Biology subjects

Lyon, K.

Publications and source records attributed to Lyon, K..

5 recordsLinked to original sources

bioRxiv2024

Arc mediates intercellular synaptic plasticity via IRSp53-dependent extracellular vesicle biogenesis.

Current models of learning and memory have focused on cell-autonomous regulation of synaptic strength; however, intercellular signaling between cells in the brain is important for normal cognition. The immediate early gene Arc is a repurposed retrotransposon critical for long-term forms of synaptic plasticity and memory. Arc protein forms virus-like capsids released in extracellular vesicles (EVs) that mediate intercellular signaling of unknown function. Here, we find that long-term potentiation stimuli induce the biogenesis of Arc EVs by recruiting the I-BAR protein IRSp53, which facilitates Arc capsid assembly, trafficking, and release from actin-rich filopodial structures in dendrites. Arc EVs transfer Arc protein and mRNA to neighboring dendrites, where translation of transferred Arc mRNA induces a loss of surface AMPA-type glutamate receptors. These results show that Arc EVs mediate an intercellular form of synaptic plasticity that may be critical for memory consolidation and reveals a new neuronal EV biogenesis pathway.

neuroscience↗

bioRxiv2020

A high-throughput metabolic microarray assay reveals antibacterial effects of black and red raspberries and blackberries against Helicobacter pylori infection

Helicobacter pylori is an important bacterial pathogen that causes chronic infection of the human stomach, leading to gastritis, peptic ulcer disease and gastric cancer. Treatment with appropriate antibiotics can eliminate H. pylori infection and reduce the risk for severe disease outcomes. However, since H. pylori is becoming increasingly resistant to standard antibiotic regimens, novel treatment strategies are needed. Previous studies have demonstrated that black and red berries may have antibacterial properties. Therefore, we analyzed organic extracts and powders from black and red raspberries and blackberries and determined their antibacterial effects on multiple H. pylori strains. We used high-performance liquid chromatography to measure berry anthocyanins, which are considered the major active ingredients. To monitor antibiotic effects of the berry preparations on H. pylori, we developed a high-throughput metabolic growth assay based on the OmniLog system. All berry preparations tested had significant bactericidal effects in vitro, with MIC90 values ranging from 0.49 to 4.17%. We next used human gastric epithelial organoids to evaluate biocompatibility of the berry preparations and showed that black raspberry extract, which had the strongest antimicrobial activity, was non-toxic at the concentration required for complete bacterial growth inhibition. To determine whether dietary black raspberry application could eliminate H. pylori infection in vivo, mice were infected with H. pylori and then were placed on a diet containing 10% black raspberry powder. However, this treatment did not significantly impact bacterial infection rates or gastric pathology. In summary, our data indicate that black and red raspberry and blackberry products have potential applications in the treatment and prevention of H. pylori infection, because of their antibacterial effects and good biocompatibility. However, delivery and formulation of berry compounds needs to be optimized to achieve significant antibacterial effects in vivo.

microbiology↗

bioRxiv2020

DeepPPPred: An Ensemble of BERT, CNN, and RNN for Classifying Co-mentions of Proteins and Phenotypes

The biomedical literature provides an extensive source of information in the form of unstructured text. One of the most important types of information hidden in biomedical literature is the relationships between human proteins and their phenotypes, which, due to the exponential growth of publications, can remain hidden. This provides a range of opportunities for the development of computational methods to extract the biomedical relationships from the unstructured text. In our previous work, we developed a supervised machine learning approach, called PPPred, for classifying the validity of a given sentence-level human protein-phenotype co-mention. In this work, we propose DeepPPPred, an ensemble classifier composed of PPPred and three deep neural network models: RNN, CNN, and BERT. Using an expanded gold-standard co-mention dataset, we demonstrate that the proposed ensemble method significantly outperforms its constituent components and provides a new state-of-the-art performance on classifying the co-mentions of human proteins and phenotype terms.

bioinformatics↗

bioRxiv2019

Detection and quantification of single mRNA dynamics with the Riboglow fluorescent RNA tag

Labeling and tracking biomolecules with fluorescent probes on the single molecule level enables quantitative insights into their dynamics in living cells. We previously developed Riboglow, a platform to label RNAs in live mammalian cells, consisting of a short RNA tag and a small organic probe that increases fluorescence upon binding RNA. Here, we demonstrate that Riboglow is capable of detecting and tracking single RNA molecules. We benchmark RNA tracking by comparing results with the established MS2 RNA tagging system. To demonstrate versatility of Riboglow, we assay translation on the single molecule level, where the translated mRNA is tagged with Riboglow and the nascent polypeptide is labeled with a fluorescent antibody. The growing effort to investigate RNA biology on the single molecule level requires sophisticated and diverse fluorescent probes for multiplexed, multi-color labeling of biomolecules of interest, and we present Riboglow as a new member in this toolbox.

cell biology↗

bioRxiv2018

Imaging of single mRNA translation repression reveals diverse interactions with mRNP granules

During cellular stress mRNAs exit translation and accumulate in stress granules and P-bodies, although the dynamics of these interactions remain unclear. We imaged in real-time single mRNAs, their translational output, and mRNA-granule interactions during stress. We observed single mRNAs interacting with stress granules and P-bodies, with mRNAs moving bidirectionality between them. While translating mRNAs only interact with RNP granules dynamically, non-translating mRNAs can form stable associations that rigidly immobilize the mRNA within the granule. Imaging thousands of individual mRNA-granule interactions showed the probability of stable association increases with both mRNA length and granule size. Therefore, the recruitment of mRNAs to RNP granules involves both highly dynamic and stable interactions, influenced by several parameters, demonstrating a new layer of complexity in mRNA regulation during stress.\n\nOne Sentence SummarymRNAs interact with stress granules and P-bodies in stable and dynamic manners influenced by ribosome association, mRNA length, and granule size.

molecular biology↗