Biology subjects

Link, V. M.

Publications and source records attributed to Link, V. M..

8 recordsLinked to original sources

bioRxiv2026

Ketogenic diet synergistic reprogramming of both host and microbiome promotes tissue regeneration

Nutrition influences host physiological processes, yet how diets reshape host physiology, microbial functions, or host-microbe interactions to promote regeneration remains poorly explored. Here, we show that a ketogenic diet (KD), enriched in fats and low in carbohydrates, reprograms both skin microbial and immune functions to promote tissue repair. KD enhances IL-17A activity in {gamma}{delta} T cells and mucosal-associated invariant T (MAIT) cells, accelerating tissue repair, while KD-induced skin lipidomic alterations enhance both the abundance and metabolic output of Staphylococcus epidermidis. Metatranscriptomic and lipidomic analyses revealed increased riboflavin biosynthesis and sphingomyelinase (Sph)-dependent ceramide production in S. epidermidis under KD conditions. Genetic depletion of microbial ribD, a key enzyme for riboflavin biosynthesis, or of sph compromised the ability of the bacteria to promote tissue repair. Thus, host nutritional status drives tissue regeneration by synergistically rewiring host and microbial functions, providing new insights into how diet can be harnessed to regulate host physiology.

immunology↗

bioRxiv2025

Endogenous retroelements promote tolerance to dietary antigens

Retroelements are transposable elements that represent a significant portion of eukaryotic genomes. Here, we show that constitutive expression of endogenous retroelements play a key regulatory role in the acquisition of food tolerance. Specifically, inhibition of retroelement reverse transcription abolishes tolerance to dietary antigens and promotes allergic responses. This phenomenon is associated with impaired regulatory T cell differentiation/accumulation and altered dendritic cell tolerogenic function. Mechanistically, innate sensing of retroelement-derived cDNA via cGAS/STING within gut epithelial cells promotes a local tolerogenic milieu. Thus, within the gut, immune reactivity to retroelements act as a local tonic signal required for regulatory T cell induction and differentiation, thereby preventing allergic responses to food. Collectively, these findings uncover retroelements as key regulatory elements and essential allies in maintaining immune tolerance.

immunology↗

bioRxiv2024

Adaptive immunity to retroelements promotes barrier integrity

Maintenance of tissue integrity is a requirement of host survival. This mandate is of prime importance at barrier sites that are constitutively exposed to the environment. Here, we show that exposure of the skin to non-inflammatory xenobiotics promotes tissue repair; more specifically, mild detergent exposure promotes the reactivation of defined retroelements leading to the induction of retroelement-specific CD8+ T cells. These T cell responses are Langerhans cell dependent and establish tissue residency within the skin. Upon injury, retroelement-specific CD8+ T cells significantly accelerate wound repair via IL-17A. Collectively, this work demonstrates that tonic environmental exposures and associated adaptive responses to retroelements can be coopted to preemptively set the tissue for maximal resilience to injury.

immunology↗

bioRxiv2023

The neuroimmune CGRP-RAMP1 axis tunes cutaneous adaptive immunity to the microbiota

The somatosensory nervous system surveils external stimuli at barrier tissues, regulating innate immune cells under infection and inflammation. The roles of sensory neurons in controlling the adaptive immune system, and more specifically immunity to the microbiota, however, remain elusive. Here, we identified a novel mechanism for direct neuroimmune communication between commensal-specific T lymphocytes and somatosensory neurons mediated by the neuropeptide Calcitonin Gene-Related Peptide (CGRP) in the skin. Intravital imaging revealed that commensal-specific T cells are in close proximity to cutaneous nerve fibers in vivo. Correspondingly, we observed upregulation of the receptor for the neuropeptide CGRP, RAMP1, in CD8+ T lymphocytes induced by skin commensal colonization. Neuroimmune CGRP-RAMP1 signaling axis functions in commensal-specific T cells to constrain Type 17 responses and moderate the activation status of microbiota-reactive lymphocytes at homeostasis. As such, modulation of neuroimmune CGRP-RAMP1 signaling in commensal-specific T cells shapes the overall activation status of the skin epithelium, thereby impacting the outcome of responses to insults such as wounding. The ability of somatosensory neurons to control adaptive immunity to the microbiota via the CGRP-RAMP1 axis underscores the various layers of regulation and multisystem coordination required for optimal microbiota-reactive T cell functions under steady state and pathology. Significance statementMultisystem coordination at barrier surfaces is critical for optimal tissue functions and integrity, in response to microbial and environmental cues. In this study, we identified a novel neuroimmune crosstalk mechanism between the sensory nervous system and the adaptive immune response to the microbiota, mediated by the neuropeptide CGRP and its receptor RAMP1 on skin microbiota-induced T lymphocytes. The neuroimmune CGPR-RAMP1 axis constrains adaptive immunity to the microbiota and overall limits the activation status of the skin epithelium, impacting tissue responses to wounding. Our study opens the door to a new avenue to modulate adaptive immunity to the microbiota utilizing neuromodulators, allowing for a more integrative and tailored approach to harnessing microbiota-induced T cells to promote barrier tissue protection and repair.

immunology↗

bioRxiv2022

Systematic analysis of transcriptional and epigenetic effects of genetic variation in Kupffer cells enables discrimination of cell intrinsic and environment-dependent mechanisms

Noncoding genetic variation is a major driver of phenotypic diversity but determining the underlying mechanisms and the cell types in which it acts remain challenging problems. Here, we investigate the impact of natural genetic variation provided by phenotypically diverse inbred strains of mice on gene expression and epigenetic landscapes of Kupffer cells. Analysis of gene expression in Kupffer cells and other liver cell types derived from C57BL/6J, BALB/cJ and A/J mice provided evidence for strain-specific differences in environmental factors influencing Kupffer cell phenotypes, including preferential Leptin signaling in BALB/cJ Kupffer cells. Systematic analysis of transcriptomic and epigenetic data from F1 hybrids of these mice, and transcriptomic data from strain-specific Kupffer cells engrafted into a common host enabled quantitative assessment of cis versus trans effects of genetic variation on gene expression and an estimate of cell autonomous versus non cell autonomous effects. Under homeostatic conditions, trans effects of genetic variation were dominant, with the majority of trans regulation being non cell autonomous. In contrast, strain specific responses to acutely administered LPS were primarily associated with genetic variation acting in cis to modify response elements for lineage determining and signal dependent transcription factors. Collectively, these findings reveal cell intrinsic and environmental effects of natural genetic variation on gene expression, demonstrate the use of enhancers as detectors of trans effects of genetic variation, and provide a new resource for understanding the impact of genetic variation on gene expression in Kupffer cells.

genomics↗

bioRxiv2021

Functional non-coding SNPs in human endothelial cells fine-map vascular trait associations

Functional consequences of genetic variation in the non-coding human genome are difficult to ascertain despite demonstrated associations to common, complex disease traits. To elucidate properties of functional non-coding SNPs with effects in human endothelial cells (EC), we utilized molecular Quantitative Trait Locus (molQTL) analysis for transcription factor binding, chromatin accessibility, and H3K27 acetylation to nominate a set of likely functional non-coding SNPs. Together with information from genome-wide association studies for vascular disease traits, we tested the ability of 34,344 variants to perturb enhancer function in ECs using the highly multiplexed STARR-seq assay. Of these, 5,592 variants validated, whose enriched attributes included: 1) mutations to TF binding motifs for ETS or AP1 that are regulators of EC state, 2) location in accessible and H3K27ac-marked EC chromatin, and 3) molQTLs associations whereby alleles associate with differences in chromatin accessibility and TF binding across genetically diverse ECs. Next, using pro-inflammatory IL1B as an activator of cell state, we observed robust evidence (>50%) of context-specific SNP effects, underscoring the prevalence of non-coding gene-by-environment (GxE) effects. Lastly, using these cumulative data, we fine-mapped vascular disease loci and highlight evidence suggesting mechanisms by which non-coding SNPs at two loci affect risk for Pulse Pressure/Large Artery Stroke, and Abdominal Aortic Aneurysm through respective effects on transcriptional regulation of POU4F1 and LDAH. Together, we highlight the attributes and context dependence of functional non-coding SNPs, and provide new mechanisms underlying vascular disease risk.

genetics↗

bioRxiv2018

Diverse motif ensembles specify non-redundant DNA binding activities of AP-1 family members in macrophages

Mechanisms by which members of the AP-1 family of transcription factors play both redundant and non-redundant biological roles despite recognizing the same DNA sequence remain poorly understood. To address this question, we investigated the molecular functions and genome-wide DNA binding patterns of AP-1 family members in macrophages. ChIP-sequencing showed overlapping and distinct binding profiles for each factor that were remodeled following TLR4 ligation. Development of a machine learning approach that jointly weighs hundreds of DNA recognition elements yielded dozens of motifs predicted to drive factor-specific binding profiles. Machine learning-based predictions were confirmed by analysis of the effects of mutations in genetically diverse mice and by loss of function experiments. These findings provide evidence that non-redundant genomic locations of different AP-1 family members in macrophages largely result from collaborative interactions with diverse, locus-specific ensembles of transcription factors and suggest a general mechanism for encoding functional specificities of their common recognition motif.

genomics↗

bioRxiv2018

MARGE: Mutation Analysis for Regulatory Genomic Elements

Cell-specific patterns of gene expression are determined by combinatorial actions of sequence-specific transcription factors at cis-regulatory elements. Studies indicate that relatively simple combinations of lineage-determining transcription factors (LDTFs) play dominant roles in the selection of enhancers that establish cell identities and functions. LDTFs require collaborative interactions with additional transcription factors to mediate enhancer function, but the identities of these factors are often unknown. We have shown that natural genetic variation between individuals has great utility for discovering collaborative transcription factors. Here, we introduce MARGE (Mutation Analysis of Regulatory Genomic Elements), the first publicly available suite of software tools that integrates genome-wide genetic variation with epigenetic data to identify collaborative transcription factor pairs. MARGE is optimized to work with chromatin accessibility assays (such as ATAC-seq or DNase I hypersensitivity), as well as transcription factor binding data collected by ChlP-seq. Herein, we provide investigators with rationale for each step in the MARGE pipeline and key differences for analysis of datasets with different experimental designs. We demonstrate the utility of MARGE using mouse peritoneal macrophages, liver cells, and human lymphoblastoid cells. MARGE provides a powerful tool to identify combinations of cell type-specific transcription factors while simultaneously interpreting functional effects of non-coding genetic variation.

bioinformatics↗