RESUMEN
Cell cycle progression relies on coordinated changes in the composition and subcellular localization of the proteome. By applying two distinct convolutional neural networks on images of millions of live yeast cells, we resolved proteome-level dynamics in both concentration and localization during the cell cycle, with resolution of â¼20 subcellular localization classes. We show that a quarter of the proteome displays cell cycle periodicity, with proteins tending to be controlled either at the level of localization or concentration, but not both. Distinct levels of protein regulation are preferentially utilized for different aspects of the cell cycle, with changes in protein concentration being mostly involved in cell cycle control and changes in protein localization in the biophysical implementation of the cell cycle program. We present a resource for exploring global proteome dynamics during the cell cycle, which will aid in understanding a fundamental biological process at a systems level.
Asunto(s)
Proteínas de Saccharomyces cerevisiae , Saccharomyces cerevisiae , Células Eucariotas/metabolismo , Redes Neurales de la Computación , Proteoma/metabolismo , Saccharomyces cerevisiae/citología , Saccharomyces cerevisiae/metabolismo , Proteínas de Saccharomyces cerevisiae/metabolismoRESUMEN
Organoids are miniaturized and simplified versions of an organ produced in vitro from stem or progenitor cells. They are used as a model system consisting of multiple cell types forming an architecture relevant to the organ and carrying out the function of the organ. They are a useful tool to study development, homeostasis, regeneration, and disease. The imaging of organoids has become a pivotal method to visualize and understand their self-organization, symmetry breaking, growth, differentiation, and function. In this review, we discuss imaging methods, how to analyze these images, and challenges in organoid research.
Asunto(s)
Organoides , Células Madre , Diferenciación CelularRESUMEN
The mouse embryo has long been central to the study of mammalian development; however, elucidating the cell behaviors governing gastrulation and the formation of tissues and organs remains a fundamental challenge. A major obstacle is the lack of live imaging and image analysis technologies capable of systematically following cellular dynamics across the developing embryo. We developed a light-sheet microscope that adapts itself to the dramatic changes in size, shape, and optical properties of the post-implantation mouse embryo and captures its development from gastrulation to early organogenesis at the cellular level. We furthermore developed a computational framework for reconstructing long-term cell tracks, cell divisions, dynamic fate maps, and maps of tissue morphogenesis across the entire embryo. By jointly analyzing cellular dynamics in multiple embryos registered in space and time, we built a dynamic atlas of post-implantation mouse development that, together with our microscopy and computational methods, is provided as a resource. VIDEO ABSTRACT.
Asunto(s)
Linaje de la Célula , Gastrulación , Organogénesis , Análisis de la Célula Individual/métodos , Animales , Ratones , Ratones Endogámicos C57BL , Modelos Estadísticos , Imagen Óptica/métodosRESUMEN
The intricate network of the brain's neurons and synapses poses unparalleled challenges for research, distinct from other biological studies. This is particularly true when dissecting how neurons and their functional units work at a cell biological level. While traditional microscopy has been foundational, it was unable to reveal the deeper complexities of neural interactions. However, an imaging renaissance has transformed our capabilities. Advancements in light and electron microscopy, combined with correlative imaging, now achieve unprecedented resolutions, uncovering the most nuanced neural structures. Maximizing these tools requires more than just technical proficiency. It is crucial to align research aims, allocate resources wisely, and analyze data effectively. At the heart of this evolution is interdisciplinary collaboration, where various experts come together to translate detailed imagery into significant biological insights. This review navigates the latest developments in microscopy, underscoring both the promise of and prerequisites for bending this powerful tool set to understanding neuronal cell biology.
Asunto(s)
Microscopía , Neuronas , Neuronas/fisiología , Animales , Humanos , Microscopía/métodos , Biología Celular , Encéfalo/fisiología , Sinapsis/fisiologíaRESUMEN
Cell-cell interactions are central to development, but exploring how a change in any given cell relates to changes in the neighbour of that cell can be technically challenging. Here, we review recent developments in synthetic biology and image analysis that are helping overcome this problem. We highlight the opportunities presented by these advances and discuss opportunities and limitations in applying them to developmental model systems.
Asunto(s)
Comunicación Celular , Biología SintéticaRESUMEN
Recent work finds that nonviolent resistance by ethnic minorities is perceived as more violent and requiring more policing than identical resistance by ethnic majorities, reducing its impact and effectiveness. We ask whether allies-advantaged group participants in disadvantaged group movements-can mitigate these barriers. On the one hand, allies can counter negative stereotypes and defuse threat perceptions among advantaged group members, while raising expectations of success and lowering expected risks among disadvantaged group members. On the other hand, allies can entail significant costs, carrying risks of cooptation, replication of power hierarchies, and marginalization of core constituencies. To shed light on this question we draw on the case of the Black Lives Matter (BLM) movement, which, in 2020, attracted unprecedented White participation. Employing a national survey experiment, we find that sizeable White presence at racial justice protests increases protest approval, reduces perceptions of violence, and raises the likelihood of participation among White audiences, while not causing significant backlash among Black audiences. Black respondents mostly see White presence as useful for advancing the movement's goals, and predominant White presence reduces expectations that protests will be forcefully repressed. We complement these results with analysis of tens of thousands of images shared on social media during the 2020 BLM protests, finding a significant association between the presence of Whites in the images and user engagement and amplification. The findings suggest that allyship can be a powerful tool for promoting sociopolitical change amid deep structural inequality.
Asunto(s)
Actitud , Política , Adulto , Femenino , Humanos , Masculino , Negro o Afroamericano/psicología , Justicia Social/psicología , Estados Unidos , Violencia/psicología , Población Blanca/psicología , Blanco , Aplicación de la Ley , Etnicidad , Racismo SistemáticoRESUMEN
Exocytosis is a fundamental process used by eukaryotes to regulate the composition of the plasma membrane and facilitate cell-cell communication. To investigate exocytosis in neuronal morphogenesis, previously we developed computational tools with a graphical user interface to enable the automatic detection and analysis of exocytic events from fluorescence timelapse images. Although these tools were useful, we found the code was brittle and not easily adapted to different experimental conditions. Here, we developed and validated a robust and versatile toolkit, named pHusion, for the analysis of exocytosis, written in ImageTank, a graphical programming language that combines image visualization and numerical methods. We tested pHusion using a variety of imaging modalities and pH-sensitive fluorophores, diverse cell types and various exocytic markers, to generate a flexible and intuitive package. Using this system, we show that VAMP3-mediated exocytosis occurs 30-times more frequently in melanoma cells compared with primary oligodendrocytes, that VAMP2-mediated fusion events in mature rat hippocampal neurons are longer lasting than those in immature murine cortical neurons, and that exocytic events are clustered in space yet random in time in developing cortical neurons.
Asunto(s)
Exocitosis , Animales , Ratas , Ratones , Neuronas/metabolismo , Neuronas/citología , Humanos , Concentración de Iones de Hidrógeno , Programas Informáticos , Hipocampo/metabolismo , Hipocampo/citologíaRESUMEN
Filopodia are slender, actin-filled membrane projections used by various cell types for environment exploration. Analyzing filopodia often involves visualizing them using actin, filopodia tip or membrane markers. Due to the diversity of cell types that extend filopodia, from amoeboid to mammalian, it can be challenging for some to find a reliable filopodia analysis workflow suited for their cell type and preferred visualization method. The lack of an automated workflow capable of analyzing amoeboid filopodia with only a filopodia tip label prompted the development of filoVision. filoVision is an adaptable deep learning platform featuring the tools filoTips and filoSkeleton. filoTips labels filopodia tips and the cytosol using a single tip marker, allowing information extraction without actin or membrane markers. In contrast, filoSkeleton combines tip marker signals with actin labeling for a more comprehensive analysis of filopodia shafts in addition to tip protein analysis. The ZeroCostDL4Mic deep learning framework facilitates accessibility and customization for different datasets and cell types, making filoVision a flexible tool for automated analysis of tip-marked filopodia across various cell types and user data.
Asunto(s)
Actinas , Aprendizaje Profundo , Animales , Actinas/metabolismo , Seudópodos/metabolismo , Mamíferos/metabolismoRESUMEN
Plant protoplasts provide starting material for of inducing pluripotent cell masses that are competent for tissue regeneration in vitro, analogous to animal induced pluripotent stem cells (iPSCs). Dedifferentiation is associated with large-scale chromatin reorganisation and massive transcriptome reprogramming, characterised by stochastic gene expression. How this cellular variability reflects on chromatin organisation in individual cells and what factors influence chromatin transitions during culturing are largely unknown. Here, we used high-throughput imaging and a custom supervised image analysis protocol extracting over 100 chromatin features of cultured protoplasts. The analysis revealed rapid, multiscale dynamics of chromatin patterns with a trajectory that strongly depended on nutrient availability. Decreased abundance in H1 (linker histones) is hallmark of chromatin transitions. We measured a high heterogeneity of chromatin patterns indicating intrinsic entropy as a hallmark of the initial cultures. We further measured an entropy decline over time, and an antagonistic influence by external and intrinsic factors, such as phytohormones and epigenetic modifiers, respectively. Collectively, our study benchmarks an approach to understand the variability and evolution of chromatin patterns underlying plant cell reprogramming in vitro.
Asunto(s)
Cromatina , Entropía , Células Madre Pluripotentes Inducidas , Cromatina/metabolismo , Cromatina/genética , Células Madre Pluripotentes Inducidas/metabolismo , Células Madre Pluripotentes Inducidas/citología , Protoplastos/metabolismo , Reprogramación Celular/genética , Histonas/metabolismo , Histonas/genética , Células Vegetales/metabolismo , Epigénesis GenéticaRESUMEN
Oocytes develop in the germline cyst, a cellular organization in which germ cells are tightly interconnected and surrounded by somatic cells. The cyst produces oocytes for follicle formation and is a hub for essential processes in meiosis and oocyte differentiation. However, the formation and organization of the cyst, and their contribution to oocyte production in vertebrates remain unclear. Here, we provide tools for three-dimensional and functional in vivo analyses of the germline cyst in the zebrafish ovary. We describe the use of serial block-face scanning electron microscopy (SBF-SEM) to resolve the three-dimensional architecture of cells and organelles in the cyst at ultrastructural resolution. We present a deep learning-based pipeline for high-throughput quantitative analysis of three-dimensional confocal datasets of cysts in vivo. We provide a method for laser ablation of cellular components for manipulating cyst cells in ovaries. These methods will facilitate the investigation of the cyst cellular organization, expand the toolkit for the study of the zebrafish ovary, and advance our understanding of female developmental reproduction. They could also be further applied to the investigation of other developmental systems.
Asunto(s)
Oogénesis , Pez Cebra , Animales , Femenino , Oocitos , Ovario , Células Germinativas/ultraestructuraRESUMEN
Biological discovery has been driven by advances in throughput and resolution of analysis technologies. They have also created an indelible bias for snapshot-based knowledge. Even though recent methods such as multi-omics single-cell assays have empowered immunological investigations, they still provide snapshots of cellular behaviors and thus, have inherent limitations in reconstructing unsynchronized dynamic events across individual cells. Here, we present a rationale for how NF-κB may convey specificity of contextual information through subtle quantitative features of its signaling dynamics. The next frontier of predictive understanding should involve functional characterization of NF-κB signaling dynamics and their immunological implications. This may help solve the apparent paradox that a ubiquitously activated transcription factor can shape accurate responses to different immune challenges.
Asunto(s)
FN-kappa B , Transducción de Señal , Humanos , FN-kappa B/metabolismo , Regulación de la Expresión GénicaRESUMEN
The analysis of cellular behavior using intravital multi-photon microscopy has contributed substantially to our understanding of the priming and effector phases of immune responses. Yet, many questions remain unanswered and unexplored. Though advancements in intravital imaging techniques and animal models continue to drive new discoveries, continued improvements in analysis methods are needed to extract detailed information about cellular behavior. Focusing on dendritic cell (DC) and T cell interactions as an exemplar, here we discuss key limitations for intravital imaging studies and review and explore alternative approaches to quantify immune cell behavior. We touch upon current developments in deep learning models, as well as established methods from unrelated fields such as ecology to detect and track objects over time. As developments in open-source software make it possible to process and interactively view larger datasets, the challenge for the field will be to determine how best to combine intravital imaging with multi-parameter imaging of larger tissue regions to discover new facets of leukocyte dynamics and how these contribute to immune responses.
Asunto(s)
Comunicación Celular , Microscopía Intravital , Animales , Diagnóstico por Imagen , Humanos , Microscopía Intravital/métodos , Leucocitos , Modelos AnimalesRESUMEN
Phenotyping of model organisms grown on Petri plates is often carried out manually, despite the procedures being time-consuming and laborious. The main reason for this is the limited availability of automated phenotyping facilities, whereas constructing a custom automated solution can be a daunting task for biologists. Here, we describe SPIRO, the Smart Plate Imaging Robot, an automated platform that acquires time-lapse photographs of up to four vertically oriented Petri plates in a single experiment, corresponding to 192 seedlings for a typical root growth assay and up to 2500 seeds for a germination assay. SPIRO is catered specifically to biologists' needs, requiring no engineering or programming expertise for assembly and operation. Its small footprint is optimized for standard incubators, the inbuilt green LED enables imaging under dark conditions, and remote control provides access to the data without interfering with sample growth. SPIRO's excellent image quality is suitable for automated image processing, which we demonstrate on the example of seed germination and root growth assays. Furthermore, the robot can be easily customized for specific uses, as all information about SPIRO is released under open-source licenses. Importantly, uninterrupted imaging allows considerably more precise assessment of seed germination parameters and root growth rates compared with manual assays. Moreover, SPIRO enables previously technically challenging assays such as phenotyping in the dark. We illustrate the benefits of SPIRO in proof-of-concept experiments which yielded a novel insight on the interplay between autophagy, nitrogen sensing, and photoblastic response.
Asunto(s)
Germinación , Plantones , Fenotipo , Germinación/fisiología , Semillas , Procesamiento de Imagen Asistido por ComputadorRESUMEN
Unwanted sample drift is a common issue that plagues microscopy experiments, preventing accurate temporal visualization and quantification of biological processes. Although multiple methods and tools exist to correct images post acquisition, performing drift correction of three-dimensional (3D) videos using open-source solutions remains challenging and time consuming. Here, we present a new tool developed for ImageJ or Fiji called Fast4DReg that can quickly correct axial and lateral drift in 3D video-microscopy datasets. Fast4DReg works by creating intensity projections along multiple axes and estimating the drift between frames using two-dimensional cross-correlations. Using synthetic and acquired datasets, we demonstrate that Fast4DReg can perform better than other state-of-the-art open-source drift-correction tools and significantly outperforms them in speed. We also demonstrate that Fast4DReg can be used to register misaligned channels in 3D using either calibration slides or misaligned images directly. Altogether, Fast4DReg provides a quick and easy-to-use method to correct 3D imaging data before further visualization and analysis.
Asunto(s)
Imagenología Tridimensional , Microscopía , Imagenología Tridimensional/métodos , Microscopía por VideoRESUMEN
BACKGROUND & AIMS: Benign ulcerative colorectal diseases (UCDs) such as ulcerative colitis, Crohn's disease, ischemic colitis, and intestinal tuberculosis share similar phenotypes with different etiologies and treatment strategies. To accurately diagnose closely related diseases like UCDs, we hypothesize that contextual learning is critical in enhancing the ability of the artificial intelligence models to differentiate the subtle differences in lesions amidst the vastly divergent spatial contexts. METHODS: White-light colonoscopy datasets of patients with confirmed UCDs and healthy controls were retrospectively collected. We developed a Multiclass Contextual Classification (MCC) model that can differentiate among the mentioned UCDs and healthy controls by incorporating the tissue object contexts surrounding the individual lesion region in a scene and spatial information from other endoscopic frames (video-level) into a unified framework. Internal and external datasets were used to validate the model's performance. RESULTS: Training datasets included 762 patients, and the internal and external testing cohorts included 257 patients and 293 patients, respectively. Our MCC model provided a rapid reference diagnosis on internal test sets with a high averaged area under the receiver operating characteristic curve (image-level: 0.950 and video-level: 0.973) and balanced accuracy (image-level: 76.1% and video-level: 80.8%), which was superior to junior endoscopists (accuracy: 71.8%, P < .0001) and similar to experts (accuracy: 79.7%, P = .732). The MCC model achieved an area under the receiver operating characteristic curve of 0.988 and balanced accuracy of 85.8% using external testing datasets. CONCLUSIONS: These results enable this model to fit in the routine endoscopic workflow, and the contextual framework to be adopted for diagnosing other closely related diseases.
Asunto(s)
Inteligencia Artificial , Colitis Ulcerosa , Colonoscopía , Humanos , Colitis Ulcerosa/diagnóstico , Estudios Retrospectivos , Femenino , Masculino , Persona de Mediana Edad , Adulto , Interpretación de Imagen Asistida por Computador/métodos , Curva ROC , Anciano , Reproducibilidad de los Resultados , Colon/patología , Colon/diagnóstico por imagen , Valor Predictivo de las Pruebas , Diagnóstico Diferencial , Grabación en Video , Aprendizaje Automático , Estudios de Casos y ControlesRESUMEN
The efficient extraction of image data from curved tissue sheets embedded in volumetric imaging data remains a serious and unsolved problem in quantitative studies of embryogenesis. Here, we present DeepProjection (DP), a trainable projection algorithm based on deep learning. This algorithm is trained on user-generated training data to locally classify 3D stack content, and to rapidly and robustly predict binary masks containing the target content, e.g. tissue boundaries, while masking highly fluorescent out-of-plane artifacts. A projection of the masked 3D stack then yields background-free 2D images with undistorted fluorescence intensity values. The binary masks can further be applied to other fluorescent channels or to extract local tissue curvature. DP is designed as a first processing step than can be followed, for example, by segmentation to track cell fate. We apply DP to follow the dynamic movements of 2D-tissue sheets during dorsal closure in Drosophila embryos and of the periderm layer in the elongating Danio embryo. DeepProjection is available as a fully documented Python package.
Asunto(s)
Aprendizaje Profundo , Microscopía , Microscopía/métodos , Algoritmos , Artefactos , Procesamiento de Imagen Asistido por Computador/métodos , Imagenología Tridimensional/métodosRESUMEN
To obtain commensurate numerical data of neuronal network morphology in vitro, network analysis needs to follow consistent guidelines. Important factors in successful analysis are sample uniformity, suitability of the analysis method for extracting relevant data and the use of established metrics. However, for the analysis of 3D neuronal cultures, there is little coherence in the analysis methods and metrics used in different studies. Here, we present a framework for the analysis of neuronal networks in 3D. First, we selected a hydrogel that supported the growth of human pluripotent stem cell-derived cortical neurons. Second, we tested and compared two software programs for tracing multi-neuron images in three dimensions and optimized a workflow for neuronal analysis using software that was considered highly suitable for this purpose. Third, as a proof of concept, we exposed 3D neuronal networks to oxygen-glucose deprivation- and ionomycin-induced damage and showed morphological differences between the damaged networks and control samples utilizing the proposed analysis workflow. With the optimized workflow, we present a protocol for preparing, challenging, imaging and analysing 3D human neuronal cultures.
Asunto(s)
Neuronas , Células Madre Pluripotentes , Humanos , Programas InformáticosRESUMEN
The human pathogen herpes simplex virus 1 (HSV-1) produces a lifelong infection in the majority of the world's population. While the generalities of alpha herpesvirus assembly and egress pathways are known, the precise molecular and spatiotemporal details remain unclear. In order to study this aspect of HSV-1 infection, we engineered a recombinant HSV-1 strain expressing a pH-sensitive reporter, gM-pHluorin. Using a variety of fluorescent microscopy modalities, we can detect individual virus particles undergoing intracellular transport and exocytosis at the plasma membrane. We show that particles exit from epithelial cells individually, not bulk release of many particles at once, as has been reported for other viruses. In multiple cell types, HSV-1 particles accumulate over time at the cell periphery and cell-cell contacts. We show that this accumulation effect is the result of individual particles undergoing exocytosis at preferential sites and that these egress sites can contribute to cell-cell spread. We also show that the viral membrane proteins gE, gI, and US9, which have important functions in intracellular transport in neurons, are not required for preferential egress and clustering in non-neuronal cells. Importantly, by comparing HSV-1 to a related alpha herpesvirus, pseudorabies virus, we show that this preferential exocytosis and clustering effect are cell type dependent, not virus dependent. This preferential egress and clustering appear to be the result of the arrangement of the microtubule cytoskeleton, as virus particles co-accumulate at the same cell protrusions as an exogenous plus end-directed kinesin motor.IMPORTANCEAlpha herpesviruses produce lifelong infections in their human and animal hosts. The majority of people in the world are infected with herpes simplex virus 1 (HSV-1), which typically causes recurrent oral or genital lesions. However, HSV-1 can also spread to the central nervous system, causing severe encephalitis, and might also contribute to the development of neurodegenerative diseases. Many of the steps of how these viruses infect and replicate inside host cells are known in depth, but the final step, exiting from the infected cell, is not fully understood. In this study, we engineered a novel variant of HSV-1 that allows us to visualize how individual virus particles exit from infected cells. With this imaging assay, we investigated preferential egress site formation in certain cell types and their contribution to the cell-cell spread of HSV-1.
Asunto(s)
Exocitosis , Herpes Simple , Herpesvirus Humano 1 , Liberación del Virus , Animales , Humanos , Transporte Biológico , Herpes Simple/virología , Herpesvirus Humano 1/fisiología , NeuronasRESUMEN
Herpes simplex virus 1 (HSV-1) is an alpha herpesvirus that infects a majority of the world population. The mechanisms and cellular host factors involved in the intracellular transport and exocytosis of HSV-1 particles are not fully understood. To elucidate these late steps in the replication cycle, we developed a live-cell fluorescence microscopy assay of HSV-1 virion intracellular trafficking and exocytosis. This method allows us to track individual virus particles and identify the precise moment and location of particle exocytosis using a pH-sensitive reporter. We show that HSV-1 uses the host cell's post-Golgi secretory pathway during egress. The small GTPase, Rab6, binds to nascent secretory vesicles at the trans-Golgi network and plays important, but non-essential, roles in vesicle traffic and exocytosis at the plasma membrane, therefore making it a useful marker of the Golgi and post-Golgi secretory pathway. We show that HSV-1 particles colocalize with Rab6a in the region of the Golgi, cotraffic with Rab6a to the cell periphery, and undergo exocytosis from Rab6a vesicles. Consistent with previous reports, we find that HSV-1 particles accumulate at preferential egress sites in infected cells. The secretory pathway mediates this preferential/polarized egress, since Rab6a vesicles accumulate near the plasma membrane similarly in uninfected cells. These data suggest that, following particle envelopment, HSV-1 egress follows a pre-existing cellular secretory pathway to exit infected cells rather than novel, virus-induced mechanisms. IMPORTANCE: Herpes simplex virus 1 (HSV-1) infects a majority of people. It establishes a life-long latent infection and occasionally reactivates, typically causing characteristic oral or genital lesions. Rarely in healthy natural hosts, but more commonly in zoonotic infections and in elderly, newborn, or immunocompromised patients, HSV-1 can cause severe herpes encephalitis. The precise cellular mechanisms used by HSV-1 remain an important area of research. In particular, the egress pathways that newly assembled virus particles use to exit from infected cells are unclear. In this study, we used fluorescence microscopy to visualize individual virus particles exiting from cells and found that HSV-1 particles use the pre-existing cellular secretory pathway.
RESUMEN
Recent advances in the field of immuno-oncology have brought transformative changes in the management of cancer patients. The immune profile of tumours has been found to have key value in predicting disease prognosis and treatment response in various cancers. Multiplex immunohistochemistry and immunofluorescence have emerged as potent tools for the simultaneous detection of multiple protein biomarkers in a single tissue section, thereby expanding opportunities for molecular and immune profiling while preserving tissue samples. By establishing the phenotype of individual tumour cells when distributed within a mixed cell population, the identification of clinically relevant biomarkers with high-throughput multiplex immunophenotyping of tumour samples has great potential to guide appropriate treatment choices. Moreover, the emergence of novel multi-marker imaging approaches can now provide unprecedented insights into the tumour microenvironment, including the potential interplay between various cell types. However, there are significant challenges to widespread integration of these technologies in daily research and clinical practice. This review addresses the challenges and potential solutions within a structured framework of action from a regulatory and clinical trial perspective. New developments within the field of immunophenotyping using multiplexed tissue imaging platforms and associated digital pathology are also described, with a specific focus on translational implications across different subtypes of cancer. © 2024 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.