Biology subjects

Kubota, N.

Publications and source records attributed to Kubota, N..

10 recordsLinked to original sources

bioRxiv2026

Gut-derived GLP-1 released by rare sugar D-allulose cooperates with insulin to activate left-sided vagal afferents and enhance insulin sensitivity

Glucagon-like peptide-1 receptor agonists (GLP-1RAs) ameliorate hyperglycemia by directly stimulating insulin secretion from the pancreas. In contrast, the physiological role of short-lived endogenous GLP-1 remains unclear, largely because of its limited access to pancreatic {beta} cells. Here, we show that D-allulose-induced intestinal GLP-1 secretion (AIGS) cooperates with insulin to reduce blood glucose levels by enhancing insulin action, rather than insulin secretion, in male mice. This cooperation and remote signaling require left-sided vagal afferents forming the common hepatic branch, but not right-sided afferents. AIGS-enhanced insulin action required both GLP-1 receptors and insulin receptor substrate 2 in these neurons. Remarkably, AIGS improved insulin resistance and hyperglycemia more rapidly and potently than the GLP-1RA exendin-4. These findings reveal that a subclass of vagal afferent neurons synergistically activated by endogenous intestinal GLP-1 and insulin does not stimulate insulin secretion but augments insulin action to improve glucose tolerance. This novel extra-pancreatic GLP-1 action mediated by vagal afferents provides a promising basis for innovative type 2 diabetes therapies. ARTICLE HIGHLIGHTO_LICompared with GLP-1 receptor agonists, the physiological roles and mechanisms of endogenous, short-lived GLP-1 in glucose metabolism remain poorly understood. C_LIO_LIWe utilized the rare sugar D-allulose, a noncaloric GLP-1 secretagogue, as a tool to elucidate the physiological actions of endogenous GLP-1. C_LIO_LID-allulose-induced intestinal GLP-1 release cooperates with insulin to activate left-sided vagal afferents, enhancing insulin action rather than insulin secretion and thereby regulating glycemic control. C_LIO_LIBecause this acute mechanism improved hyperglycemia in type 2 diabetes more effectively than GLP-1 receptor agonists, targeting GLP-1/insulin-vagal signaling may inform novel therapies and dietary or nutritional interventions for T2DM. C_LI

physiology↗

bioRxiv2025

Pseudomonas aeruginosa biofilm-deficient mutants undergo parallel adaptation during chronic infection

Pseudomonas aeruginosa readily adapts to infection by acquiring stable and heritable mutations. Previously, we discovered that the first adaptations in a porcine wound model were rugose small-colony variants (RSCVs) caused by mutations in the wsp operon. These mutants overproduce Pel and Psl biofilm exopolysaccharides that improve defense against host responses. To identify other mechanisms of host adaptation that lead to hyperbiofilm phenotypes, we created a mutant with an activated wsp pathway but unable to produce these exopolysaccharides ({Delta}wspF{Delta}pelA{Delta}pslBCD). Porcine wounds were infected with this mutant and biopsies were sampled at days 7, 14 and 35. Small colony variants were isolated from the wound, and whole genome sequencing revealed these variants had acquired mutations in genes in lipopolysaccharide and type IV pili biosynthesis, with wzy and pilU genes being most commonly targeted. pilU mutants were associated with a hyperbiofilm phenotype that outcompeted the parental strain, and wzy mutants were associated with a hyperbiofilm phenotype and increased tolerance to host antimicrobial products. We further identified that several variants had acquired large genome deletions that spanned up to 320 consecutive genes and other variants with high copy numbers of Pf6 filamentous phage. Together our results suggest that the hyperbiofilm phenotype is adaptive in chronic infections and that P. aeruginosa has redundant and diverse pathways to generate this phenotype.

microbiology↗

bioRxiv2025

Lineage-Traced PTBP1 Depletion in Mature Astrocytes Reveals Distinct Splicing Alterations Without Neuronal Features

Astrocyte-to-neuron reprogramming via depletion of PTBP1, a potent repressor of neuronal splicing, has been proposed as a therapeutic strategy, but its efficacy remains debated. While some reported successful conversion, others disputed this, citing a lack of neuronal gene expression as evidence of failed reprogramming. This interpretation was further challenged, attributed to incomplete PTBP1 inactivation, fueling ongoing controversy. Mechanistic understanding of the conversion, or the lack thereof, requires investigating, in conjunction with lineage tracing, the effect of Ptbp1 loss of function in mature astrocytes on RNA splicing, which has not yet been examined. Here, we genetically ablated PTBP1 in adult Aldh1l1-Cre/ERT2 Ai14 mice to determine whether lineage traced Ptbp1 knockout astrocytes exhibited RNA splicing alterations congruent with neuronal differentiation. We found no widespread induction of neurons, despite a minuscule fraction of knockout cells showing neuron-like transcriptomic signatures. Importantly, PTBP1 loss in mature astrocytes induced splicing alterations unlike neuronal splicing patterns. These findings suggest that targeting PTBP1 alone is ineffective to drive neuronal reprogramming and highlight the need for combining splicing and lineage analyses. Loss of astrocytic PTBP1 is insufficient to induce neuronal splicing, contrasting with its well-known role in other non-neuronal cells, and instead affects a distinct astrocytic splicing program.

neuroscience↗

bioRxiv2024

Shiba: A unified computational method for robust identification of differential RNA splicing across platforms

Alternative pre-mRNA splicing (AS) is a fundamental regulatory process that generates transcript diversity and cell type variation. We developed Shiba, a comprehensive method that integrates transcript assembly, splicing event identification, read counting, and differential splicing analysis across RNA-seq platforms. Shiba excels in capturing annotated and unannotated AS events with superior accuracy, sensitivity, and reproducibility. It addresses the often-overlooked issue of junction read imbalance, significantly reducing false positives to aid target prioritization and downstream analyses. Unlike other tools that require large numbers of biological replicates or resulting in low sensitivity and high false positives, Shibas statistics framework is agnostic to sample size, as demonstrated by simulated data and its effective application to real n=1 RNA-seq datasets. To extend its utility to single-cell RNA-seq, we developed scShiba, which applies Shibas pseudobulk approach to analyze splicing at the cluster level. scShiba successfully revealed AS regulation in developmental dopaminergic neurons and differences between excitatory and inhibitory neurons. Both Shiba and scShiba are available in Docker/Singularity containers and Snakemake pipelines, ensuring reproducibility. With their comprehensive capabilities, Shiba and scShiba enable systematic quantification of alternative splicing events across various platforms, laying a solid foundation for mechanistic exploration of the functional complexity in RNA splicing.

bioinformatics↗

bioRxiv2023

STIE: Single-cell level deconvolution, convolution, and clustering in spatial transcriptomics by aligning spot level transcriptome to nuclear morphology

In spot-based spatial transcriptomics, spots that are of the same size and printed at the fixed location cannot precisely capture the actual randomly located single cells, therefore failing to profile the transcriptome at the single-cell level. The current studies primarily focused on enhancing the spot resolution in size via computational imputation or technical improvement, however, they largely overlooked that single-cell resolution, i.e., resolution in cellular or even smaller size, does not equal single-cell level. Using both real and simulated spatial transcriptomics data, we demonstrated that even the high-resolution spatial transcriptomics still has a large number of spots partially covering multiple cells simultaneously, revealing the intrinsic non-single-cell level of spot-based spatial transcriptomics regardless of spot size. To this end, we present STIE, an EM algorithm that aligns the spatial transcriptome to its matched histology image-based nuclear morphology and recovers missing cells from up to [~]70% gap area between spots via the nuclear morphological similarity and neighborhood information, thereby achieving the real single-cell level and whole-slide scale deconvolution/convolution and clustering for both low- and high-resolution spots. On both real and simulation spatial transcriptomics data, STIE characterizes the cell-type specific gene expression variation and demonstrates the outperforming concordance with the single-cell RNAseq-derived cell type transcriptomic signatures compared to the other spot- and subspot-level methods. Furthermore, STIE enabled us to gain novel insights that failed to be revealed by the existing methods due to the lack of single-cell level, for instance, lower actual spot resolution than its reported spot size, the additional contribution of cellular morphology to cell typing beyond transcriptome, unbiased evaluation of cell type colocalization, superior power of high-resolution spot in distinguishing nuanced cell types, and spatially resolved cell-cell interactions at the single-cell level other than spot level. The STIE code is publicly available as an R package at https://github.com/zhushijia/STIE.

bioinformatics↗

bioRxiv2023

L. pneumophila resists its self-harming metabolite HGA via secreted factors and collective peroxide scavenging

Many pathogenic bacteria, including Legionella pneumophila, infect humans from environmental reservoirs. To survive in these reservoirs, bacteria must withstand microbe-on-microbe competition. We previously discovered that L. pneumophila can compete with neighboring bacteria via an antimicrobial metabolite called homogentisic acid (HGA) (Levin, Goldspiel, and Malik 2019). Curiously, L. pneumophila strains that secrete HGA are not wholly immune to its effects: low-density bacteria are strongly inhibited by HGA whereas high-density cells are tolerant. How do these bacteria tolerate HGA and avoid self-harm during interbacterial competition? Here, we find that HGA toxicity occurs via the production of toxic hydroperoxides and multiple factors facilitate high-density tolerance. First, HGA only becomes fully toxic after >1 hour of oxidation. While this manifests as a delay in killing within well-mixed liquid cultures, in a biofilm environment, this could provide time for HGA to diffuse away before becoming toxic. Second, HGA generates quantities of hydroperoxides that can be collectively scavenged by high-density, but not low-density cells. And third, high-density cells produce one or more secreted factors that are transiently protective from HGA. In combination, we propose that the bacteria are able to deploy HGA to generate a pool of reactive oxygen species surrounding their own biofilms, while maintaining non-toxic conditions within them. Overall, these findings help to explain how broadly toxic molecules can be used as inter-bacterial weapons. They also provide insights about why some of our current decontamination methods to control L. pneumophila are ineffective, leading to recurrent disease outbreaks.

microbiology↗

bioRxiv2023

Positive selection of somatically mutated clones identifies adaptive pathways in metabolic liver disease

Somatic mutations in non-malignant tissues accumulate with age and insult, but whether these mutations are adaptive on the cellular or organismal levels is unclear. To interrogate mutations found in human metabolic disease, we performed lineage tracing in mice harboring somatic mosaicism subjected to non-alcoholic steatohepatitis (NASH). Proof-of-concept studies with mosaic loss of Mboat7, a membrane lipid acyltransferase, showed that increased steatosis accelerated clonal disappearance. Next, we induced pooled mosaicism in 63 known NASH genes, allowing us to trace mutant clones side-by-side. This in vivo tracing platform, which we coined MOSAICS, selected for mutations that ameliorate lipotoxicity, including mutant genes identified in human NASH. To prioritize new genes, additional screening of 472 candidates identified 23 somatic perturbations that promoted clonal expansion. In validation studies, liver-wide deletion of Bcl6, Tbx3, or Smyd2 resulted in protection against NASH. Selection for clonal fitness in mouse and human livers identifies pathways that regulate metabolic disease. HighlightsO_LIMosaic Mboat7 mutations that increase lipotoxicity lead to clonal disappearance in NASH. C_LIO_LIIn vivo screening can identify genes that alter hepatocyte fitness in NASH. C_LIO_LIMosaic Gpam mutations are positively selected due to reduced lipogenesis. C_LIO_LIIn vivo screening of transcription factors and epifactors identified new therapeutic targets in NASH. C_LI

cell biology↗

bioRxiv2022

Mapping of promoter usage QTL using RNA-seq data reveals their contributions to complex traits

Genomic variations are associated with gene expression levels, which are called expression quantitative trait loci (eQTL). Most eQTL may affect the total gene expression levels by regulating transcriptional activities of a specific promoter. However, the direct exploration of genomic loci associated with promoter activities using RNA-seq data has been challenging because eQTL analyses treat the total expression levels estimated by summing those of all isoforms transcribed from distinct promoters. Here we propose a computational framework for identifying genomic loci associated with promoter activities, called promoter usage quantitative trait loci (puQTL), using conventional RNA-seq data. By leveraging public RNA-seq datasets from the lymphoblastoid cell lines of 438 individuals from the GEUVADIS project, we obtained promoter activity estimates and mapped 2,592 puQTL at the 10% FDR level. The results of puQTL mapping enabled us to interpret the manner in which genomic variations regulate gene expression. We found that 310 puQTL genes (16.1%) were not detected by eQTL analysis, suggesting that our pipeline can identify novel variant-gene associations. Furthermore, we identified genomic loci associated with the activity of "hidden" promoters, which the standard eQTL studies have ignored. We found that most puQTL signals were concordant with at least one genome-wide association study (GWAS) signal, enabling novel interpretations of the molecular mechanisms of complex traits. Our results emphasize the importance of the re-analysis of public RNA-seq datasets to obtain novel insights into gene regulation by genomic variations and their contributions to complex traits.

genomics↗

bioRxiv2021

Functional variants in hematopoietic transcription factor footprints and their roles in the risk of immune system diseases

Genome-wide association studies (GWAS) have been performed to identify thousands of variants in the human genome as disease risk markers, but functional variants that actually affect gene regulation and their genomic features remain largely unknown. Here we performed a comprehensive survey of functional variants in the regulatory elements of the human genome. We integrated hematopoietic transcription factor (TF) footprints datasets generated by ENCODE project with multiple quantitative trait locus (QTL) datasets (eQTL, caQTL, bQTL, and hQTL) and investigated the associations of functional variants and immune system disease risk. We identified candidate regulatory variants highly linked with GWAS lead variants and found that they were strongly enriched in active enhancers in hematopoietic cells, emphasizing the clinical relevance of enhancers in disease risk. Moreover, we found some strong relationships between traits and hematopoietic cell types or TFs. We highlighted some credible regulatory variants and found that a variant, rs2291668, which potentially functions in the molecular pathogenesis of multiple sclerosis, is located within a TF footprint present in a protein-coding exon of the TNFSF14 gene, indicating that protein-coding exons as well as noncoding regions can possess clinically relevant regulatory elements. Collectively, our results shed light on the molecular pathogenesis of immune system diseases. The methods described in this study can readily be applied to the study of the risk factors of other diseases.

genomics↗

bioRxiv2018

A transgenic mutant mouse line accompanied by the complete deletion of interleukin-33 showed insulin and leptin resistances

Interleukin (IL) -33 has been identified as a member of the IL-1 family. Members of the IL-1 family have been reported to be involved in the regulation of energy homeostasis and glucose metabolism. Homozygous transgenic mutant mice of FLP14 line, that we previously generated, unexpectedly developed mature-onset obesity and diabetes. Through genetic investigations, we found that insertion of the transgenes had resulted in complete deletion of the Il33 gene. These obese male homozygous mutant mice exhibited hyperphagia with hyperleptinemia and insulin resistance caused by increased hepatic gluconeogenesis and decreased glucose uptake in skeletal muscle. As a result of examining preobese male homozygous mutant mice to investigate with the exclusion of the effect of obesity, hyperphagia with hyperleptinemina and insulin resistance caused by decreased glucose uptake in skeletal muscle were already observed, but the increased hepatic glucose production was not. To investigate whether the insulin resistance was caused by deletion of the Il33 gene, we treated these preobese homozygous mutant mice with recombinant IL-33 protein and noted a significant improvement in insulin resistance. Thus, insulin resistance in these homozygous mutant mice was caused, at least in part, by IL-33 deficiency, suggesting a favorable role of IL-33 for glucose metabolism in the skeletal muscle.

molecular biology↗