Herpesviruses mimic zygotic genome activation to promote viral replication.

DUX4 is a germline transcription factor and a master regulator of zygotic genome activation. During early embryogenesis, DUX4 is crucial for maternal to zygotic transition at the 2-8-cell stage in order to overcome silencing of genes and enable transcription from the zygotic genome. In adult somatic cells, DUX4 expression is silenced and its activation in adult muscle cells causes the genetic disorder Facioscapulohumeral Muscular Dystrophy (FSHD). Here we show that herpesviruses from alpha-, beta- and gamma-herpesvirus subfamilies as well as papillomaviruses actively induce DUX4 expression to promote viral transcription and replication. We demonstrate that HSV-1 immediate early proteins directly induce expression of DUX4 and its target genes including endogenous retroelements, which mimics zygotic genome activation. We further show that DUX4 directly binds to the viral genome and promotes viral transcription. DUX4 is functionally required for herpesvirus infection, since genetic depletion of DUX4 by CRISPR/Cas9 abrogates viral replication. Our results show that herpesviruses induce DUX4 expression and its downstream germline-specific genes and retroelements, thus mimicking an early embryonic-like transcriptional program that prevents epigenetic silencing of the viral genome and facilitates herpesviral gene expression.

OrganoID: A versatile deep learning platform for tracking and analysis of single-organoid dynamics.

Organoids have immense potential as ex vivo disease models for drug discovery and personalized drug screening. Dynamic changes in individual organoid morphology, number, and size can indicate important drug responses. However, these metrics are difficult and labor-intensive to obtain for high-throughput image datasets. Here, we present OrganoID, a robust image analysis platform that automatically recognizes, labels, and tracks single organoids, pixel-by-pixel, in brightfield and phase-contrast microscopy experiments. The platform was trained on images of pancreatic cancer organoids and validated on separate images of pancreatic, lung, colon, and adenoid cystic carcinoma organoids, which showed excellent agreement with manual measurements of organoid count (95%) and size (97%) without any parameter adjustments. Single-organoid tracking accuracy remained above 89% over a four-day time-lapse microscopy study. Automated single-organoid morphology analysis of a chemotherapy dose-response experiment identified strong dose effect sizes on organoid circularity, solidity, and eccentricity. OrganoID enables straightforward, detailed, and accurate image analysis to accelerate the use of organoids in high-throughput, data-intensive biomedical applications.

Cannabidiol inhibits SARS-CoV-2 replication through induction of the host ER stress and innate immune responses.

The spread of SARS-CoV-2 and ongoing COVID-19 pandemic underscores the need for new treatments. Here we report that cannabidiol (CBD) inhibits infection of SARS-CoV-2 in cells and mice. CBD and its metabolite 7-OH-CBD, but not THC or other congeneric cannabinoids tested, potently block SARS-CoV-2 replication in lung epithelial cells. CBD acts after viral entry, inhibiting viral gene expression and reversing many effects of SARS-CoV-2 on host gene transcription. CBD inhibits SARS-CoV-2 replication in part by up-regulating the host IRE1α RNase endoplasmic reticulum (ER) stress response and interferon signaling pathways. In matched groups of human patients from the National COVID Cohort Collaborative, CBD (100 mg/ml oral solution per medical records) had a significant negative association with positive SARS-CoV-2 tests. This study highlights CBD as a potential preventative agent for early-stage SARS-CoV-2 infection and merits future clinical trials. We caution against use of non-medical formulations including edibles, inhalants or topicals as a preventative or treatment therapy at the present time.

High-throughput RNA sequencing of paraformaldehyde-fixed single cells.

Single-cell transcriptomic studies that require intracellular protein staining, rare cell sorting, or inactivation of infectious pathogens are severely limited. This is because current high-throughput single-cell RNA sequencing methods are either incompatible with or necessitate laborious sample preprocessing for paraformaldehyde treatment, a common tissue and cell fixation and preservation technique. Here we present FD-seq (Fixed Droplet RNA sequencing), a high-throughput method for droplet-based RNA sequencing of paraformaldehyde-fixed, permeabilized and sorted single cells. We show that FD-seq preserves the RNA integrity and relative gene expression levels after fixation and permeabilization. Furthermore, FD-seq can detect a higher number of genes and transcripts than methanol fixation. We first apply FD-seq to analyze a rare subpopulation of cells supporting lytic reactivation of the human tumor virus KSHV, and identify TMEM119 as a potential host factor that mediates viral reactivation. Second, we find that infection with the human betacoronavirus OC43 leads to upregulation of pro-inflammatory pathways in cells that are exposed to the virus but fail to express high levels of viral genes. FD-seq thus enables integrating phenotypic with transcriptomic information in rare cell subpopulations, and preserving and inactivating pathogenic samples.

Masitinib is a broad coronavirus 3CL inhibitor that blocks replication of SARS-CoV-2.

There is an urgent need for antiviral agents that treat severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. We screened a library of 1900 clinically safe drugs against OC43, a human beta coronavirus that causes the common cold, and evaluated the top hits against SARS-CoV-2. Twenty drugs significantly inhibited replication of both viruses in cultured human cells. Eight of these drugs inhibited the activity of the SARS-CoV-2 main protease, 3CLpro, with the most potent being masitinib, an orally bioavailable tyrosine kinase inhibitor. X-ray crystallography and biochemistry show that masitinib acts as a competitive inhibitor of 3CLpro. Mice infected with SARS-CoV-2 and then treated with masitinib showed >200-fold reduction in viral titers in the lungs and nose, as well as reduced lung inflammation. Masitinib was also effective in vitro against all tested variants of concern (B.1.1.7, B.1.351, and P.1).

NF-κB responds to absolute differences in cytokine concentrations.

Cells receive a wide range of dynamic signaling inputs during immune regulation, but how gene regulatory networks measure such dynamic inputs is not well understood. Here, we used microfluidic single-cell analysis and mathematical modeling to study how the NF-κB pathway responds to immune inputs that vary over time such as increasing, decreasing, or fluctuating cytokine signals. We found that NF-κB activity responded to the absolute difference in cytokine concentration and not to the concentration itself. Our analyses revealed that negative feedback by the regulatory proteins A20 and IκBα enabled differential responses to changes in cytokine dose by providing a short-term memory of previous cytokine concentrations and by continuously resetting kinase cycling and receptor abundance. Investigation of NF-κB target gene expression showed that cells exhibited distinct transcriptional responses under different dynamic cytokine profiles. Our results demonstrate how cells use simple network motifs and transcription factor dynamics to efficiently extract information from complex signaling environments.

Discovery of SARS-CoV-2 main protease inhibitors using a synthesis-directed de novo design model.

The SARS-CoV-2 main viral protease (Mpro) is an attractive target for antivirals given its distinctiveness from host proteases, essentiality in the viral life cycle and conservation across coronaviridae. We launched the COVID Moonshot initiative to rapidly develop patent-free antivirals with open science and open data. Here we report the use of machine learning for de novo design, coupled with synthesis route prediction, in our campaign. We discover novel chemical scaffolds active in biochemical and live virus assays, synthesized with model generated routes.

Fixed single-cell RNA sequencing for understanding virus infection and host response.

Single-cell transcriptomic studies that require intracellular protein staining, rare cell sorting, or inactivation of infectious pathogens are severely limited because current high-throughput RNA sequencing methods are incompatible with paraformaldehyde treatment, a common tissue and cell fixation and preservation technique. Here we present FD-seq, a high-throughput method for droplet-based RNA sequencing of paraformaldehyde-fixed, stained and sorted single-cells. We show that FD-seq preserves the mRNA integrity and relative abundances during fixation and subsequent cell retrieval. Furthermore, FD-seq detects a higher number of genes and transcripts than methanol fixation. We applied FD-seq to investigate two important questions in Virology. First, by analyzing a rare population of cells supporting lytic reactivation of the human tumor virus KSHV, we identified TMEM119 as a host factor that mediates viral reactivation. Second, we found that upon infection with the betacoronavirus OC43, which causes the common cold and is a close relative of SARS-CoV-2, pro-inflammatory pathways are primarily upregulated in lowly-infected cells that are exposed to the virus but fail to express high levels of viral genes. FD-seq thus enables integrating phenotypic with transcriptomic information in rare cell populations, and preserving and inactivating pathogenic samples that cannot be handled under regular biosafety measures.

Automated microfluidic platform for dynamic and combinatorial drug screening of tumor organoids.

Three-dimensional (3D) cell culture technologies, such as organoids, are physiologically relevant models for basic and clinical applications. Automated microfluidics offers advantages in high-throughput and precision analysis of cells but is not yet compatible with organoids. Here, we present an automated, high-throughput, microfluidic 3D organoid culture and analysis system to facilitate preclinical research and personalized therapies. Our system provides combinatorial and dynamic drug treatments to hundreds of cultures and enables real-time analysis of organoids. We validate our system by performing individual, combinatorial, and sequential drug screens on human-derived pancreatic tumor organoids. We observe significant differences in the response of individual patient-based organoids to drug treatments and find that temporally-modified drug treatments can be more effective than constant-dose monotherapy or combination therapy in vitro. This integrated platform advances organoids models to screen and mirror real patient treatment courses with potential to facilitate treatment decisions for personalized therapy.

Drug repurposing screen identifies masitinib as a 3CLpro inhibitor that blocks replication of SARS-CoV-2 in vitro.

There is an urgent need for anti-viral agents that treat SARS-CoV-2 infection. The shortest path to clinical use is repurposing of drugs that have an established safety profile in humans. Here, we first screened a library of 1,900 clinically safe drugs for inhibiting replication of OC43, a human beta-coronavirus that causes the common-cold and is a relative of SARS-CoV-2, and identified 108 effective drugs. We further evaluated the top 26 hits and determined their ability to inhibit SARS-CoV-2, as well as other pathogenic RNA viruses. 20 of the 26 drugs significantly inhibited SARS-CoV-2 replication in human lung cells (A549 epithelial cell line), with EC50 values ranging from 0.1 to 8 micromolar. We investigated the mechanism of action for these and found that masitinib, a drug originally developed as a tyrosine-kinase inhibitor for cancer treatment, strongly inhibited the activity of the SARS-CoV-2 main protease 3CLpro. X-ray crystallography revealed that masitinib directly binds to the active site of 3CLpro, thereby blocking its enzymatic activity. Mastinib also inhibited the related viral protease of picornaviruses and blocked picornaviruses replication. Thus, our results show that masitinib has broad anti-viral activity against two distinct beta-coronaviruses and multiple picornaviruses that cause human disease and is a strong candidate for clinical trials to treat SARS-CoV-2 infection.

Ultrasensitive digital quantification of cytokines and bacteria predicts septic shock outcomes.

Quantification of pathogen and host biomarkers is essential for the diagnosis, monitoring, and treatment of infectious diseases. Here, we demonstrate sensitive and rapid quantification of bacterial load and cytokines from human biological samples to generate actionable hypotheses. Our digital assay measures IL-6 and TNF-α proteins, gram-negative (GN) and gram-positive (GP) bacterial DNA, and the antibiotic-resistance gene blaTEM with femtomolar sensitivity. We use our method to characterize bronchoalveolar lavage fluid from patients with asthma, and find elevated GN bacteria and IL-6 levels compared to healthy subjects. We then analyze plasma from patients with septic shock and find that increasing levels of IL-6 and blaTEM are associated with mortality, while decreasing IL-6 levels are associated with recovery. Surprisingly, lower GN bacteria levels are associated with higher probability of death. Applying decision-tree analysis to our measurements, we are able to predict mortality and rate of recovery from septic shock with over 90% accuracy.

Ultra-multiplexed analysis of single-cell dynamics reveals logic rules in differentiation.

Dynamical control of cellular microenvironments is highly desirable to study complex processes such as stem cell differentiation and immune signaling. We present an ultra-multiplexed microfluidic system for high-throughput single-cell analysis in precisely defined dynamic signaling environments. Our system delivers combinatorial and time-varying signals to 1500 independently programmable culture chambers in week-long live-cell experiments by performing nearly 106 pipetting steps, where single cells, two-dimensional (2D) populations, or 3D neurospheres are chemically stimulated and tracked. Using our system and statistical analysis, we investigated the signaling landscape of neural stem cell differentiation and discovered "cellular logic rules" that revealed the critical role of signal timing and sequence in cell fate decisions. We find synergistic and antagonistic signal interactions and show that differentiation pathways are highly redundant. Our system allows dissection of hidden aspects of cellular dynamics and enables accelerated biological discovery.

Automated Microfluidic System for Dynamic Stimulation and Tracking of Single Cells.

Dynamic environments determine cell fate decisions and function. Understanding the relationship between extrinsic signals on cellular responses and cell fate requires the ability to dynamically change environmental inputs in vitro, while continuously observing individual cells over extended periods of time. This is challenging for nonadherent cells, such as hematopoietic stem and progenitor cells, because media flow displaces and disturbs such cells, preventing culture and tracking of single cells. Here, we present a programmable microfluidic system designed for the long-term culture and time-lapse imaging of nonadherent cells in dynamically changing cell culture conditions without losing track of individual cells. The dynamic, valve-controlled design permits targeted seeding of cells in up to 48 independently controlled culture chambers, each providing sufficient space for long-term cell colony expansion. Diffusion-based media exchange occurs rapidly and minimizes displacement of cells and eliminates shear stress. The chip was successfully tested with long-term culture and tracking of primary hematopoietic stem and progenitor cells, and murine embryonic stem cells. This system will have important applications to analyze dynamic signaling inputs controlling fate choices.

Integrated platform for cell culture and dynamic quantification of cell secretion.

We developed an automated microfluidic chip that can measure dynamic cytokine secretion and transcription factor activation from cells responding to time-varying stimuli. Our chip patterns antibodies, exposes cells to time-varying inputs, measures cell secretion dynamics, and quantifies secretion all in the same platform. Secretion dynamics are measured using micrometer-sized immunoassays patterned directly inside the chip. All processes are automated, so that no user input is needed for conducting a complete cycle of device preparation, cell experiments, and secretion quantification. Using this system, we simulated an immune response by exposing cells to stimuli indicative of chronic and increasing inflammation. Specifically, we quantified how macrophages respond to changing levels of the bacterial ligand LPS, in terms of transcription factor NF-κB activity and TNF cytokine secretion. The integration of assay preparation with experimental automation of our system simplifies protocols for measuring cell responses to dynamic and physiologically relevant conditions and enables simpler and more error free means of microfluidic cellular investigations.

Noise Induces Hopping between NF-κB Entrainment Modes.

Oscillations and noise drive many processes in biology, but how both affect the activity of the transcription factor nuclear factor κB (NF-κB) is not understood. Here, we observe that when NF-κB oscillations are entrained by periodic tumor necrosis factor (TNF) inputs in experiments, NF-κB exhibits jumps between frequency modes, a phenomenon we call "cellular mode-hopping." By comparing stochastic simulations of NF-κB oscillations to deterministic simulations conducted inside and outside the chaotic regime of parameter space, we show that noise facilitates mode-hopping in all regimes. However, when the deterministic system is driven by chaotic dynamics, hops between modes are erratic and short-lived, whereas in experiments, the system spends several periods in one entrainment mode before hopping and rarely visits more than two modes. The experimental behavior matches our simulations of noise-induced mode-hopping outside the chaotic regime. We suggest that mode-hopping is a mechanism by which different NF-κB-dependent genes under frequency control can be expressed at different times.

A microfluidic device for measuring cell migration towards substrate-bound and soluble chemokine gradients.

Cellular locomotion is a central hallmark of eukaryotic life. It is governed by cell-extrinsic molecular factors, which can either emerge in the soluble phase or as immobilized, often adhesive ligands. To encode for direction, every cue must be present as a spatial or temporal gradient. Here, we developed a microfluidic chamber that allows measurement of cell migration in combined response to surface immobilized and soluble molecular gradients. As a proof of principle we study the response of dendritic cells to their major guidance cues, chemokines. The majority of data on chemokine gradient sensing is based on in vitro studies employing soluble gradients. Despite evidence suggesting that in vivo chemokines are often immobilized to sugar residues, limited information is available how cells respond to immobilized chemokines. We tracked migration of dendritic cells towards immobilized gradients of the chemokine CCL21 and varying superimposed soluble gradients of CCL19. Differential migratory patterns illustrate the potential of our setup to quantitatively study the competitive response to both types of gradients. Beyond chemokines our approach is broadly applicable to alternative systems of chemo- and haptotaxis such as cells migrating along gradients of adhesion receptor ligands vs. any soluble cue.

High-Content Quantification of Single-Cell Immune Dynamics.

Cells receive time-varying signals from the environment and generate functional responses by secreting their own signaling molecules. Characterizing dynamic input-output relationships in single cells is crucial for understanding and modeling cellular systems. We developed an automated microfluidic system that delivers precisely defined dynamical inputs to individual living cells and simultaneously measures key immune parameters dynamically. Our system combines nanoliter immunoassays, microfluidic input generation, and time-lapse microscopy, enabling study of previously untestable aspects of immunity by measuring time-dependent cytokine secretion and transcription factor activity from single cells stimulated with dynamic inflammatory inputs. Employing this system to analyze macrophage signal processing under pathogen inputs, we found that the dynamics of TNF secretion are highly heterogeneous and surprisingly uncorrelated with the dynamics of NF-κB, the transcription factor controlling TNF production. Computational modeling of the LPS/TLR4 pathway shows that post-transcriptional regulation by TRIF is a key determinant of noisy and uncorrelated TNF secretion dynamics in single macrophages.

Single-Cell Analysis: The Differences That Kill.

Using single-cell RNA sequencing, Avraham et al. investigate how variability in macrophage response to infection is controlled by variability within the pathogen population. They find that heterogeneous expression of the Salmonella virulence factor PhoP and subsequent cell-wall modifications lead to the bimodal induction of the interferon-response in infected macrophages.

Automated co-culture system for spatiotemporal analysis of cell-to-cell communication.

We present a microfluidic co-culture system that generates localized and precisely formulated immune signals among a population of cells, enabling spatiotemporal analysis of paracrine signal transmission between different cell types. The automated system allows us to create temporally modulated chemical inputs that can be delivered to single signal-transmitting and receiving cells in a highly controlled way. Using this system we stimulated a single macrophage with brief pulses of bacterial LPS and observed the macrophage transmitted TNF signal propagating in a population of fibroblasts via NF-κB activation. The signal receiving fibroblasts transformed the TNF signal into a spatiotemporally distributed NF-κB output, recapitulating the initiation of immune response to bacterial infection.

Noise facilitates transcriptional control under dynamic inputs.

Cells must respond sensitively to time-varying inputs in complex signaling environments. To understand how signaling networks process dynamic inputs into gene expression outputs and the role of noise in cellular information processing, we studied the immune pathway NF-κB under periodic cytokine inputs using microfluidic single-cell measurements and stochastic modeling. We find that NF-κB dynamics in fibroblasts synchronize with oscillating TNF signal and become entrained, leading to significantly increased NF-κB oscillation amplitude and mRNA output compared to non-entrained response. Simulations show that intrinsic biochemical noise in individual cells improves NF-κB oscillation and entrainment, whereas cell-to-cell variability in NF-κB natural frequency creates population robustness, together enabling entrainment over a wider range of dynamic inputs. This wide range is confirmed by experiments where entrained cells were measured under all input periods. These results indicate that synergy between oscillation and noise allows cells to achieve efficient gene expression in dynamically changing signaling environments.