laboratory for Human Health Research, Department of Chemistry, North Carolina State University, Raleigh, NC 27695, USA; Molecular Education, Technology and Research Innovation Center, North Carolina State University, Raleigh, NC 27695, USA
| | - Xiaoyang Su
- Metabolomics Shared Resource, Rutgers Cancer Institute of New Jersey, Rutgers University, New Brunswick, NJ 08903, USA; Department of Medicine, Robert Wood Johnson Medical School, Rutgers University, New Brunswick, NJ 08901, USA
| | - Ian Williamson
- Department of Biomedical Engineering, Pratt School of Engineering, Duke University, Durham, NC 27708, USA; Gastroenterology Division, Department of Medicine, Duke University, Durham, NC 27710, USA.
| | - Xiling Shen
- Department of Biomedical Engineering, Pratt School of Engineering, Duke University, Durham, NC 27708, USA; Terasaki Institute for Biomedical Innovation, Los Angeles, CA 90024, USA.
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Pace CL, Garrard KP, Muddiman DC. Sequential paired covariance for improved visualization of mass spectrometry imaging datasets. JOURNAL OF MASS SPECTROMETRY : JMS 2022; 57:e4872. [PMID: 35734788 PMCID: PMC9287032 DOI: 10.1002/jms.4872] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/30/2022] [Revised: 05/02/2022] [Accepted: 06/09/2022] [Indexed: 05/25/2023]
Abstract
Untargeted analyses in mass spectrometry imaging produce hundreds of ion images representing spatial distributions of biomolecules in biological tissues. Due to the large diversity of ions detected in untargeted analyses, normalization standards are often difficult to implement to account for pixel-to-pixel variability in imaging studies. Many normalization strategies exist to account for this variability, but they largely do not improve image quality. In this study, we present a new approach for improving image quality and visualization of tissue features by application of sequential paired covariance (SPC). This approach was demonstrated using previously published tissue datasets such as rat brain and human prostate with different biomolecules like metabolites and N-linked glycans. Data transformation by SPC improved ion images resulting in increased smoothing of biological features compared with commonly used normalization approaches.
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Affiliation(s)
- Crystal L. Pace
- FTMS Laboratory for Human Health Research, Department of ChemistryNorth Carolina State UniversityRaleighNorth CarolinaUSA
| | - Kenneth P. Garrard
- FTMS Laboratory for Human Health Research, Department of ChemistryNorth Carolina State UniversityRaleighNorth CarolinaUSA
- The Precision Engineering ConsortiumNorth Carolina State UniversityRaleighNorth CarolinaUSA
- Molecular Education, Technology and Research Innovation Center (METRIC)North Carolina State UniversityRaleighNorth CarolinaUSA
| | - David C. Muddiman
- FTMS Laboratory for Human Health Research, Department of ChemistryNorth Carolina State UniversityRaleighNorth CarolinaUSA
- Molecular Education, Technology and Research Innovation Center (METRIC)North Carolina State UniversityRaleighNorth CarolinaUSA
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9
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Mellinger AL, Muddiman DC, Gamcsik MP. Highlighting Functional Mass Spectrometry Imaging Methods in Bioanalysis. J Proteome Res 2022; 21:1800-1807. [PMID: 35749637 DOI: 10.1021/acs.jproteome.2c00220] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Most mass spectrometry imaging (MSI) methods provide a molecular map of tissue content but little information on tissue function. Mapping tissue function is possible using several well-known examples of "functional imaging" such as positron emission tomography and functional magnetic resonance imaging that can provide the spatial distribution of time-dependent biological processes. These functional imaging methods represent the net output of molecular networks influenced by local tissue environments that are difficult to predict from molecular/cellular content alone. However, for decades, MSI methods have also been demonstrated to provide functional imaging data on a variety of biological processes. In fact, MSI exceeds some of the classic functional imaging methods, demonstrating the ability to provide functional data from the nanoscale (subcellular) to whole tissue or organ level. This Perspective highlights several examples of how different MSI ionization and detection technologies can provide unprecedented detailed spatial maps of time-dependent biological processes, namely, nucleic acid synthesis, lipid metabolism, bioenergetics, and protein metabolism. By classifying various MSI methods under the umbrella of "functional MSI", we hope to draw attention to both the unique capabilities and accessibility with the aim of expanding this underappreciated field to include new approaches and applications.
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Affiliation(s)
- Allyson L Mellinger
- FTMS Laboratory for Human Health Research, Department of Chemistry, North Carolina State University, Raleigh, North Carolina 27695, United States
| | - David C Muddiman
- FTMS Laboratory for Human Health Research, Department of Chemistry, North Carolina State University, Raleigh, North Carolina 27695, United States.,Molecular Education, Technology and Research Innovation Center (METRIC), North Carolina State University, Raleigh, North Carolina 27695, United States
| | - Michael P Gamcsik
- UNC/NCSU Joint Department of Biomedical Engineering, Raleigh, North Carolina 27695, United States
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