Fluorescent dye ProteoStat to detect and discriminate intracellular amyloid-like aggregates in Escherichia coli

Research output: Contribution to journalArticleResearchpeer-review

40 Citations (Scopus)

Abstract

© 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim. The formation of amyloid aggregates is linked to the onset of an increasing number of human disorders. Thus, there is an increasing need for methodologies able to provide insights into protein deposition and its modulation. Many approaches exist to study amyloids in vitro, but the techniques available for the study of amyloid aggregation in cells are still limited and non-specific. In this study we developed a methodology for the detection of amyloid-like aggregates inside cells that discriminates these ordered assemblies from other intracellular aggregates. We chose bacteria as model system, since the inclusion bodies formed by amyloid proteins in the cytosol of bacteria resemble toxic amyloids both structurally and functionally. Using confocal microscopy, fluorescence spectroscopy, and flow cytometry, we show that the recently developed red fluorescent dye ProteoStat can detect the presence of intracellular amyloid-like deposits in living bacterial cells with high specificity, even when the target proteins are expressed at low levels. This methodology allows quantitation of the intracellular amyloid content, shows the potential to replace in vitro screenings in the search for therapeutic anti-amyloidogenic compounds, and might be useful for identifying conditions that prevent the aggregation of therapeutic recombinant proteins.
Original languageEnglish
Pages (from-to)1259-1266
JournalBiotechnology Journal
Volume9
Issue number10
DOIs
Publication statusPublished - 1 Jan 2014

Keywords

  • Amyloid
  • Bacteria
  • Inclusion bodies
  • Protein aggregation
  • ProteoStat

Fingerprint

Dive into the research topics of 'Fluorescent dye ProteoStat to detect and discriminate intracellular amyloid-like aggregates in Escherichia coli'. Together they form a unique fingerprint.

Cite this