1
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Geng Z, Jin Q, Liu L, Huang Y, Zhou X, Zhang X, Sun W. Enhanced MALDI-2 Sensitivity with Reflecting Post-Ionization Laser for High-Resolution MS Imaging Combined with Real-Time Microscope Imaging. Anal Chem 2024. [PMID: 39093983 DOI: 10.1021/acs.analchem.4c00576] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/04/2024]
Abstract
Laser-induced matrix-assisted laser desorption/ionization post-ionization (MALDI-2) could improve the MALDI sensitivity of biological metabolites by over 1 order of magnitude. Herein, we demonstrate that MALDI-2 sensitivity can be further enhanced with reflecting post-ionization laser that multiplies the intersection times between laser and MALDI plume. This method, which we named MALDI-2+, typically brought over 2 times sensitivity improvement from conventional MALDI-2. Advancing in sensitivity thereby prompted us to pursue higher mass spectrometry imaging (MSI) spatial resolution. A dedicated T-shaped ion guide was designed to allow perpendicular incidence of ablation laser in reflection geometry MALDI. Although 8-10 μm pixel was used in MALDI imaging due to the limited precision of the motorized stage, the laser spot diameter could be down to 2.5 μm for potentially higher spatial resolution. In addition, this ion source enabled real-time and high-quality microscope imaging from backward of the sample plate. Beneficially, we were able to monitor the actual laser spot condition in real time as well as obtain high-resolution microscopic sample images that inherently register with MSI images. All of these benefits have been demonstrated by analyzing standard samples and imaging of cells. We believe that the enhancement in sensitivity, spatial resolution, and microscope capacity of our design could facilitate spatial omics studies.
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Affiliation(s)
- Zhi Geng
- Shimadzu Research Laboratory (Shanghai) Co., Ltd., Shanghai 201206, China
| | - Qiao Jin
- Shimadzu Research Laboratory (Shanghai) Co., Ltd., Shanghai 201206, China
| | - Lin Liu
- Shimadzu Research Laboratory (Shanghai) Co., Ltd., Shanghai 201206, China
| | - Yuanyuan Huang
- Shimadzu Research Laboratory (Shanghai) Co., Ltd., Shanghai 201206, China
| | - Xinfeng Zhou
- Shimadzu Research Laboratory (Shanghai) Co., Ltd., Shanghai 201206, China
| | - Xiaoqiang Zhang
- Shimadzu Research Laboratory (Shanghai) Co., Ltd., Shanghai 201206, China
| | - Wenjian Sun
- Shimadzu Research Laboratory (Shanghai) Co., Ltd., Shanghai 201206, China
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2
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Eshel YD, Sharaha U, Beck G, Cohen-Logasi G, Lapidot I, Huleihel M, Mordechai S, Kapelushnik J, Salman A. Monitoring the efficacy of antibiotic therapy in febrile pediatric oncology patients with bacteremia using infrared spectroscopy of white blood cells-based machine learning. Talanta 2024; 270:125619. [PMID: 38199122 DOI: 10.1016/j.talanta.2023.125619] [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: 10/15/2023] [Revised: 12/29/2023] [Accepted: 12/30/2023] [Indexed: 01/12/2024]
Abstract
Bacteremia refers to the presence of bacteria in the bloodstream, which can lead to a serious and potentially life-threatening condition. In oncology patients, individuals undergoing cancer treatment have a higher risk of developing bacteremia due to a weakened immune system resulting from the disease itself or the treatments they receive. Prompt and accurate detection of bacterial infections and monitoring the effectiveness of antibiotic therapy are essential for enhancing patient outcomes and preventing the development and dissemination of multidrug-resistant bacteria. Traditional methods of infection monitoring, such as blood cultures and clinical observations, are time-consuming, labor-intensive, and often subject to limitations. This manuscript presents an innovative application of infrared spectroscopy of leucocytes of pediatric oncology patients with bacteremia combined with machine learning to diagnose the etiology of infection as bacterial and simultaneously monitor the efficacy of the antibiotic therapy in febrile pediatric oncology patients with bacteremia infections. Through the implementation of effective monitoring, it becomes possible to promptly identify any indications of treatment failure. This, in turn, indirectly serves to limit the progression of antibiotic resistance. The logistic regression (LR) classifier was able to differentiate the samples as bacterial or control within an hour, after receiving the blood samples with a success rate of over 95 %. Additionally, initial findings indicate that employing infrared spectroscopy of white blood cells (WBCs) along with machine learning is viable for monitoring the success of antibiotic therapy. Our follow up results demonstrate an accuracy of 87.5 % in assessing the effectiveness of the antibiotic treatment.
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Affiliation(s)
- Yotam D Eshel
- Department of Hematology and Oncology, Saban Pediatric Medical Center Soroka University Medical Center and Faculty of Health Sciences, Beer-Sheva, 84105, Israel
| | - Uraib Sharaha
- Department of Microbiology, Immunology, and Genetics, Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer-Sheva, 84105, Israel; Department of Biology, Science and Technology College, Hebron University, Hebron, P760, Palestine
| | - Guy Beck
- Department of Hematology and Oncology, Saban Pediatric Medical Center Soroka University Medical Center and Faculty of Health Sciences, Beer-Sheva, 84105, Israel
| | - Gal Cohen-Logasi
- Department of Green Engineering, SCE-Sami Shamoon College of Engineering, Beer-Sheva, 84100, Israel
| | - Itshak Lapidot
- Department of Electrical and Electronics Engineering, ACLP-Afeka Center for Language Processing, Afeka Tel-Aviv Academic College of Engineering, Tel-Aviv, 69107, Israel; LIA Avignon Université, 339 Chemin des Meinajaries, Avignon, 84000, France
| | - Mahmoud Huleihel
- Department of Microbiology, Immunology, and Genetics, Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer-Sheva, 84105, Israel
| | - Shaul Mordechai
- Department of Physics, Ben-Gurion University, Beer-Sheva, 84105, Israel
| | - Joseph Kapelushnik
- Department of Hematology and Oncology, Saban Pediatric Medical Center Soroka University Medical Center and Faculty of Health Sciences, Beer-Sheva, 84105, Israel
| | - Ahmad Salman
- Department of Physics, SCE-Sami Shamoon College of Engineering, Beer-Sheva, 84100, Israel.
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3
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Croslow SW, Trinklein TJ, Sweedler JV. Advances in multimodal mass spectrometry for single-cell analysis and imaging enhancement. FEBS Lett 2024; 598:591-601. [PMID: 38243373 PMCID: PMC10963143 DOI: 10.1002/1873-3468.14798] [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: 11/12/2023] [Revised: 12/11/2023] [Accepted: 12/18/2023] [Indexed: 01/21/2024]
Abstract
Multimodal mass spectrometry (MMS) incorporates an imaging modality with probe-based mass spectrometry (MS) to enable precise, targeted data acquisition and provide additional biological and chemical data not available by MS alone. Two categories of MMS are covered; in the first, an imaging modality guides the MS probe to target individual cells and to reduce acquisition time by automatically defining regions of interest. In the second category, imaging and MS data are coupled in the data analysis pipeline to increase the effective spatial resolution using a higher resolution imaging method, correct for tissue deformation, and incorporate fine morphological features in an MS imaging dataset. Recent methodological and computational developments are covered along with their application to single-cell and imaging analyses.
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Affiliation(s)
- Seth W. Croslow
- Department of Chemistry, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
| | - Timothy J. Trinklein
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
| | - Jonathan V. Sweedler
- Department of Chemistry, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
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4
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Rittel MF, Schmidt S, Weis CA, Birgin E, van Marwick B, Rädle M, Diehl SJ, Rahbari NN, Marx A, Hopf C. Spatial Omics Imaging of Fresh-Frozen Tissue and Routine FFPE Histopathology of a Single Cancer Needle Core Biopsy: A Freezing Device and Multimodal Workflow. Cancers (Basel) 2023; 15:2676. [PMID: 37345020 DOI: 10.3390/cancers15102676] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2023] [Revised: 04/16/2023] [Accepted: 05/06/2023] [Indexed: 06/23/2023] Open
Abstract
The complex molecular alterations that underlie cancer pathophysiology are studied in depth with omics methods using bulk tissue extracts. For spatially resolved tissue diagnostics using needle biopsy cores, however, histopathological analysis using stained FFPE tissue and the immunohistochemistry (IHC) of a few marker proteins is currently the main clinical focus. Today, spatial omics imaging using MSI or IRI is an emerging diagnostic technology for the identification and classification of various cancer types. However, to conserve tissue-specific metabolomic states, fast, reliable, and precise methods for the preparation of fresh-frozen (FF) tissue sections are crucial. Such methods are often incompatible with clinical practice, since spatial metabolomics and the routine histopathology of needle biopsies currently require two biopsies for FF and FFPE sampling, respectively. Therefore, we developed a device and corresponding laboratory and computational workflows for the multimodal spatial omics analysis of fresh-frozen, longitudinally sectioned needle biopsies to accompany standard FFPE histopathology of the same biopsy core. As a proof-of-concept, we analyzed surgical human liver cancer specimens using IRI and MSI with precise co-registration and, following FFPE processing, by sequential clinical pathology analysis of the same biopsy core. This workflow allowed for a spatial comparison between different spectral profiles and alterations in tissue histology, as well as a direct comparison for histological diagnosis without the need for an extra biopsy.
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Affiliation(s)
- Miriam F Rittel
- Center for Mass Spectrometry and Optical Spectroscopy (CeMOS), Mannheim University of Applied Sciences, Paul-Wittsack-Str. 10, 68163 Mannheim, Germany
- Institute of Medical Technology, Heidelberg University and Mannheim University of Applied Sciences, Paul-Wittsack-Str. 10, 68163 Mannheim, Germany
- Medical Faculty Mannheim, Heidelberg University, Theodor-Kutzer-Ufer 1-3, 68167 Mannheim, Germany
| | - Stefan Schmidt
- Center for Mass Spectrometry and Optical Spectroscopy (CeMOS), Mannheim University of Applied Sciences, Paul-Wittsack-Str. 10, 68163 Mannheim, Germany
| | - Cleo-Aron Weis
- Institute of Pathology, University Medical Centre Mannheim, Theodor-Kutzer-Ufer 1-3, 68167 Mannheim, Germany
| | - Emrullah Birgin
- Department of Surgery, University Medical Centre Mannheim, Theodor-Kutzer-Ufer 1-3, 68167 Mannheim, Germany
| | - Björn van Marwick
- Center for Mass Spectrometry and Optical Spectroscopy (CeMOS), Mannheim University of Applied Sciences, Paul-Wittsack-Str. 10, 68163 Mannheim, Germany
| | - Matthias Rädle
- Center for Mass Spectrometry and Optical Spectroscopy (CeMOS), Mannheim University of Applied Sciences, Paul-Wittsack-Str. 10, 68163 Mannheim, Germany
- Institute of Medical Technology, Heidelberg University and Mannheim University of Applied Sciences, Paul-Wittsack-Str. 10, 68163 Mannheim, Germany
- Medical Faculty Mannheim, Heidelberg University, Theodor-Kutzer-Ufer 1-3, 68167 Mannheim, Germany
| | - Steffen J Diehl
- Medical Faculty Mannheim, Heidelberg University, Theodor-Kutzer-Ufer 1-3, 68167 Mannheim, Germany
- Clinic of Clinical Radiology and Nuclear Medicine, University Medical Center Mannheim, Theodor-Kutzer-Ufer 1-3, 68167 Mannheim, Germany
| | - Nuh N Rahbari
- Medical Faculty Mannheim, Heidelberg University, Theodor-Kutzer-Ufer 1-3, 68167 Mannheim, Germany
- Department of Surgery, University Medical Centre Mannheim, Theodor-Kutzer-Ufer 1-3, 68167 Mannheim, Germany
| | - Alexander Marx
- Medical Faculty Mannheim, Heidelberg University, Theodor-Kutzer-Ufer 1-3, 68167 Mannheim, Germany
- Institute of Pathology, University Medical Centre Mannheim, Theodor-Kutzer-Ufer 1-3, 68167 Mannheim, Germany
| | - Carsten Hopf
- Center for Mass Spectrometry and Optical Spectroscopy (CeMOS), Mannheim University of Applied Sciences, Paul-Wittsack-Str. 10, 68163 Mannheim, Germany
- Institute of Medical Technology, Heidelberg University and Mannheim University of Applied Sciences, Paul-Wittsack-Str. 10, 68163 Mannheim, Germany
- Medical Faculty Mannheim, Heidelberg University, Theodor-Kutzer-Ufer 1-3, 68167 Mannheim, Germany
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5
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Hu H, Laskin J. Emerging Computational Methods in Mass Spectrometry Imaging. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2022; 9:e2203339. [PMID: 36253139 PMCID: PMC9731724 DOI: 10.1002/advs.202203339] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/07/2022] [Revised: 09/17/2022] [Indexed: 05/10/2023]
Abstract
Mass spectrometry imaging (MSI) is a powerful analytical technique that generates maps of hundreds of molecules in biological samples with high sensitivity and molecular specificity. Advanced MSI platforms with capability of high-spatial resolution and high-throughput acquisition generate vast amount of data, which necessitates the development of computational tools for MSI data analysis. In addition, computation-driven MSI experiments have recently emerged as enabling technologies for further improving the MSI capabilities with little or no hardware modification. This review provides a critical summary of computational methods and resources developed for MSI data analysis and interpretation along with computational approaches for improving throughput and molecular coverage in MSI experiments. This review is focused on the recently developed artificial intelligence methods and provides an outlook for a future paradigm shift in MSI with transformative computational methods.
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Affiliation(s)
- Hang Hu
- Department of ChemistryPurdue University560 Oval DriveWest LafayetteIN47907USA
| | - Julia Laskin
- Department of ChemistryPurdue University560 Oval DriveWest LafayetteIN47907USA
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6
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Azam KSF, Ryabchykov O, Bocklitz T. A Review on Data Fusion of Multidimensional Medical and Biomedical Data. Molecules 2022; 27:7448. [PMID: 36364272 PMCID: PMC9655963 DOI: 10.3390/molecules27217448] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2022] [Revised: 09/19/2022] [Accepted: 10/21/2022] [Indexed: 08/05/2024] Open
Abstract
Data fusion aims to provide a more accurate description of a sample than any one source of data alone. At the same time, data fusion minimizes the uncertainty of the results by combining data from multiple sources. Both aim to improve the characterization of samples and might improve clinical diagnosis and prognosis. In this paper, we present an overview of the advances achieved over the last decades in data fusion approaches in the context of the medical and biomedical fields. We collected approaches for interpreting multiple sources of data in different combinations: image to image, image to biomarker, spectra to image, spectra to spectra, spectra to biomarker, and others. We found that the most prevalent combination is the image-to-image fusion and that most data fusion approaches were applied together with deep learning or machine learning methods.
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Affiliation(s)
- Kazi Sultana Farhana Azam
- Leibniz Institute of Photonic Technology, Member of Leibniz-Research Alliance “Health Technologies”, Albert-Einstein-Straße 9, 07745 Jena, Germany
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University Jena, Helmholtzweg 4, 07743 Jena, Germany
| | - Oleg Ryabchykov
- Leibniz Institute of Photonic Technology, Member of Leibniz-Research Alliance “Health Technologies”, Albert-Einstein-Straße 9, 07745 Jena, Germany
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University Jena, Helmholtzweg 4, 07743 Jena, Germany
| | - Thomas Bocklitz
- Leibniz Institute of Photonic Technology, Member of Leibniz-Research Alliance “Health Technologies”, Albert-Einstein-Straße 9, 07745 Jena, Germany
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University Jena, Helmholtzweg 4, 07743 Jena, Germany
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7
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Tuck M, Grélard F, Blanc L, Desbenoit N. MALDI-MSI Towards Multimodal Imaging: Challenges and Perspectives. Front Chem 2022; 10:904688. [PMID: 35615316 PMCID: PMC9124797 DOI: 10.3389/fchem.2022.904688] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2022] [Accepted: 04/14/2022] [Indexed: 01/22/2023] Open
Abstract
Multimodal imaging is a powerful strategy for combining information from multiple images. It involves several fields in the acquisition, processing and interpretation of images. As multimodal imaging is a vast subject area with various combinations of imaging techniques, it has been extensively reviewed. Here we focus on Matrix-assisted Laser Desorption Ionization Mass Spectrometry Imaging (MALDI-MSI) coupling other imaging modalities in multimodal approaches. While MALDI-MS images convey a substantial amount of chemical information, they are not readily informative about the morphological nature of the tissue. By providing a supplementary modality, MALDI-MS images can be more informative and better reflect the nature of the tissue. In this mini review, we emphasize the analytical and computational strategies to address multimodal MALDI-MSI.
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8
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Ritschar S, Schirmer E, Hufnagl B, Löder MGJ, Römpp A, Laforsch C. Classification of target tissues of Eisenia fetida using sequential multimodal chemical analysis and machine learning. Histochem Cell Biol 2022; 157:127-137. [PMID: 34750664 PMCID: PMC8847259 DOI: 10.1007/s00418-021-02037-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/21/2021] [Indexed: 12/22/2022]
Abstract
Acquiring comprehensive knowledge about the uptake of pollutants, impact on tissue integrity and the effects at the molecular level in organisms is of increasing interest due to the environmental exposure to numerous contaminants. The analysis of tissues can be performed by histological examination, which is still time-consuming and restricted to target-specific staining methods. The histological approaches can be complemented with chemical imaging analysis. Chemical imaging of tissue sections is typically performed using a single imaging approach. However, for toxicological testing of environmental pollutants, a multimodal approach combined with improved data acquisition and evaluation is desirable, since it may allow for more rapid tissue characterization and give further information on ecotoxicological effects at the tissue level. Therefore, using the soil model organism Eisenia fetida as a model, we developed a sequential workflow combining Fourier transform infrared spectroscopy (FTIR) and matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) for chemical analysis of the same tissue sections. Data analysis of the FTIR spectra via random decision forest (RDF) classification enabled the rapid identification of target tissues (e.g., digestive tissue), which are relevant from an ecotoxicological point of view. MALDI imaging analysis provided specific lipid species which are sensitive to metabolic changes and environmental stressors. Taken together, our approach provides a fast and reproducible workflow for label-free histochemical tissue analyses in E. fetida, which can be applied to other model organisms as well.
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Affiliation(s)
- Sven Ritschar
- Department of Animal Ecology i and BayCEER, University of Bayreuth, Bayreuth, Germany
| | - Elisabeth Schirmer
- Department of Bioanalytical Sciences and Food Analysis, University of Bayreuth, Bayreuth, Germany
| | - Benedikt Hufnagl
- Institute of Chemical Technologies and Analytics, Vienna, TU, Austria
- Purency GmbH, Walfischgasse 8/34, T1010, Vienna, Austria
| | - Martin G J Löder
- Department of Animal Ecology i and BayCEER, University of Bayreuth, Bayreuth, Germany
| | - Andreas Römpp
- Department of Bioanalytical Sciences and Food Analysis, University of Bayreuth, Bayreuth, Germany.
| | - Christian Laforsch
- Department of Animal Ecology i and BayCEER, University of Bayreuth, Bayreuth, Germany.
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9
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Iakab SA, Baquer G, Lafuente M, Pina MP, Ramírez JL, Ràfols P, Correig-Blanchar X, García-Altares M. SALDI-MS and SERS Multimodal Imaging: One Nanostructured Substrate to Rule Them Both. Anal Chem 2022; 94:2785-2793. [PMID: 35102738 PMCID: PMC8851428 DOI: 10.1021/acs.analchem.1c04118] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
![]()
Imaging techniques
based on mass spectrometry or spectroscopy methods
inform in situ about the chemical composition of
biological tissues or organisms, but they are sometimes limited by
their specificity, sensitivity, or spatial resolution. Multimodal
imaging addresses these limitations by combining several imaging modalities;
however, measuring the same sample with the same preparation using
multiple imaging techniques is still uncommon due to the incompatibility
between substrates, sample preparation protocols, and data formats.
We present a multimodal imaging approach that employs a gold-coated
nanostructured silicon substrate to couple surface-assisted laser
desorption/ionization mass spectrometry (SALDI-MS) and surface-enhanced
Raman spectroscopy (SERS). Our approach integrates both imaging modalities
by using the same substrate, sample preparation, and data analysis
software on the same sample, allowing the coregistration of both images.
We transferred molecules from clean fingertips and fingertips covered
with plasticine modeling clay onto our nanostructure and analyzed
their chemical composition and distribution by SALDI-MS and SERS.
Multimodal analysis located the traces of plasticine on fingermarks
and provided chemical information on the composition of the clay.
Our multimodal approach effectively combines the advantages of mass
spectrometry and vibrational spectroscopy with the signal enhancing
abilities of our nanostructured substrate.
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Affiliation(s)
- Stefania-Alexandra Iakab
- Department of Electronic Engineering, Rovira i Virgili University, Tarragona 43007, Spain.,Spanish Biomedical Research Centre in Diabetes and Associated Metabolic Disorders (CIBERDEM), Madrid 28029, Spain
| | - Gerard Baquer
- Department of Electronic Engineering, Rovira i Virgili University, Tarragona 43007, Spain
| | - Marta Lafuente
- Instituto de Nanociencia y Materiales de Aragón (INMA), CSIC-Universidad de Zaragoza, Zaragoza 50009, Spain.,Departamento de Ingeniería Química y Tecnologías del Medio Ambiente, Universidad de Zaragoza, Campus Río Ebro-Edificio I+D+i, C/Mariano Esquillor s/n, Zaragoza 50018, Spain
| | - Maria Pilar Pina
- Instituto de Nanociencia y Materiales de Aragón (INMA), CSIC-Universidad de Zaragoza, Zaragoza 50009, Spain.,Departamento de Ingeniería Química y Tecnologías del Medio Ambiente, Universidad de Zaragoza, Campus Río Ebro-Edificio I+D+i, C/Mariano Esquillor s/n, Zaragoza 50018, Spain.,Networking Research Center on Bioengineering, Biomaterials and Nanomedicine, CIBER-BBN, Madrid 28029, Spain
| | - José Luis Ramírez
- Department of Electronic Engineering, Rovira i Virgili University, Tarragona 43007, Spain
| | - Pere Ràfols
- Department of Electronic Engineering, Rovira i Virgili University, Tarragona 43007, Spain.,Spanish Biomedical Research Centre in Diabetes and Associated Metabolic Disorders (CIBERDEM), Madrid 28029, Spain
| | - Xavier Correig-Blanchar
- Department of Electronic Engineering, Rovira i Virgili University, Tarragona 43007, Spain.,Spanish Biomedical Research Centre in Diabetes and Associated Metabolic Disorders (CIBERDEM), Madrid 28029, Spain.,Institut d'Investigació Sanitària Pere Virgili (IISPV), Reus 43204, Spain
| | - María García-Altares
- Department of Electronic Engineering, Rovira i Virgili University, Tarragona 43007, Spain.,Spanish Biomedical Research Centre in Diabetes and Associated Metabolic Disorders (CIBERDEM), Madrid 28029, Spain
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10
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Engel KM, Prabutzki P, Leopold J, Nimptsch A, Lemmnitzer K, Vos DRN, Hopf C, Schiller J. A new update of MALDI-TOF mass spectrometry in lipid research. Prog Lipid Res 2022; 86:101145. [PMID: 34995672 DOI: 10.1016/j.plipres.2021.101145] [Citation(s) in RCA: 25] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2021] [Revised: 12/06/2021] [Accepted: 12/29/2021] [Indexed: 01/06/2023]
Abstract
Matrix-assisted laser desorption and ionization (MALDI) mass spectrometry (MS) is an indispensable tool in modern lipid research since it is fast, sensitive, tolerates sample impurities and provides spectra without major analyte fragmentation. We will discuss some methodological aspects, the related ion-forming processes and the MALDI MS characteristics of the different lipid classes (with the focus on glycerophospholipids) and the progress, which was achieved during the last ten years. Particular attention will be given to quantitative aspects of MALDI MS since this is widely considered as the most serious drawback of the method. Although the detailed role of the matrix is not yet completely understood, it will be explicitly shown that the careful choice of the matrix is crucial (besides the careful evaluation of the positive and negative ion mass spectra) in order to be able to detect all lipid classes of interest. Two developments will be highlighted: spatially resolved Imaging MS is nowadays well established and the distribution of lipids in tissues merits increasing interest because lipids are readily detectable and represent ubiquitous compounds. It will also be shown that a combination of MALDI MS with thin-layer chromatography (TLC) enables a fast spatially resolved screening of an entire TLC plate which makes the method competitive with LC/MS.
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Affiliation(s)
- Kathrin M Engel
- Leipzig University, Faculty of Medicine, Institute for Medical Physics and Biophysics, Härtelstraße 16-18, D-04107, Germany
| | - Patricia Prabutzki
- Leipzig University, Faculty of Medicine, Institute for Medical Physics and Biophysics, Härtelstraße 16-18, D-04107, Germany
| | - Jenny Leopold
- Leipzig University, Faculty of Medicine, Institute for Medical Physics and Biophysics, Härtelstraße 16-18, D-04107, Germany
| | - Ariane Nimptsch
- Leipzig University, Faculty of Medicine, Institute for Medical Physics and Biophysics, Härtelstraße 16-18, D-04107, Germany
| | - Katharina Lemmnitzer
- Leipzig University, Faculty of Medicine, Institute for Medical Physics and Biophysics, Härtelstraße 16-18, D-04107, Germany
| | - D R Naomi Vos
- Center for Biomedical Mass Spectrometry and Optical Spectroscopy (CeMOS), Mannheim University of Applied Sciences, Paul-Wittsack-Strasse 10, D-68163 Mannheim, Germany
| | - Carsten Hopf
- Center for Biomedical Mass Spectrometry and Optical Spectroscopy (CeMOS), Mannheim University of Applied Sciences, Paul-Wittsack-Strasse 10, D-68163 Mannheim, Germany
| | - Jürgen Schiller
- Leipzig University, Faculty of Medicine, Institute for Medical Physics and Biophysics, Härtelstraße 16-18, D-04107, Germany.
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11
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Guendel A, Hilo A, Rolletschek H, Borisjuk L. Probing the Metabolic Landscape of Plant Vascular Bundles by Infrared Fingerprint Analysis, Imaging and Mass Spectrometry. Biomolecules 2021; 11:1717. [PMID: 34827716 PMCID: PMC8615794 DOI: 10.3390/biom11111717] [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: 08/20/2021] [Revised: 11/15/2021] [Accepted: 11/16/2021] [Indexed: 11/27/2022] Open
Abstract
Fingerprint analysis is a common technique in forensic and criminal investigations. Similar techniques exist in the field of infrared spectroscopy to identify biomolecules according to their characteristic spectral fingerprint features. These unique markers are located in a wavenumber range from 1800 to 600 cm-1 in the mid infrared region. Here, a novel bioanalytical concept of correlating these spectral features with corresponding mass spectrometry datasets to unravel metabolic clusters within complex plant tissues was applied. As proof of concept, vascular bundles of oilseed rape (Brassica napus) were investigated, one of the most important and widely cultivated temperate zone oilseed crops. The link between mass spectrometry data and spectral data identified features that co-aligned within both datasets. Regions of origin were then detected by searching for these features in hyperspectral images of plant tissues. This approach, based on co-alignment and co-localization, finally enabled the detection of eight distinct metabolic clusters, reflecting functional and structural arrangements within the vascular bundle. The proposed analytical concept may assist future synergistic research approaches and may lead to biotechnological innovations with regard to crop yield and sustainability.
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Affiliation(s)
| | | | | | - Ljudmilla Borisjuk
- Department of Molecular Genetics, Leibniz Institute for Plant Genetics and Crop Plant Research, 06466 Gatersleben, Germany; (A.G.); (A.H.); (H.R.)
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12
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Al Jedani S, Whitley CA, Ellis BG, Triantafyllou A, Smith CI, Gunning PJ, Gardner P, Risk JM, Weightman P, Barrett SD. Image fusion of IR and optical microscopy for mapping of biomolecules in tissue. Analyst 2021; 146:5848-5854. [PMID: 34498612 PMCID: PMC8475953 DOI: 10.1039/d1an01161h] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2021] [Accepted: 08/30/2021] [Indexed: 11/21/2022]
Abstract
It is shown that a pixel-level image fusion technique can produce images that combine the spatial resolution of optical microscopy images of haematoxylin and eosin (H&E) stained tissue with the chemical information in Fourier transform infrared (FTIR) images. The fused images show minimal distortion and the higher spatial resolution of the H&E images overcomes the diffraction limit on the spatial resolution of the FTIR images. A consideration of the FTIR spectra of nucleic acids and collagen can explain the changes in contrast between non-cancerous oral epithelium and underlying stroma within fused images formed by combining an H&E stain of oral tissue with FTIR images of the tissue obtained at a number of wavenumbers.
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Affiliation(s)
- Safaa Al Jedani
- Department of Physics, University of Liverpool, L69 7ZE, UK.
| | - Conor A Whitley
- Department of Physics, University of Liverpool, L69 7ZE, UK.
| | - Barnaby G Ellis
- Department of Physics, University of Liverpool, L69 7ZE, UK.
| | - Asterios Triantafyllou
- Department of Pathology, Liverpool Clinical Laboratories, University of Liverpool, Liverpool, L69 3GA, UK
| | | | - Philip J Gunning
- Department of Molecular and Clinical Cancer Medicine, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, L3 9TA, UK
| | - Peter Gardner
- Manchester Institute of Biotechnology, University of Manchester, 131 Princess Street, Manchester, M1 7DN, UK
| | - Janet M Risk
- Department of Molecular and Clinical Cancer Medicine, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, L3 9TA, UK
| | - Peter Weightman
- Department of Physics, University of Liverpool, L69 7ZE, UK.
| | - Steve D Barrett
- Department of Physics, University of Liverpool, L69 7ZE, UK.
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13
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Rapid brain structure and tumour margin detection on whole frozen tissue sections by fast multiphotometric mid-infrared scanning. Sci Rep 2021; 11:11307. [PMID: 34050224 PMCID: PMC8163866 DOI: 10.1038/s41598-021-90777-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2021] [Accepted: 05/17/2021] [Indexed: 01/31/2023] Open
Abstract
Frozen section analysis is a frequently used method for examination of tissue samples, especially for tumour detection. In the majority of cases, the aim is to identify characteristic tissue morphologies or tumour margins. Depending on the type of tissue, a high number of misdiagnoses are associated with this process. In this work, a fast spectroscopic measurement device and workflow was developed that significantly improves the speed of whole frozen tissue section analyses and provides sufficient information to visualize tissue structures and tumour margins, dependent on their lipid and protein molecular vibrations. That optical and non-destructive method is based on selected wavenumbers in the mid-infrared (MIR) range. We present a measuring system that substantially outperforms a commercially available Fourier Transform Infrared (FT-IR) Imaging system, since it enables acquisition of reduced spectral information at a scan field of 1 cm2 in 3 s, with a spatial resolution of 20 µm. This allows fast visualization of segmented structure areas with little computational effort. For the first time, this multiphotometric MIR system is applied to biomedical tissue sections. We are referencing our novel MIR scanner on cryopreserved murine sagittal and coronal brain sections, especially focusing on the hippocampus, and show its usability for rapid identification of primary hepatocellular carcinoma (HCC) in mouse liver.
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14
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Saigusa D, Matsukawa N, Hishinuma E, Koshiba S. Identification of biomarkers to diagnose diseases and find adverse drug reactions by metabolomics. Drug Metab Pharmacokinet 2020; 37:100373. [PMID: 33631535 DOI: 10.1016/j.dmpk.2020.11.008] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2020] [Revised: 11/24/2020] [Accepted: 11/25/2020] [Indexed: 12/12/2022]
Abstract
Metabolomics has been widely used for investigating the biological functions of disease expression and has the potential to discover biomarkers in circulating biofluids or tissue extracts that reflect in phenotypic changes. Metabolic profiling has advantages because of the use of unbiased techniques, including multivariate analysis, and has been applied in pharmacological studies to predict therapeutic and adverse reactions of drugs, which is called pharmacometabolomics (PMx). Nuclear magnetic resonance (NMR)- and mass spectrometry (MS)-based metabolomics has contributed to the discovery of recent disease biomarkers; however, the optimal strategy for the study purpose must be selected from many established protocols, methodologies and analytical platforms. Additionally, information on molecular localization in tissue is essential for further functional analyses related to therapeutic and adverse effects of drugs in the process of drug development. MS imaging (MSI) is a promising technology that can visualize molecules on tissue surfaces without labeling and thus provide localized information. This review summarizes recent uses of MS-based global and wide-targeted metabolomics technologies and the advantages of the MSI approach for PMx and highlights the PMx technique for the biomarker discovery of adverse drug effects.
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Affiliation(s)
- Daisuke Saigusa
- Department of Integrative Genomics, Tohoku University Tohoku Medical Megabank Organization, 2-1 Seiryo-machi, Aoba-ku, Sendai, 980-8573, Japan; Medical Biochemistry, Tohoku University Graduate School of Medicine, 2-1 Seiryo-machi, Aoba-ku, Sendai, 980-8575, Japan.
| | - Naomi Matsukawa
- Department of Integrative Genomics, Tohoku University Tohoku Medical Megabank Organization, 2-1 Seiryo-machi, Aoba-ku, Sendai, 980-8573, Japan; Medical Biochemistry, Tohoku University Graduate School of Medicine, 2-1 Seiryo-machi, Aoba-ku, Sendai, 980-8575, Japan.
| | - Eiji Hishinuma
- Department of Integrative Genomics, Tohoku University Tohoku Medical Megabank Organization, 2-1 Seiryo-machi, Aoba-ku, Sendai, 980-8573, Japan; Advanced Research Center for Innovations in Next-Generation Medicine, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, 980-8573, Japan.
| | - Seizo Koshiba
- Department of Integrative Genomics, Tohoku University Tohoku Medical Megabank Organization, 2-1 Seiryo-machi, Aoba-ku, Sendai, 980-8573, Japan; Medical Biochemistry, Tohoku University Graduate School of Medicine, 2-1 Seiryo-machi, Aoba-ku, Sendai, 980-8575, Japan; Advanced Research Center for Innovations in Next-Generation Medicine, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, 980-8573, Japan.
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15
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Neumann EK, Djambazova KV, Caprioli RM, Spraggins JM. Multimodal Imaging Mass Spectrometry: Next Generation Molecular Mapping in Biology and Medicine. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2020; 31:2401-2415. [PMID: 32886506 PMCID: PMC9278956 DOI: 10.1021/jasms.0c00232] [Citation(s) in RCA: 59] [Impact Index Per Article: 14.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/05/2023]
Abstract
Imaging mass spectrometry has become a mature molecular mapping technology that is used for molecular discovery in many medical and biological systems. While powerful by itself, imaging mass spectrometry can be complemented by the addition of other orthogonal, chemically informative imaging technologies to maximize the information gained from a single experiment and enable deeper understanding of biological processes. Within this review, we describe MALDI, SIMS, and DESI imaging mass spectrometric technologies and how these have been integrated with other analytical modalities such as microscopy, transcriptomics, spectroscopy, and electrochemistry in a field termed multimodal imaging. We explore the future of this field and discuss forthcoming developments that will bring new insights to help unravel the molecular complexities of biological systems, from single cells to functional tissue structures and organs.
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Affiliation(s)
- Elizabeth K Neumann
- Department of Biochemistry, Vanderbilt University, 607 Light Hall, Nashville, Tennessee 37205, United States
- Mass Spectrometry Research Center, Vanderbilt University, 465 21st Avenue S #9160, Nashville, Tennessee 37235, United States
| | - Katerina V Djambazova
- Mass Spectrometry Research Center, Vanderbilt University, 465 21st Avenue S #9160, Nashville, Tennessee 37235, United States
- Department of Chemistry, Vanderbilt University, 7330 Stevenson Center, Station B 351822, Nashville, Tennessee 37235, United States
| | - Richard M Caprioli
- Department of Biochemistry, Vanderbilt University, 607 Light Hall, Nashville, Tennessee 37205, United States
- Mass Spectrometry Research Center, Vanderbilt University, 465 21st Avenue S #9160, Nashville, Tennessee 37235, United States
- Department of Chemistry, Vanderbilt University, 7330 Stevenson Center, Station B 351822, Nashville, Tennessee 37235, United States
- Department of Pharmacology, Vanderbilt University, 2220 Pierce Avenue, Nashville, Tennessee 37232, United States
- Department of Medicine, Vanderbilt University, 465 21st Avenue S #9160, Nashville, Tennessee 37235, United States
| | - Jeffrey M Spraggins
- Department of Biochemistry, Vanderbilt University, 607 Light Hall, Nashville, Tennessee 37205, United States
- Mass Spectrometry Research Center, Vanderbilt University, 465 21st Avenue S #9160, Nashville, Tennessee 37235, United States
- Department of Chemistry, Vanderbilt University, 7330 Stevenson Center, Station B 351822, Nashville, Tennessee 37235, United States
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16
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Benz M, Asperger A, Hamester M, Welle A, Heissler S, Levkin PA. A combined high-throughput and high-content platform for unified on-chip synthesis, characterization and biological screening. Nat Commun 2020; 11:5391. [PMID: 33106489 PMCID: PMC7589500 DOI: 10.1038/s41467-020-19040-0] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2020] [Accepted: 08/27/2020] [Indexed: 11/09/2022] Open
Abstract
Acceleration and unification of drug discovery is important to reduce the effort and cost of new drug development. Diverse chemical and biological conditions, specialized infrastructure and incompatibility between existing analytical methods with high-throughput, nanoliter scale chemistry make the whole drug discovery process lengthy and expensive. Here, we demonstrate a chemBIOS platform combining on-chip chemical synthesis, characterization and biological screening. We developed a dendrimer-based surface patterning that enables the generation of high-density nanodroplet arrays for both organic and aqueous liquids. Each droplet (among > 50,000 droplets per plate) functions as an individual, spatially separated nanovessel, that can be used for solution-based synthesis or analytical assays. An additional indium-tin oxide coating enables ultra-fast on-chip detection down to the attomole per droplet by matrix-assisted laser desorption/ionization mass spectrometry. The excellent optical properties of the chemBIOS platform allow for on-chip characterization and in-situ reaction monitoring in the ultraviolet, visible (on-chip UV-Vis spectroscopy and optical microscopy) and infrared (on-chip IR spectroscopy) regions. The platform is compatible with various cell-biological screenings, which opens new avenues in the fields of high-throughput synthesis and drug discovery.
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Affiliation(s)
- Maximilian Benz
- Karlsruhe Institute of Technology (KIT), Institute of Biological and Chemical Systems-Functional Molecular Systems (IBCS-FMS), Hermann-von-Helmholtz-Platz 1, 76344, Eggenstein-Leopoldshafen, Germany
| | - Arndt Asperger
- Bruker Daltonik GmbH, Fahrenheitstraße 4, 28359, Bremen, Germany
| | - Meike Hamester
- Bruker Daltonik GmbH, Fahrenheitstraße 4, 28359, Bremen, Germany
| | - Alexander Welle
- Karlsruhe Institute of Technology (KIT), Institute of Functional Interfaces (IFG), Hermann-von-Helmholtz-Platz 1, 76344, Eggenstein-Leopoldshafen, Germany
| | - Stefan Heissler
- Karlsruhe Institute of Technology (KIT), Institute of Functional Interfaces (IFG), Hermann-von-Helmholtz-Platz 1, 76344, Eggenstein-Leopoldshafen, Germany
| | - Pavel A Levkin
- Karlsruhe Institute of Technology (KIT), Institute of Biological and Chemical Systems-Functional Molecular Systems (IBCS-FMS), Hermann-von-Helmholtz-Platz 1, 76344, Eggenstein-Leopoldshafen, Germany. .,Karlsruhe Institute of Technology (KIT), Institute of Organic Chemistry (IOC), Kaiserstraße 12, 76131, Karlsruhe, Germany.
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17
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Agbaria AH, Beck G, Lapidot I, Rich DH, Kapelushnik J, Mordechai S, Salman A, Huleihel M. Diagnosis of inaccessible infections using infrared microscopy of white blood cells and machine learning algorithms. Analyst 2020; 145:6955-6967. [PMID: 32852502 DOI: 10.1039/d0an00752h] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Physicians diagnose subjectively the etiology of inaccessible infections where sampling is not feasible (such as, pneumonia, sinusitis, cholecystitis, peritonitis), as bacterial or viral. The diagnosis is based on their experience with some medical markers like blood counts and medical symptoms since it is harder to obtain swabs and reliable laboratory results for most cases. In this study, infrared spectroscopy with machine learning algorithms was used for the rapid and objective diagnosis of the etiology of inaccessible infections and enables an assessment of the error for the subjective diagnosis of the etiology of these infections by physicians. Our approach allows for diagnoses of the etiology of both accessible and inaccessible infections as based on an analysis of the innate immune system response through infrared spectroscopy measurements of white blood cell (WBC) samples. In the present study, we examined 343 individuals involving 113 controls, 89 inaccessible bacterial infections, 54 accessible bacterial infections, 60 inaccessible viral infections, and 27 accessible viral infections. Using our approach, the results show that it is possible to differentiate between controls and infections (combined bacterial and viral) with 95% accuracy, and enabling the diagnosis of the etiology of accessible infections as bacterial or viral with >94% sensitivity and > 90% specificity within one hour after the collection of the blood sample with error rate <6%. Based on our approach, the error rate of the physicians' subjective diagnosis of the etiology of inaccessible infections was found to be >23%.
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Affiliation(s)
- Adam H Agbaria
- Department of Physics, Ben-Gurion University, Beer-Sheva 84105, Israel
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18
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Iakab SA, Sementé L, García-Altares M, Correig X, Ràfols P. Raman2imzML converts Raman imaging data into the standard mass spectrometry imaging format. BMC Bioinformatics 2020; 21:448. [PMID: 33036551 PMCID: PMC7547406 DOI: 10.1186/s12859-020-03789-8] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2020] [Accepted: 09/29/2020] [Indexed: 12/21/2022] Open
Abstract
BACKGROUND Multimodal imaging that combines mass spectrometry imaging (MSI) with Raman imaging is a rapidly developing multidisciplinary analytical method used by a growing number of research groups. Computational tools that can visualize and aid the analysis of datasets by both techniques are in demand. RESULTS Raman2imzML was developed as an open-source converter that transforms Raman imaging data into imzML, a standardized common data format created and adopted by the mass spectrometry community. We successfully converted Raman datasets to imzML and visualized Raman images using open-source software designed for MSI applications. CONCLUSION Raman2imzML enables both MSI and Raman images to be visualized using the same file format and the same software for a straightforward exploratory imaging analysis.
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Affiliation(s)
- Stefania Alexandra Iakab
- Department of Electronic Engineering, Rovira i Virgili University, 43007, Tarragona, Spain.,Spanish Biomedical Research Centre in Diabetes and Associated Metabolic Disorders (CIBERDEM), 28029, Madrid, Spain
| | - Lluc Sementé
- Department of Electronic Engineering, Rovira i Virgili University, 43007, Tarragona, Spain
| | - María García-Altares
- Department of Electronic Engineering, Rovira i Virgili University, 43007, Tarragona, Spain. .,Spanish Biomedical Research Centre in Diabetes and Associated Metabolic Disorders (CIBERDEM), 28029, Madrid, Spain.
| | - Xavier Correig
- Department of Electronic Engineering, Rovira i Virgili University, 43007, Tarragona, Spain.,Spanish Biomedical Research Centre in Diabetes and Associated Metabolic Disorders (CIBERDEM), 28029, Madrid, Spain.,Institut d'Investigació Sanitària Pere Virgili, Tarragona, Spain
| | - Pere Ràfols
- Department of Electronic Engineering, Rovira i Virgili University, 43007, Tarragona, Spain
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19
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Kong D, Peng W, Zong R, Cui G, Yu X. Morphological and Biochemical Properties of Human Astrocytes, Microglia, Glioma, and Glioblastoma Cells Using Fourier Transform Infrared Spectroscopy. Med Sci Monit 2020; 26:e925754. [PMID: 33077704 PMCID: PMC7552879 DOI: 10.12659/msm.925754] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND With infiltration, high-grade glioma easily causes the boundary between tumor tissue and adjacent tissue to become unclear and results in tumor recurrence at or near the resection margin according to the incomplete surgical resection. Fourier transform infrared spectroscopy (FTIR) technique has been demonstrated to be a useful tool that yields a molecular fingerprint and provides rapid, nondestructive, high-throughput and clinically relevant diagnostic information. MATERIAL AND METHODS FTIR was used to investigate the morphological and biochemical properties of human astrocytes (HA), microglia (HM1900), glioma cells (U87), and glioblastoma cells (BT325) cultured in vitro to simulate the infiltration area, with the use of multi-peak fitting and principal component analysis (PCA) of amide I of FTIR spectra and the use of hierarchical cluster analysis (HCA). RESULTS We found that the secondary structures of the 4 types of cells were significantly different. The contents of a-helix structure in glial cells was significantly higher than in the glioma cells, but the levels of ß-sheet, ß-turn, and random coil structures were lower. The 4 types of cells could be clearly separated with 85% for PC1 and 12.2% for PC2. CONCLUSIONS FTIR can be used to distinguish between human astrocytes, microglia, glioma, and glioblastoma cells in vitro. The protein secondary structure can be used as an indicator to distinguish tumor cells from glial cells. Further tissue-based and in vivo studies are needed to determine whether FTIR can identify cerebral glioma.
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Affiliation(s)
- Dongsheng Kong
- Department of Neurosurgery, Chinese People's Liberation Army (PLA) General Hospital, Beijing, China (mainland)
| | - Wenyu Peng
- Science and Technology on High Power Microwave Laboratory, Northwest Institute of Nuclear Technology, Xi'an, China (mainland)
| | - Rui Zong
- Department of Neurosurgery, Chinese People's Liberation Army (PLA) General Hospital, Beijing, China (mainland)
| | - Gangqiang Cui
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, China (mainland)
| | - Xinguang Yu
- Department of Neurosurgery, Chinese People's Liberation Army (PLA) General Hospital, Beijing, China (mainland)
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20
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Pathmasiri KC, Pergande MR, Tobias F, Rebiai R, Rosenhouse-Dantsker A, Bongarzone ER, Cologna SM. Mass spectrometry imaging and LC/MS reveal decreased cerebellar phosphoinositides in Niemann-Pick type C1-null mice. J Lipid Res 2020; 61:1004-1013. [PMID: 32371566 DOI: 10.1194/jlr.ra119000606] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2019] [Revised: 04/21/2020] [Indexed: 12/18/2022] Open
Abstract
Niemann-Pick disease type C1 (NPC1) is a lipid storage disorder in which cholesterol and glycosphingolipids accumulate in late endosomal/lysosomal compartments because of mutations in the NPC1 gene. A hallmark of NPC1 is progressive neurodegeneration of the cerebellum as well as visceral organ damage; however, the mechanisms driving this disease pathology are not fully understood. Phosphoinositides are phospholipids that play distinct roles in signal transduction and vesicle trafficking. Here, we utilized a consensus spectra analysis of MS imaging data sets and orthogonal LC/MS analyses to evaluate the spatial distribution of phosphoinositides and quantify them in cerebellar tissue from Npc1-null mice. Our results suggest significant depletion of multiple phosphoinositide species, including PI, PIP, and PIP2, in the cerebellum of the Npc1-null mice in both whole-tissue lysates and myelin-enriched fractions. Additionally, we observed altered levels of the regulatory enzyme phosphatidylinositol 4-kinase type 2α in Npc1-null mice. In contrast, the levels of related kinases, phosphatases, and transfer proteins were unaltered in the Npc1-null mouse model, as observed by Western blot analysis. Our discovery of phosphoinositide lipid biomarkers for NPC1 opens new perspectives on the pathophysiology underlying this fatal neurodegenerative disease.
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Affiliation(s)
| | | | - Fernando Tobias
- Department of Chemistry, University of Illinois at Chicago, Chicago, IL
| | - Rima Rebiai
- Laboratory of Integrated Neuroscience, University of Illinois at Chicago, Chicago, IL; Department of Anatomy and Cell Biology, University of Illinois at Chicago, Chicago, IL
| | | | - Ernesto R Bongarzone
- Department of Anatomy and Cell Biology, University of Illinois at Chicago, Chicago, IL
| | - Stephanie M Cologna
- Department of Chemistry, University of Illinois at Chicago, Chicago, IL; Laboratory of Integrated Neuroscience, University of Illinois at Chicago, Chicago, IL. mailto:
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21
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Molecule Sensitive Optical Imaging and Monitoring Techniques-A Review of Applications in Micro-Process Engineering. MICROMACHINES 2020; 11:mi11040353. [PMID: 32231076 PMCID: PMC7230497 DOI: 10.3390/mi11040353] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/24/2020] [Revised: 03/23/2020] [Accepted: 03/25/2020] [Indexed: 01/21/2023]
Abstract
This paper provides an overview of how molecule-sensitive, spatially-resolved technologies can be applied for monitoring and measuring in microchannels. The principles of elastic light scattering, fluorescence, near-infrared, mid-infrared, and Raman imaging, as well as combination techniques, are briefly presented, and their advantages and disadvantages are explained. With optical methods, images can be acquired both scanning and simultaneously as a complete image. Scanning technologies require more acquisition time, and fast moving processes are not easily observable. On the other hand, molecular selectivity is very high, especially in Raman and mid-infrared (MIR) scanning. For near-infrared (NIR) images, the entire measuring range can be simultaneously recorded with indium gallium arsenide (InGaAs) cameras. However, in this wavelength range, water is the dominant molecule, so it is sometimes necessary to use complex learning algorithms that increase the preparation effort before the actual measurement. These technologies excite molecular vibrations in a variety of ways, making these methods suitable for specific products. Besides measurements of the fluid composition, technologies for particle detection are of additional importance. With scattered light techniques and evaluation according to the Mie theory, particles in the range of 0.2–1 µm can be detected, and fast growth processes can be observed. Local multispectral measurements can also be carried out with fiber optic-coupled systems through small probe heads of approximately 1 mm diameter.
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22
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Agbaria AH, Rosen GB, Lapidot I, Rich DH, Mordechai S, Kapelushnik J, Huleihel M, Salman A. Rapid diagnosis of infection etiology in febrile pediatric oncology patients using infrared spectroscopy of leukocytes. JOURNAL OF BIOPHOTONICS 2020; 13:e201900215. [PMID: 31566906 DOI: 10.1002/jbio.201900215] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/31/2019] [Revised: 08/27/2019] [Accepted: 09/15/2019] [Indexed: 06/10/2023]
Abstract
Rapid diagnosis of the etiology of infection is highly important for an effective treatment of the infected patients. Bacterial and viral infections are serious diseases that can cause death in many cases. The human immune system deals with many viral and bacterial infections that cause no symptoms and pass quietly without treatment. However, oncology patients undergoing chemotherapy have a very weak immune system caused by leukopenia, and even minor pathogen infection threatens their lives. For this reason, physicians tend to prescribe immediately several types of antibiotics for febrile pediatric oncology patients (FPOPs). Uncontrolled use of antibiotics is one of the major contributors to the development of resistant bacteria. Therefore, for oncology patients, a rapid and objective diagnosis of the etiology of the infection is extremely critical. Current identification methods are time-consuming (>24 h). In this study, the potential of midinfrared spectroscopy in tandem with machine learning algorithms is evaluated for rapid and objective diagnosis of the etiology of infections in FPOPs using simple peripheral blood samples. Our results show that infrared spectroscopy enables the diagnosis of the etiology of infection as bacterial or viral within 70 minutes after the collection of the blood sample with 93% sensitivity and 88% specificity.
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Affiliation(s)
- Adam H Agbaria
- Department of Physics, Ben-Gurion University, Beer-Sheva, Israel
| | - Guy Beck Rosen
- Department of Hematology, Soroka University Medical Center, Beer-Sheva, Israel
| | - Itshak Lapidot
- Department of Electrical and Electronics Engineering, ACLP-Afeka Center for Language Processing, Afeka Tel-Aviv Academic College of Engineering, Tel-Aviv, Israel
| | - Daniel H Rich
- Department of Physics, Ben-Gurion University, Beer-Sheva, Israel
| | - Shaul Mordechai
- Department of Physics, Ben-Gurion University, Beer-Sheva, Israel
| | - Joseph Kapelushnik
- Department of Hematology, Soroka University Medical Center, Beer-Sheva, Israel
| | - Mahmoud Huleihel
- Department of Microbiology, Immunology and Genetics, Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer-Sheva, Israel
| | - Ahmad Salman
- Department of Physics, SCE-Sami Shamoon College of Engineering, Beer-Sheva, Israel
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23
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Kümmel T, Teumer T, Dörnhofer P, Methner FJ, Wängler B, Rädle M. Contrast enhancement of surface layers with fast middle-infrared scanning. Heliyon 2019; 5:e02442. [PMID: 31528751 PMCID: PMC6742858 DOI: 10.1016/j.heliyon.2019.e02442] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2019] [Revised: 07/19/2019] [Accepted: 09/04/2019] [Indexed: 11/16/2022] Open
Abstract
In this study, we present an efficient and innovative method to visualize absorption differences in the mid-infrared range with spatial resolution using laser technology. We focus on only two lasers with wavelengths between 3.4 μm and 3.6 μm and a spatial resolution of 20 μm and thus achieve a scanning speed up to 300 kS/s for fast image generation. In this article, we focus especially on the detection of C–H bands in this region of the absorption spectrum. Concealed structures are examined by calculating the measured structures with both wavelengths. In our results, we demonstrate exemplary measurements on 130-μm-thick polyvinyl chloride layers. In turn, these structures are suitable for further processing in rapid quantitative quality control.
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Affiliation(s)
- Tim Kümmel
- Center for Mass Spectrometry and Optical Spectroscopy, Mannheim University of Applied Sciences, Paul-Wittsack-Str. 10, Mannheim, 68163, Germany.,University of Heidelberg, Medical Faculty Mannheim, Theodor-Kutzer-Ufer 1-3, Mannheim, 68167, Germany
| | - Tobias Teumer
- Center for Mass Spectrometry and Optical Spectroscopy, Mannheim University of Applied Sciences, Paul-Wittsack-Str. 10, Mannheim, 68163, Germany.,Institute of Food Technology and Food Chemistry, Technische Universität Berlin, Seestraße 13, Berlin, 13353, Germany
| | - Patrick Dörnhofer
- Center for Mass Spectrometry and Optical Spectroscopy, Mannheim University of Applied Sciences, Paul-Wittsack-Str. 10, Mannheim, 68163, Germany
| | - Frank-Jürgen Methner
- Institute of Food Technology and Food Chemistry, Technische Universität Berlin, Seestraße 13, Berlin, 13353, Germany
| | - Björn Wängler
- University of Heidelberg, Medical Faculty Mannheim, Theodor-Kutzer-Ufer 1-3, Mannheim, 68167, Germany
| | - Matthias Rädle
- Center for Mass Spectrometry and Optical Spectroscopy, Mannheim University of Applied Sciences, Paul-Wittsack-Str. 10, Mannheim, 68163, Germany
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24
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Schmitt ND, Rawlins CM, Randall EC, Wang X, Koller A, Auclair JR, Kowalski JM, Kowalski PJ, Luther E, Ivanov AR, Agar NY, Agar JN. Genetically Encoded Fluorescent Proteins Enable High-Throughput Assignment of Cell Cohorts Directly from MALDI-MS Images. Anal Chem 2019; 91:3810-3817. [PMID: 30839199 PMCID: PMC6827431 DOI: 10.1021/acs.analchem.8b03454] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) provides a unique in situ chemical profile that can include drugs, nucleic acids, metabolites, lipids, and proteins. MSI of individual cells (of a known cell type) affords a unique insight into normal and disease-related processes and is a prerequisite for combining the results of MSI and other single-cell modalities (e.g. mass cytometry and next-generation sequencing). Technological barriers have prevented the high-throughput assignment of MSI spectra from solid tissue preparations to their cell type. These barriers include obtaining a suitable cell-identifying image (e.g. immunohistochemistry) and obtaining sufficiently accurate registration of the cell-identifying and MALDI-MS images. This study introduces a technique that overcame these barriers by assigning cell type directly from mass spectra. We hypothesized that, in MSI from mice with a defined fluorescent protein expression pattern, the fluorescent protein's molecular ion could be used to identify cell cohorts. A method was developed for the purification of enhanced yellow fluorescent protein (EYFP) from mice. To determine EYFP's molecular mass for MSI studies, we performed intact mass analysis and characterized the protein's primary structure and post-translational modifications through various techniques. MALDI-MSI methods were developed to enhance the detection of EYFP in situ, and by extraction of EYFP's molecular ion from MALDI-MS images, automated, whole-image assignment of cell cohorts was achieved. This method was validated using a well-characterized mouse line that expresses EYFP in motor and sensory neurons and should be applicable to hundreds of commercially available mice (and other animal) strains comprising a multitude of cell-specific fluorescent labels.
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Affiliation(s)
- Nicholas D. Schmitt
- Department of Chemistry and Chemical Biology, and Barnett Institute of Chemical and Biological Analysis, Northeastern University, Boston, MA, 02115, USA
- These authors contributed equally to this work
| | - Catherine M. Rawlins
- Department of Chemistry and Chemical Biology, and Barnett Institute of Chemical and Biological Analysis, Northeastern University, Boston, MA, 02115, USA
- These authors contributed equally to this work
| | - Elizabeth C. Randall
- Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, 02115, USA
| | - Xianzhe Wang
- Department of Chemistry and Chemical Biology, and Barnett Institute of Chemical and Biological Analysis, Northeastern University, Boston, MA, 02115, USA
| | - Antonius Koller
- Department of Chemistry and Chemical Biology, and Barnett Institute of Chemical and Biological Analysis, Northeastern University, Boston, MA, 02115, USA
| | - Jared R. Auclair
- Department of Chemistry and Chemical Biology, and Barnett Institute of Chemical and Biological Analysis, Northeastern University, Boston, MA, 02115, USA
- Biopharmaceutical Analysis Training Laboratory (BATL), Northeastern University Innovation Campus, Burlington, MA, 01803, USA
| | | | | | - Ed Luther
- Department of Pharmaceutical Sciences, Northeastern University, Boston, MA, 02115, USA
| | - Alexander R. Ivanov
- Department of Chemistry and Chemical Biology, and Barnett Institute of Chemical and Biological Analysis, Northeastern University, Boston, MA, 02115, USA
| | - Nathalie Y.R. Agar
- Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, 02115, USA
- Department of Neurosurgery, Brigham and Women’s Hospital, Department of Cancer Biology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, 02115, USA
| | - Jeffrey N. Agar
- Department of Chemistry and Chemical Biology, and Barnett Institute of Chemical and Biological Analysis, Northeastern University, Boston, MA, 02115, USA
- Department of Pharmaceutical Sciences, Northeastern University, Boston, MA, 02115, USA
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25
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Schulz S, Becker M, Groseclose MR, Schadt S, Hopf C. Advanced MALDI mass spectrometry imaging in pharmaceutical research and drug development. Curr Opin Biotechnol 2019; 55:51-59. [DOI: 10.1016/j.copbio.2018.08.003] [Citation(s) in RCA: 115] [Impact Index Per Article: 23.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2018] [Revised: 07/21/2018] [Accepted: 08/03/2018] [Indexed: 12/20/2022]
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26
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Comparato Filho OO, Morais FV, Bhattacharjee T, Castilho ML, Raniero L. Rapid identification of Paracoccidioides lutzii and P. Brasiliensis using Fourier Transform Infrared spectroscopy. J Mol Struct 2019. [DOI: 10.1016/j.molstruc.2018.09.016] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
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27
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Xu G, Li J. Recent advances in mass spectrometry imaging for multiomics application in neurology. J Comp Neurol 2018; 527:2158-2169. [DOI: 10.1002/cne.24571] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2018] [Revised: 10/14/2018] [Accepted: 10/24/2018] [Indexed: 12/12/2022]
Affiliation(s)
- Guang Xu
- Hubei Education Cloud Service Engineering Technology Research CenterHubei University of Education Wuhan China
| | - Jianjun Li
- Human Health TherapeuticsNational Research Council Canada Ottawa Ontario
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28
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Patterson NH, Tuck M, Lewis A, Kaushansky A, Norris JL, Van de Plas R, Caprioli RM. Next Generation Histology-Directed Imaging Mass Spectrometry Driven by Autofluorescence Microscopy. Anal Chem 2018; 90:12404-12413. [PMID: 30274514 DOI: 10.1021/acs.analchem.8b02885] [Citation(s) in RCA: 36] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
Abstract
Histology-directed imaging mass spectrometry (IMS) is a spatially targeted IMS acquisition method informed by expert annotation that provides rapid molecular characterization of select tissue structures. The expert annotations are usually determined on digital whole slide images of histological stains where the staining preparation is incompatible with optimal IMS preparation, necessitating serial sections: one for annotation, one for IMS. Registration is then used to align staining annotations onto the IMS tissue section. Herein, we report a next-generation histology-directed platform implementing IMS-compatible autofluorescence (AF) microscopy taken prior to any staining or IMS. The platform enables two histology-directed workflows, one that improves the registration process between two separate tissue sections using automated, computational monomodal AF-to-AF microscopy image registration, and a registration-free approach that utilizes AF directly to identify ROIs and acquire IMS on the same section. The registration approach is fully automated and delivers state of the art accuracy in histology-directed workflows for transfer of annotations (∼3-10 μm based on 4 organs from 2 species) while the direct AF approach is registration-free, allowing targeting of the finest structures visible by AF microscopy. We demonstrate the platform in biologically relevant case studies of liver stage malaria and human kidney disease with spatially targeted acquisition of sparsely distributed (composing less than one tenth of 1% of the tissue section area) malaria infected mouse hepatocytes and glomeruli in the human kidney case study.
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Affiliation(s)
| | | | - Adam Lewis
- Center for Infectious Disease Research , formerly Seattle Biomedical Research Institute, Seattle , Washington 98109 , United States.,Department of Global Health , University of Washington , Seattle , Washington 98195 , United States
| | - Alexis Kaushansky
- Center for Infectious Disease Research , formerly Seattle Biomedical Research Institute, Seattle , Washington 98109 , United States.,Department of Global Health , University of Washington , Seattle , Washington 98195 , United States
| | | | - Raf Van de Plas
- Delft Center for Systems and Control (DCSC) , Delft University of Technology , 2628 CD , Delft , The Netherlands
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29
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Tobias F, Olson MT, Cologna SM. Mass spectrometry imaging of lipids: untargeted consensus spectra reveal spatial distributions in Niemann-Pick disease type C1. J Lipid Res 2018; 59:2446-2455. [PMID: 30266834 DOI: 10.1194/jlr.d086090] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2018] [Revised: 09/24/2018] [Indexed: 12/12/2022] Open
Abstract
Mass spectrometry imaging (MSI) is a tool to rapidly map the spatial location of analytes without the need for tagging or a reporter system. Niemann-Pick disease type C1 (NPC1) is a neurodegenerative, lysosomal storage disorder characterized by accumulation of unesterified cholesterol and sphingolipids in the endo-lysosomal system. Here, we use MSI to visualize lipids including cholesterol in cerebellar brain tissue from the NPC1 symptomatic mouse model and unaffected controls. To complement the imaging studies, a data-processing pipeline was developed to generate consensus mass spectra, thereby using both technical and biological image replicates to assess differences. The consensus spectra are used to determine true differences in lipid relative abundance; lipid distributions can be determined in an unbiased fashion without prior knowledge of location. We show the cerebellar distribution of gangliosides GM1, GM2, and GM3, including variants of lipid chain length. We also performed MALDI-MSI of cholesterol. Further analysis of lobules IV/V and X of the cerebellum gangliosides indicates regional differences. The specificity achieved highlights the power of MSI, and this new workflow demonstrates a universal approach for addressing reproducibility in imaging experiments applied to NPC1.
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Affiliation(s)
- Fernando Tobias
- Department of Chemistry University of Illinois at Chicago, Chicago, IL 60607
| | - Matthew T Olson
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Jacksonville, FL 32224
| | - Stephanie M Cologna
- Department of Chemistry University of Illinois at Chicago, Chicago, IL 60607 .,Laboratory of Integrative Neuroscience, University of Illinois at Chicago, Chicago, IL 60607
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