Approaches to increasing analytical throughput of human samples with multi‐isotope imaging mass spectrometry
Year: 2014
Type: article
Abstract: Multi‐isotope imaging mass spectrometry (MIMS) combines stable isotope tracers with the quantitative imaging of NanoSIMS ion microscopy. With extensive safety precedent, use of stable isotopes in MIMS applications opens the possibility of studying a wide array of biological questions in humans. Here we describe a series of approaches to increase the effective analytical throughput for detecting rare nuclear labeling events with MIMS. At the level of sample preparation, cells in suspension were smeared at high density or pelleted cells were embedded and sectioned to reach nuclear depth. Presputtering conditions were optimized for each cell type to ensure the reproducible sampling of nuclei. Adipose tissue posed a different challenge as the large volume of adipocytes results in an obligatorily low density of nuclei in any given plane. Before introducing samples to the NanoSIMS instrument, all nuclei were fluorescently stained and imaged, and their coordinates were recorded, allowing automated analysis of fields that contained at least one nucleus and therefore minimizing analysis of dead space. These data emphasize unique challenges posed by human studies, where both ethical and practical issues may limit the administration of stable isotope labels for prolonged periods of time as may be necessary to achieve high labeling frequencies in cells that divide infrequently. Copyright © 2014 John Wiley & Sons, Ltd.
Source: Surface and Interface Analysis
DOI: 10.1002/sia.5580
Institutions: Brigham and Women's Hospital, Harvard University
Language: English
Subfield: Computational Mechanics
Field: Engineering
Domain: Physical Sciences
Open Access status: green
Awards: G2014571086, National Resource for Imaging Mass Spectrometry, NanoSIMS 50L Ion Micro-Analyzer, Neural stem cells in the aging brain, Cell fate and tissue turnover in the aged studied with multi-isotope imaging mass, National Resource for Imaging Mass Spectrometry, G776136168, Cardiomyocyte Lineage and Turnover by Metabolic Fate-Mapping
OpenAlex ID: W2117001676
