Fluorescent proteins (FPs) are pivotal for examining protein production, localization, and dynamics in live bacterial cells. However, the use of FPs in time-lapse imaging is frequently constrained by issues such as oligomerization or limited photostability. Here, we report the engineering of novel cyan, green, yellow, and red FPs that exhibit improved photostability and aggregation properties while retaining high in vivo brightness. We first derived superfolder green fluorescent protein into mChartreuse, a brighter, more photostable, and monomeric fluorophore. mChartreuse was further derived into cyan and yellow variants with enhanced photostability and dispersibility. We also report a mutation that eliminates residual oligomerization in red FPs derived from Discosoma sp., such as mCherry or mApple. Incorporation of this mutation in mApple among other substitutions yielded mLychee, a bright and photostable monomeric red FP. These novel FPs advance fluorescence time-lapse analysis in bacteria, and their spectral properties match current imaging standards, ensuring seamless integration into existing research workflows.

Fluorescent proteins are indispensable molecular tools for visualizing biological structures and processes, but their limited photostability restricts the duration of dynamic imaging experiments. Yellow fluorescent proteins (YFPs), in particular, photobleach rapidly. Here, we introduce mGold2s and mGold2t, YFPs with up to 25-fold greater photostability than mVenus and mCitrine, two commonly used YFPs, while maintaining comparable brightness. These variants were identified using a high-throughput pooled single-cell platform, simultaneously screening for high brightness and photostability. Compared with our previous benchmark, mGold, the mGold2 variants display a ~4-fold increase in photostability without sacrificing brightness. mGold2s and mGold2t extend imaging durations across diverse modalities, including widefield, total internal reflection fluorescence (TIRF), super-resolution, single-molecule, and laser-scanning confocal microscopy. When incorporated into fluorescence resonance energy transfer (FRET)-based biosensors, the proposed YFPs enable more reliable, prolonged imaging of dynamic cellular processes. Overall, the enhanced photostability of mGold2s and mGold2t enables high-sensitivity imaging of subcellular structures and cellular activity over extended periods, broadening the scope and precision of biological imaging.

Allergic diseases affect more than a quarter of individuals in industrialized countries, and are a major public health concern1,2. The high-affinity Fc receptor for immunoglobulin E (FcεRI), which is mainly present on mast cells and basophils, has a crucial role in allergic diseases3-5. Monomeric immunoglobulin E (IgE) binding to FcεRI regulates mast cell survival, differentiation and maturation6-8. However, the underlying molecular mechanism remains unclear. Here we demonstrate that prior to IgE binding, FcεRI exists mostly as a homodimer on human mast cell membranes. The structure of human FcεRI confirms the dimeric organization, with each promoter comprising one α subunit, one β subunit and two γ subunits. The transmembrane helices of the α subunits form a layered arrangement with those of the γ and β subunits. The dimeric interface is mediated by a four-helix bundle of the α and γ subunits at the intracellular juxtamembrane region. Cholesterol-like molecules embedded within the transmembrane domain may stabilize the dimeric assembly. Upon IgE binding, the dimeric FcεRI dissociates into two protomers, each of which binds to an IgE molecule. This process elicits transcriptional activation of Egr1, Egr3 and Ccl2 in rat basophils, which can be attenuated by inhibiting the FcεRI dimer-to-monomer transition. Collectively, our study reveals the mechanism of antigen-independent, IgE-mediated FcεRI activation.

Optical pooled screening (OPS) is a scalable method for linking image-based phenotypes with cellular perturbations. However, it has thus far been restricted to relatively low-plex phenotypic readouts in cancer cell lines in culture due to limitations associated with in situ sequencing of perturbation barcodes. Here, we develop PerturbView, an OPS technology that leverages in vitro transcription to amplify barcodes before in situ sequencing, enabling screens with highly multiplexed phenotypic readouts across diverse systems, including primary cells and tissues. We demonstrate PerturbView in induced pluripotent stem cell-derived neurons, primary immune cells and tumor tissue sections from animal models. In a screen of immune signaling pathways in primary bone marrow-derived macrophages, PerturbView uncovered both known and novel regulators of NF-κB signaling. Furthermore, we combine PerturbView with spatial transcriptomics in tissue sections from a mouse xenograft model, paving the way to in situ screens with rich optical and transcriptomic phenotypes. PerturbView broadens the scope of OPS to a wide range of models and applications.

Every collected photon is precious in live-cell super-resolution (SR) microscopy. Here, we describe a data-efficient, deep learning-based denoising solution to improve diverse SR imaging modalities. The method, SN2N, is a Self-inspired Noise2Noise module with self-supervised data generation and self-constrained learning process. SN2N is fully competitive with supervised learning methods and circumvents the need for large training set and clean ground truth, requiring only a single noisy frame for training. We show that SN2N improves photon efficiency by one-to-two orders of magnitude and is compatible with multiple imaging modalities for volumetric, multicolor, time-lapse SR microscopy. We further integrated SN2N into different SR reconstruction algorithms to effectively mitigate image artifacts. We anticipate SN2N will enable improved live-SR imaging and inspire further advances.

Fluorescent proteins (FPs) are essential tools in biology. The utility of FPs depends on their brightness, photostability, efficient folding, monomeric state, and compatibility with different cellular environments. Despite the proliferation of available FPs, derivatives of the originally identified Aequorea victoria green fluorescent protein often show superior behavior as fusion tags. We recently generated msGFP2, an optimized monomeric superfolder variant of A. victoria GFP. Here, we describe two derivatives of msGFP2. The monomeric variant msYFP2 is a yellow superfolder FP with high photostability. The monomeric variant moxGFP2 lacks cysteines but retains significant folding stability, so it works well in the lumen of the secretory pathway. These new FPs are useful for common imaging applications.

Comprehensively charting the biologically causal circuits that govern the phenotypic space of human cells has often been viewed as an insurmountable challenge. However, in the last decade, a suite of interleaved experimental and computational technologies has arisen that is making this fundamental goal increasingly tractable. Pooled CRISPR-based perturbation screens with high-content molecular and/or image-based readouts are now enabling researchers to probe, map, and decipher genetically causal circuits at increasing scale. This scale is now eminently suitable for the deployment of artificial intelligence and machine learning (AI/ML) to both direct further experiments and to predict or generate information that was not-and sometimes cannot-be gathered experimentally. By combining and iterating those through experiments that are designed for inference, we now envision a Perturbation Cell Atlas as a generative causal foundation model to unify human cell biology.

Over the past six decades, fluorescence-activated cell sorting (FACS) has become an essential technology for basic and clinical research by enabling the isolation of cells of interest in high throughput. Recent technological advancements have started a new era of flow cytometry. By combining the spatial resolution of microscopy with high-speed cell sorting, new instruments allow cell sorting based on simple image-derived parameters or sophisticated image analysis algorithms, thereby greatly expanding the scope of applications. In this review, we discuss the systems that are commercially available or have been described in enough methodological and engineering detail to allow their replication. We summarize their strengths and limitations and highlight applications that have the potential to transform various fields in basic life science research and clinical settings.

Genetically-encoded redox biosensors have become invaluable tools for monitoring cellular redox processes with high spatiotemporal resolution, coupling the presence of the redox-active analyte with a change in fluorescence signal that can be easily recorded. This review summarizes the available fluorescence recording methods and presents an in-depth classification of the redox biosensors, organized by the analytes they respond to. In addition to the fluorescent protein-based architectures, this review also describes the recent advances on fluorescent, chemigenetic-based redox biosensors and other emerging chemigenetic strategies. This review examines how these biosensors are designed, the biosensors sensing mechanism, and their practical advantages and disadvantages.

Single-cell analysis has become an essential tool in modern biological research, providing unprecedented insights into cellular behavior and heterogeneity. By examining individual cells, this approach surpasses conventional population-based methods, revealing critical variations in cellular states, responses to environmental cues, and molecular signatures. In the context of cancer, with its diverse cell populations, single-cell analysis is critical for investigating tumor evolution, metastasis, and therapy resistance. Understanding the phenotype-genotype relationship at the single-cell level is crucial for deciphering the molecular mechanisms driving tumor development and progression. This review highlights innovative strategies for selective cell isolation based on desired phenotypes, including robotic aspiration, laser detachment, microraft arrays, optical traps, and droplet-based microfluidic systems. These advanced tools facilitate high-throughput single-cell phenotypic analysis and sorting, enabling the identification and characterization of specific cell subsets, thereby advancing therapeutic innovations in cancer and other diseases.

We present mCLIFY: a monomeric, bright, yellow, and long-lived fluorescent protein (FP) created by circular permutation of YPet, the brightest yellow FP from Aequorea Victoria for use in cellular and in vitro single molecule studies. mCLIFY retains the enhanced photophysical properties of YPET as a monomer at concentrations ≤ 40 μM. In contrast, we determined that YPet has a dimerization dissociation constant (K D 1-2) of 3.4 μM. Dimerization of YPet can cause homo-FRET, which underlies quantitative errors due to dimerization and homo-FRET. We determined the atomic structure of mCLIFY at 1.57 Å resolution and used its similarity with Venus for guided chromophore-targeted substitution studies to provide insights into its enhanced photophysical properties. The mutation V58L within the chromophore pocket improved quantum yield and extinction coefficient, making mCLIFY ~30% brighter than Venus. The extensive characterization of the photophysical and structural properties of YPet and mCLIFY presented here allowed us to reveal the basis of their long lifetimes and enhanced brightness and the basis of YPet's dimerization.

Genetically encoded fluorescent biosensors have revolutionized the study of cell signaling and metabolism, as they allow for live-cell measurements with high spatiotemporal resolution. This success has spurred the development of tailor-made biosensors that enable the study of dynamic phenomena on different timescales and length scales. In this review, we discuss different approaches to enhancing and developing new biosensors. We summarize the technologies used to gain structural insights into biosensor design and comment on useful screening technologies. Furthermore, we give an overview of different applications where biosensors have led to key advances over recent years. Finally, we give our perspective on where future work is bound to make a large impact.

Gamma delta (γδ) T cells, a unique T cell subgroup, are crucial in various immune responses and immunopathology1-3. The γδ T cell receptor (TCR), which is generated by γδ T cells, recognizes a diverse range of antigens independently of the major histocompatibility complex2. The γδ TCR associates with CD3 subunits, initiating T cell activation and holding great potential in immunotherapy4. Here we report the structures of two prototypical human Vγ9Vδ2 and Vγ5Vδ1 TCR-CD3 complexes5,6, revealing two distinct assembly mechanisms that depend on Vγ usage. The Vγ9Vδ2 TCR-CD3 complex is monomeric, with considerable conformational flexibility in the TCRγ-TCRδ extracellular domain and connecting peptides. The length of the connecting peptides regulates the ligand association and T cell activation. A cholesterol-like molecule wedges into the transmembrane region, exerting an inhibitory role in TCR signalling. The Vγ5Vδ1 TCR-CD3 complex displays a dimeric architecture, whereby two protomers nestle back to back through the Vγ5 domains of the TCR extracellular domains. Our biochemical and biophysical assays further corroborate the dimeric structure. Importantly, the dimeric form of the Vγ5Vδ1 TCR is essential for T cell activation. These findings reveal organizing principles of the γδ TCR-CD3 complex, providing insights into the unique properties of γδ TCR and facilitating immunotherapeutic interventions.

Biopharmaceuticals have emerged as powerful therapeutic agents, revolutionizing the treatment landscape for various diseases, including cancer, infectious diseases, autoimmune and genetic disorders. These biotherapeutics pave the way for precision medicine with their unique and targeted capabilities. The production of high-quality biologics entails intricate manufacturing processes, including cell culture, fermentation, purification, and formulation, necessitating specialized facilities and expertise. These complex processes are subject to rigorous regulatory oversight to evaluate the safety, efficacy, and quality of biotherapeutics prior to clinical approval. Consequently, these drugs undergo extensive purification unit operations to achieve high purity by effectively removing impurities and contaminants. The field of personalized precision medicine necessitates the development of novel and highly efficient technologies. Microfluidic technology addresses unmet needs by enabling precise and compact separation, allowing rapid, integrated and continuous purification modules. Moreover, the integration of intelligent biomanufacturing systems with miniaturized devices presents an opportunity to significantly enhance the robustness of complex downstream processing of biopharmaceuticals, with the benefits of automation and advanced control. This allows seamless data exchange, real-time monitoring, and synchronization of purification steps, leading to improved process efficiency, data management, and decision-making. Integrating autonomous systems into biopharmaceutical purification ensures adherence to regulatory standards, such as good manufacturing practice (GMP), positioning the industry to effectively address emerging market demands for personalized precision nano-medicines. This perspective review will emphasize on the significance, challenges, and prospects associated with the adoption of continuous, integrated, and intelligent methodologies in small-scale downstream processing for various types of biologics. By utilizing microfluidic technology and intelligent systems, purification processes can be enhanced for increased efficiency, cost-effectiveness, and regulatory compliance, shaping the future of biopharmaceutical production and enabling the development of personalized and targeted therapies.

Genetically encoded fluorescent metal ion sensors are powerful tools for elucidating metal dynamics in living systems. Over the last 25 years since the first examples of genetically encoded fluorescent protein-based calcium indicators, this toolbox of probes has expanded to include other essential and non-essential metal ions. Collectively, these tools have illuminated fundamental aspects of metal homeostasis and trafficking that are crucial to fields ranging from neurobiology to human nutrition. Despite these advances, much of the application of metal ion sensors remains limited to mammalian cells and tissues and a limited number of essential metals. Applications beyond mammalian systems and in vivo applications in living organisms have primarily used genetically encoded calcium ion sensors. The aim of this Perspective is to provide, with the support of historical and recent literature, an updated and critical view of the design and use of fluorescent protein-based sensors for detecting essential metal ions in various organisms. We highlight the historical progress and achievements with calcium sensors and discuss more recent advances and opportunities for the detection of other essential metal ions. We also discuss outstanding challenges in the field and directions for future studies, including detecting a wider variety of metal ions, developing and implementing a broader spectral range of sensors for multiplexing experiments, and applying sensors to a wider range of single- and multi-species biological systems.

Fluorescent proteins (FPs) are essential tools in biology. The utility of FPs depends on their brightness, photostability, efficient folding, monomeric state, and compatibility with different cellular environments. Despite the proliferation of available FPs, derivatives of the originally identified Aequorea victoria GFP often show superior behavior as fusion tags. We recently generated msGFP2, an optimized monomeric superfolder variant of A. victoria GFP. Here, we describe two derivatives of msGFP2. The monomeric variant msYFP2 is a yellow superfolder FP with high photostability. The monomeric variant moxGFP2 lacks cysteines but retains significant folding stability, so it works well in the lumen of the secretory pathway. These new FPs are useful for common imaging applications.

Synthetic biology relies on the screening and quantification of genetic components to assemble sophisticated gene circuits with specific functions. Microscopy is a powerful tool for characterizing complex cellular phenotypes with increasing spatial and temporal resolution to library screening of genetic elements. Microscopy-based assays are powerful tools for characterizing cellular phenotypes with spatial and temporal resolution and can be applied to large-scale samples for library screening of genetic elements. However, strategies for high-throughput microscopy experiments remain limited. Here, we present a high-throughput, microscopy-based platform that can simultaneously complete the preparation of an 8 × 12-well agarose pad plate, allowing for the screening of 96 independent strains or experimental conditions in a single experiment. Using this platform, we screened a library of natural intrinsic promoters from Pseudomonas aeruginosa and identified a small subset of robust promoters that drives stable levels of gene expression under varying growth conditions. Additionally, the platform allowed for single-cell measurement of genetic elements over time, enabling the identification of complex and dynamic phenotypes to map genotype in high throughput. We expected that the platform could be employed to accelerate the identification and characterization of genetic elements in various biological systems, as well as to understand the relationship between cellular phenotypes and internal states, including genotypes and gene expression programs.

Protein mutagenesis is essential for unveiling the molecular mechanisms underlying protein function in health, disease, and evolution. In the past decade, deep mutational scanning methods have evolved to support the functional analysis of nearly all possible single-amino acid changes in a protein of interest. While historically these methods were developed in lower organisms such as E. coli and yeast, recent technological advancements have resulted in the increased use of mammalian cells, particularly for studying proteins involved in human disease. These advancements will aid significantly in the classification and interpretation of variants of unknown significance, which are being discovered at large scale due to the current surge in the use of whole-genome sequencing in clinical contexts. Here, we explore the experimental aspects of deep mutational scanning studies in mammalian cells and report the different methods used in each step of the workflow, ultimately providing a useful guide toward the design of such studies.

Glutathione (GSH) is the main determinant of intracellular redox potential and participates in multiple cellular signalling pathways. Achieving a detailed understanding of intracellular GSH homeostasis depends on the development of tools to map GSH compartmentalization and intra-organelle fluctuations. Here we present a GSH-sensing platform for live-cell imaging, termed targetable ratiometric quantitative GSH (TRaQ-G). This chemogenetic sensor possesses a unique reactivity turn-on mechanism, ensuring that the small molecule is only sensitive to GSH in a desired location. Furthermore, TRaQ-G can be fused to a fluorescent protein to give a ratiometric response. Using TRaQ-G fused to a redox-insensitive fluorescent protein, we demonstrate that the nuclear and cytosolic GSH pools are independently regulated during cell proliferation. This sensor was used in combination with a redox-sensitive fluorescent protein to quantify redox potential and GSH concentration simultaneously in the endoplasmic reticulum. Finally, by exchanging the fluorescent protein, we created a near-infrared, targetable and quantitative GSH sensor.

Fluorescent protein (FP)-based biosensors are genetically encoded tools that enable the imaging of biological processes in the context of cells, tissues, or live animals. Though widely used in biological research, practically all existing biosensors are far from ideal in terms of their performance, properties, and applicability for multiplexed imaging. These limitations have inspired researchers to explore an increasing number of innovative and creative ways to improve and maximize biosensor performance. Such strategies include new molecular biology methods to develop promising biosensor prototypes, high throughput microfluidics-based directed evolution screening strategies, and improved ways to perform multiplexed imaging. Yet another approach is to effectively replace components of biosensors with self-labeling proteins, such as HaloTag, that enable the biocompatible incorporation of synthetic fluorophores or other ligands in cells or tissues. This mini-review will summarize and highlight recent innovations and strategies for enhancing the performance of FP-based biosensors for multiplexed imaging to advance the frontiers of research.

Genetically encoded fluorescent indicators are powerful tools for tracking cellular dynamic processes. Engineering these indicators requires balancing screening dimensions with screening throughput. Herein, we present a functional imaging-guided photoactivatable cell selection platform, Faculae (functional imaging-activated molecular evolution), for linking microscopic phenotype with the underlying genotype in a pooled mutant library. Faculae is capable of assessing tens of thousands of variants in mammalian cells simultaneously while achieving photoactivation with single-cell resolution in seconds. To demonstrate the feasibility of this approach, we applied Faculae to perform multidimensional directed evolution for far-red genetically encoded calcium indicators (FR-GECIs) with improved brightness (Nier1b) and signal-to-baseline ratio (Nier1s). We anticipate that this image-based pooled screening method will facilitate the development of a wide variety of biomolecular tools.

Video-based screening of pooled libraries is a powerful approach for directed evolution of biosensors because it enables selection along multiple dimensions simultaneously from large libraries. Here we develop a screening platform, Photopick, which achieves precise phenotype-activated photoselection over a large field of view (2.3 × 2.3 mm, containing >103 cells, per shot). We used the Photopick platform to evolve archaerhodopsin-derived genetically encoded voltage indicators (GEVIs) with improved signal-to-noise ratio (QuasAr6a) and kinetics (QuasAr6b). These GEVIs gave improved signals in cultured neurons and in live mouse brains. By combining targeted in vivo optogenetic stimulation with high-precision voltage imaging, we characterized inhibitory synaptic coupling between individual cortical NDNF (neuron-derived neurotrophic factor) interneurons, and excitatory electrical synapses between individual hippocampal parvalbumin neurons. The QuasAr6 GEVIs are powerful tools for all-optical electrophysiology and the Photopick approach could be adapted to evolve a broad range of biosensors.

The genetically encoded fluorescent sensors convert chemical and physical signals into light. They are powerful tools for the visualisation of physiological processes in living cells and freely moving animals. The fluorescent protein is the reporter module of a genetically encoded biosensor. In this study, we first review the history of the fluorescent protein in full emission spectra on a structural basis. Then, we discuss the design of the genetically encoded biosensor. Finally, we briefly review several major types of genetically encoded biosensors that are currently widely used based on their design and molecular targets, which may be useful for the future design of fluorescent biosensors.

Over the last 25 years, protein engineers have developed an impressive collection of optical tools to interface with biological systems: indicators to eavesdrop on cellular activity and actuators to poke and prod native processes. To reach the performance level required for their downstream applications, protein-based tools are usually sculpted by iterative rounds of mutagenesis. In each round, libraries of variants are made and evaluated, and the most promising hits are then retrieved, sequenced, and further characterized. Early efforts to engineer protein-based optical tools were largely manual, suffering from low throughput, human error, and tedium. Here, we describe approaches to automating the screening of libraries generated as colonies on agar, multiwell plates, and pooled populations of single-cell variants. We also briefly discuss emerging approaches for screening, including cell-free systems and machine learning.

Most human genetic variation is classified as variants of uncertain significance. While advances in genome editing have allowed innovation in pooled screening platforms, many screens deal with relatively simple readouts (viability, fluorescence) and cannot identify the complex cellular phenotypes that underlie most human diseases. In this paper, we present a generalizable functional genomics platform that combines high-content imaging, machine learning, and microraft isolation in a method termed "Raft-Seq". We highlight the efficacy of our platform by showing its ability to distinguish pathogenic point mutations of the mitochondrial regulator Mitofusin 2, even when the cellular phenotype is subtle. We also show that our platform achieves its efficacy using multiple cellular features, which can be configured on-the-fly. Raft-Seq enables a way to perform pooled screening on sets of mutations in biologically relevant cells, with the ability to physically capture any cell with a perturbed phenotype and expand it clonally, directly from the primary screen.

Genetically encoded voltage indicators are emerging tools for monitoring voltage dynamics with cell-type specificity. However, current indicators enable a narrow range of applications due to poor performance under two-photon microscopy, a method of choice for deep-tissue recording. To improve indicators, we developed a multiparameter high-throughput platform to optimize voltage indicators for two-photon microscopy. Using this system, we identified JEDI-2P, an indicator that is faster, brighter, and more sensitive and photostable than its predecessors. We demonstrate that JEDI-2P can report light-evoked responses in axonal termini of Drosophila interneurons and the dendrites and somata of amacrine cells of isolated mouse retina. JEDI-2P can also optically record the voltage dynamics of individual cortical neurons in awake behaving mice for more than 30 min using both resonant-scanning and ULoVE random-access microscopy. Finally, ULoVE recording of JEDI-2P can robustly detect spikes at depths exceeding 400 μm and report voltage correlations in pairs of neurons.

Recent advances in fluorescence imaging permit large-scale recording of neural activity and dynamics of neurochemical release with unprecedented resolution in behaving animals. Calcium imaging with highly optimized genetically encoded indicators provides a mesoscopic view of neural activity from genetically defined populations at cellular and subcellular resolutions. Rigorously improved voltage sensors and microscopy allow for robust spike imaging of populational neurons in various brain regions. In addition, recent protein engineering efforts in the past few years have led to the development of sensors for neurotransmitters and neuromodulators. Here, we discuss the development and applications of these genetically encoded fluorescent indicators in reporting neural activity in response to various behaviors in different biological systems as well as in drug discovery. We also report a simple model to guide sensor selection and optimization.

The low photostability of fluorescent proteins is a limiting factor in many applications of fluorescence microscopy. Here we present StayGold, a green fluorescent protein (GFP) derived from the jellyfish Cytaeis uchidae. StayGold is over one order of magnitude more photostable than any currently available fluorescent protein and has a cellular brightness similar to mNeonGreen. We used StayGold to image the dynamics of the endoplasmic reticulum (ER) with high spatiotemporal resolution over several minutes using structured illumination microscopy (SIM) and observed substantially less photobleaching than with a GFP variant optimized for stability in the ER. Using StayGold fusions and SIM, we also imaged the dynamics of mitochondrial fusion and fission and mapped the viral spike proteins in fixed cells infected with severe acute respiratory syndrome coronavirus 2. As StayGold is a dimer, we created a tandem dimer version that allowed us to observe the dynamics of microtubules and the excitatory post-synaptic density in neurons. StayGold will substantially reduce the limitations imposed by photobleaching, especially in live cell or volumetric imaging.

Molecular processes depend on the concerted and dynamic interactions of proteins, either by one-on-one interactions of the same or different proteins or by the assembly of larger protein complexes consisting of many different proteins. Here, not only the protein-protein interaction (PPI) itself, but also the localization and activity of the protein of interest (POI) within the cell is essential. Therefore, in all cell biological experiments, preserving the spatio-temporal state of one POI relative to another is key to understanding the underlying complex and dynamic regulatory mechanisms in vivo. In this review, we examine some of the applicable techniques to measure PPIs in planta as well as recent combinatorial advances of PPI methods to measure the formation of higher order complexes with an emphasis on in vivo imaging techniques. We compare the different methods and discuss their benefits and potential pitfalls to facilitate the selection of appropriate techniques by providing a comprehensive overview of how to measure in vivo PPIs in plants.

Pooled genetic libraries have improved screening throughput for mapping genotypes to phenotypes. However, selectable phenotypes are limited, restricting screening to outcomes with a low spatiotemporal resolution. Here, we integrated live-cell imaging with pooled library-based screening. To enable intracellular multiplexing, we developed a method called EPICode that uses a combination of short epitopes, which can also appear in various subcellular locations. EPICode thus enables the use of live-cell microscopy to characterize a phenotype of interest over time, including after sequential stimulatory/inhibitory manipulations, and directly connects behavior to the cellular genotype. To test EPICode's capacity against an important milestone-engineering and optimizing dynamic, live-cell reporters-we developed a live-cell PKA kinase translocation reporter with improved sensitivity and specificity. The use of epitopes as fluorescent barcodes introduces a scalable strategy for high-throughput screening broadly applicable to protein engineering and drug discovery settings where image-based phenotyping is desired.

Photobleaching is the permanent loss of fluorescence after extended exposure to light and is a major limiting factor in super-resolution microscopy (SRM) that restricts spatiotemporal resolution and observation time. Strategies for preventing or overcoming photobleaching in SRM are reviewed developing new probes and chemical environments. Photostabilization strategies are introduced first, which are borrowed from conventional fluorescence microscopy, that are employed in SRM. SRM-specific strategies are then highlighted that exploit the on-off transitions of fluorescence, which is the key mechanism for achieving super-resolution, which are becoming new routes to address photobleaching in SRM. Off states can serve as a shelter from excitation by light or an exit to release a damaged probe and replace it with a fresh one. Such efforts in overcoming the photobleaching limits are anticipated to enhance resolution to molecular scales and to extend the observation time to physiological lifespans.

In vivo imaging of model organisms is heavily reliant on fluorescent proteins with high intracellular brightness. Here we describe a practical method for rapid optimization of fluorescent proteins via directed molecular evolution in cultured mammalian cells. Using this method, we were able to perform screening of large gene libraries containing up to 2 × 107 independent random genes of fluorescent proteins expressed in HEK cells, completing one iteration of directed evolution in a course of 8 days. We employed this approach to develop a set of green and near-infrared fluorescent proteins with enhanced intracellular brightness. The developed near-infrared fluorescent proteins demonstrated high performance for fluorescent labeling of neurons in culture and in vivo in model organisms such as Caenorhabditis elegans, Drosophila, zebrafish, and mice. Spectral properties of the optimized near-infrared fluorescent proteins enabled crosstalk-free multicolor imaging in combination with common green and red fluorescent proteins, as well as dual-color near-infrared fluorescence imaging. The described method has a great potential to be adopted by protein engineers due to its simplicity and practicality. We also believe that the new enhanced fluorescent proteins will find wide application for in vivo multicolor imaging of small model organisms.

Discovery of the genetic components underpinning fundamental and disease-related processes is being rapidly accelerated by combining efficient, programmable genetic engineering with phenotypic readouts of high spatial, temporal and/or molecular resolution. Microscopy is a fundamental tool for studying cell biology, but its lack of high-throughput sequence readouts hinders integration in large-scale genetic screens. Optical pooled screens using in situ sequencing provide massively scalable integration of barcoded lentiviral libraries (e.g., CRISPR perturbation libraries) with high-content imaging assays, including dynamic processes in live cells. The protocol uses standard lentiviral vectors and molecular biology, providing single-cell resolution of phenotype and engineered genotype, scalability to millions of cells and accurate sequence reads sufficient to distinguish >106 perturbations. In situ amplification takes ~2 d, while sequencing can be performed in ~1.5 h per cycle. The image analysis pipeline provided enables fully parallel automated sequencing analysis using a cloud or cluster computing environment.

The forward genetic screen is a powerful, unbiased method to gain insights into biological processes, yet this approach has infrequently been used in vivo in mammals because of high resource demands. Here, we use in vivo somatic Cas9 mutagenesis to perform an in vivo forward genetic screen in mice to identify regulators of cardiomyocyte (CM) maturation, the coordinated changes in phenotype and gene expression that occur in neonatal CMs. We discover and validate a number of transcriptional regulators of this process. Among these are RNF20 and RNF40, which form a complex that monoubiquitinates H2B on lysine 120. Mechanistic studies indicate that this epigenetic mark controls dynamic changes in gene expression required for CM maturation. These insights into CM maturation will inform efforts in cardiac regenerative medicine. More broadly, our approach will enable unbiased forward genetics across mammalian organ systems.

The ability to effectively separate and isolate biological cells into specific and well-defined subpopulations is crucial for the advancement of our understanding of cellular heterogeneity and its relevance to living systems. Here is described the development of the functional phenotype flow cytometer (FPFC), a new device designed to separate cells on the basis of their in situ real-time phenotypic responses to stimuli. The FPFC performs a cascade of cell processing steps on a microfluidic platform: introduces biological cells one at a time into a solution of a biological reagent that acts as a stimulus, incubates the cells with the stimulus solution in a flow, and sorts the cells into subpopulations according to their phenotypic responses to the provided stimulus. The presented implementation of the FPFC uses intracellular fluorescence as a readout, incubates cells for 75 s, and operates at a throughput of up to 4 cells min^-1 -resulting in the profiling and sorting of hundreds of cells within a few hours. The design and operation of the FPFC are validated by sorting cells from the human Burkitt's lymphoma cancerous cell line Ramos on the basis of their response to activation of the B cell antigen receptor (BCR) by a targeted monoclonal antibody.

A cell's phenotype is the culmination of several cellular processes through a complex network of molecular interactions that ultimately result in a unique morphological signature. Visual cell phenotyping is the characterization and quantification of these observable cellular traits in images. Recently, cellular phenotyping has undergone a massive overhaul in terms of scale, resolution, and throughput, which is attributable to advances across electronic, optical, and chemical technologies for imaging cells. Coupled with the rapid acceleration of deep learning-based computational tools, these advances have opened up new avenues for innovation across a wide variety of high-throughput cell biology applications. Here, we review applications wherein deep learning is powering the recognition, profiling, and prediction of visual phenotypes to answer important biological questions. As the complexity and scale of imaging assays increase, deep learning offers computational solutions to elucidate the details of previously unexplored cellular phenotypes.