Biology subjects

Tay, S.

Publications and source records attributed to Tay, S..

18 recordsLinked to original sources

bioRxiv2025

Massively multiplexed microfluidics maps combinatorial andsequential antibiotic responses in 3D

Current microbial culture and antibiotic susceptibility testing platforms lack dynamic chemical control and do not scale to high-throughput 3D culture. We present an automated microfluidic system that creates 512 independently programmable 3D hydrogel-culture chambers and delivers each chamber a distinct combinatorial and time-varying drug protocol. Automated workflows execute thousands of micro-pipetting operations and track 10,000 bacterial colonies via live-cell microscopy, and generate half a million single colony images to quantify growth, drug response and morphology. Using this system, we study how hydrogel stiffness and nutrient timing alter colony architecture and modulate antibiotic susceptibility and resistance. We then profile the efficacy of antibiotic pairs using simultaneous and sequential (temporally ordered) dosing across 2,700 drug-dose combinations, revealing synergy, antagonism and order dependent shifts in drug efficacy. This platform integrates serial and parallel multiplexing, automation, and dynamic 3D microenvironments to map the chemical and mechanical determinants of antibiotic response and drug interactions.

bioengineering↗

bioRxiv2025

Spatial proximity sequencing maps developmental dynamics in the germinal center

Spatial profiling of proteins and protein interactions is essential for immunology, signaling, development, and cancer. We present Spatial Proximity-Sequencing (Sprox-seq), a multi-omic technique that simultaneously measures proteins, protein complexes and mRNAs, where location of each molecule is also recorded. Sprox-seq profiled 32 proteins, 528 pairwise protein interactions and thousands of mRNAs across human tonsil tissues and germinal centers. Mapping protein interactions recapitulated RNA-defined tissue architecture in germinal centers, but also revealed much higher interaction complexity in the Light zone. Developmental trajectories inferred from protein interactions uncovered a B cell maturation pathway distinct from that inferred by RNA. Integrated protein-complex and mRNA analysis related spatially-enriched complexes with immune regulation and mitotic gene-expression pathways. Furthermore, Sprox-seq captured B cell-Follicular Dendritic Cell interactions mediated by the protein complex VLA-4-VCAM1 in the Light zone. Sprox-seq provides a multi-modal view of cell states and a powerful tool for studying protein and cellular interactions across tissues.

immunology↗

bioRxiv2025

Accurate processing of ultra-short immune signals by singlemacrophages

Accurately interpreting short-lived signals is challenging within noisy cellular microenvironments. It is not known if cells can distinguish different signaling molecules under transient exposure. Here, we explored the temporal limits of signal detection by single macrophages. Microfluidic experiments monitoring NF-{kappa}B dynamics showed that macrophages strongly respond even to 1-second pulses of cytokine and pathogen ligands. Information theory showed that short-pulse response is highly specific to the stimulating ligand, comparable to that under long-term stimulation. Macrophages were mainly sensitive to the duration of cytokines, and the dose of pathogen ligands. Stimulus duration altered the ranking of response strengths among different pathogenic ligands. Mathematical modeling showed that receptor cooperativity is crucial for robust responses to transient signals, while receptor pathway variability leads to accurate signaling in fluctuating environments. These findings demonstrate that dynamic transcription factor specificity is preserved across varying signal durations and uncover network-level mechanisms that accurately distinguish transiently encountered threats.

systems biology↗

bioRxiv2023

Computational prediction of protein interactions on single cells by proximity sequencing

Proximity sequencing (Prox-seq) measures gene expression, protein expression, and protein complexes at the single cell level, using information from dual-antibody binding events and a single cell sequencing readout. Prox-seq provides multi-dimensional phenotyping of single cells and was recently used to track the formation of receptor complexes during inflammatory signaling in macrophages and to discover a new interaction between CD9/CD8 proteins on naive T cells. The distribution of protein abundance affects identification of protein complexes in a complicated manner in dual-binding assays like Prox-seq. These effects are difficult to explore with experiments, yet important for accurate quantification of protein complexes. Here, we introduce a physical model for protein dimer formation on single cells and computationally evaluate several different methods for reducing background noise when quantifying protein complexes. Furthermore, we developed an improved method for analysis of Prox-seq single-cell data, which resulted in more accurate and robust quantification of protein complexes. Finally, our model offers a simple way to investigate the behavior of Prox-seq under various biological conditions and guide users toward selecting the best analysis method for their data.

systems biology↗

bioRxiv2022

OrganoID: a versatile deep learning platform for organoid image analysis

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 (96%) and size (95%) 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 decreased organoid circularity as an important morphological feature reflecting drug response. OrganoID enables straightforward, detailed, and accurate image analysis to accelerate the use of organoids in high-throughput, data-intensive biomedical applications.

bioengineering↗

bioRxiv2022

NF-κB memory coordinates transcriptional responses to dynamic inflammatory stimuli

Many scenarios in cellular communication requires cells to interpret multiple dynamic signals. It is unclear how exposure to immune stimuli alters transcriptional responses to subsequent stimulus under inflammatory conditions. Using high-throughput microfluidic live cell analysis, we systematically profiled the NF-{kappa}B response to different signal sequences in single cells. We found that NF-{kappa}B dynamics stores the history of signals received by cells: depending on the dose and type of prior pathogenic and cytokine signal, the NF-{kappa}B response to subsequent stimuli varied widely, from no response to full activation. Using information theory, we revealed that these stimulus-dependent changes in the NF-{kappa}B response encode and reflect information about the identity and dose of the prior stimulus. Small-molecule inhibition, computational modeling, and gene expression profiling show that this encoding is driven by stimulus-dependent engagement of negative feedback modules. These results provide a model for how signal transduction networks process sequences of inflammatory stimuli to coordinate cellular responses in complex dynamic environments.

systems biology↗

bioRxiv2021

SARS-CoV-2 diverges from other betacoronaviruses in only partially activating the IRE1α/XBP1 ER stress pathway in human lung-derived cells

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has killed over 6 million individuals worldwide and continues to spread in countries where vaccines are not yet widely available, or its citizens are hesitant to become vaccinated. Therefore, it is critical to unravel the molecular mechanisms that allow SARS-CoV-2 and other coronaviruses to infect and overtake the host machinery of human cells. Coronavirus replication triggers endoplasmic reticulum (ER) stress and activation of the unfolded protein response (UPR), a key host cell pathway widely believed essential for viral replication. We examined the master UPR sensor IRE1 kinase/RNase and its downstream transcription factor effector XBP1s, which is processed through an IRE1-mediated mRNA splicing event, in human lung-derived cells infected with betacoronaviruses. We found human respiratory coronavirus OC43 (HCoV-OC43), Middle East respiratory syndrome coronavirus (MERS-CoV), and murine coronavirus (MHV) all induce ER stress and strongly trigger the kinase and RNase activities of IRE1 as well as XBP1 splicing. In contrast, SARS-CoV-2 only partially activates IRE1 through autophosphorylation, but its RNase activity fails to splice XBP1. Moreover, while IRE1 was dispensable for replication in human cells for all coronaviruses tested, it was required for maximal expression of genes associated with several key cellular functions, including the interferon signaling pathway, during SARS-CoV-2 infection. Our data suggest that SARS-CoV-2 actively inhibits the RNase of autophosphorylated IRE1, perhaps as a strategy to eliminate detection by the host immune system. IMPORTANCESARS-CoV-2 is the third lethal respiratory coronavirus after MERS-CoV and SARS-CoV to emerge this century, causing millions of deaths world-wide. Other common coronaviruses such as HCoV-OC43 cause less severe respiratory disease. Thus, it is imperative to understand the similarities and differences among these viruses in how each interacts with host cells. We focused here on the inositol-requiring enzyme 1 (IRE1) pathway, part of the host unfolded protein response to virus-induced stress. We found that while MERS-CoV and HCoV-OC43 fully activate the IRE1 kinase and RNase activities, SARS-CoV-2 only partially activates IRE1, promoting its kinase activity but not RNase activity. Based on IRE1-dependent gene expression changes during infection, we propose that SARS-CoV-2 prevents IRE1 RNase activation as a strategy to limit detection by the host immune system.

microbiology↗

bioRxiv2021

Spatiotemporal NF-κB dynamics encodes the position, amplitude and duration of local immune inputs

Infected cells communicate through secreted signaling molecules like cytokines, which inform nearby cells about the type, severity and location of pathogens. How differences in cytokine secretion affect inflammatory signaling over space and time, and how responding cells decode information from propagating cytokine signals are not understood. By computationally and experimentally studying NF-{kappa}B dynamics in co-cultures of signal sending cells (macrophages) and receiving cells (fibroblasts), we found that cytokine signals are transmitted by wave-like propagation of NF-{kappa}B activity and create well-defined cellular activation zones in a responding cell population. Remarkably, NF-{kappa}B dynamics in responding cells can simultaneously encode information about cytokine dose, duration, and distance to the cytokine source. Spatially-resolved transcriptional analysis revealed that responding cells transmit local cytokine information to distance specific pro-inflammatory gene expression patterns, creating "gene expression zones" in the population. Despite single-cell variability, the size and duration of the signaling zone is tightly controlled by the macrophage cytokine secretion profile. Our results highlight how macrophages tune their cytokine secretion dynamics to control signal transmission distance, and how NF-{kappa}B interprets these signals to coordinate inflammatory response in space and time.

systems biology↗

bioRxiv2021

Herpesviral induction of germline transcription factor DUX4 is critical for viral gene expression

DUX4 is a transcription factor and a master regulator of embryonic genome activation (EGA). During early embryogenesis, EGA is crucial for maternal to zygotic transition at the 8-cell stage in order to overcome silencing of genes and enable transcription from the zygotic genome. In adult somatic cells, DUX4 expression is largely silenced. Activation is likely pathogenic, and in adult muscle cells causes genetic disorder Facioscapulohumeral Muscular Dystrophy (FSHD). We identified activation of DUX4 expression upon lytic replication of the herpesviruses HSV-1, HCMV, EBV and KSHV, but not of adenoviruses, negative strand RNA viruses or positive strand RNA viruses. We demonstrate by RNA-Seq analysis that DUX4 expression upon herpesviral replication leads to the induction of hundreds of DUX4 target genes including germline-specific retroelements as well as several members of the TRIM, PRAMEF and ZSCAN protein families. Moreover, we show that DUX4 expression is a direct consequence of herpesviral infection. DUX4 can be stimulated by overexpression of HSV-1 immediate early proteins, indicating active induction of EGA genes by herpesviral infection. We further show that DUX4 expression is critical for driving HSV-1 gene expression. Our results show that viruses from alpha-, beta- and gamma-herpesvirus subfamilies induce DUX4 expression and downstream germline-specific genes and retroelements. We hypothesize that herpesviruses induce DUX4 expression in order to induce an early embryonic-like transcriptional program that prevents epigenetic silencing of the viral genome and facilitates herpesviral gene expression.

microbiology↗

bioRxiv2021

Cannabidiol Inhibits SARS-CoV-2 Replication and Promotes the Host Innate Immune Response

The rapid spread of COVID-19 underscores the need for new treatments. Here we report that cannabidiol (CBD), a compound produced by the cannabis plant, inhibits SARS-CoV-2 infection. CBD and its metabolite, 7-OH-CBD, but not congeneric cannabinoids, potently block SARS-CoV-2 replication in lung epithelial cells. CBD acts after cellular infection, inhibiting viral gene expression and reversing many effects of SARS-CoV-2 on host gene transcription. CBD induces interferon expression and up-regulates its antiviral signaling pathway. A cohort of human patients previously taking CBD had significantly lower SARS-CoV-2 infection incidence of up to an order of magnitude relative to matched pairs or the general population. This study highlights CBD, and its active metabolite, 7-OH-CBD, as potential preventative agents and therapeutic treatments for SARS-CoV-2 at early stages of infection.

microbiology↗

bioRxiv2020

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.

genomics↗

bioRxiv2020

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.

microbiology↗

bioRxiv2020

Quantification of proteins, protein complexes and mRNA in single cells by proximity-sequencing

Multiplexed analysis of single-cells enables accurate modeling of cellular behaviors, classification of new cell types, and characterization of their functional states. Here we present proximity-sequencing (Prox-seq), a method for simultaneous measurement of an individual cells proteins, protein complexes and mRNA. Prox-seq utilizes deep sequencing and barcoded proximity assays to measure proteins and their complexes from all pairwise combinations of targeted proteins, in thousands of single-cells. The number of measured protein complexes scales quadratically with the number of targeted proteins, providing unparalleled multiplexing capacity. We developed a high-throughput experimental and computational pipeline and demonstrated the potential of Prox-Seq for multi-omic analysis with a panel of 13 barcoded proximity probes, enabling the measurement of 91 protein complexes, along with thousands of mRNA molecules in single T-cells and B-cells. Prox-seq provides access to an untapped yet powerful measurement modality for single-cell phenotyping and can discover new protein interactions in signaling and drug studies.

bioengineering↗

bioRxiv2019

High-throughput isolation and sorting of gut microbes reduce biases of traditional cultivation strategies

Traditional cultivation approaches in microbiology are labor-intensive, low-throughput, and often yield biased sampling of taxa due to ecological and evolutionary factors. New strategies are needed to enable ample representation of rare taxa and slow-growers that are outcompeted by fast-growing organisms. We developed a microfluidic platform that anaerobically isolates and cultivates microbial cells in millions of picoliter droplets and automatically sorts droplets based on colony density. We applied our strategy to mouse and human gut microbiomes and used 16S ribosomal RNA gene amplicons to characterize taxonomic composition of cells grown using different media. We found up to 4-fold increase in richness and larger representation of rare taxa among cells grown in droplets compared to conventional culture plates. Automated sorting of droplets for slow-growing colonies further enhanced the relative abundance of rare populations. Our method improves the cultivation and analysis of diverse microbiomes to gain deeper insights into microbial functioning and lifestyles.

microbiology↗

bioRxiv2019

Input dose differentiation by NF-κB

Cells receive a wide range of dynamic signaling inputs during immune regulation, but how gene regulatory networks measure and interpret such dynamic inputs is not understood. Here, we used microfluidic live-cell analysis and mathematical modeling to study how NF-{kappa}B pathway in single-cells responds to time-varying immune inputs such as increasing, decreasing or fluctuating cytokine signals. Surprisingly, we found that NF-{kappa}B acts as a differentiator, responding strictly to the absolute difference in cytokine concentration, and not to the concentration itself. Our analyses revealed that negative feedbacks by the regulatory proteins A20 and I{kappa}B enable dose differentiation by providing short-term memory of prior cytokine level and continuously resetting kinase cycling and receptor levels. Investigation of NF-{kappa}B target gene expression showed that cells create unique 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.

systems biology↗

bioRxiv2019

Deep learning reveals hidden variables underlying NF-κB activation in single cells

Individual cells show great heterogeneity when responding to environmental cues. For example, under cytokine stimulation some cells activate immune signaling pathways while others completely ignore the signal. The underlying sources of cellular variability have been inaccessible due to the destructive nature of experiments. Here we apply deep learning, live-cell analysis, and mechanistic modeling to uncover hidden variables controlling NF-{kappa}B activation in single-cells. Our computer-vision algorithm accurately predicts cells that will respond to pro-inflammatory TNF stimulation and shows that single-cell activation is pre-determined by minute amounts of \"leaky\" nuclear NF-{kappa}B localization before stimulation. Theoretical analysis predicts and experiments confirm that the ratio of NF-{kappa}B to its inhibitor I{kappa}B determines the activation probability of a given cell. Our results demonstrate how computer vision can study living-cells without the use of destructive measurements and settles the question of whether heterogenous NF-{kappa}B activation is controlled by pre-existing deterministic variables or purely stochastic ones.

systems biology↗

bioRxiv2019

HSV-1 single cell analysis reveals anti-viral and developmental programs activation in distinct sub-populations

Viral infection is usually studied at the population level by averaging over millions of cells. However, infection at the single-cell level is highly heterogeneous. Here, we combine live-cell imaging and single-cell RNA sequencing to characterize viral and host transcriptional heterogeneity during HSV-1 infection of primary human cells. We find extreme variability in the level of viral gene expression among individually infected cells and show that they cluster into transcriptionally distinct sub-populations. We find that anti-viral signaling is initiated in a rare group of abortively infected cells, while highly infected cells undergo cellular reprogramming to an embryonic-like transcriptional state. This reprogramming involves the recruitment of beta-catenin to the host nucleus and viral replication compartments and is required for late viral gene expression and progeny production. These findings uncover the transcriptional differences in cells with variable infection outcomes and shed new light on the manipulation of host pathways by HSV-1.

microbiology↗

bioRxiv2017

Universal Microfluidic System for Analysis and Control of Cell Dynamics

Dynamical control of the cellular microenvironment is highly desired for quantitative studies of stem cells and immune signaling. Here, we present an automated microfluidic system for high-throughput culture, differentiation and analysis of a wide range of cells in precisely defined dynamic microenvironments recapitulating cellular niches. This system delivers complex, time-varying biochemical signals to 1,500 independently programmable cultures containing either single cells, 2-D populations, or 3-D organoids, and dynamically stimulates adherent or non-adherent cells while tracking and retrieving them for end-point analysis. Using this system, we investigated the signaling landscape of neural stem cell differentiation under combinatorial and dynamic stimulation with growth factors. Experimental and computational analyses identified \"cellular logic rules\" for stem cell differentiation, and demonstrated the importance of signaling sequence and timing in brain development. This universal platform greatly enhances capabilities of microfluidic cell culture, allows dissection of previously hidden aspects of cellular dynamics, and enables accelerated biological discovery.

bioengineering↗