Literature DB >> 30274514

Next Generation Histology-Directed Imaging Mass Spectrometry Driven by Autofluorescence Microscopy.

Nathan Heath Patterson, Michael Tuck, Adam Lewis1,2, Alexis Kaushansky1,2, Jeremy L Norris, Raf Van de Plas3, Richard M Caprioli.   

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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Year:  2018        PMID: 30274514      PMCID: PMC6309458          DOI: 10.1021/acs.analchem.8b02885

Source DB:  PubMed          Journal:  Anal Chem        ISSN: 0003-2700            Impact factor:   6.986


  31 in total

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2.  Mass Spectrometry Imaging Can Distinguish on a Proteomic Level Between Proliferative Nodules Within a Benign Congenital Nevus and Malignant Melanoma.

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3.  Sublimation of new matrix candidates for high spatial resolution imaging mass spectrometry of lipids: enhanced information in both positive and negative polarities after 1,5-diaminonapthalene deposition.

Authors:  Aurélien Thomas; Jade Laveaux Charbonneau; Erik Fournaise; Pierre Chaurand
Journal:  Anal Chem       Date:  2012-02-08       Impact factor: 6.986

Review 4.  Selection and refinement: the malaria parasite's infection and exploitation of host hepatocytes.

Authors:  Alexis Kaushansky; Stefan Hi Kappe
Journal:  Curr Opin Microbiol       Date:  2015-06-21       Impact factor: 7.934

5.  Monitoring time-dependent degradation of phospholipids in sectioned tissues by MALDI imaging mass spectrometry.

Authors:  Nathan Heath Patterson; Aurélien Thomas; Pierre Chaurand
Journal:  J Mass Spectrom       Date:  2014-07       Impact factor: 1.982

6.  Molecular imaging of biological samples: localization of peptides and proteins using MALDI-TOF MS.

Authors:  R M Caprioli; T B Farmer; J Gile
Journal:  Anal Chem       Date:  1997-12-01       Impact factor: 6.986

7.  Invasive mucinous cystic neoplasms of the pancreas.

Authors:  Michael L Baker; E Scott Seeley; Reetesh Pai; Arief A Suriawinata; Mari Mino-Kenudson; Giuseppe Zamboni; Günter Klöppel; Daniel S Longnecker
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8.  Histology-Guided High-Resolution Matrix-Assisted Laser Desorption Ionization Mass Spectrometry Imaging.

Authors:  Bram Heijs; Walid M Abdelmoula; Sha Lou; Inge H Briaire-de Bruijn; Jouke Dijkstra; Judith V M G Bovée; Liam A McDonnell
Journal:  Anal Chem       Date:  2015-12-04       Impact factor: 6.986

9.  Diagnosis of tumors during tissue-conserving surgery with integrated autofluorescence and Raman scattering microscopy.

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10.  Image fusion of mass spectrometry and microscopy: a multimodality paradigm for molecular tissue mapping.

Authors:  Raf Van de Plas; Junhai Yang; Jeffrey Spraggins; Richard M Caprioli
Journal:  Nat Methods       Date:  2015-02-23       Impact factor: 28.547

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  20 in total

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Authors:  Richard M Caprioli
Journal:  J Biomol Tech       Date:  2019-04

2.  Single-Cell Metabolomics by Mass Spectrometry Imaging.

Authors:  Maria Emilia Dueñas; Young Jin Lee
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Review 3.  Unsupervised machine learning for exploratory data analysis in imaging mass spectrometry.

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Journal:  Mass Spectrom Rev       Date:  2019-10-11       Impact factor: 10.946

4.  MicroLESA: Integrating Autofluorescence Microscopy, In Situ Micro-Digestions, and Liquid Extraction Surface Analysis for High Spatial Resolution Targeted Proteomic Studies.

Authors:  Daniel J Ryan; Nathan Heath Patterson; Nicole E Putnam; Aimee D Wilde; Andy Weiss; William J Perry; James E Cassat; Eric P Skaar; Richard M Caprioli; Jeffrey M Spraggins
Journal:  Anal Chem       Date:  2019-05-31       Impact factor: 6.986

5.  Response Surface Methodology As a New Approach for Finding Optimal MALDI Matrix Spraying Parameters for Mass Spectrometry Imaging.

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Journal:  J Am Soc Mass Spectrom       Date:  2020-02-06       Impact factor: 3.109

6.  Discovering New Lipidomic Features Using Cell Type Specific Fluorophore Expression to Provide Spatial and Biological Specificity in a Multimodal Workflow with MALDI Imaging Mass Spectrometry.

Authors:  Marissa A Jones; Sung Hoon Cho; Nathan Heath Patterson; Raf Van de Plas; Jeffrey M Spraggins; Mark R Boothby; Richard M Caprioli
Journal:  Anal Chem       Date:  2020-05-06       Impact factor: 6.986

Review 7.  Integrated molecular imaging technologies for investigation of metals in biological systems: A brief review.

Authors:  William J Perry; Andy Weiss; Raf Van de Plas; Jeffrey M Spraggins; Richard M Caprioli; Eric P Skaar
Journal:  Curr Opin Chem Biol       Date:  2020-02-19       Impact factor: 8.822

Review 8.  ADVANCES IN HIGH-RESOLUTION MALDI MASS SPECTROMETRY FOR NEUROBIOLOGY.

Authors:  Kellen DeLaney; Ashley Phetsanthad; Lingjun Li
Journal:  Mass Spectrom Rev       Date:  2020-11-09       Impact factor: 10.946

9.  massNet: integrated processing and classification of spatially resolved mass spectrometry data using deep learning for rapid tumor delineation.

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10.  Diagnosis of melanoma by imaging mass spectrometry: Development and validation of a melanoma prediction model.

Authors:  Rami N Al-Rohil; Jessica L Moore; Nathan Heath Patterson; Sarah Nicholson; Nico Verbeeck; Marc Claesen; Jameelah Z Muhammad; Richard M Caprioli; Jeremy L Norris; Sara Kantrow; Margaret Compton; Jason Robbins; Ahmed K Alomari
Journal:  J Cutan Pathol       Date:  2021-07-02       Impact factor: 1.587

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