Biology subjects

King, N. J. C.

Publications and source records attributed to King, N. J. C..

5 recordsLinked to original sources

bioRxiv2024

High fat low carbohydrate diet is linked to protection against CNS autoimmunity

Multiple sclerosis (MS) is a common central nervous system (CNS) autoimmune disease, and diets and nutrients are emerging as critical contributing factors. However, a comprehensive understanding of their impacts and the underlying mechanisms involved is lacking. Harnessing state-of-the-art nutritional geometry analytical methods, we first revealed that globally, increased carbohydrate supply was associated with increased MS disease burden, while fat supply had an opposite effect. Furthermore, in a preclinical MS mouse model, experimental autoimmune encephalomyelitis (EAE), we found that an isocaloric diet high in carbohydrate aggravated EAE, while a diet enriched in fat was fully protective. This was reflected by reduced neuroinflammation and skewing towards anti-inflammatory phenotypes, which involved transcriptomic, epigenetic and immunometabolic changes. We showcased that manipulating diets is a potentially efficient and cost-effective approach to prevent and/or ameliorate EAE. This exhibits translational potentials for intervention/prevention of MS and possibly other autoimmune diseases.

immunology↗

bioRxiv2023

Fecal microbial transfer and complex carbohydrates mediate protection against COPD

ObjectiveChronic obstructive pulmonary disease (COPD) is a major cause of global illness and death, most commonly caused by cigarette smoke. The mechanisms of pathogenesis remain poorly understood, limiting the development of effective therapies. The gastrointestinal microbiome has been implicated in chronic lung diseases via the gut-lung axis, but its role is unclear. DesignUsing an in vivo mouse model of cigarette smoke-induced COPD and fecal microbial transfer (FMT), we characterized the fecal microbiota using metagenomics, proteomics and metabolomics. Findings were correlated with airway and systemic inflammation, lung and gut histopathology, and lung function. Complex carbohydrates were assessed in mice using a high resistant starch diet, and in sixteen COPD patients using a randomized, double-blind, placebo-controlled pilot study of inulin supplementation. ResultsFMT alleviated hallmark features of COPD (inflammation, alveolar destruction, impaired lung function), gastrointestinal pathology and systemic immune changes. Protective effects were additive to smoking cessation. Disease features correlated with the relative abundance of Muribaculaceae, Desulfovibrionaceae and Lachnospiraceae family members. Proteomics and metabolomics identified downregulation of glucose and starch metabolism in cigarette smoke-associated microbiota, and supplementation of mice or human patients with complex carbohydrates improved disease outcomes. ConclusionThe gut microbiome contributes to COPD pathogenesis and can be targeted therapeutically. What is already known on this topicO_LIChanges in gut microbiota are associated with COPD but the underlying host and microbial mechanisms are unclear, limiting the therapeutic applications. C_LI What this study addsO_LIMicrobiome composition and metabolism is reproducibly correlated with lung and gastrointestinal pathology in experimental COPD. C_LIO_LIMicrobiome modifying interventions effectively alleviate disease, including protective effects supplementing smoking cessation. C_LIO_LINutritional interventions targeting the microbiome in COPD patients demonstrate efficacy in a small pilot study. C_LI How this study might affect research, practice or policyO_LIMicrobiome-targeting therapeutics and nutritional interventions may be developed for COPD, including as supplements to smoking cessation. C_LI

physiology↗

bioRxiv2023

A unique human cord blood CD8+CD45RA+CD27+CD161+ T cell subset identified by flow cytometric data analysis using Seurat

Advances in single cell analysis, especially cytometric approaches, have profoundly innovated immunological research. This has resulted in an expansion of high dimensional data, posing great challenges for comprehensive and unbiased analysis. Conventional manual analysis thus becomes untenable, while most computational methods lack flexibility and interoperability, hampering usability. Here, for the first time, we adapted Seurat, a single cell RNA sequencing (scRNA-seq) analysis package, for end-to-end flow cytometric data analysis. We showcased its robust analytical capacity by analyzing the adult blood and cord blood T cell profiles, which was validated by Spectre, another cytometric data analysis package, and manual analysis. Importantly, a unique CD8+CD45RA+CD27+CD161+ T cell subset, was identified in cord blood and characterized using flow cytometry and scRNA-seq analysis from a published dataset. Collectively, Seurat possesses great potential for cytometric data analysis. It facilitates thorough interpretations of high dimensional data using a single pipeline, implementing data-driven investigation in clinical immunology.

immunology↗

bioRxiv2022

Early microglial response, myelin deterioration and lethality in mice deficient for very long chain ceramide synthesis in oligodendrocytes

The sphingolipids galactosylceramide (GalCer), sulfatide (ST) and sphingomyelin (SM) are essential for myelin stability and function. GalCer and ST are synthesized mostly from C22-C24 ceramides, generated by Ceramide Synthase 2 (CerS2). To clarify the requirement for C22-C24 sphingolipid synthesis in myelin lipid biosynthesis and stability, we generated mice lacking CerS2 specifically in myelinating cells (CerS2{Delta}O/{Delta}O). At 6 weeks of age, normal-appearing myelin had formed in CerS2{Delta}O/{Delta}O mice, however there was a reduction in myelin thickness and the percentage of myelinated axons. Pronounced loss of C22-C24 sphingolipids in myelin of CerS2{Delta}O/{Delta}O mice was compensated by greatly increased levels of C18 sphingolipids. A distinct microglial population expressing high levels of activation and phagocytic markers such as CD64, CD11c, MHC class II, and CD68 was apparent at 6 weeks of age in CerS2{Delta}O/{Delta}O mice, and had increased by 10 weeks. Increased staining for denatured myelin basic protein was also apparent in 6-week-old CerS2{Delta}O/{Delta}O mice. By 16 weeks, CerS2{Delta}O/{Delta}O mice showed pronounced myelin atrophy, motor deficits, and axon beading, a hallmark of axon stress. 90% of CerS2{Delta}O/{Delta}O mice died between 16 and 26 weeks of age. This study highlights the importance of sphingolipid acyl chain length for the structural integrity of myelin, demonstrating how a modest reduction in lipid chain length causes exposure of a denatured myelin protein epitope and expansion of phagocytic microglia, followed by axon pathology, myelin degeneration, and motor deficits. Understanding the molecular trigger for microglial activation should aid the development of therapeutics for demyelinating and neurodegenerative diseases. Main PointsO_LIOligodendrocytes lacking CerS2 produce myelin using sphingolipids with C16/C18 instead of C22/C24 N-acyl chains C_LIO_LIC22/C24 myelin sphingolipids are essential for myelin stability, microglial quiescence, and survival beyond young adulthood C_LI Table of Contents Image O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=172 SRC="FIGDIR/small/493337v2_ufig1.gif" ALT="Figure 1"> View larger version (52K): org.highwire.dtl.DTLVardef@1125540org.highwire.dtl.DTLVardef@9aeebdorg.highwire.dtl.DTLVardef@1afbeb4org.highwire.dtl.DTLVardef@11156c2_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

bioRxiv2020

Integration, exploration, and analysis of high-dimensional single-cell cytometry data using Spectre

As the size and complexity of high-dimensional cytometry data continue to expand, comprehensive, scalable, and methodical computational analysis approaches are essential. Yet, contemporary clustering and dimensionality reduction tools alone are insufficient to analyze or reproduce analyses across large numbers of samples, batches, or experiments. Moreover, approaches that allow for the integration of data across batches or experiments are not well incorporated into computational toolkits to allow for streamlined workflows. Here we present Spectre, an R package that enables comprehensive end-to-end integration and analysis of high-dimensional cytometry data from different batches or experiments. Spectre streamlines the analytical stages of raw data pre-processing, batch alignment, data integration, clustering, dimensionality reduction, visualization and population labelling, as well as quantitative and statistical analysis. Critically, the fundamental data structures used within Spectre, along with the implementation of machine learning classifiers, allow for the scalable analysis of very large high-dimensional datasets, generated by flow cytometry, mass cytometry (CyTOF), or spectral cytometry. Using open and flexible data structures, Spectre can also be used to analyze data generated by single-cell RNA sequencing (scRNAseq) or high-dimensional imaging technologies, such as Imaging Mass Cytometry (IMC). The simple, clear, and modular design of analysis workflows allow these tools to be used by bioinformaticians and laboratory scientists alike. Spectre is available as an R package or Docker container. R code is available on Github (https://github.com/immunedynamics/spectre).

immunology↗