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A Co-Culture-Based Multiparametric Imaging Technique to Dissect Local H2O2 Signals with Targeted HyPer7.

  • M Secilmis
  • , HY Altun
  • , Johannes Pilic
  • , Yusuf Ceyhun Erdogan
  • , Z Cokluk
  • , BN Ata
  • , G Sevimli
  • , AG Zaki
  • , EN Yigit
  • , G Öztürk
  • , Roland Malli* (Last author)
  • , Emrah EROGLU* (Last author)
  • *Corresponding author for this work

Research output: Contribution to journalResearch article

13 Citations (Web of Science)

Abstract

Multispectral live-cell imaging is an informative approach that permits detecting biological processes simultaneously in the spatial and temporal domain by exploiting spectrally distinct biosensors. However, the combination of fluorescent biosensors with distinct spectral properties such as different sensitivities, and dynamic ranges can undermine accurate co-imaging of the same analyte in different subcellular locales. We advanced a single-color multiparametric imaging method, which allows simultaneous detection of hydrogen peroxide (H2O2) in multiple cell locales (nucleus, cytosol, mitochondria) using the H2O2 biosensor HyPer7. Co-culturing of endothelial cells stably expressing differentially targeted HyPer7 biosensors paved the way for co-imaging compartmentalized H2O2 signals simultaneously in neighboring cells in a single experimental setup. We termed this approach COMPARE IT, which is an acronym for co-culture-based multiparametric imaging technique. Employing this approach, we detected lower H2O2 levels in mitochondria of endothelial cells compared to the cell nucleus and cytosol under basal conditions. Upon administering exogenous H2O2, the cytosolic and nuclear-targeted probes displayed similarly slow and moderate HyPer7 responses, whereas the mitochondria-targeted HyPer7 signal plateaued faster and reached higher amplitudes. Our results indicate striking differences in mitochondrial H2O2 accumulation of endothelial cells. Here, we present the method's potential as a practicable and informative multiparametric live-cell imaging technique.

Original languageEnglish
Article number338
Number of pages11
JournalBiosensors
Volume11
Issue number9
DOIs
Publication statusPublished - 14 Sept 2021

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Branches of science

  • 106 Biology
  • 209 Industrial Biotechnology
  • 301 Medical-Theoretical Sciences, Pharmacy

Research Fields

  • Cancer Research
  • Metabolism and Circulation
  • Neuroscience

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