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Histology-Compatible MALDI Mass Spectrometry Based Imaging of Neuronal Lipids for Subsequent Immunofluorescent Staining.
KayaHistology.pdf - ["content_typename_Accepted version" not defined]
Restricted to Access restricted until 21 March 2018.
Matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI-IMS) enables acquisition of spatial distribution maps for molecular species in situ. This can provide comprehensive insights on the pathophysiology of different diseases. However, current sample preparation and MALDI-IMS acquisition methods have limitations in preserving molecular and histological tissue morphology, resulting in interfered correspondence of MALDI-IMS data with subsequently acquired immunofluorescent staining results. We here investigated the histology compatibility of MALDI-IMS to image neuronal lipids in rodent brain tissue with subsequent immunohistochemistry and fluorescent staining of histological features. This was achieved by sublimation of a low ionization energy matrix compound, 1,5-diaminonapthalene (1,5-DAN), minimizing the number of low-energy laser shots. This yielded improved lipid spectral quality and speed of data acquisition and reduced matrix cluster formation along with preservation of specific histological information at cellular levels. This gentle, histology-compatible MALDI-IMS protocol also diminished thermal effects and mechanical stress created during nanosecond laser ablation processes that were prominent in subsequent immunofluorescent staining images but not with classical hematoxylin and eosin (H&E) staining on the same tissue section. Furthermore, this methodology proved to be a powerful strategy for investigating β-amyloid (Aβ) plaque-associated neuronal lipids as exemplified by performing high-resolution MALDI-IMS with subsequent fluorescent amyloid staining in a transgenic mouse model of Alzheimer's disease (tgSwe).
|Title:||Histology-Compatible MALDI Mass Spectrometry Based Imaging of Neuronal Lipids for Subsequent Immunofluorescent Staining.|
|Additional information:||This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.|
|UCL classification:||UCL > School of Life and Medical Sciences
UCL > School of Life and Medical Sciences > Faculty of Brain Sciences
UCL > School of Life and Medical Sciences > Faculty of Brain Sciences > Institute of Neurology
UCL > School of Life and Medical Sciences > Faculty of Brain Sciences > Institute of Neurology > Molecular Neuroscience
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