Dataset Information

Optimization of Zebrafish Larvae Sectioning for Mass Spectrometry Imaging.

ABSTRACT: The utility of zebrafish is becoming more frequent due to lower costs and high similarities to humans. Zebrafish larvae are attractive subjects for drug screening and drug metabolism research. However, obtaining good quality zebrafish larvae sections for batch samples at designated planes, angles, and locations for comparison purposes is a challenging task. We report here the optimization of fresh frozen zebrafish larvae sectioning for mass spectrometry imaging. We utilized the gelatin solutions that were created at two different temperatures (50 and 85 °C) as embedding media. Gelatin-50 (gelatin created under 50 °C, solid gel under room temperature) was used to make a larvae-shaped mold and gelatin-85 (gelatin created under 85 °C, liquid under room temperature) was used to embed the larvae. H&E staining of sections shows well-preserved morphology and minimal histological interference. More importantly, the position of the larvae was well controlled resulting in more consistent sectioning of the larvae.

SUBMITTER: Yang J

PROVIDER: S-EPMC9608760 | biostudies-literature | 2022 Oct

REPOSITORIES: biostudies-literature

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Optimization of Zebrafish Larvae Sectioning for Mass Spectrometry Imaging.

Yang Junhai J Rendino Lauren L Cassar Steven S Buck Wayne W Sawicki James J Talaty Nari N Wagner David D

Pharmaceuticals (Basel, Switzerland) 20221007 10

The utility of zebrafish is becoming more frequent due to lower costs and high similarities to humans. Zebrafish larvae are attractive subjects for drug screening and drug metabolism research. However, obtaining good quality zebrafish larvae sections for batch samples at designated planes, angles, and locations for comparison purposes is a challenging task. We report here the optimization of fresh frozen zebrafish larvae sectioning for mass spectrometry imaging. We utilized the gelatin solutions ...[more]

PMID: 36297342

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Project description:Transcriptomic studies have attempted to classify glioblastoma (GB) into subtypes that predict survival and that have different therapeutic vulnerabilities. Here we identified three metabolic subtypes: glycolytic, oxidative and a mixed glycolytic/oxidative by mass spectrometry imaging of rapidly excised tumour sections from two GB patients infused with [U-13C]glucose and from spatial transcriptomic analysis of contiguous sections. The phenotypes did not correlate with microenvironmental features, including proliferation rate, immune cell infiltration, and vascularisation, were retained when patient-derived cells were grown in vitro, or as orthotopically implanted xenografts, and were robust to changes in oxygen concentration, demonstrating their cell intrinsic nature. The spatial extent of the regions occupied by cells displaying these distinct metabolic phenotypes are large enough to be detected using clinically applicable metabolic imaging techniques. A limitation of the study is that it is based on only two patient tumours, albeit on multiple sections, and therefore represents a proof-of-concept study. Glioblastoma is the most common primary adult brain cancer. Transcriptomic analyses have attempted to classify GB into subtypes that could predict treatment response, with a recent study that used a pathway-based classification defining metabolism-associated subtypes with distinct therapeutic vulnerabilities. These included a mitochondrial subtype, which is associated with a more favourable clinical outcome and that is sensitive to inhibitors of oxidative phosphorylation, and a glycolytic/plurimetabolic subtype that is resistant to multiple treatment types. An important question is the extent to which the metabolism displayed by tumour cells in vivo are cell intrinsic and how much they are defined by the tumour microenvironment. We have addressed this question using mass spectrometry imaging of rapidly excised tumour sections from GB patients infused with [U-13C]glucose immediately prior to surgery to image tumour cell metabolic fluxes in vivo and from a spatial transcriptomic analysis of adjacent sections. To our knowledge, this is the first report demonstrating high resolution imaging of metabolic fluxes in a human tumour in vivo.

Dataset Information

Optimization of Zebrafish Larvae Sectioning for Mass Spectrometry Imaging.

Publications

Optimization of Zebrafish Larvae Sectioning for Mass Spectrometry Imaging.

Similar Datasets

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