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.

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.

Single-Cell Proteomics.

The inability to make broad, minimally biased measurements of a cell's proteome stands as a major bottleneck for understanding how gene expression translates into cellular phenotype. Unlike sequencing for nucleic acids, there is no dominant method for making single-cell proteomic measurements. Instead, methods typically focus on either absolute quantification of a small number of proteins or highly multiplexed protein measurements. Advances in microfluidics and output encoding have led to major improvements in both aspects. Here, we review the most recent progress that has enabled hundreds of protein measurements and ultrahigh-sensitivity quantification. We also highlight emerging technologies such as single-cell mass spectrometry that may enable unbiased measurement of cellular proteomes.

Quantification of extracellular proteins, protein complexes and mRNAs in single cells by proximity sequencing.

We present proximity sequencing (Prox-seq) for simultaneous measurement of proteins, protein complexes and mRNAs in thousands of single cells. Prox-seq combines proximity ligation assay with single-cell sequencing to measure proteins and their complexes from all pairwise combinations of targeted proteins, providing quadratically scaled multiplexing. We validate Prox-seq and analyze a mixture of T cells and B cells to show that it accurately identifies these cell types and detects well-known protein complexes. Next, by studying human peripheral blood mononuclear cells, we discover that naïve CD8+ T cells display the protein complex CD8-CD9. Finally, we study protein interactions during Toll-like receptor (TLR) signaling in human macrophages. We observe the formation of signal-specific protein complexes, find CD36 co-receptor activity and additive signal integration under lipopolysaccharide (TLR4) and Pam2CSK4 (TLR2) stimulation, and show that quantification of protein complexes identifies signaling inputs received by macrophages. Prox-seq provides access to an untapped measurement modality for single-cell phenotyping and can discover uncharacterized protein interactions in different cell types.

Computational prediction of protein interactions in single cells by proximity sequencing.

Proximity sequencing (Prox-seq) simultaneously measures gene expression, protein expression and protein complexes on single cells. Using information from dual-antibody binding events, Prox-seq infers surface protein dimers at the single-cell level. Prox-seq provides multi-dimensional phenotyping of single cells in high throughput, and was recently used to track the formation of receptor complexes during cell signaling and discovered a novel interaction between CD9 and CD8 in naïve T cells. The distribution of protein abundance can affect 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 of Prox-seq 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 data, which resulted in more accurate and robust quantification of protein complexes. Finally, our Prox-seq model offers a simple way to investigate the behavior of Prox-seq data under various biological conditions and guide users toward selecting the best analysis method for their data.

Shared sequence characteristics identified in non-canonical rearrangements of HSV-1 genomes.

IMPORTANCE: Mutations and genetic rearrangements are the primary driving forces of evolution. Viruses provide valuable model systems for investigating these mechanisms due to their rapid evolutionary rates and vast genetic variability. To investigate genetic rearrangements in the double-stranded DNA genome of herpes simplex virus type 1, the viral population was serially passaged in various cell types. The serial passaging led to formation of defective genomes, resulted from cell-specific non-canonical rearrangements (NCRs). Interestingly, we discovered shared sequence characteristics underlying the formation of these NCRs across all cell types. Moreover, most NCRs identified in clinical samples shared these characteristics. Based on our findings, we propose a model elucidating the formation of NCRs during viral replication within the nucleus of eukaryotic cells.

Digital Quantification of Proteins and mRNA in Single Mammalian Cells.

Absolute quantification of macromolecules in single cells is critical for understanding and modeling biological systems that feature cellular heterogeneity. Here we show extremely sensitive and absolute quantification of both proteins and mRNA in single mammalian cells by a very practical workflow that combines proximity ligation assay (PLA) and digital PCR. This digital PLA method has femtomolar sensitivity, which enables the quantification of very small protein concentration changes over its entire 3-log dynamic range, a quality necessary for accounting for single-cell heterogeneity. We counted both endogenous (CD147) and exogenously expressed (GFP-p65) proteins from hundreds of single cells and determined the correlation between CD147 mRNA and the protein it encodes. Using our data, a stochastic two-state model of the central dogma was constructed and verified using joint mRNA/protein distributions, allowing us to estimate transcription burst sizes and extrinsic noise strength and calculate the transcription and translation rate constants in single mammalian cells.

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.

Development of Masitinib Derivatives with Enhanced Mpro Ligand Efficiency and Reduced Cytotoxicity.

Recently, a high-throughput screen of 1900 clinically used drugs identified masitinib, an orally bioavailable tyrosine kinase inhibitor, as a potential treatment for COVID-19. Masitinib acts as a broad-spectrum inhibitor for human coronaviruses, including SARS-CoV-2 and several of its variants. In this work, we rely on atomistic molecular dynamics simulations with advanced sampling methods to develop a deeper understanding of masitinib's mechanism of Mpro inhibition. To improve the inhibitory efficiency and to increase the ligand selectivity for the viral target, we determined the minimal portion of the molecule (fragment) that is responsible for most of the interactions that arise within the masitinib-Mpro complex. We found that masitinib forms highly stable and specific H-bond interactions with Mpro through its pyridine and aminothiazole rings. Importantly, the interaction with His163 is a key anchoring point of the inhibitor, and its perturbation leads to ligand unbinding within nanoseconds. Based on these observations, a small library of rationally designed masitinib derivatives (M1-M5) was proposed. Our results show increased inhibitory efficiency and highly reduced cytotoxicity for the M3 and M4 derivatives compared to masitinib.

COVIDomic: A multi-modal cloud-based platform for identification of risk factors associated with COVID-19 severity.

Coronavirus disease 2019 (COVID-19) is an acute infection of the respiratory tract that emerged in December 2019 in Wuhan, China. It was quickly established that both the symptoms and the disease severity may vary from one case to another and several strains of SARS-CoV-2 have been identified. To gain a better understanding of the wide variety of SARS-CoV-2 strains and their associated symptoms, thousands of SARS-CoV-2 genomes have been sequenced in dozens of countries. In this article, we introduce COVIDomic, a multi-omics online platform designed to facilitate the analysis and interpretation of the large amount of health data collected from patients with COVID-19. The COVIDomic platform provides a comprehensive set of bioinformatic tools for the multi-modal metatranscriptomic data analysis of COVID-19 patients to determine the origin of the coronavirus strain and the expected severity of the disease. An integrative analytical workflow, which includes microbial pathogens community analysis, COVID-19 genetic epidemiology and patient stratification, allows to analyze the presence of the most common microbial organisms, their antibiotic resistance, the severity of the infection and the set of the most probable geographical locations from which the studied strain could have originated. The online platform integrates a user friendly interface which allows easy visualization of the results. We envision this tool will not only have immediate implications for management of the ongoing COVID-19 pandemic, but will also improve our readiness to respond to other infectious outbreaks.

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.

The Immune-Metabolic Basis of Effector Memory CD4+ T Cell Function under Hypoxic Conditions.

Effector memory (EM) CD4(+) T cells recirculate between normoxic blood and hypoxic tissues to screen for cognate Ag. How mitochondria of these cells, shuttling between normoxia and hypoxia, maintain bioenergetic efficiency and stably uphold antiapoptotic features is unknown. In this study, we found that human EM CD4(+) T cells had greater spare respiratory capacity (SRC) than did naive counterparts, which was immediately accessed under hypoxia. Consequently, hypoxic EM cells maintained ATP levels, survived and migrated better than did hypoxic naive cells, and hypoxia did not impair their capacity to produce IFN-γ. EM CD4(+) T cells also had more abundant cytosolic GAPDH and increased glycolytic reserve. In contrast to SRC, glycolytic reserve was not tapped under hypoxic conditions, and, under hypoxia, glucose metabolism contributed similarly to ATP production in naive and EM cells. However, both under normoxic and hypoxic conditions, glucose was critical for EM CD4(+) T cell survival. Mechanistically, in the absence of glycolysis, mitochondrial membrane potential (ΔΨm) of EM cells declined and intrinsic apoptosis was triggered. Restoring pyruvate levels, the end product of glycolysis, preserved ΔΨm and prevented apoptosis. Furthermore, reconstitution of reactive oxygen species (ROS), whose production depends on ΔΨm, also rescued viability, whereas scavenging mitochondrial ROS exacerbated apoptosis. Rapid access of SRC in hypoxia, linked with built-in, oxygen-resistant glycolytic reserve that functionally insulates ΔΨm and mitochondrial ROS production from oxygen tension changes, provides an immune-metabolic basis supporting survival, migration, and function of EM CD4(+) T cells in normoxic and hypoxic conditions.

Single-cell NF-kappaB dynamics reveal digital activation and analogue information processing.

Cells operate in dynamic environments using extraordinary communication capabilities that emerge from the interactions of genetic circuitry. The mammalian immune response is a striking example of the coordination of different cell types. Cell-to-cell communication is primarily mediated by signalling molecules that form spatiotemporal concentration gradients, requiring cells to respond to a wide range of signal intensities. Here we use high-throughput microfluidic cell culture and fluorescence microscopy, quantitative gene expression analysis and mathematical modelling to investigate how single mammalian cells respond to different concentrations of the signalling molecule tumour-necrosis factor (TNF)-alpha, and relay information to the gene expression programs by means of the transcription factor nuclear factor (NF)-kappaB. We measured NF-kappaB activity in thousands of live cells under TNF-alpha doses covering four orders of magnitude. We find, in contrast to population-level studies with bulk assays, that the activation is heterogeneous and is a digital process at the single-cell level with fewer cells responding at lower doses. Cells also encode a subtle set of analogue parameters to modulate the outcome; these parameters include NF-kappaB peak intensity, response time and number of oscillations. We developed a stochastic mathematical model that reproduces both the digital and analogue dynamics as well as most gene expression profiles at all measured conditions, constituting a broadly applicable model for TNF-alpha-induced NF-kappaB signalling in various types of cells. These results highlight the value of high-throughput quantitative measurements with single-cell resolution in understanding how biological systems operate.

Migration of cells in a social context.

In multicellular organisms and complex ecosystems, cells migrate in a social context. Whereas this is essential for the basic processes of life, the influence of neighboring cells on the individual remains poorly understood. Previous work on isolated cells has observed a stereotypical migratory behavior characterized by short-time directional persistence with long-time random movement. We discovered a much richer dynamic in the social context, with significant variations in directionality, displacement, and speed, which are all modulated by local cell density. We developed a mathematical model based on the experimentally identified "cellular traffic rules" and basic physics that revealed that these emergent behaviors are caused by the interplay of single-cell properties and intercellular interactions, the latter being dominated by a pseudopod formation bias mediated by secreted chemicals and pseudopod collapse following collisions. The model demonstrates how aspects of complex biology can be explained by simple rules of physics and constitutes a rapid test bed for future studies of collective migration of individual cells.

An updatable holographic three-dimensional display.

Holographic three-dimensional (3D) displays provide realistic images without the need for special eyewear, making them valuable tools for applications that require situational awareness, such as medical, industrial and military imaging. Currently commercially available holographic 3D displays use photopolymers that lack image-updating capability, resulting in restricted use and high cost. Photorefractive polymers are dynamic holographic recording materials that allow updating of images and have a wide range of applications, including optical correlation, imaging through scattering media and optical communication. To be suitable for 3D displays, photorefractive polymers need to have nearly 100% diffraction efficiency, fast writing time, hours of image persistence, rapid erasure, and large area-a combination of properties that has not been shown before. Here, we report an updatable holographic 3D display based on photorefractive polymers with such properties, capable of recording and displaying new images every few minutes. This is the largest photorefractive 3D display to date (4 x 4 inches in size); it can be recorded within a few minutes, viewed for several hours without the need for refreshing, and can be completely erased and updated with new images when desired.

A drug repurposing screen identifies decitabine as an HSV-1 antiviral.

Herpes simplex virus type 1 (HSV-1) is a highly prevalent human pathogen that causes a range of clinical manifestations, including oral and genital herpes, keratitis, encephalitis, and disseminated neonatal disease. Despite its significant health and economic burden, there is currently only a handful of approved antiviral drugs to treat HSV-1 infection. Acyclovir and its analogs are the first-line treatment, but resistance often arises during prolonged treatment periods, such as in immunocompromised patients. Therefore, there is a critical need to identify novel antiviral agents against HSV-1. Here, we performed a drug repurposing screen, testing the ability of 1,900 safe-in-human drugs to inhibit HSV-1 infection in vitro. The screen identified decitabine, a cytidine analog that is used to treat myelodysplastic syndromes and acute myeloid leukemia, as a potent anti-HSV-1 agent. We show that decitabine is effective in inhibiting HSV-1 infection in multiple cell types, including human keratinocytes, that it synergizes with acyclovir, and acyclovir-resistant HSV-1 is still sensitive to decitabine. We further show that decitabine causes G > C and C > G transversions across the viral genome, suggesting it exerts its antiviral activity by lethal mutagenesis, although a role for decitabine's known targets, DNA methyl-transferases, has not been ruled out. IMPORTANCE: Herpes simplex virus type 1 (HSV-1) is a prevalent human pathogen with a limited arsenal of antiviral agents, resistance to which can often develop during prolonged treatment, such as in the case of immunocompromised individuals. Development of novel antiviral agents is a costly and prolonged process, making new antivirals few and far between. Here, we employed an approach called drug repurposing to investigate the potential anti-HSV-1 activity of drugs that are known to be safe in humans, shortening the process of drug development considerably. We identified a nucleoside analog named decitabine as a potent anti-HSV-1 agent in cell culture and investigated its mechanism of action. Decitabine synergizes with the current anti herpetic acyclovir and increases the rate of mutations in the viral genome. Thus, decitabine is an attractive candidate for future studies in animal models to inform its possible application as a novel HSV-1 therapy.

Proximity sequencing for the detection of mRNA, extracellular proteins and extracellular protein complexes in single cells.

Complex cellular functions occur via the coordinated formation and dissociation of protein complexes. Functions such as the response to a signaling ligand can incorporate dozens of proteins and hundreds of complexes. Until recently, it has been difficult to measure multiple protein complexes at the single-cell level. Here, we present a step-by-step procedure for proximity sequencing, which enables the simultaneous measurement of proteins, mRNA and hundreds of protein complexes located on the outer membrane of cells. We guide the user through probe creation, sample preparation, staining, sequencing and computational quantification of protein complexes. This protocol empowers researchers to study, for example, the interplay between transcriptional states and cellular functions by coupling measurements of transcription to measurements of linked effector molecules, yet could be generalizable to other paired events. The protocol requires roughly 16 h spread over several days to complete by users with expertise in basic molecular biology and single-cell sequencing.

Single-cell chemoproteomics identifies metastatic activity signatures in breast cancer.

Protein activity state, rather than protein or mRNA abundance, is a biologically regulated and relevant input to many processes in signaling, differentiation, development, and diseases such as cancer. While there are numerous methods to detect and quantify mRNA and protein abundance in biological samples, there are no general approaches to detect and quantify endogenous protein activity with single-cell resolution. Here, we report the development of a chemoproteomic platform, single-cell activity-dependent proximity ligation, which uses automated, microfluidics-based single-cell capture and nanoliter volume manipulations to convert the interactions of family-wide chemical activity probes with native protein targets into multiplexed, amplifiable oligonucleotide barcodes. We demonstrate accurate, reproducible, and multiplexed quantitation of a six-enzyme (Ag-6) panel with known ties to cancer cell aggressiveness directly in single cells. We further identified increased Ag-6 enzyme activity across breast cancer cell lines of increasing metastatic potential, as well as in primary patient-derived tumor cells and organoids from patients with breast cancer.

High-throughput co-culture system for analysis of spatiotemporal cell-cell signaling.

Study of spatial and temporal aspects of signaling between individual cells is essential in understanding development, the immune response, and host-pathogen interactions. We present an automated high-throughput microfluidic platform that chemically stimulates immune cells to initiate cytokine secretion, and controls the formation of signal gradients that activate neighboring cell populations. Furthermore, our system enables controlling the cell type and density based on distance, and retrieval of cells from different regions for gene expression analysis. Our device performs these tasks in 192 independent chambers to simultaneously test different co-culture conditions. We demonstrate these capabilities by creating various cellular communication scenarios between macrophages and fibroblasts in vitro. We find that spatial distribution of macrophages and heterogeneity in cytokine secretion determine spatiotemporal gene expression responses. Furthermore, we describe how gene expression dynamics depend on a cell's distance from the signaling source. Our device addresses key challenges in the study of cell-to-cell signaling, and provides high-throughput and automated analysis over a wide range of co-culture conditions.