Analysis insights for three FRET pairs of chemically unlinked two-molecule FRET cytometry

Förster resonance energy transfer (FRET) is the direct energy exchange between two-component fluorescent molecules. FRET methods utilize chemically linked molecules or unlinked fluorescence protein-protein interactions. FRET is therefore a powerful indicator of molecular proximity, but standardized determination of FRET efficiency is challenged when investigating natural (chemically unlinked) interactions. In this paper, we have examined the interactions of tumor necrosis factor receptor-1 (TNFR1) molecules expressed as recombinant fusion proteins of cyan, yellow, or red fluorescent protein (-CFP, -YFP, or -RFP) to evaluate two-molecule chemically unlinked FRET by flow cytometry. We demonstrate three independent FRET pairs CFP→YFP (FRET-1), YFP→RFP (FRET-2) and CFP→RFP (FRET-3), comparing TNFR1+TNFR1 with non-interacting TNFR1+CD27 proteins, on both LSR-II and Fortessa X-20 cytometers. We describe genuine FRET activities reflecting TNFR1 homotypic interactions. FRET events can be visualized during sample acquisition via the use of "spiked" FRET donor cells, together with TNFR1+TNFR1 co-transfected cells, as FRET channel MFI overlays. FRET events are subsequentially indicated by comparing concatenated files of cells expressing either FRET positive events (TNFR1+TNFR1) or FRET negative events (TNFR1+CD27) to generate single-cell scatter plots showing loss of FRET donor brightness. Robust determination of FRET efficiency is then confirmed at the single-cell level by applying matrix calculations based on the measurements of FRET donor, acceptor and FRET fluorescent intensities (I), detector channel emission coefficient (S), fluorescent protein extinction coefficients (ε) and α factor. In this TNFR based system, the mean CFP→YFP FRET-1 efficiency is 0.43 (LSR-II) and 0.41 (Fortessa), the mean YFP→RFP FRET-2 efficiency is 0.30 (LSR-II) and 0.29 (Fortessa), and the mean CFP→RFP FRET-3 efficiency is 0.56 (LSR-II) and 0.54 (Fortessa). This study also embraces multidimensional clustering using t-SNE, Fit-SNE, UMAP, Tri-Map and PaCMAP to further demonstrate FRET. These approaches establish a robust system for standardized detection of chemically unlinked TNFR1 homotypic interactions with three individual FRET pairs.

Expanding NIST Calibration of Fluorescent Microspheres for Flow Cytometry to More Fluorescence Channels and Smaller Particles

The National Institute of Standards and Technology (NIST), the National Institutes of Health (NIH) and other industry stakeholders have been working together to enable fluorescence intensities of flow cytometer calibration beads to be assigned quantitative equivalent reference fluorophore (ERF) values with high accuracy and precision. The ultimate goal of this effort is to accurately quantify the number of antibodies bound to individual living cells. The expansion of this effort to assign ERF values to more than 50 fluorescence channels and particles with diameters ranging from 10 μm down to 80 nm is reported here.

Biofluidic Random Laser Cytometer for Biophysical Phenotyping of Cell Suspensions

Phenotypic profiling of single floating cells in liquid biopsies is the key to the era of precision medicine. A random laser in biofluids is a promising tool for the label-free characterization of the biophysical properties as a result of the high brightness and sharp peaks of the lasing spectra, yet previous reports were limited to the random laser in solid tissues with dense scattering. In this report, a random laser cytometer is demonstrated in an optofluidic device filled with gain medium and human breast normal/cancerous cells. The multiple lightscattering event induced by the microscale human cells promotes random lasing and influences the lasing properties in term of laser modes, spectral wavelengths, and lasing thresholds. A sensing strategy based on analyzing the lasing properties is developed to determine both the whole cell and the subcellular biophysical properties, and the malignant alterations of the cell suspensions are successfully detected. Our results provide a new approach to designing a label-free biophysical cytometer based on optofluidic random laser devices, which is advantageous for further research in the field of random laser bioapplication.

Hacking CD/DVD/Blu-ray for Biosensing

The optical pickup unit (OPU) within a CD/DVD/Blu-ray drive integrates 780, 650, and 405 nm wavelength lasers, diffraction-limited optics, a high-bandwidth optoelectronic transducer up to 400 MHz, and a nanoresolution x-, z-axis, and tilt actuator in a compact size. In addition, the OPU is a remarkable piece of engineering and could enable different scientific applications such as sub-angstrom displacement sensing, micro- and nanoimaging, and nanolithography. Although off-the-shelf OPUs can be easily obtained, manufacturers protect their datasheets under nondisclosure agreements to impede their availability to the public. Thus, OPUs are black boxes that few people can use for research, and only experienced researchers can access all their functions. This review details the OPU mechanism and components. In addition, we explain how to utilize three commercially available triple-wavelength OPUs from scratch and optimize sensing quality. Then, we discuss scientific research using OPUs, from standard optical drive-based turnkey-biomarker array reading and OPU direct bioapplications (cytometry, optical tweezing, bioimaging) to modified OPU-based biosensing (DNA chip fluorescence scanning, biomolecular diagnostics). We conclude by presenting future trends on optical storage devices and potential applications. Hacking low-cost and high-performance OPUs may spread micro- and nanoscale biosensing research from research laboratories to citizen scientists around the globe.

Automated Micro-Object Detection for Mobile Diagnostics Using Lens-Free Imaging Technology

Lens-free imaging technology has been extensively used recently for microparticle and biological cell analysis because of its high throughput, low cost, and simple and compact arrangement. However, this technology still lacks a dedicated and automated detection system. In this paper, we describe a custom-developed automated micro-object detection method for a lens-free imaging system. In our previous work (Roy et al.), we developed a lens-free imaging system using low-cost components. This system was used to generate and capture the diffraction patterns of micro-objects and a global threshold was used to locate the diffraction patterns. In this work we used the same setup to develop an improved automated detection and analysis algorithm based on adaptive threshold and clustering of signals. For this purpose images from the lens-free system were then used to understand the features and characteristics of the diffraction patterns of several types of samples. On the basis of this information, we custom-developed an automated algorithm for the lens-free imaging system. Next, all the lens-free images were processed using this custom-developed automated algorithm. The performance of this approach was evaluated by comparing the counting results with standard optical microscope results. We evaluated the counting results for polystyrene microbeads, red blood cells, HepG2, HeLa, and MCF7 cells lines. The comparison shows good agreement between the systems, with a correlation coefficient of 0.91 and linearity slope of 0.877. We also evaluated the automated size profiles of the microparticle samples. This Wi-Fi-enabled lens-free imaging system, along with the dedicated software, possesses great potential for telemedicine applications in resource-limited settings.