Excitation-multiplexed multicolor superresolution imaging with fm-STORM and fm-DNA-PAINT.

Recent advancements in single-molecule-based superresolution microscopy have made it possible to visualize biological structures with unprecedented spatial resolution. Determining the spatial coorganization of these structures within cells under physiological and pathological conditions is an important biological goal. This goal has been stymied by the current limitations of carrying out superresolution microscopy in multiple colors. Here, we develop an approach for simultaneous multicolor superresolution imaging which relies solely on fluorophore excitation, rather than fluorescence emission properties. By modulating the intensity of the excitation lasers at different frequencies, we show that the color channel can be determined based on the fluorophore's response to the modulated excitation. We use this frequency multiplexing to reduce the image acquisition time of multicolor superresolution DNA-PAINT while maintaining all its advantages: minimal color cross-talk, minimal photobleaching, maximal signal throughput, ability to maintain the fluorophore density per imaged color, and ability to use the full camera field of view. We refer to this imaging modality as "frequency multiplexed DNA-PAINT," or fm-DNA-PAINT for short. We also show that frequency multiplexing is fully compatible with STORM superresolution imaging, which we term fm-STORM. Unlike fm-DNA-PAINT, fm-STORM is prone to color cross-talk. To overcome this caveat, we further develop a machine-learning algorithm to correct for color cross-talk with more than 95% accuracy, without the need for prior information about the imaged structure.

Eph-ephrin signaling modulated by polymerization and condensation of receptors.

Eph receptor signaling plays key roles in vertebrate tissue boundary formation, axonal pathfinding, and stem cell regeneration by steering cells to positions defined by its ligand ephrin. Some of the key events in Eph-ephrin signaling are understood: ephrin binding triggers the clustering of the Eph receptor, fostering transphosphorylation and signal transduction into the cell. However, a quantitative and mechanistic understanding of how the signal is processed by the recipient cell into precise and proportional responses is largely lacking. Studying Eph activation kinetics requires spatiotemporal data on the number and distribution of receptor oligomers, which is beyond the quantitative power offered by prevalent imaging methods. Here we describe an enhanced fluorescence fluctuation imaging analysis, which employs statistical resampling to measure the Eph receptor aggregation distribution within each pixel of an image. By performing this analysis over time courses extending tens of minutes, the information-rich 4D space (x, y, oligomerization, time) results were coupled to straightforward biophysical models of protein aggregation. This analysis reveals that Eph clustering can be explained by the combined contribution of polymerization of receptors into clusters, followed by their condensation into far larger aggregates. The modeling reveals that these two competing oligomerization mechanisms play distinct roles: polymerization mediates the activation of the receptor by assembling monomers into 6- to 8-mer oligomers; condensation of the preassembled oligomers into large clusters containing hundreds of monomers dampens the signaling. We propose that the polymerization-condensation dynamics creates mechanistic explanation for how cells properly respond to variable ligand concentrations and gradients.

Relating influenza virus membrane fusion kinetics to stoichiometry of neutralizing antibodies at the single-particle level.

The ability of antibodies binding the influenza hemagglutinin (HA) protein to neutralize viral infectivity is of key importance in the design of next-generation vaccines and for prophylactic and therapeutic use. The two antibodies CR6261 and CR8020 have recently been shown to efficiently neutralize influenza A infection by binding to and inhibiting the influenza A HA protein that is responsible for membrane fusion in the early steps of viral infection. Here, we use single-particle fluorescence microscopy to correlate the number of antibodies or antibody fragments (Fab) bound to an individual virion with the capacity of the same virus particle to undergo membrane fusion. To this end, individual, infectious virus particles bound by fluorescently labeled antibodies/Fab are visualized as they fuse to a planar, supported lipid bilayer. The fluorescence intensity arising from the virus-bound antibodies/Fab is used to determine the number of molecules attached to viral HA while a fluorescent marker in the viral membrane is used to simultaneously obtain kinetic information on the fusion process. We experimentally determine that the stoichiometry required for fusion inhibition by both antibody and Fab leaves large numbers of unbound HA epitopes on the viral surface. Kinetic measurements of the fusion process reveal that those few particles capable of fusion at high antibody/Fab coverage display significantly slower hemifusion kinetics. Overall, our results support a membrane fusion mechanism requiring the stochastic, coordinated action of multiple HA trimers and a model of fusion inhibition by stem-binding antibodies through disruption of this coordinated action.

Technologies bringing young Zebrafish from a niche field to the limelight.

Fundamental life science and pharmaceutical research are continually striving to provide physiologically relevant context for their biological studies. Zebrafish present an opportunity for high-content screening (HCS) to bring a true in vivo model system to screening studies. Zebrafish embryos and young larvae are an economical, human-relevant model organism that are amenable to both genetic engineering and modification, and direct inspection via microscopy. The use of these organisms entails unique challenges that new technologies are overcoming, including artificial intelligence (AI). In this perspective article, we describe the state-of-the-art in terms of automated sample handling, imaging, and data analysis with zebrafish during early developmental stages. We highlight advances in orienting the embryos, including the use of robots, microfluidics, and creative multi-well plate solutions. Analyzing the micrographs in a fast, reliable fashion that maintains the anatomical context of the fluorescently labeled cells is a crucial step. Existing software solutions range from AI-driven commercial solutions to bespoke analysis algorithms. Deep learning appears to be a critical tool that researchers are only beginning to apply, but already facilitates many automated steps in the experimental workflow. Currently, such work has permitted the cellular quantification of multiple cell types in vivo, including stem cell responses to stress and drugs, neuronal myelination and macrophage behavior during inflammation and infection. We evaluate pro and cons of proprietary versus open-source methodologies for combining technologies into fully automated workflows of zebrafish studies. Zebrafish are poised to charge into HCS with ever-greater presence, bringing a new level of physiological context.

Mechanisms of hemagglutinin targeted influenza virus neutralization.

Human monoclonal antibodies have been identified which neutralize broad spectra of influenza A or B viruses. Here, we dissect the mechanisms by which such antibodies interfere with infectivity. We distinguish four mechanisms that link the conserved hemagglutinin (HA) epitopes of broadly neutralizing antibodies to critical processes in the viral life cycle. HA-stem binding antibodies can act intracellularly by blocking fusion between the viral and endosomal membranes and extracellularly by preventing the proteolytic activation of HA. HA-head binding antibodies prevent viral attachment and release. These insights into newly identified ways by which the human immune system can interfere with influenza virus infection may aid the development of novel universal vaccines and antivirals.