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Iliopoulou, M.

Publications and source records attributed to Iliopoulou, M..

2 recordsLinked to original sources

Single-cell glycolytic activity regulates membrane tension 1 and HIV-1 fusion

There has been resurgence in determining the role of host metabolism in viral infection yet deciphering how the metabolic state of single cells affects viral entry and fusion remains unknown. Here, we have developed a novel assay multiplexing genetically encoded biosensors with single virus tracking (SVT) to evaluate the influence of global metabolic processes on the success rate of virus entry in single cells. We found that cells with a lower ATP:ADP ratio prior to virus addition were less permissive to virus fusion and infection. These results indicated a relationship between host metabolic state and the likelihood for virus-cell fusion to occur. SVT revealed that HIV-1 viruses were arrested at hemifusion in glycolytically-inactive cells. Interestingly, cells acutely treated with glycolysis inhibitor 2-deoxyglucose (2-DG) become resistant to virus infection and also display less surface membrane cholesterol. Addition of cholesterol in these in glycolytically-inactive cells rescued the virus entry block at hemifusion and enabled completion of HIV-1 fusion. Further investigation with FRET-based membrane tension and membrane-order reporters revealed a link between host cell glycolytic activity and host membrane order and tension. Indeed, cells treated with 2-DG possessed lower plasma membrane lipid order and higher tension values, respectively. Our novel imaging approach that combines lifetime imaging (FLIM) and SVT revealed not only changes in plasma membrane tension at the point of viral fusion, but also that HIV is less likely to enter cells at areas of higher membrane tension. We therefore have identified a connection between host cell glycolytic activity and membrane tension that influences HIV-1 fusion in real-time at the single-virus fusion level in live cells. As glycolytic activity sets membrane tension levels by altering cellular cholesterol surface levels, our results suggest additional previously unknown benefits of cholesterol-lowering medication in HIV-1 infection.

immunology

Robin Hood: non-fitting, non-smoothing image detrending for bleaching correction

Recent advances in protein labelling--gene tagging with CRIPSR-Cas9--have made it possible to label proteins of interest endogenously. This represents a major breakthrough in the field of quantitative microscopy, especially when quantifying protein-protein interactions. This is because over-expression of labelled proteins may cause a distortion in localization, function and perhaps artificially force protein-protein interactions due to crowding effects. A microscopy technique that is particularly well suited to detect protein interactions with low photon budgets is number and brightness (N&B). Detrending (removal of global trends in data) is a necessary pre-processing step to N&B calculations, but all current detrending methods perform poorly at low intensities. Here, we present the Robin Hood automatic detrending algorithm which performs well at low intensities, evaluating it with simulated and low photon budget live cell images. RH is available as an ImageJ plugin and as an R package.\n\nSTATEMENT OF SIGNIFICANCEFluorescence microscopy in general and Fluorescence fluctuation methods in particular are very much dependent on detrend algorithms and so far, the user needs to decide an arbitrary number to correct for bleaching when using the box plot or the running average approach. Here, we have developed a tool available to everybody as an ImageJ plugin that is automatic, user-free and able to correct bleached images with very low photon counts.

biophysics