Open Source High Content Analysis Utilizing Automated Fluorescence Lifetime Imaging Microscopy

We present an open source high content analysis instrument utilizing automated fluorescence lifetime imaging (FLIM) for assaying protein interactions ...

Imperial College London

A fluorescence lifetime imaging (FLIM) technology platform intended to read out changes in Förster resonance energy transfer (FRET) efficiency is presented for the study of protein interactions across the drug-discovery pipeline. FLIM provides a robust, inherently ratiometric imaging modality for drug discovery that could allow the same sensor constructs to be translated from automated cell-based assays through small transparent organisms such as zebrafish to mammals. To this end, an automated FLIM multiwell-plate reader is described for high content analysis of fixed and live cells, tomographic FLIM in zebrafish and FLIM FRET of live cells via confocal endomicroscopy. For cell-based assays, an exemplar application reading out protein aggregation using FLIM FRET is presented, and the potential for multiple simultaneous FLIM (FRET) readouts in microscopy is illustrated.

FLIM FRET technology for drug discovery: automated multiwell-plate high-content analysis, multiplexed readouts and application in situ.

Fluorescence lifetime measurements can provide quantitative readouts of local fluorophore environment and can be applied to biomolecular interactions via Förster resonant energy transfer (FRET). Fluorescence lifetime imaging (FLIM) can therefore provide a high content analysis (HCA) modality to map protein-protein interactions (PPIs) with applications in drug discovery, systems biology and basic research. We present here an automated multiwell plate reader able to perform rapid unsupervised optically sectioned FLIM of fixed and live biological samples and illustrate its potential to assay PPIs through application to Gag protein aggregation during the HIV life cycle. We demonstrate both hetero-FRET and homo-FRET readouts of protein aggregation and report the first quantitative evaluation of a FLIM HCA assay by generating dose response curves through addition of an inhibitor of Gag myristoylation. Z' factors exceeding 0.6 are realised for this FLIM FRET assay.

Automated fluorescence lifetime imaging plate reader and its application to Förster resonant energy transfer readout of Gag protein aggregation.

Fluorescence lifetime imaging (FLIM) is widely applied to obtain quantitative information from fluorescence signals, particularly using Förster Resonant Energy Transfer (FRET) measurements to map, for example, protein-protein interactions. Extracting FRET efficiencies or population fractions typically entails fitting data to complex fluorescence decay models but such experiments are frequently photon constrained, particularly for live cell or in vivo imaging, and this leads to unacceptable errors when analysing data on a pixel-wise basis. Lifetimes and population fractions may, however, be more robustly extracted using global analysis to simultaneously fit the fluorescence decay data of all pixels in an image or dataset to a multi-exponential model under the assumption that the lifetime components are invariant across the image (dataset). This approach is often considered to be prohibitively slow and/or computationally expensive but we present here a computationally efficient global analysis algorithm for the analysis of time-correlated single photon counting (TCSPC) or time-gated FLIM data based on variable projection. It makes efficient use of both computer processor and memory resources, requiring less than a minute to analyse time series and multiwell plate datasets with hundreds of FLIM images on standard personal computers. This lifetime analysis takes account of repetitive excitation, including fluorescence photons excited by earlier pulses contributing to the fit, and is able to accommodate time-varying backgrounds and instrument response functions. We demonstrate that this global approach allows us to readily fit time-resolved fluorescence data to complex models including a four-exponential model of a FRET system, for which the FRET efficiencies of the two species of a bi-exponential donor are linked, and polarisation-resolved lifetime data, where a fluorescence intensity and bi-exponential anisotropy decay model is applied to the analysis of live cell homo-FRET data. A software package implementing this algorithm, FLIMfit, is available under an open source licence through the Open Microscopy Environment.

Rapid global fitting of large fluorescence lifetime imaging microscopy datasets.

Collagen is the most abundant protein in the animal kingdom. It is of fundamental importance during development for cell differentiation and tissue morphogenesis as well as in pathological processes such as fibrosis and cancer cell migration. However, our understanding of the mechanisms of procollagen secretion remains limited. Here, we show that TFG organizes transitional ER (tER) and ER exit sites (ERESs) into larger structures. Depletion of TFG results in dispersion of tER elements that remain associated with individual ER-Golgi intermediate compartments (ERGICs) as largely functional ERESs. We show that TFG is not required for the transport and packaging of small soluble cargoes but is necessary for the export of procollagen from the ER. Our work therefore suggests a key relationship between the structure and function of ERESs and a central role for TFG in optimizing COPII assembly for procollagen export.

TFG Promotes Organization of Transitional ER and Efficient Collagen Secretion.

Cerebrovascular remodeling in the SHR may be causative to the known brainstem hypoperfusion. Using RNA sequencing, we examined age-related processes that may govern remodeling of the cerebral arteries in the SHR.

Dominic Alibhai

Institute for Chemical Biology,
Department of Chemistry,
Institute for Chemical Biology, Department of Chemistry

Imperial College London

Open Source High Content Analysis Utilizing Automated Fluorescence Lifetime Imaging Microscopy

Dominic Alibhai

.css-o250i3{font-size:18px;font-family:Open Sans,sans-serif;line-height:21.6px;}Institute for Chemical Biology,Department of Chemistry,Institute for Chemical Biology, Department of Chemistry

Imperial College London

Open Source High Content Analysis Utilizing Automated Fluorescence Lifetime Imaging Microscopy

Institute for Chemical Biology,
Department of Chemistry,
Institute for Chemical Biology, Department of Chemistry