Biology subjects

Smith, C. B.

Publications and source records attributed to Smith, C. B..

5 recordsLinked to original sources

bioRxiv2024

Microbial Metabolite Trimethylamine N-Oxide Promotes Campylobacter jejuni Infection by Escalating Intestinal Inflammation, Epithelial Damage, and Barrier Disruption

The interactions between Campylobacter jejuni, a critical foodborne cause of gastroenteritis, and the intestinal microbiota during infection are not completely understood. The crosstalk between C. jejuni and its host is impacted by the gut microbiota through mechanisms of competitive exclusion, microbial metabolites, or immune response. To investigate the role of gut microbiota on C. jejuni pathogenesis, we examined campylobacteriosis in the IL10KO mouse model, which was characterized by an increase in the relative abundance of intestinal proteobacteria, E. coli, and inflammatory cytokines during C. jejuni infection. We also found a significantly increased abundance of microbial metabolite Trimethylamine N-Oxide (TMAO) in the colonic lumens of IL10KO mice. We further investigated the effects of TMAO on C. jejuni pathogenesis. We determined that C. jejuni senses TMAO as a chemoattractant and the administration of TMAO promotes C. jejuni invasion into Caco-2 monolayers. TMAO also increased the transmigration of C. jejuni across polarized monolayers of Caco-2 cells, decreased TEER, and increased C. jejuni-mediated intestinal barrier damage. Interestingly, TMAO treatment and presence during C. jejuni infection of Caco-2 cells synergistically caused an increased inflammatory cytokine expression, specifically IL-1{beta} and IL-8. These results establish that C. jejuni utilizes microbial metabolite TMAO for increased virulence during infection.

microbiology↗

bioRxiv2024

Digital Microbe: A Genome-Informed Data Integration Framework for Collaborative Research on Emerging Model Organisms

The remarkable pace of genomic data generation is rapidly transforming our understanding of life at the micron scale. Yet this data stream also creates challenges for team science. A single microbe can have multiple versions of genome architecture, functional gene annotations, and gene identifiers; additionally, the lack of mechanisms for collating and preserving advances in this knowledge raises barriers to community coalescence around shared datasets. "Digital Microbes" are frameworks for interoperable and reproducible collaborative science through open source, community-curated data packages built on a (pan)genomic foundation. Housed within an integrative software environment, Digital Microbes ensure real-time alignment of research efforts for collaborative teams and facilitate novel scientific insights as new layers of data are added. Here we describe two Digital Microbes: 1) the heterotrophic marine bacterium Ruegeria pomeroyi DSS-3 with >100 transcriptomic datasets from lab and field studies, and 2) the pangenome of the cosmopolitan marine heterotroph Alteromonas containing 339 genomes. Examples demonstrate how an integrated framework collating public (pan)genome-informed data can generate novel and reproducible findings.

bioinformatics↗

bioRxiv2023

Local and dynamic regulation of neuronal glycolysis in vivo

Energy metabolism supports neuronal function. While it is well established that changes in energy metabolism underpin brain plasticity and function, less is known about how individual neurons modulate their metabolic states to meet varying energy demands. This is because most approaches used to examine metabolism in living organisms lack the resolution to visualize energy metabolism within individual circuits, cells, or subcellular regions. Here we adapted a biosensor for glycolysis, HYlight, for use in C. elegans to image dynamic changes in glycolysis within individual neurons and in vivo. We determined that neurons perform glycolysis cell-autonomously, and modulate glycolytic states upon energy stress. By examining glycolysis in specific neurons, we documented a neuronal energy landscape comprising three general observations: 1) glycolytic states in neurons are diverse across individual cell types; 2) for a given condition, glycolytic states within individual neurons are reproducible across animals; and 3) for varying conditions of energy stress, glycolytic states are plastic and adapt to energy demands. Through genetic analyses, we uncovered roles for regulatory enzymes and mitochondrial localization in the cellular and subcellular dynamic regulation of glycolysis. Our study demonstrates the use of a single-cell glycolytic biosensor to examine how energy metabolism is distributed across cells and coupled to dynamic states of neuronal function, and uncovers new relationships between neuronal identities and metabolic landscapes in vivo. Significance statementWhile it is generally accepted that energy metabolism underpins neuronal function, how it is distributed and dynamically regulated in different tissues of the brain to meet varying energy demands is not well understood. Here we utilized a fluorescent biosensor, HYlight, to observe glycolytic metabolism at cellular and subcellular scales in vivo. By leveraging both the stereotyped identities of individual neurons in C. elegans, and genetic tools for manipulating glycolytic metabolism, we determined that neurons perform and dynamically regulate glycolysis to match changing cellular demands for energy. Our findings support a model whereby glycolytic states should be considered distinct and related to individual neuron identities in vivo, and introduce new questions about the interconnected nature of metabolism and neuronal function.

neuroscience↗

bioRxiv2021

Cell-type specific circadian bioluminescence rhythms recorded from Dbp reporter mice reveal circadian oscillator misalignment

Circadian rhythms are endogenously generated physiological and molecular rhythms with a cycle length of about 24 h. Bioluminescent reporters have been exceptionally useful for studying circadian rhythms in numerous species. Here, we report development of a reporter mouse generated by modification of a widely expressed and highly rhythmic gene encoding D-site albumin promoter binding protein (Dbp). In this line of mice, firefly luciferase is expressed from the Dbp locus in a Cre-recombinase-dependent manner, allowing assessment of bioluminescence rhythms in specific cellular populations. A mouse line in which luciferase expression was Cre-independent was also generated. The Dbp reporter alleles do not alter Dbp gene expression rhythms in liver or circadian locomotor activity rhythms. In vivo and ex vivo studies show the utility of the reporter alleles for monitoring rhythmicity. Our studies reveal cell-type specific characteristics of rhythms among neuronal populations within the suprachiasmatic nuclei ex vivo. In vivo studies show Dbp-driven bioluminescence rhythms in the liver of Albumin-Cre;DbpKI/+ "liver reporter" mice. After a shift of the lighting schedule, locomotor activity achieved the proper phase relationship with the new lighting cycle more rapidly than hepatic bioluminescence did. As previously shown, restricting food access to the daytime altered the phase of hepatic rhythmicity. Our model allowed assessment of the rate of recovery from misalignment once animals were provided with food ad libitum. These studies confirm the previously demonstrated circadian misalignment following environmental perturbations and reveal the utility of this model for minimally invasive, longitudinal monitoring of rhythmicity from specific mouse tissues.

physiology↗

bioRxiv2020

A sort-seq approach to the development of single fluorescent protein biosensors

The utility of single fluorescent protein biosensors (SFPBs) in biological research is offset by the difficulty in engineering these tools. SFPBs generally consist of three basic components: a circularly permuted fluorescent protein, a ligand-binding domain, and a pair of linkers connecting the two domains. In the absence of predictive methods for biosensor engineering, most designs combining these three components will fail to produce allosteric coupling between ligand binding and fluorescence emission. Methods to construct libraries of biosensor designs with variations in the site of GFP insertion and linker sequences have been developed, however, our ability to construct new variants has exceeded our ability to test them for function. Here, we address this challenge by applying a massively parallel assay termed "sort-seq" to the characterization of biosensor libraries. Sort-seq combines binned fluorescence-activated cell sorting, next-generation sequencing, and maximum likelihood estimation to quantify the dynamic range of many biosensor variants in parallel. We applied this method to two common biosensor optimization tasks: choice of insertion site and optimization of linker sequences. The sort-seq assay applied to a maltose-binding protein domain-insertion library not only identified previously described high-dynamic-range variants but also discovered new functional insertion-sites with diverse properties. A sort-seq assay performed on a pyruvate biosensor linker library expressed in mammalian cell culture identified linker variants with substantially improved dynamic range. Machine learning models trained on the resulting data can predict dynamic range from linker sequence. This high-throughput approach will accelerate the design and optimization of SFPBs, expanding the biosensor toolbox.

biochemistry↗