Application SpotLIGHT – January 2021: Time-lapse Imaging with SOLA Light Engine®

The Relevance of Time-lapse Imaging of GFP Expression Using the SOLA Light Engine® to COVID-19 vaccine Efficacy

The delivery of mRNA through lipid-based transfection has been a longstanding challenge for the development of RNA therapeutics. Moreover, it has acquired a new and urgent prominence from the development of COVID-19 vaccines consisting of mRNAs encapsulated in lipid nanoparticles by Pfizer/BioNTech and Moderna. It is clearly important to understand the effects of mRNA-lipid complex formulation and extracellular medium composition on downstream expression of the protein immunogen that in turn determines vaccine efficacy.  In 2019, before the start of the COVID-19 pandemic, a team of researchers from Ludwig-Maximilians-University in Munich and Stony Brook University, New York described the use of live-cell imaging on single-cell arrays (LISCA) to monitor the onset and rate of GFP expression following mRNA lipoplex transfection [1].  Single cells are arrayed on a micropatterned fibronectin substrate (Figure 1A), incubated with mRNA-lipid complexes for 1 hour and then monitored by time-lapse fluorescence microscopy for 20 hours (Figure 1B).  For GFP fluorescence to give an authentic representation of protein expression levels, stable and reproducible excitation is essential, making the SOLA Light Engine the ideal illumination source for this application.  As well as characterizing the pronounced cell-to-cell variability in onset times and rates of protein expression (Figure 1), LISCA was used to determine the effect of serum proteins on the cellular uptake of different mRNA-lipid complex formulations.

Figure 1. (A) Single GFP-expressing HuH7 cells arrayed on micropatterned fibronectin. (B) Single cell fluorescence trajectories representing GFP expression. The gray-shaded area represents the initial 1-hour period of incubation with mRNA-lipid complexes. (C) Enlarged region of (B) showing cell-to-cell variation in onset of protein expression. Reproduced from Reiser et al. (2019) [1] under the terms of the Creative Commons Attribution License.


[1] A Reiser, D Woschée, JO Rädler et al.  Integr Biol (2019) 11:362–371

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October 2020 Application spotLIGHT: Single-cell Characterization of Immunization Responses with SOLA light engine

Single-cell Characterization of Immunization Responses

The current Covid-19 pandemic has sparked an urgent need for improvements in the characterization of the immune response to vaccinations. Although simple and robust, conventional antibody titer measurements provide little information on the phenotypic diversity of IgG-secreting cells (IgG-SCs), the functional properties of the antibodies they produce or the temporal profile of the immune reaction in response to an antigenic challenge. In a recent paper published in the Journal of Immunology [1] and other recent publications [2,3], a team of researchers based in Paris and Zurich describe the application of a single-cell analysis technique known as DropMap to provide quantitative analysis of the distribution of antibody secretion rates and affinities over the course of an immune response. The DropMap protocol begins with microfluidically controlled compartmentalization of single splenocytes, extracted from mice at time points up to 8 weeks after immunization, in individual 50-picoliter droplets together with immunomagnetic beads and fluorescently-labeled antigens and anti-IgG antibodies. The beads are magnetically aligned to form micrometer-sized structures that can be visualized by fluorescence microscopy using a SOLA light engine.  Bead capture of red-fluorescent anti-IgG (Fc) identifies IgG-SCs, allowing determination of their frequency.  Capture of green-fluorescent antigen provides information on antigen binding affinity. To accumulate population statistics, two-dimensional arrays containing >10,000 cell-containing droplets are imaged every 7.5 minutes over 37.5 minutes. The SOLA light engine provides the exceptional light output stability required to extract reliable quantitative information across thousands of droplets and multiple time points.


[1]  K Eyer,  C Castrillon, J Baudry et al. J Immunol (2020) 205:1176–1184

[2]  Y Bounab, K Eyer, C Védrine et al.  Nat Protoc (2020) 15:2920–2955

[3] K Eyer, RCL Doineau, J Baudry et al. Nat Biotechol (2017) 35:977–982

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Industrial SpotLIGHT – September 2020: SOLA SM light engine® Provides High-speed Imaging for Material Science Applications

High-Speed Imaging of Powder Bed Fusion

Metal additive manufacturing is the process of joining materials to make objects from 3D computer-aided design (CAD) model data.  Laser powder bed fusion (PBF) is one such process, in which thermal energy derived from a laser beam selectively fuses regions of a powder bed.  A team from Heriot-Watt University, Edinburgh, and the University of Birmingham in the UK used high-speed imaging to investigate the interaction of the laser beam with the powder bed at sub-atmospheric pressures.  They used a SOLA SM Light Engine® to illuminate a circle of ~10 mm diameter on a stainless steel powder bed inside a vacuum chamber.  Image sequences were recorded at 40,000 frames per second by a monochrome camera.  The data obtained indicate that operating in a soft vacuum (>50 mbar) would provide the simplest implementation of PBF at sub-atmospheric pressures.  The reduction in vaporization temperature at reduced pressure means that the same penetration depth can be achieved at lower laser powers, resulting in a stabilizing effect on the process.

High-speed images at 20mbar. Laser power and scan speeds of (a) 50W and 0.2m/s, (b) 100W and 0.4m/s and (c) 200W and 0.8m/s.

Article Reference: P. Bidare, I. Bitharas, R.M. Ward, M.M. Attallah, A.J. Moore, Laser powder bed fusion at sub-atmospheric pressures, International Journal of Machine Tools and Manufacture, Volumes 130–131, 2018, Pages 65-72

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Industrial SpotLIGHT – September 2020: Characterization of Superhydrophobic Surface Coatings

Characterization of Superhydrophobic Surface Coatings

When two or more water droplets coalesce on a superhydrophobic surface, the resulting droplet can jump away from the surface due to inertial−capillary energy conversion. The resulting passive shedding of micro-scale water droplets has the potential to enhance heat transfer, anti-icing, and self-cleaning properties. To study this process, researchers at the University of Illinois developed an improved imaging technique called focal plane shift imaging (FPSI) to measure three-dimensional (3D) droplet trajectories. A high-speed camera is used to obtain video recordings at variable frame rates up to 500,000 frames per second. Illumination is supplied by a SOLA SM light engine®, specifically chosen for its high-intensity, low-power consumption and narrow spectral range (380−680 nm) in order to minimize heat generation at the surface due to light absorption. The effects of initial droplet size mismatch and multiple droplet coalescence on the jumping droplet velocity are revealed, showing that multi-droplet jumping has the potential to enhance the droplet departure speed.

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Application SpotLIGHT – May 2020: Multiplexed imaging of gene expression using the CELESTA light engine®

Multiplexed imaging of gene expression using the CELESTA light engine®

MERFISH (multiplex error robust fluorescence in situ hybridization) is an imaging technique that profiles cell populations based on the identification of thousands oRNA transcripts per cell.  The CELESTA light engine is an ideal and widely-adopted illumination source for this application.  In a recent paper published in Nature [1], Wheeler and co-workers used MERFISH imaging with a CELESTA light engine to quantify the expression of nine specific astrocyte and T-cell markers.  Five of the CELESTA light engine’s seven laser lines were used in the highly multiplexed MERFISH imaging protocol.  The overall objective of the research described in the paper was to characterize astrocyte populations that contribute to pathogenesis in a preclinical model of multiple sclerosis.

MA Wheeler, JR Moffitt, IC Clark, EC Tjon, Z Li, SE J Zandee, CP Couturier, BR Watson, G Scalisi, S Alkwai, V Rothhammer, A Rotem, JA Heyman, S Thaploo, LM Sanmarco, J Ragoussis, DA Weitz, K Petrecca, JR Moffitt, B Becher, JP Antel, A Prat, FJ Quintana, Nature (2020) 578:593–5990

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