Unhealthy Cells Research Articles

Mechanical Torque Promotes Bipolarity of the Mitotic Spindle Through Multi-centrosomal Clustering.

Intracellular forces shape cellular organization and function. One example is the mitotic spindle, a cellular machine consisting of multiple chromosomes and centrosomes which interact via dynamic microtubule filaments and motor proteins, resulting in complicated spatially dependent forces. For a cell to divide properly, it is important for the spindle to be bipolar, with chromosomes at the center and multiple centrosomes clustered into two 'poles' at opposite sides of the chromosomes. Experimental observations show that in unhealthy cells, the spindle can take on a variety of patterns. What forces drive each of these patterns? It is known that attraction between centrosomes is key to bipolarity, but what prevents the centrosomes from collapsing into a monopolar configuration? Here, we explore the hypothesis that torque rotating chromosome arms into orientations perpendicular to the centrosome-centromere vector promotes spindle bipolarity. To test this hypothesis, we construct a pairwise-interaction model of the spindle. On a continuum version of the model, an integro-PDE system, we perform linear stability analysis and construct numerical solutions which display a variety of spatial patterns. We also simulate a discrete particle model resulting in a phase diagram that confirms that the spindle bipolarity emerges most robustly with torque. Altogether, our results suggest that rotational forces may play an important role in dictating spindle patterning.

Attention-based Long Short Term Memory Model for DNA Damage Prediction in Mammalian Cells

The understanding of DNA damage intensity – concentration-level is critical for biological and biomedical research, such as cellular homeostasis, tumor suppression, immunity, and gametogenesis. Therefore, recognizing and quantifying DNA damage intensity levels is a substantial issue, which requires further robust and effective approaches. DNA damage has several intensity levels. These levels of DNA damage in malignant cells and in other unhealthy cells are significant in the assessment of lesion stages located in normal cells. There is a need to get more insight from the available biological data to predict, explore and classify DNA damage intensity levels. Herein, the development process relied on the available biological dataset related to DNA damage signaling pathways, which plays a crucial role in DNA damage in the mammalian cell system. The biological dataset that was used in the proposed model consists of 15000 records intensity – concentration-level for a set of five proteins which regulate DNA damage. This research paper proposes an innovative deep learning model, which consists of an attention-based long short term-memory (AT-LSTM) model for DNA damage multi class predictions. The proposed model splits the prediction procedure into dual stages. For the first stage, we adopt the related feature sequences which are inserted as input to the LSTM neural network. In the next stage, the attention feature is applied efficiently to adopt the related feature sequences which are inserted as input to the softmax layer for prediction in the following frame. Our developed framework not only solves the long-term dependence problem of prediction effectively, but also enhances the interpretability of the prediction methods that was established on the neural network. We conducted a novel proposed model on big and complex biological datasets to perform prediction and multi classification tasks. Indeed, the (AT-LSTM) model has the ability to predict and classify the DNA damage in several classes: No-Damage, Low-damage, Medium-damage, High-damage, and Excess-damage. The experimental results show that our framework for DNA damage intensity level can be considered as state of the art for the biological DNA damage prediction domain.

Mapping blood biochemistry by Raman spectroscopy at the cellular level.

We report how Raman difference imaging provides insight on cellular biochemistry in vivo as a function of sub-cellular dimensions and the cellular environment. We show that this approach offers a sensitive diagnostic to address blood biochemistry at the cellular level. We examine Raman microscopic images of the distribution of the different hemoglobins in both healthy (discocyte) and unhealthy (echinocyte) blood cells and interpret these images using pre-calculated, accurate pre-resonant Raman tensors for scattering intensities specific to hemoglobins. These tensors are developed from theoretical calculations of models of the oxy, deoxy and met forms of heme benchmarked against the experimental visible spectra of the corresponding hemoglobins. The calculations also enable assignments of the electronic transitions responsible for the colour of blood: these are mainly ligand to metal charge transfer transitions.

Establishing intranasal administration as an alternative to intravitreal delivery of fluorescent annexin

AbstractPurposeDARC (detection of apoptosing retinal cells) facilitates in vivo assessment of retinal pathology using a confocal laser scanning ophthalmoscope. The technology uses fluorescent annexin to mark unhealthy cells in the retina. In vivo imaging of intravitreally administered DARC allows for a unique assessment of neuronal health, applicable to a broad range of neurodegenerative pathologies. To avoid both the potential complications and discomfort arising from intravitreal administration, intranasal delivery of DARC was investigated as an alternative route of delivery.Methods5 female 3xTg transgenic Alzheimer’s disease (3xTg‐AD) model mice were used as a model of retinal cell death and 5 C57 mice were used as healthy controls (all animals from The Jackson Laboratory). Intranasal DARC administration involved restraining the animal and applying 5 µL of DARC to each nostril. Retinas were imaged in vivo at baseline and 2 hours after DARC administration a Multiline Spectralis OCT. Animals were then sacrificed, and the retinas were extracted, fixed, and imaged with fluorescent microscopy. Spots were counted using an automated image analysis script for in vivo images.ResultsIntranasal DARC demonstrated discrimination between healthy and diseased eyes in vivo (significantly more spots in disease; p < 0.05) and produced images of similar quality to those acquired from animals receiving intravitreal DARC. A higher intranasal DARC dose was required compared to intravitreal administration (approximately 10‐fold increase).ConclusionsIntranasal DARC has been shown as a viable alternative to intravitreal administration, thus helping to refine animal procedures. Optimisation of an intranasal buffer to enhance delivery and reduce dose, followed by expansion to rat models are to be established in future work. In the long term, standardisation of administration route to intranasal across animal and human applications may help to improve the applicability of DARC‐based research.

Silencing Survivin: a Key Therapeutic Strategy for Cardiac Hypertrophy.

Cardiac hypertrophy, in its aspects of localized thickening of the interventricular septum and concentric increase of the left ventricle, constitutes a risk factor of heart failure. Myocardial hypertrophy, in the presence of different degree of myocardial fibrosis, is paralleled by significant molecular, cellular, and histological changes inducing alteration of cardiac extracellular matrix composition as well as sarcomeres and cytoskeleton remodeling. Previous studies indicate osteopontin (OPN) and more recently survivin (SURV) overexpression as the hallmarks of heart failure although SURV function in the heart is not completely clarified. In this study, we investigated the involvement of SURV in intracellular signaling of hypertrophic cardiomyocytes and the impact of its transcriptional silencing, laying the foundation for novel target gene therapy in cardiac hypertrophy. Oligonucleotide-based molecules, like theranostic optical nanosensors (molecular beacons) and siRNAs, targeting SURV and OPN mRNAs, were developed. Their diagnostic and therapeutic potential was evaluated in vitro in hypertrophic FGF23-induced human cardiomyocytes and in vivo in transverse aortic constriction hypertrophic mouse model. Engineered erythrocyte was used as shuttle to selectively target and transfer siRNA molecules into unhealthy cardiac cells in vivo. The results highlight how the SURV knockdown could negatively influence the expression of genes involved in myocardial fibrosis in vitro and restores structural, functional, and morphometric features in vivo. Together, these data suggested that SURV is a key factor in inducing cardiomyocytes hypertrophy, and its shutdown is crucial in slowing disease progression as well as reversing cardiac hypertrophy. In the perspective, targeted delivery of siRNAs through engineered erythrocytes can represent a promising therapeutic strategy to treat cardiac hypertrophy. Theranostic SURV molecular beacon (MB-SURV), transfected into FGF23-induced hypertrophic human cardiomyocytes, significantly dampened SURV overexpression. SURV down-regulation determines the tuning down of MMP9, TIMP1 and TIMP4 extracellular matrix remodeling factors while induces the overexpression of the cardioprotective MCAD factor, which counterbalance the absence of pro-survival and anti-apoptotic SURV activity to protect cardiomyocytes from death. In transverse aortic constriction (TAC) mouse model, the SURV silencing restores the LV mass levels to values not different from the sham group and counteracts the progressive decline of EF, maintaining its values always higher with respect to TAC group. These data demonstrate the central role of SURV in the cardiac reverse remodeling and its therapeutic potential to reverse cardiac hypertrophy.

Automatic Cell Nucleus Segmentation Using Superpixels and Clustering Methods in Histopathological Images

It is seen that there is an increase in cancer and cancer-related deaths day by day. Early diagnosis is vital for the early treatment of the cancerous area. Computer-aided programs allow for early diagnosis of unhealthy cells that specialist pathologists diagnose as a result of efforts. In this study, kMeans and Fuzzy C Means methods, which are among the global segmentation methods, and SLIC, Quickshift, Felzenszwalb, Watershed and ERS algorithms, which are among the superpixel segmentation methods, were used for automatic cell nucleus detection in high resolution histopathological images with computer aided programs. As a result of the study, the success performances of the segmentation algorithms were analyzed and evaluated. It is seen that better success is obtained in watershed and FCM algorithms in high resolution histopathological images used. Quickshift and SLIC methods gave better results in terms of precision. It is seen that there are k-Means and FCM algorithms that provide the best performance in F measure (F-M) and the true negative rate (TNR) is more successful in Quickshift, k-Means and SLIC methods.

A biotin-guided two-photon fluorescent probe for detection of hydrogen peroxide in cancer cells ferroptosis process

Hydrogen peroxide (H2O2) plays a vital role in organism due to its strong oxidizability, especially in resisting the invasion of pathogens. Cancer cells have abnormal concentrations of hydrogen peroxide due to their disordered reproduction. In complex biological systems, however, conventional fluorescent probes based solely on their fluorescent response to abnormal H2O2 overexpression in cancer cells are not enough to distinguish cancer cells from other unhealthy or immune cells. Therefore, it is necessary to develop other methods to allow the probe to selectively enter the cancer cells and perform fluorescence imaging of the hydrogen peroxide in the cancer cells. Herein, we developed a biotin-guided, two-photon fluorescent probe (BT-HP) for sensitive detection of H2O2 in cancer cells. Through the study on the properties of the probe, it was found that the probe can selectively enter cancer cells. The depth penetration imaging of H2O2 in cancer cells and tumor tissues by two-photon microscope proves the potential of the probe BT-HP as a tumor targeting H2O2 biosensor. The probe was further applied to detect hydrogen peroxide in cancer cells during the ferroptosis process.

Identifying the predictors of Covid-19 infection outcomes and development of prediction models

BackgroundThe infection of Corona Virus Disease (Covid-19) is challenging health problems worldwide. COVID-19 pandemic is spreading all over the world with the number of infected cases increased to 54.4 million with 1.32 million deaths. Different types of statistical models have been developed to predict viral infection and multiple studies have compared the performance of these predictive models, but results were not consistent. This study aimed to develop and provide easy to use model to predict the Covid-19 infection severity in the patients and to help understanding the patient’s condition. MethodsThis study analyzed simulated data obtained from the large database for 340 patients with an active Covid-19 infection. The study identified predictors of Covid-19 outcomes that may be measured in two different ways: the total T-cell levels in the blood with T-cell subsets and number of cells in the blood infected with virus. All measures are relatively unobtrusive as they only require a blood sample, however there is a significant laboratory cost implications for measuring the number of cells infected with virus. This study used methodological approach using two different methods showing how multiple regression and logistic regression can be used in the context of Covid-19 longitudinal data to develop the prediction models. ResultsThis study has identified the predictors of Covid-19 infection outcomes and developed prediction models. In the regression model of Total_T Cell, the predictors BMI, comorbidity and Total_Tcell were all associated with increased levels of infection severity (p < 0.001). For BMI, the mean % of unhealthy cells increased by 0.42 (95% CI 0.24 to 0.60) and comorbidity predictor has on average 8.3% more unhealthy liver cells than without comorbidity (95% CI — 2.9%–1.29%). The results of multivariate logistic regression model predicting the Covid-19 Infection severity were promising. The significant predictors were observed such as Age (OR 0.95, p = 0.02, 95% CI: 0.91–0.99), Helper T_cells (OR O.93, p = 0.03, 95% CI: 0.87–0.99), Basic_Tcell (OR 1.11, p = 0.001, 95% CI: 1.06–1.71) and Comorbidity (OR 0.41, p = 0.05, 95% CI: 0.16–1.07). ConclusionsIn this study recommendation has been provided to clinical researchers on the best way to use the various Covid-19 infections measures along with identifying other possible predictors of Covid-19 infection. It is imperative to monitor closely the T-cell subsets using prediction models that might provide valuable information about the patient’s condition during the treatment process.

COMPLEX FRACTIONAL-ORDER HIV DIFFUSION MODEL BASED ON AMPLITUDE EQUATIONS WITH TURING PATTERNS AND TURING INSTABILITY

A weakly nonlinear analysis provides a system constituting amplitude equations and its related analysis is capable of predicting parameter regimes with different patterns expected to co-exist in dynamical circumstances that exhibit complex fractional-order system characteristics. The Turing mechanism of pattern formation as a result of diffusion-induced instability of the homogeneous steady state is concerned with unpredictable conditions. The Turing instability caused by fractional diffusion in a Human Immunodeficiency Virus model has been addressed in this study. It is important that the effect of the Human Immunodeficiency Virus to the immune system can be modeled by the interaction of uninfected cells, unhealthy cells, virus particles and antigen-specific. Initially, all potential equilibrium points are defined and the stability of the interior equilibrium point is then evaluated using the Routh–Hurwitz criteria. The conditions for Turing instability are obtained by local equilibrium points with stability analysis. In the neighborhood of the Turing bifurcation point, weakly nonlinear analysis is employed to deduce the amplitude equations. After applying amplitude equations, it is observed that this system has a very rich dynamical behavior. The constraints for the formation of the patterns like a hexagon, spot, mixed and stripe patterns are identified for the amplitude equations by dynamic analysis. Furthermore, by using the numerical simulations, the theoretical results are verified. Within this framework, this study through the dynamical behavior of the complex system perspective and bifurcation point based on the viral death rate can provide the basis for several researchers working on Human Immunodeficiency Virus model through various aspects. Accordingly, the Turing bifurcation point and weakly nonlinear analysis employed within the complex fractional-order dynamics addressed herein are highly relevant experimentally since the related effects can be studied and applied concerning different mathematical, physical, engineering and biological models.

Refractive Index Imaging of Cellular Structures

Label free microscopic approaches have become a necessity to explore, image, and understand, complex biological systems with minimal sample modifications [1]. These innovative microscopes exploit the native photophysical processes present when light interacts with matter, presenting a plethora of options not only for introducing image contrast, but in providing information unobtainable with traditional approaches [2]. When paired with the recent and significant advances in computational approaches, label free imaging is a profoundly powerful tool to image biological systems in innovative ways. In particular, the way in which light is slowed when passing through a sample, known as it's phase shift, is a label-free paradigm particularly useful for biological samples. This is because the refractive index is essentially a relation of the different chemical or physical properties of the sample, and if obtained quantitatively can be used to characterize the contents and distribution of cellular contents [3]. In this work the phase information from our custom ptychographic microscope is compared and combined with traditional fluorescent images, as well as advanced label-free techniques [4], to extract refractive index information of healthy and unhealthy cells. Our results showcase the ability of ptychography to not only provide high quality images of samples, but to also deliver complimentary information about the processes within a cell, currently not able to be captured with standard high-resolution approaches.

Fluorescent Pyrazole Derivatives: An Attractive Scaffold for Biological Imaging Applications

Among the huge number of fluorescent compounds described recently, pyrazole derivatives could play a paramount role in the design of probes for bioimaging applications–an important and simple tool for modern biology because of their easy synthetic methodologies, remarkable optical properties and chelating points. In this mini-review, we highlighted some pyrazole derivatives that have shown remarkable performance in this area; from the detection of chromium (III) with limits of detection of 37 &amp;#215; 10&lt;sub&gt;-12&lt;/sub&gt; M to sensing glutathione in biological samples, as well as small molecule labeling of drugs and identifying unhealthy cells such as HeLa and labeling subcellular organelles. Evidently, this important class of N-heterocyclic compounds is part of interesting applications.

APAMARGAKSHARA IN THE MANAGEMENT OF CERVICAL EROSION – A PHARMACOLOGICAL REVIEW

Cervical erosion happens when cells that line the inside of cervix grow on the outside of cervix. That means the squamous epithelium of the cervix is replaced by columnar epithelium. Nowadays it is very common among women in reproductive age. The women with cervical erosion complaints of vaginal discharge, vulval itching, dyspareunia, low back ache etc. In the parallel medical field it is managed by electrocautery, cryotherapy and CO2 laser vaporization. This condition can be correlated with Garbhashayamukhagata Vrana or Karnini Yonivyapada. In Ayurveda, it is treated by Ksharakarma along with internal medications. Ksharakarma itself is sufficient to clear the wound and to promote the healing process. This reviewing is done to know the pharmacological effect of Ksharakarma using Apamarga Kshara. It concluded that the procedure (Ksharakarma) and the drug used to perform the procedure (Apamarga) have the capacity to enhance the reduction of severity of the condition and gradually lead to the complete cure of the same. It is due to the efficacy of Ksharakarma to clear the unhealthy epithelial cells and the presence of wound healing components like tannins, flavonoids, antioxidants etc. in Apamarga. In effect it has equivalent result as modern management, cost effective, easy procedure, brief procedure, no or less complications, less chances for the recurrence of the same.

The Global Dynamics of HIV Latency Model Including Cell-to-Cell Viral Transmission

HIV spreads by cell-to-cell transfer and the release of cell-free particles. A slightly more effective method of retroviral transmission is the direct cell-to-cell transfer of HIV, according to recent reports. Intracellular interaction between unhealthy and healthy cells, in combination with cytokine discharged by the cells included, may affect the susceptibility of a target resting CD4+T cell to HIV infection and the formation of latent infection. We suggest a class of HIV latency mathematical model, integrating both cell-free virus transmission and direct cell-to-cell diffusion to improve the understanding of the dynamics of the latent reservoirs. We incorporate four components in our model: the uninfected T cells, the latently infected T cells, the active-infected T cells and the HIV viruses. We examine the latency model by introducing the basic reproduction number. We first establish the non-negativity and boundedness of the solutions of the system, and then we investigate the global stability of the steady states. The diseased-free equilibrium is globally stable when the basic reproduction number is less than 1 and if the basic reproduction number is greater than 1, the diseased equilibrium exists and is globally stable. Numerical simulations are executed to interpret the theoretical outcomes and evaluate the relative contribution of latency fractions in the virus production and the HIV latent reservoir by providing estimates.

Live Imaging of Apoptotic Extrusion and Quantification of Apical Extrusion in Epithelial Cells.

Apoptotic cell death eliminates unhealthy cells and maintains homeostatic cell numbers within tissues. Epithelia, which serve as fundamental tissue barriers for the body, depend on a physical expulsion of dying cells (apoptotic cell extrusion) to remain sealed and intact. Apoptotic cell extrusion has been widely studied over recent years, with researchers using various approaches to induce apoptotic cell death. Unfortunately, the majority of chemical-based approaches for cell death induction rely on sporadically occurring apoptosis and extrusion, making imagining lengthy, often unsuccessful, and difficult to capture in high-quality images because of the frequent frame sampling needed to visualise the key molecular processes that drive extrusion. Here, we present a protocol that describes steps needed for laser-mediated induction of apoptosis in a cell of choice, followed by imaging of apoptotic extrusion in confluent monolayers of epithelial cells. Moreover, we provide the description of a new approach involving the mixing of labelled and unlabelled cells. In particular, this protocol characterises how cells surrounding apoptotic cells behave, with high spatial and temporal resolution. This can be achieved without the optical interference that apoptotic cells cause as they are physically expelled from the monolayer and move out of focus for imaging. Finally, the protocol is accompanied by detailed procedures describing cell preparation for apoptotic extrusion experiments, as well as post-acquisition analysis required to evaluate rates of successful extrusion.

TCR Recognition of Peptide-MHC-I: Rule Makers and Breakers.

T cells are a critical part of the adaptive immune system that are able to distinguish between healthy and unhealthy cells. Upon recognition of protein fragments (peptides), activated T cells will contribute to the immune response and help clear infection. The major histocompatibility complex (MHC) molecules, or human leukocyte antigens (HLA) in humans, bind these peptides to present them to T cells that recognise them with their surface T cell receptors (TCR). This recognition event is the first step that leads to T cell activation, and in turn can dictate disease outcomes. The visualisation of TCR interaction with pMHC using structural biology has been crucial in understanding this key event, unravelling the parameters that drive this interaction and their impact on the immune response. The last five years has been the most productive within the field, wherein half of current unique TCR–pMHC-I structures to date were determined within this time. Here, we review the new insights learned from these recent TCR–pMHC-I structures and their impact on T cell activation.

Senescence and Apoptosis During in vitro Embryo Development in a Bovine Model.

According to the World Health Organization, infertility affects up to 14% of couples under reproductive age, leading to an exponential rise in the use of assisted reproduction as a route for conceiving a baby. In the same way, thousands of embryos are produced in cattle and other farm animals annually, leading to increased numbers of individuals born. All reproductive manipulations entail deviations of natural phenotypes and genotypes, with in vitro embryo technologies perhaps showing the biggest effects, although these alterations are still emerging. Most of these indications have been provided by animal models, in particular the bovine species, due to its similarities to human early embryo development. Oocytes and embryos are highly sensitive to environmental stress in vivo and in vitro. Thus, during in vitro culture, a number of stressful conditions affect embryonic quality and viability, inducing subfertility and/or long-term consequences that may reach the offspring. A high proportion of the embryos produced in vitro are arrested at a species-specific stage of development during the first cell divisions. These arrested embryos do not show signs of programmed cell death during early cleavage stages. Instead, defective in vitro produced embryos would enter a permanent cell cycle arrest compatible with cellular senescence, in which they show active metabolism and high reactive oxygen species levels. Later in development, mainly during the morula and blastocyst stages, apoptosis would mediate the elimination of certain cells, accomplishing both a physiological role in to balancing cell proliferation and death, and a pathological role preventing the transmission of damaged cells with an altered genome. The latter would acquire relevant importance in in vitro produced embryos that are submitted to stressful environmental stimuli. In this article, we review the mechanisms mediating apoptosis and senescence during early embryo development, with a focus on in vitro produced bovine embryos. Additionally, we shed light on the protective role of senescence and apoptosis to ensure that unhealthy cells and early embryos do not progress in development, avoiding long-term detrimental effects.

Probing sulfatide-tissue lectin recognition with functionalized glycodendrimersomes.

SummaryThe small 3-O-sulfated galactose head group of sulfatides, an abundant glycosphingolipid class, poses the (sphinx-like) riddle on involvement of glycan bridging by tissue lectins (sugar code). First, synthesis of head group derivatives for functionalization of amphiphilic dendrimers is performed. Aggregation of resulting (biomimetic) vesicles, alone or in combination with lactose, demonstrates bridging by a tissue lectin (galectin-4). Physiologically, this can stabilize glycolipid-rich microdomains (rafts) and associate sulfatide-rich regions with specific glycoproteins. Further testing documents importance of heterobivalency and linker length. Structurally, sulfatide recognition by galectin-8 is shown to involve sphingosine's OH group as substitute for the 3′-hydroxyl of glucose of lactose. These discoveries underscore functionality of this small determinant on biomembranes intracellularly and on the cell surface. Moreover, they provide a role model to examine counterreceptor capacity of more complex glycans of glycosphingolipids and to start their bottom-up glycotope surface programming.

The Essence of Health and Longevity

The health of global societies is worsening; this is reflected not only in the increasing prevalence of co-morbidities in the population but also in already registered shortened lifespan. Systems science and the dynamic systems model have been used to study the core issues of unhealthy biologic systems, cascading down to cellular level. The still-evolving COVID-19 pandemic has exposed the vulnerabilities and spiraling penalties of unhealthy lifestyles. Dysfunctional immune system, a boundary, has been put in focus in this study, for its role in not only failing to protect but, through its components breakdown, also cause damage to the entire biologic system of human body; more than the ‘virus’, human decisions, and their impact on health, have been the significant upstream etiology of the pandemic because viruses favor unhealthy cells for their replication. The path to regain health, individually and collectively, is not in new drugs but in inculcating the importance of highly-structured decisions-consequences learning loop; in addition, interval training, spanning intensive physical exercise and selectivity of caloric and sensory input, benefits all levels of living systems-from cells to societies.

Highly Efficient Cell Membrane Tracker Based on a Solvatochromic Dye with Near-Infrared Emission.

The cell membrane is composed of a phospholipid bilayer with embedded proteins and maintains cell homeostasis through dynamic changes. An abnormal cell membrane shape could be a sign of unhealthy cells. Probes for subcellular fluorescence imaging that can identify the abnormal plasma membrane and record the dynamic changes are needed. Based on a solvatochromic dye with a near-infrared emission strategy, the amphipathic molecule (E)-2,2′-((4-(2-(4-(dicyanomethylene)-4H-chromen-2-yl)vinyl)phenyl)azanediyl)bis(ethane-1-sulfonic acid) (MRL) contained a hydrophilic sulfo group and a hydrophobic chromone group, which was designed and synthesized for staining the cell membrane and monitoring the morphology of the membranes under different conditions. MRL exhibited an excellent photostability and low cytotoxicity; when cells were incubated with MRL, cell membranes were specifically labeled. MRL is capable of long-term monitoring of the morphological changes of cell membrane.

Pooled CRISPR screens with imaging on microraft arrays reveals stress granule-regulatory factors.

Genetic screens using pooled CRISPR-based approaches are scalable and inexpensive, but restricted to standard readouts including survival, proliferation and sortable markers. However, many biologically relevant cell states involve cellular and subcellular changes that are only accessible by microscopic visualization, and are currently impossible to screen with pooled methods. Here we combine pooled CRISPR/Cas9 screening with microRaft array technology and high-content imaging to screen image-based phenotypes (CRaft-ID; CRISPR-based microRaft, followed by gRNA Identification). By isolating microRafts that contain genetic clones harboring individual guide RNAs, we identify RNA binding proteins (RBPs) that influence the formation of stress granules, punctate protein-RNA assemblies, that form during stress. To automate hit identification, we developed a machine-learning model trained on nuclear morphology to remove unhealthy cells or imaging artifacts. In doing so, we identified and validated previously uncharacterized RBPs that modulate stress granule abundance, highlighting the applicability of our approach to facilitate image-based pooled CRISPR screens.