Maximizing the quantitative accuracy and reproducibility of Förster resonance energy transfer measurement for screening by high throughput widefield microscopy

Abstract

Förster resonance energy transfer (FRET) between fluorescent proteins (FPs) provides insights into the proximities and orientations of FPs as surrogates of the biochemical interactions and structures of the factors to which the FPs are genetically fused. As powerful as FRET methods are, technical issues have impeded their broad adoption in the biologic sciences. One hurdle to accurate and reproducible FRET microscopy measurement stems from variable fluorescence backgrounds both within a field and between different fields. Those variations introduce errors into the precise quantification of fluorescence levels on which the quantitative accuracy of FRET measurement is highly dependent. This measurement error is particularly problematic for screening campaigns since minimal well-to-well variation is necessary to faithfully identify wells with altered values. High content screening depends also upon maximizing the numbers of cells imaged, which is best achieved by low magnification high throughput microscopy. But, low magnification introduces flat-field correction issues that degrade the accuracy of background correction to cause poor reproducibility in FRET measurement. For live cell imaging, fluorescence of cell culture media in the fluorescence collection channels for the FPs commonly used for FRET analysis is a high source of background error. These signal-to-noise problems are compounded by the desire to express proteins at biologically meaningful levels that may only be marginally above the strong fluorescence background. Here, techniques are presented that correct for background fluctuations. Accurate calculation of FRET is realized even from images in which a non-flat background is 10-fold higher than the signal.

Advantages and Limitations of Androgen Receptor-Based Methods for Detecting Anabolic Androgenic Steroid Abuse as Performance Enhancing Drugs

“…The AR BioAssay used here quantifies the androgen-mediated movement of a fluorescent protein (FP)-tagged human AR from the cytoplasm to the cell nucleus and was previously developed for high throughput quantification of AR response to androgenic drugs [ 26 , 29 ]. That AR BioAssay consists of a HeLa cell line that stably expresses the yellow FP (YFP)-tagged AR together with an mCherry-NLS-mCherry construct (where NLS is nuclear localization signal).…”

“…One day following the addition of urine, green fluorescence from the YFP-tagged AR and red fluorescence from the mCherry-linked nuclear marker were collected on an IXMicro High Throughput Microscope (Molecular Devices Corp., Sunnyvale, CA, USA) using filter sets previously described [ 29 ] and a 10x objective that our prior studies had shown to maximize the numbers of cells collected in a field at a magnification sufficient to distinguish the margins of adjacent cell nuclei and enable accurate image analysis [ 26 , 29 ]. Although the CFP-AR-YFP reporter also expresses CFP, CFP fluorescence was not quantified because the loss of CFP fluorescence by energy transfer to YFP changes with the types of AR ligands available [ 26 , 35 , 45 , 46 ].…”

“…Another confounding variable of CFP measurement is a very high level of autofluorescence from the cell culture media in the channel used to collect CFP. The resulting weak CFP signal against a high background noise can be corrected for laboriously [ 29 ], but the introduction of such imprecision into quantification of the CFP-tagged AR fluorescence in the cell nucleus is unnecessary given the YFP measurement. The mCherry image was used to define the margins of each cell nucleus using the ‘Count Nuclei’ program of the IXMicro analysis software (Molecular Devices Corp).…”

“…The YFP fluorescence image was used to detect the margins of the cytoplasm outside of the cell nucleus using the ‘Cell Scoring’ program of the analysis software. The ‘background’ fluorescence intensities over the non-cellular areas, together with calibration images that correct for the uneven background fluorescence originating with optical effects, were used to background-correct YFP intensity levels (see section 3.5 in [ 29 ]). The average correction relative to the calibration image in wells without and with urine were identical (2.20 vs 2.17 fluorescence intensity units on a 0–4095 scale), which indicates that the urine samples were not independently fluorescent.…”

Auto-FPFA: An Automated Microscope for Characterizing Genetically Encoded Biosensors

“…We believe that this limitation on the design pallet available to biosensor developers arises primarily because of a lack of instrumentation that can 1: rapidly & reliably, and 2: simultaneously measure multiple photo-physical changes in biosensors. Automated microscopes 11 – 15 have been developed to address the first issue, but robotic systems that can concurrently monitor multiple photo-physical properties have not been reported. In this paper, we describe the design, construction, and utility of an automated multi-modal microscope that simultaneously measures fluorescence intensity (photon count), lifetime, time-resolved anisotropy, molecular brightness, concentration, and lateral diffusion.…”