Image-based pooled whole-genome CRISPRi screening for subcellular phenotypes

Multiplexed, image-based pooled screens in primary cells and tissues with PerturbView

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.

Toward a foundation model of causal cell and tissue biology with a Perturbation Cell and Tissue Atlas

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.

Accessible high-speed image-activated cell sorting

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.

Pathogenic variants in TMEM184B cause a neurodevelopmental syndrome via alteration of metabolic signaling

Transmembrane protein 184B (TMEM184B) is an endosomal 7-pass transmembrane protein with evolutionarily conserved roles in synaptic structure and axon degeneration. We report six pediatric patients who have de novo heterozygous variants in TMEM184B. All individuals harbor rare missense or mRNA splicing changes and have neurodevelopmental deficits including intellectual disability, corpus callosum hypoplasia, seizures, and/or microcephaly. TMEM184B is predicted to contain a pore domain, wherein many human disease-associated variants cluster. Structural modeling suggests that all missense variants alter TMEM184B protein stability. To understand the contribution of TMEM184B to neural development in vivo, we suppressed the TMEM184B ortholog in zebrafish and observed microcephaly and reduced anterior commissural neurons, aligning with patient symptoms. Ectopic TMEM184B expression resulted in dominant effects for K184E and G162R. However, in vivo complementation studies demonstrate that all other variants tested result in diminished protein function and indicate a haploinsufficiency basis for disease. Expression of K184E and other variants increased apoptosis in cell lines and altered nuclear localization of transcription factor EB (TFEB), a master regulator of lysosomal biogenesis, suggesting disrupted nutrient signaling pathways. Together, our data indicate that TMEM184B variants cause cellular metabolic disruption likely through divergent molecular effects that all result in abnormal neural development.

Genome-scale requirements for dynein-based transport revealed by a high-content arrayed CRISPR screen

The microtubule motor dynein plays a key role in cellular organization. However, little is known about how dynein's biosynthesis, assembly, and functional diversity are orchestrated. To address this issue, we have conducted an arrayed CRISPR loss-of-function screen in human cells using the distribution of dynein-tethered peroxisomes and early endosomes as readouts. From a genome-wide gRNA library, 195 validated hits were recovered and parsed into those impacting multiple dynein cargoes and those whose effects are restricted to a subset of cargoes. Clustering of high-dimensional phenotypic fingerprints revealed co-functional proteins involved in many cellular processes, including several candidate novel regulators of core dynein functions. Further analysis of one of these factors, the RNA-binding protein SUGP1, indicates that it promotes cargo trafficking by sustaining functional expression of the dynein activator LIS1. Our data represent a rich source of new hypotheses for investigating microtubule-based transport, as well as several other aspects of cellular organization captured by our high-content imaging.

CRISPRi: a way to integrate iPSC-derived neuronal models

The genetic landscape of neurodegenerative diseases encompasses genes affecting multiple cellular pathways which exert effects in an array of neuronal and glial cell-types. Deconvolution of the roles of genes implicated in disease and the effects of disease-associated variants remains a vital step in the understanding of neurodegeneration and the development of therapeutics. Disease modelling using patient induced pluripotent stem cells (iPSCs) has enabled the generation of key cell-types associated with disease whilst maintaining the genomic variants that predispose to neurodegeneration. The use of CRISPR interference (CRISPRi), alongside other CRISPR-perturbations, allows the modelling of the effects of these disease-associated variants or identifying genes which modify disease phenotypes. This review summarises the current applications of CRISPRi in iPSC-derived neuronal models, such as fluorescence-activated cell sorting (FACS)-based screens, and discusses the future opportunities for disease modelling, identification of disease risk modifiers and target/drug discovery in neurodegeneration.

Next-generation forward genetic screens: uniting high-throughput perturbations with single-cell analysis

Programmable genome-engineering technologies, such as CRISPR (clustered regularly interspaced short palindromic repeats) nucleases and massively parallel CRISPR screens that capitalize on this programmability, have transformed biomedical science. These screens connect genes and noncoding genome elements to disease-relevant phenotypes, but until recently have been limited to individual phenotypes such as growth or fluorescent reporters of gene expression. By pairing massively parallel screens with high-dimensional profiling of single-cell types/states, we can now measure how individual genetic perturbations or combinations of perturbations impact the cellular transcriptome, proteome, and epigenome. We review technologies that pair CRISPR screens with single-cell multiomics and the unique opportunities afforded by extending pooled screens using deep multimodal phenotyping.

Epigenetic repression of antiviral genes by SARS-CoV-2 NSP1

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) evades the innate immune machinery through multiple viral proteins, including nonstructural protein 1 (NSP1). While NSP1 is known to suppress translation of host mRNAs, the mechanisms underlying its immune evasion properties remain elusive. By integrating RNA-seq, ribosome footprinting, and ChIP-seq in A549 cells we found that NSP1 predominantly represses transcription of immune-related genes by favoring Histone 3 Lysine 9 dimethylation (H3K9me2). G9a/GLP H3K9 methyltransferase inhibitor UNC0638 restored expression of antiviral genes and restricted SARS-CoV-2 replication. Our multi-omics study unravels an epigenetic mechanism underlying host immune evasion by SARS-CoV-2 NSP1. Elucidating the factors involved in this phenomenon, may have implications for understanding and treating viral infections and other immunomodulatory diseases.

Molecular Modulators and Receptors of Selective Autophagy: Disease Implication and Identification Strategies

Autophagy is a highly conserved physiological process that maintains cellular homeostasis by recycling cellular contents. Selective autophagy is based on the specificity of cargo recognition and has been implicated in various human diseases, including neurodegenerative diseases and cancer. Selective autophagy receptors and modulators play key roles in this process. Identifying these receptors and modulators and their roles is critical for understanding the machinery and physiological function of selective autophagy and providing therapeutic value for diseases. Using modern researching tools and novel screening technologies, an increasing number of selective autophagy receptors and modulators have been identified. A variety of Strategies and approaches, including protein-protein interactions (PPIs)-based identification and genome-wide screening, have been used to identify selective autophagy receptors and modulators. Understanding the strengths and challenges of these approaches not only promotes the discovery of even more such receptors and modulators but also provides a useful reference for the identification of regulatory proteins or genes involved in other cellular mechanisms. In this review, we summarize the functions, disease association, and identification strategies of selective autophagy receptors and modulators.

Pooled Genome-Scale CRISPR Screens in Single Cells

Assigning functions to genes and learning how to control their expression are part of the foundation of cell biology and therapeutic development. An efficient and unbiased method to accomplish this is genetic screening, which historically required laborious clone generation and phenotyping and is still limited by scale today. The rapid technological progress on modulating gene function with CRISPR-Cas and measuring it in individual cells has now relaxed the major experimental constraints and enabled pooled screening with complex readouts from single cells. Here, we review the principles and practical considerations for pooled single-cell CRISPR screening. We discuss perturbation strategies, experimental model systems, matching the perturbation to the individual cells, reading out cell phenotypes, and data analysis. Our focus is on single-cell RNA sequencing and cell sorting-based readouts, including image-enabled cell sorting. We expect this transformative approach to fuel biomedical research for the next several decades.

Regulation of the length of neuronal primary cilia and its potential effects on signalling

Primary cilia protrude from most vertebrate cell bodies and act as specialized 'signalling antennae' that can substantially lengthen or retract in minutes to hours in response to specific stimuli. Here, we review the conditions and mechanisms responsible for regulating primary cilia length (PCL) in mammalian nonsensory neurons, and propose four models of how they could affect ciliary signalling and alter cell state and suggest experiments to distinguish between them. These models include (i) the passive indicator model, where changes in PCL have no consequence; (ii) the rheostat model, in which a longer cilium enhances signalling; (iii) the local concentration model, where ciliary shortening increases the local protein concentration to facilitate signalling; and (iv) the altered composition model where changes in PCL skew signalling.

CRISPR/dCas9 Tools: Epigenetic Mechanism and Application in Gene Transcriptional Regulation

CRISPR/Cas9-mediated cleavage of DNA, which depends on the endonuclease activity of Cas9, has been widely used for gene editing due to its excellent programmability and specificity. However, the changes to the DNA sequence that are mediated by CRISPR/Cas9 affect the structures and stability of the genome, which may affect the accuracy of results. Mutations in the RuvC and HNH regions of the Cas9 protein lead to the inactivation of Cas9 into dCas9 with no endonuclease activity. Despite the loss of endonuclease activity, dCas9 can still bind the DNA strand using guide RNA. Recently, proteins with active/inhibitory effects have been linked to the end of the dCas9 protein to form fusion proteins with transcriptional active/inhibitory effects, named CRISPRa and CRISPRi, respectively. These CRISPR tools mediate the transcription activity of protein-coding and non-coding genes by regulating the chromosomal modification states of target gene promoters, enhancers, and other functional elements. Here, we highlight the epigenetic mechanisms and applications of the common CRISPR/dCas9 tools, by which we hope to provide a reference for future related gene regulation, gene function, high-throughput target gene screening, and disease treatment.

High throughput microscopy and single cell phenotypic image-based analysis in toxicology and drug discovery

Measuring single cell responses to the universe of chemicals (drugs, natural products, environmental toxicants etc.) is of paramount importance to human health as phenotypic variability in sensing stimuli is a hallmark of biology that is considered during high throughput screening. One of the ways to approach this problem is via high throughput, microscopy-based assays coupled with multi-dimensional single cell analysis methods. Here, we will summarize some of the efforts in this vast and growing field, focusing on phenotypic screens (e.g., Cell Painting), single cell analytics and quality control, with particular attention to environmental toxicology and drug screening. We will discuss advantages and limitations of high throughput assays with various end points and levels of complexity.

Functional imaging-guided cell selection for evolving genetically encoded fluorescent indicators

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.

A genome-wide atlas of human cell morphology

A key challenge of the modern genomics era is developing data-driven representations of gene function. Here, we present the first unbiased morphology-based genome-wide perturbation atlas in human cells, containing three genome-scale genotype-phenotype maps comprising >20,000 single-gene CRISPR-Cas9-based knockout experiments in >30 million cells. Our optical pooled cell profiling approach (PERISCOPE) combines a de-stainable high-dimensional phenotyping panel (based on Cell Painting1,2) with optical sequencing of molecular barcodes and a scalable open-source analysis pipeline to facilitate massively parallel screening of pooled perturbation libraries. This approach provides high-dimensional phenotypic profiles of individual cells, while simultaneously enabling interrogation of subcellular processes. Our atlas reconstructs known pathways and protein-protein interaction networks, identifies culture media-specific responses to gene knockout, and clusters thousands of human genes by phenotypic similarity. Using this atlas, we identify the poorly-characterized disease-associated transmembrane protein TMEM251/LYSET as a Golgi-resident protein essential for mannose-6-phosphate-dependent trafficking of lysosomal enzymes, showing the power of these representations. In sum, our atlas and screening technology represent a rich and accessible resource for connecting genes to cellular functions at scale.

Spatial topology of organelle is a new breast cancer cell classifier

Genomics and proteomics have been central to identify tumor cell populations, but more accurate approaches to classify cell subtypes are still lacking. We propose a new methodology to accurately classify cancer cells based on their organelle spatial topology. Herein, we developed an organelle topology-based cell classification pipeline (OTCCP), which integrates artificial intelligence (AI) and imaging quantification to analyze organelle spatial distribution and inter-organelle topology. OTCCP was used to classify a panel of human breast cancer cells, grown as 2D monolayer or 3D tumor spheroids using early endosomes, mitochondria, and their inter-organelle contacts. Organelle topology allows for a highly precise differentiation between cell lines of different subtypes and aggressiveness. These findings lay the groundwork for using organelle topological profiling as a fast and efficient method for phenotyping breast cancer function as well as a discovery tool to advance our understanding of cancer cell biology at the subcellular level.

Deep learning in CRISPR-Cas systems: a review of recent studies

In genetic engineering, the revolutionary CRISPR-Cas system has proven to be a vital tool for precise genome editing. Simultaneously, the emergence and rapid evolution of deep learning methodologies has provided an impetus to the scientific exploration of genomic data. These concurrent advancements mandate regular investigation of the state-of-the-art, particularly given the pace of recent developments. This review focuses on the significant progress achieved during 2019-2023 in the utilization of deep learning for predicting guide RNA (gRNA) activity in the CRISPR-Cas system, a key element determining the effectiveness and specificity of genome editing procedures. In this paper, an analytical overview of contemporary research is provided, with emphasis placed on the amalgamation of artificial intelligence and genetic engineering. The importance of our review is underscored by the necessity to comprehend the rapidly evolving deep learning methodologies and their potential impact on the effectiveness of the CRISPR-Cas system. By analyzing recent literature, this review highlights the achievements and emerging trends in the integration of deep learning with the CRISPR-Cas systems, thus contributing to the future direction of this essential interdisciplinary research area.

Video-based pooled screening yields improved far-red genetically encoded voltage indicators

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.

Understanding neural development and diseases using CRISPR screens in human pluripotent stem cell-derived cultures

The brain is arguably the most complex part of the human body in form and function. Much remains unclear about the molecular mechanisms that regulate its normal and pathological physiology. This lack of knowledge largely stems from the inaccessible nature of the human brain, and the limitation of animal models. As a result, brain disorders are difficult to understand and even more difficult to treat. Recent advances in generating human pluripotent stem cells (hPSCs)-derived 2-dimensional (2D) and 3-dimensional (3D) neural cultures have provided an accessible system to model the human brain. Breakthroughs in gene editing technologies such as CRISPR/Cas9 further elevate the hPSCs into a genetically tractable experimental system. Powerful genetic screens, previously reserved for model organisms and transformed cell lines, can now be performed in human neural cells. Combined with the rapidly expanding single-cell genomics toolkit, these technological advances culminate to create an unprecedented opportunity to study the human brain using functional genomics. This review will summarize the current progress of applying CRISPR-based genetic screens in hPSCs-derived 2D neural cultures and 3D brain organoids. We will also evaluate the key technologies involved and discuss their related experimental considerations and future applications.

Cell sorters see things more clearly now

Microscopy and fluorescence-activated cell sorting (FACS) are two of the most important tools for single-cell phenotyping in basic and biomedical research. Microscopy provides high-resolution snapshots of cell morphology and the inner workings of cells, while FACS isolates thousands of cells per second using simple parameters, such as the intensity of fluorescent protein labels. Recent technologies are now combining both methods to enable the fast isolation of cells with microscopic phenotypes of interest, thereby bridging a long-standing gap in the life sciences. In this Commentary, we discuss the technical advancements made by image-enabled cell sorting and highlight novel experimental strategies in functional genomics and single-cell research.

Genome-scale requirements for dynein-based trafficking revealed by a high-content arrayed CRISPR screen

The cytoplasmic dynein-1 (dynein) motor plays a key role in cellular organisation by transporting a wide variety of cellular constituents towards the minus ends of microtubules. However, relatively little is known about how the biosynthesis, assembly and functional diversity of the motor is orchestrated. To address this issue, we have conducted an arrayed CRISPR loss-of-function screen in human cells using the distribution of dynein-tethered peroxisomes and early endosomes as readouts. From a guide RNA library targeting 18,253 genes, 195 validated hits were recovered and parsed into those impacting multiple dynein cargoes and those whose effects are restricted to a subset of cargoes. Clustering of high-dimensional phenotypic fingerprints generated from multiplexed images revealed co-functional genes involved in many cellular processes, including several candidate novel regulators of core dynein functions. Mechanistic analysis of one of these proteins, the RNA-binding protein SUGP1, provides evidence that it promotes cargo trafficking by sustaining functional expression of the dynein activator LIS1. Our dataset represents a rich source of new hypotheses for investigating microtubule-based transport, as well as several other aspects of cellular organisation that were captured by our high-content imaging.

Adding a Chemical Biology Twist to CRISPR Screening

In less than a decade, CRISPR screening has revolutionized forward genetics and cell and molecular biology. Advances in screening technologies, including sgRNA libraries, Cas9-expressing cell lines, and streamlined sequencing pipelines, have democratized pooled CRISPR screens at genome-wide scale. Initially, many such screens were survival-based, identifying essential genes in physiological or perturbed processes. With the application of new chemical biology tools to CRISPR screening, the phenotypic space is no longer limited to live/dead selection or screening for levels of conventional fluorescent protein reporters. Further, the resolution has been increased from cell populations to single cells or even the subcellular level. We highlight advances in pooled CRISPR screening, powered by chemical biology, that have expanded phenotypic space, resolution, scope, and scalability as well as strengthened the CRISPR/Cas enzyme toolkit to enable biological hypothesis generation and discovery.

A CRISPR view on autophagy

Autophagy is a fundamental pathway for the degradation of cytoplasmic content in response to pleiotropic extracellular and intracellular stimuli. Recent advances in the autophagy field have demonstrated that different organelles can also be specifically targeted for autophagy with broad implications on cellular and organismal health. This opens new dimensions in the autophagy field and more unanswered questions on the rationale and underlying mechanisms to degrade different organelles. Functional genomics via clustered regularly interspaced short palindromic repeats (CRISPR)-Cas9-based screening has gained popularity in the autophagy field to understand the common and unique factors that are implicated in the signaling, recognition, and execution of different cargo-specific autophagies. We focus on recent applications of CRISPR-based screens in the autophagy field, their discoveries, and the future directions of autophagy screens.

Scalable Functional Assays for the Interpretation of Human Genetic Variation

Scalable sequence-function studies have enabled the systematic analysis and cataloging of hundreds of thousands of coding and noncoding genetic variants in the human genome. This has improved clinical variant interpretation and provided insights into the molecular, biophysical, and cellular effects of genetic variants at an astonishing scale and resolution across the spectrum of allele frequencies. In this review, we explore current applications and prospects for the field and outline the principles underlying scalable functional assay design, with a focus on the study of single-nucleotide coding and noncoding variants.

The phenotypic landscape of essential human genes

Understanding the basis for cellular growth, proliferation, and function requires determining the roles of essential genes in diverse cellular processes, including visualizing their contributions to cellular organization and morphology. Here, we combined pooled CRISPR-Cas9-based functional screening of 5,072 fitness-conferring genes in human HeLa cells with microscopy-based imaging of DNA, the DNA damage response, actin, and microtubules. Analysis of >31 million individual cells identified measurable phenotypes for >90% of gene knockouts, implicating gene targets in specific cellular processes. Clustering of phenotypic similarities based on hundreds of quantitative parameters further revealed co-functional genes across diverse cellular activities, providing predictions for gene functions and associations. By conducting pooled live-cell screening of ∼450,000 cell division events for 239 genes, we additionally identified diverse genes with functional contributions to chromosome segregation. Our work establishes a resource detailing the consequences of disrupting core cellular processes that represents the functional landscape of essential human genes.

Towards elucidating disease-relevant states of neurons and glia by CRISPR-based functional genomics

Our understanding of neurological diseases has been tremendously enhanced over the past decade by the application of new technologies. Genome-wide association studies have highlighted glial cells as important players in diseases. Single-cell profiling technologies are providing descriptions of disease states of neurons and glia at unprecedented molecular resolution. However, significant gaps remain in our understanding of the mechanisms driving disease-associated cell states, and how these states contribute to disease. These gaps in our understanding can be bridged by CRISPR-based functional genomics, a powerful approach to systematically interrogate gene function. In this review, we will briefly review the current literature on neurological disease-associated cell states and introduce CRISPR-based functional genomics. We discuss how advances in CRISPR-based screens, especially when implemented in the relevant brain cell types or cellular environments, have paved the way towards uncovering mechanisms underlying neurological disease-associated cell states. Finally, we will delineate current challenges and future directions for CRISPR-based functional genomics to further our understanding of neurological diseases and potential therapeutic strategies.

Pooled genetic screens with image-based profiling

Spatial structure in biology, spanning molecular, organellular, cellular, tissue, and organismal scales, is encoded through a combination of genetic and epigenetic factors in individual cells. Microscopy remains the most direct approach to exploring the intricate spatial complexity defining biological systems and the structured dynamic responses of these systems to perturbations. Genetic screens with deep single-cell profiling via image features or gene expression programs have the capacity to show how biological systems work in detail by cataloging many cellular phenotypes with one experimental assay. Microscopy-based cellular profiling provides information complementary to next-generation sequencing (NGS) profiling and has only recently become compatible with large-scale genetic screens. Optical screening now offers the scale needed for systematic characterization and is poised for further scale-up. We discuss how these methodologies, together with emerging technologies for genetic perturbation and microscopy-based multiplexed molecular phenotyping, are powering new approaches to reveal genotype-phenotype relationships.

A fast blind zero-shot denoiser

Image noise is a common problem in light microscopy. This is particularly true in real-time live-cell imaging applications in which long-term cell viability necessitates low-light conditions. Modern denoisers are typically trained on a representative dataset, sometimes consisting of just unpaired noisy shots. However, when data are acquired in real time to track dynamic cellular processes, it is not always practical nor economical to generate these training sets. Recently, denoisers have emerged that allow us to denoise single images without a training set or knowledge about the underlying noise. But such methods are currently too slow to be integrated into imaging pipelines that require rapid, real-time hardware feedback. Here we present Noise2Fast, which can overcome these limitations. Noise2Fast uses a novel downsampling technique we refer to as ‘chequerboard downsampling’. This allows us to train on a discrete 4-image training set, while convergence can be monitored using the original noisy image. We show that Noise2Fast is faster than all similar methods with only a small drop in accuracy compared to the gold standard. We integrate Noise2Fast into real-time multi-modal imaging applications and demonstrate its broad applicability to diverse imaging and analysis pipelines.

Pooled image-base screening of mitochondria with microraft isolation distinguishes pathogenic mitofusin 2 mutations

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.

A multiplexed epitope barcoding strategy that enables dynamic cellular phenotypic screens

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.

Lysosomal dysfunction in neurodegeneration: emerging concepts and methods

The understanding of lysosomes has come a long way since the initial discovery of their role in degrading cellular waste. The lysosome is now recognized as a highly dynamic organelle positioned at the crossroads of cell signaling, transcription, and metabolism. Underscoring its importance is the observation that, in addition to rare monogenic lysosomal storage disorders, genes regulating lysosomal function are implicated in common sporadic neurodegenerative diseases, including Alzheimer's disease (AD), Parkinson's disease (PD), and amyotrophic lateral sclerosis (ALS). Developing therapies for these disorders is particularly challenging, largely due to gaps in knowledge of the underlying molecular and cellular processes. In this review, we discuss technological advances that have propelled deeper understanding of the lysosome in neurodegeneration, from elucidating the functions of lysosome-related disease risk variants at the level of the organelle, cell, and tissue, to the development of disease-specific biological models that recapitulate disease manifestations. Finally, we identify key questions to be addressed to successfully bridge the gap to the clinic.

High-content CRISPR screening

CRISPR screens are a powerful source of biological discovery, enabling the unbiased interrogation of gene function in a wide range of applications and species. In pooled CRISPR screens, various genetically encoded perturbations are introduced into pools of cells. The targeted cells proliferate under a biological challenge such as cell competition, drug treatment or viral infection. Subsequently, the perturbation-induced effects are evaluated by sequencing-based counting of the guide RNAs that specify each perturbation. The typical results of such screens are ranked lists of genes that confer sensitivity or resistance to the biological challenge of interest. Contributing to the broad utility of CRISPR screens, adaptations of the core CRISPR technology make it possible to activate, silence or otherwise manipulate the target genes. Moreover, high-content read-outs such as single-cell RNA sequencing and spatial imaging help characterize screened cells with unprecedented detail. Dedicated software tools facilitate bioinformatic analysis and enhance reproducibility. CRISPR screening has unravelled various molecular mechanisms in basic biology, medical genetics, cancer research, immunology, infectious diseases, microbiology and other fields. This Primer describes the basic and advanced concepts of CRISPR screening and its application as a flexible and reliable method for biological discovery, biomedical research and drug development - with a special emphasis on high-content methods that make it possible to obtain detailed biological insights directly as part of the screen.

Label-Free and In Situ Identification of Cells via Combinational Machine Learning Models

Cell identification and counting in living and coculture systems are crucial in cell interaction studies, but current methods primarily rely on complicated and time-consuming staining techniques. Here, a label-free method to precisely recognize, identify, and instantly count cells in situ in coculture systems via combinational machine learning models s presented. A convolutional neural network (CNN) model is first used to generate virtual images of cell nuclei based on unlabeled phase-contrast images. Coordinates of all the cells are then returned according to the virtual nucleus images using two clustering algorithms. Finally, phase-contrast images of single cells are cropped based on the coordinates and sent into another CNN model for cell-type identification. This combinational approach is highly automatic and efficient, which requires few to no manual annotations of images in the training phase. It shows practical performance in different cell culture conditions including cell ratios, densities, and substrate materials, having great potential in real-time cell tracking and analyzing.

Pooled genetic perturbation screens with image-based phenotypes

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.

High-speed fluorescence image-enabled cell sorting

Fast and selective isolation of single cells with unique spatial and morphological traits remains a technical challenge. Here, we address this by establishing high-speed image-enabled cell sorting (ICS), which records multicolor fluorescence images and sorts cells based on measurements from image data at speeds up to 15,000 events per second. We show that ICS quantifies cell morphology and localization of labeled proteins and increases the resolution of cell cycle analyses by separating mitotic stages. We combine ICS with CRISPR-pooled screens to identify regulators of the nuclear factor κB (NF-κB) pathway, enabling the completion of genome-wide image-based screens in about 9 hours of run time. By assessing complex cellular phenotypes, ICS substantially expands the phenotypic space accessible to cell-sorting applications and pooled genetic screening.

Tools for Decoding Ubiquitin Signaling in DNA Repair

The maintenance of genome stability requires dedicated DNA repair processes and pathways that are essential for the faithful duplication and propagation of chromosomes. These DNA repair mechanisms counteract the potentially deleterious impact of the frequent genotoxic challenges faced by cells from both exogenous and endogenous agents. Intrinsic to these mechanisms, cells have an arsenal of protein factors that can be utilised to promote repair processes in response to DNA lesions. Orchestration of the protein factors within the various cellular DNA repair pathways is performed, in part, by post-translational modifications, such as phosphorylation, ubiquitin, SUMO and other ubiquitin-like modifiers (UBLs). In this review, we firstly explore recent advances in the tools for identifying factors involved in both DNA repair and ubiquitin signaling pathways. We then expand on this by evaluating the growing repertoire of proteomic, biochemical and structural techniques available to further understand the mechanistic basis by which these complex modifications regulate DNA repair. Together, we provide a snapshot of the range of methods now available to investigate and decode how ubiquitin signaling can promote DNA repair and maintain genome stability in mammalian cells.

Fluorescence sensors for imaging membrane lipid domains and cholesterol

Lipid membrane domains are supramolecular lateral heterogeneities of biological membranes. Of nanoscopic dimensions, they constitute specialized hubs used by the cell as transient signaling platforms for a great variety of biologically important mechanisms. Their property to form and dissolve in the bulk lipid bilayer endow them with the ability to engage in highly dynamic processes, and temporarily recruit subpopulations of membrane proteins in reduced nanometric compartments that can coalesce to form larger mesoscale assemblies. Cholesterol is an essential component of these lipid domains; its unique molecular structure is suitable for interacting intricately with crevices and cavities of transmembrane protein surfaces through its rough β face while "talking" to fatty acid acyl chains of glycerophospholipids and sphingolipids via its smooth α face. Progress in the field of membrane domains has been closely associated with innovative improvements in fluorescence microscopy and new fluorescence sensors. These advances enabled the exploration of the biophysical properties of lipids and their supramolecular platforms. Here I review the rationale behind the use of biosensors over the last few decades and their contributions towards elucidation of the in-plane and transbilayer topography of cholesterol-enriched lipid domains and their molecular constituents. The challenges introduced by super-resolution optical microscopy are discussed, as well as possible scenarios for future developments in the field, including virtual ("no staining") staining.

Deliver on Time or Pay the Fine: Scheduling in Membrane Trafficking

Membrane trafficking is all about time. Automation in such a biological process is crucial to ensure management and delivery of cellular cargoes with spatiotemporal precision. Shared molecular regulators and differential engagement of trafficking components improve robustness of molecular sorting. Sequential recruitment of low affinity protein complexes ensures directionality of the process and, concomitantly, serves as a kinetic proofreading mechanism to discriminate cargoes from the whole endocytosed material. This strategy helps cells to minimize losses and operating errors in membrane trafficking, thereby matching the appealed deadline. Here, we summarize the molecular pathways of molecular sorting, focusing on their timing and efficacy. We also highlight experimental procedures and genetic approaches to robustly probe these pathways, in order to guide mechanistic studies at the interface between biochemistry and quantitative biology.

A new era in functional genomics screens

The past 25 years of genomics research first revealed which genes are encoded by the human genome and then a detailed catalogue of human genome variation associated with many diseases. Despite this, the function of many genes and gene regulatory elements remains poorly characterized, which limits our ability to apply these insights to human disease. The advent of new CRISPR functional genomics tools allows for scalable and multiplexable characterization of genes and gene regulatory elements encoded by the human genome. These approaches promise to reveal mechanisms of gene function and regulation, and to enable exploration of how genes work together to modulate complex phenotypes.

An engineered transcriptional reporter of protein localization identifies regulators of mitochondrial and ER membrane protein trafficking in high-throughput CRISPRi screens

The trafficking of specific protein cohorts to correct subcellular locations at correct times is essential for every signaling and regulatory process in biology. Gene perturbation screens could provide a powerful approach to probe the molecular mechanisms of protein trafficking, but only if protein localization or mislocalization can be tied to a simple and robust phenotype for cell selection, such as cell proliferation or fluorescence-activated cell sorting (FACS). To empower the study of protein trafficking processes with gene perturbation, we developed a genetically encoded molecular tool named HiLITR (High-throughput Localization Indicator with Transcriptional Readout). HiLITR converts protein colocalization into proteolytic release of a membrane-anchored transcription factor, which drives the expression of a chosen reporter gene. Using HiLITR in combination with FACS-based CRISPRi screening in human cell lines, we identified genes that influence the trafficking of mitochondrial and ER tail-anchored proteins. We show that loss of the SUMO E1 component SAE1 results in mislocalization and destabilization of many mitochondrial tail-anchored proteins. We also demonstrate a distinct regulatory role for EMC10 in the ER membrane complex, opposing the transmembrane-domain insertion activity of the complex. Through transcriptional integration of complex cellular functions, HiLITR expands the scope of biological processes that can be studied by genetic perturbation screening technologies.

Single-cell image analysis to explore cell-to-cell heterogeneity in isogenic populations

Single-cell image analysis provides a powerful approach for studying cell-to-cell heterogeneity, which is an important attribute of isogenic cell populations, from microbial cultures to individual cells in multicellular organisms. This phenotypic variability must be explained at a mechanistic level if biologists are to fully understand cellular function and address the genotype-to-phenotype relationship. Variability in single-cell phenotypes is obscured by bulk readouts or averaging of phenotypes from individual cells in a sample; thus, single-cell image analysis enables a higher resolution view of cellular function. Here, we consider examples of both small- and large-scale studies carried out with isogenic cell populations assessed by fluorescence microscopy, and we illustrate the advantages, challenges, and the promise of quantitative single-cell image analysis.

Imaging-based screens of pool-synthesized cell libraries

Mapping a genetic perturbation to a change in phenotype is at the core of biological research. Advances in microscopy have transformed these studies, but they have largely been confined to examining a few strains or cell lines at a time. In parallel, there has been a revolution in creating synthetic libraries of genetically altered cells with relative ease. Here we describe methods that combine these powerful tools to perform live-cell imaging of pool-generated strain libraries for improved biological discovery.