Frontiers in Live-Cell Imaging and Analysis

How do cells, tissues, and organs work together in normal health and disease? This is the familiar ongoing question that’s foundational to many biologists’ research programs, in academia and industry. It’s also essential to future advances in medicine. For example, the Human Cell Atlas (Regev et al. 2018) aims to be the reference for all human cells and, thus, provide genetic insights on individual patients that will help guide targeted therapies. Live-cell imaging (LCI) is indispensable for such work and has a large, expanding market. In fact, Arizton (2022) predicts that the LCI global market will be $3.54 billion by 2027 (for pharma and biotech companies); 62.6% growth compared with 2021.

A major challenge for LCI projects is transitioning from custom-built methodologies to commercial platforms, and proper choice of tools (Lemon and McDole 2020). What microscopies are having the biggest impact on LCI, and thus should be the focus of such work? A recent editorial in Communications Biology (Fritsche 2022) identifies four especially promising LCI techniques: light-sheet, structured illumination, Airyscan, and multiphoton microscopies. Here, we highlight unique characteristics of each, and present representative state-of-the-art developments.

Lightsheet microscopy: Giving the side-eye

Lightsheet microscopy illuminates samples in a thin slice perpendicular to the viewing plane, and thus reduces photodamage compared with widefield imaging. The spatial resolution is comparable with confocal imaging, yet can be enhanced by super-resolution techniques. Light-sheet microscopy is commonly used to image organs and organisms.

For example, Patel et al. (2022) performed histological evaluations of tissue sections, and stitched together 2D sections into 3D volumes at a rate of 10 sections per second. They plan to use this technology to evaluate cancerous tissue samples without the necessity of tissue extraction, in scenarios that bring clinical value to patients. In a preprint, Lamb et al. (2022) developed open-source software for real-time imaging by oblique plane microscopy, a variant of light-sheet microscopy. The output frame rate was hardware-limited, depending on the camera exposure time and the pixel dimensions of the region of interest. This development will help researchers scan various fields of view and perspectives before settling on a particular area to image.

Structured illumination microscopy: Interfere with me

Structured illumination microscopy uses a moving diffraction grating to focus laser light onto a small region of the sample and reconstruct the resulting interference patterns into an image. The spatial resolution is approximately 2× improved compared with confocal imaging, yet further enhancements by combining with super-resolution techniques are generally difficult. Structured illumination microscopy is commonly used to image thin samples such as cells.

For example, Ward et al. (2022) used multicolor imaging and machine learning to track mitochondria and lysosomes within endoplasmic reticulum networks. They plan to extend their methodology to 3D imaging. Rodermund et al. (2021) quantitated the dynamics of the noncoding RNA Xist in living cells, in the context of better understanding X chromosome inactivation. They plan to test the hypothesis that Xist ribonucleoproteins translocate in a stepwise manner. In addition to normal development of mammalian female cells, X chromosome inactivation is pertinent to the severity of hemophilia B and other diseases.

Airyscan microscopy: Ditching the pinhole

Airyscan microscopy uses a detector array, instead of a physical pinhole and single detector, to minimize out-of-focus light. The spatial resolution can reach an extent that’s achievable in confocal microscopy only by reducing the pinhole size, yet without a corresponding loss of signal-to-noise. Airyscan microscopy is compatible with cell and tissue imaging.

For example, McKellar et al. (2023) identified the pertinence of a conserved leucine residue in the N-terminal domain of myxovirus resistance protein 1 to the protein’s antiviral activity and subcellular localization. This work might be useful in developing new therapies for influenza A and other viruses. Moore et al. (2021) confirmed an actin-based mixing hypothesis of mitochondrial segregation by symmetrically dividing cells. This work helps explain the means by which organelles are equally yet randomly segregated over the process of symmetric cell division. The aforementioned mixing hypothesis was long controversial due to prior difficulties of imaging sparse actin assemblies within a crowd of similar assemblies.

Multiphoton microscopy: Uncommon light

Multiphoton microscopy is based on the principle that the analyte absorbs photons only at the laser focal point. A spatial resolution of tens of nanometers is possible; much improved compared with that of conventional confocal microscopy. Multiphoton microscopy is compatible with cellular to whole-organism imaging.

For example, Guan et al. (2021) combined second harmonic generation and coherent anti-Stokes Raman microscopy to confirm reproduction of the pathology of liver fibrosis within an engineered, human-based organoid model, by quantitative imaging of collagen fibers and intracellular lipids. Yildirim et al. (2022)  used three-photon microscopy to image myelination defects in intact human organoids, in the context of Rett syndrome. These and future related studies will be useful for testing medical hypotheses and therapies in model systems that are more clinically relevant than animal models.

Scientists’ perspectives

Of course, advanced microscopy instrumentation only works as well as the chemical tools used to highlight cellular structures. What do scientists at the forefront of the field say? “There continues to be a need for tools that enable real-time, functional imaging of endogenous cellular processes,” says Dr. Kristin Riching, Senior Research Scientist at Promega. For example, their NanoLuc and NanoBiT luciferase assays are “particularly well-suited in the expanding area of bioluminescence imaging due to high signal-to-background and no need for an excitation source.”

The multidisciplinary nature that’s common to live-cell imaging brings together diverse tools and perspectives that help answer questions at the forefront of biological and medical research. Regardless of your scientific background, if you have a pertinent research direction, there are many live-cell imaging researchers who would appreciate collaborating with you and bringing out the full potential of your ideas.

References

Arizton (2022). Live cell imaging market – Global outlook & forecast market 2022-2027. Sep 2022.  (last accessed Jan 5, 2023)

Fritzsche M (2022). Live microscopy: Cracking the challenge to image biology unfolding in cells, tissues, and organs. Comm. Biol. 5:665. 

Guan Y, et al. (2021). A human multi-lineage hepatic organoid model for liver fibrosis. Nat. Commun. 12:6138. 

Lamb JR, et al. (2022). An open-source software package for on-the-fly deskewing and live viewing of volumetric lightsheet microscopy data. arXiv preprint 2211.00645. 

Lemon WC, McDole K (2020). Live-cell imaging in the era of too many microscopes. Curr. Opin. Cell Biol. 66:34–42. 

McKellar J, et al. (2023). An evolutionarily conserved N-terminal leucine is essential for MX1 GTPase antiviral activity against different families of RNA viruses. J. Biol. Chem. 299(1):102747. 

Moore AS, et al. (2021). Actin cables and comet tails organize mitochondrial networks in mitosis. Nature 591:659–664. 

Patel KB, et al. (2022). High-speed light-sheet microscopy for the in-situ acquisition of volumetric histological images of living tissue. Nat. Biomed. Eng. 6:569–583. 

Regev A, et al. (2018). The Human Cell Atlas white paper. arXiv preprint 1810.05192. 

Rodermund L, et al. (2021). Time-resolved structured illumination microscopy reveals key principles of Xist RNA spreading. Science 372(6547):eabe7500. 

Ward EN, et al. (2022). Machine learning assisted interferometric structured illumination microscopy for dynamic biological imaging. Nat. Commun. 13:7836. 

Yildirim M, et al. (2022). Label-free three-photon imaging of intact human cerebral organoids for tracking early events in brain development and deficits in Rett syndrome. eLife Jul 29.