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Salmonella enterica serovar Typhimurium must adapt to rapid environmental shifts, including those encountered upon entry and during replication to survive within macrophages during pathogenesis. Despite extensive RNA-seq-based investigations, questions remain regarding the range, timing and magnitude of response dynamics. Here we constructed a comprehensive GFP-reporter strain library representing 2,901 computationally identified Salmonella promoter regions to study time-resolved Salmonella transcriptional responses. Promoter activity was measured during in vitro growth and during intracellular infection of RAW 264.7 macrophages. Using bulk measurements and single-cell imaging, we uncovered condition-specific transcriptional regulation and population-level heterogeneity in SPI2-related promoter activity. We also discovered previously unidentified transcriptional activity from 234 promoters. These analyses revealed metabolic shifts including requirements for mntS expression to support manganese homeostasis and expression of Entner–Doudoroff pathway-associated genes to support growth within macrophages. Our library and datasets, made available through the online tool SalComKinetics, provide resources for systems-level interrogation of Salmonella transcriptional dynamics. 

Much of sensory neuroscience focuses on sensory features that are chosen by the experimenter because they are thought to be behaviorally relevant to the organism. However, it is not generally known what these features are in complex, natural scenes. This work focuses on using the retinal encoding of natural movies to determine the presumably behaviorally-relevant features that the brain represents. It is prohibitive to parameterize a natural movie and its respective retinal encoding fully. We use time within a natural movie as a proxy for the whole suite of features evolving across the scene. We then use a task-agnostic deep architecture, an encoder-decoder, to model the retinal encoding process and characterize its representation of``time in the natural scene''in a compressed latent space. In our end-to-end training, an encoder learns a compressed latent representation from a large population of salamander retinal ganglion cells responding to natural movies, while a decoder samples from this compressed latent space to generate the appropriate movie frame. By comparing latent representations of retinal activity from three movies, we find that the retina performs transfer learning to encode time: the precise, low-dimensional representation of time learned from one movie can be used to represent time in a different movie, with up to 17ms resolution. We then show that static textures and velocity features of a natural movie are synergistic. The retina simultaneously encodes both to establishes a generalizable, low-dimensional representation of time in the natural scene. 

Abstract Engineered signaling networks can impart cells with new functionalities useful for directing differentiation and actuating cellular therapies. For such applications, the engineered networks must be tunable, precisely regulate target gene expression, and be robust to perturbations within the complex context of mammalian cells. Here, we use bacterial two-component signaling proteins to develop synthetic phosphoregulation devices that exhibit these properties in mammalian cells. First, we engineer a synthetic covalent modification cycle based on kinase and phosphatase proteins derived from the bifunctional histidine kinase EnvZ, enabling analog tuning of gene expression via its response regulator OmpR. By regulating phosphatase expression with endogenous miRNAs, we demonstrate cell-type specific signaling responses and a new strategy for accurate cell type classification. Finally, we implement a tunable negative feedback controller via a small molecule-stabilized phosphatase, reducing output expression variance and mitigating the context-dependent effects of off-target regulation and resource competition. Our work lays the foundation for establishing tunable, precise, and robust control over cell behavior with synthetic signaling networks. 

Abstract Pandemic and endemic strains ofVibrio choleraearise from toxigenic conversion by the CTXφ bacteriophage, a process by which CTXφ infects nontoxigenic strains ofV. cholerae.CTXφ encodes the cholera toxin, an enterotoxin responsible for the watery diarrhea associated with cholera infections. Despite the critical role of CTXφ during infections, signals that affect CTXφ‐driven toxigenic conversion or expression of the CTXφ‐encoded cholera toxin remain poorly characterized, particularly in the context of the gut mucosa. Here, we identify mucin polymers as potent regulators of CTXφ‐driven pathogenicity inV. cholerae.Our results indicate that mucin‐associatedO‐glycans block toxigenic conversion by CTXφ and suppress the expression of CTXφ‐related virulence factors, including the toxin co‐regulated pilus and cholera toxin, by interfering with the TcpP/ToxR/ToxT virulence pathway. By synthesizing individual mucin glycan structuresde novo, we identify the Core 2 motif as the critical structure governing this virulence attenuation. Overall, our results highlight a novel mechanism by which mucins and their associatedO‐glycan structures affect CTXφ‐mediated evolution and pathogenicity ofV. cholerae, underscoring the potential regulatory power housed within mucus.