Biology subjects

Chun, E.

Publications and source records attributed to Chun, E..

6 recordsLinked to original sources

bioRxiv2026

Microbial-associated acylated putrescines as immunomodulatory molecules in inflammatory bowel diseases

The gut microbiota regulates intestinal immunity through metabolite production, yet most disease-associated metabolites remain functionally uncharacterized. In inflammatory bowel diseases (IBD), where the microbial metabolome is profoundly altered, we identify N-acyl putrescines as microbiome-associated metabolites enriched across two independent cohorts. N-oleoylputrescine (NOP) emerges as the primary immunomodulatory candidate, inducing robust transcriptional responses in dendritic cells and colonic organoids. Enterocloster species harboring nonribosomal peptide synthetase gene clusters synthesize NOP, confirmed by isotope-tracing in vitro and germ-free mouse colonization in vivo. NOP suppresses core IBD inflammatory pathways in mouse dendritic cells and human monocytes, reducing signatures of histologic inflammation and therapy non-response. NOP dampens inflammation in four colitis models, decreases myeloid cell NF-{kappa}B activation, and suppresses type 1 immune responses through a T cell-intrinsic mechanism. That NOP accumulates in IBD despite its anti-inflammatory properties reveals a holobiont defense strategy: the gut microbiota deploys immunomodulatory metabolites as a compensatory response to restore homeostasis.

immunology↗

bioRxiv2026

Integrating single-cell and bulk transcriptomic perturbation resources reveals complementary therapeutic spaces for drug repurposing

Transcriptome-based drug repurposing can accelerate therapeutic discovery, but is limited by fragmented resources, inconsistent quality control, and reliance on single perturbation databases. We developed CDRPipe (Computational Drug Repurposing Pipeline), a unified framework that interrogates disease signatures against drug perturbation signatures generated by distinct experimental technologies. Specifically, CDRPipe harmonizes microarray perturbation profiles from the Connectivity Map (CMap; 1,968 quality-filtered experiments) with pseudo-bulk profiles derived from large-scale single-cell RNA sequencing experiments in the Tahoe-100M database (56,827 experiments). CDRPipe standardizes preprocessing, computes rank-based connectivity scores, and evaluates significance using empirical null models. We applied CDRPipe to 233 curated disease signatures from GEO and CREEDS and evaluated performance using known drug-disease associations from Open Targets. Single-cell-derived pseudo-bulk profiles recovered more annotated therapeutics than microarray profiles (median recall 50.0% vs. 6.2%; Wilcoxon p < 10-{superscript 1}{superscript 1}), thought these differences partly reflect differences in drug library composition and clinical annotation coverage. Importantly, the two resources were highly complementary, with only 3.5% overlap in recovered drugs, indicating that integrating predictions across independent perturbation resources expands therapeutic coverage and enables identification of high-confidence consensus candidates. Case studies in autoimmune disease and endometriosis further demonstrate that CDRPipe recovers clinically relevant therapies while revealing technology-dependent patterns of discovery. These results show that integrating heterogeneous transcriptomic perturbation resources improves the robustness and interpretability of transcriptional drug repurposing. One Sentence SummaryIntegrating drug perturbation resources from distinct transcriptomic platforms improves the robustness and accuracy of drug repurposing predictions.

bioinformatics↗

bioRxiv2024

Proteomic Profiling Reveals Age-Related Changes in Transporter Proteins in the Human Blood-Brain Barrier

The Blood-Brain Barrier (BBB) is a crucial, selective barrier that regulates the entry of molecules including nutrients, environmental toxins, and therapeutic medications into the brain. This function relies heavily on brain endothelial cell proteins, particularly transporters and tight junction proteins. The BBB continues to develop postnatally, adapting its selective barrier function across different developmental phases, and alters with aging and disease. Here we present a global proteomics analysis focused on the ontogeny and aging of proteins in human brain microvessels (BMVs), predominantly composed of brain endothelial cells. Our proteomic profiling quantified 6,223 proteins and revealed possible age-related alteration in BBB permeability due to basement membrane component changes through the early developmental stage and age-dependent changes in transporter expression. Notable changes in expression levels were observed with development and age in nutrient transporters and transporters that play critical roles in drug disposition. This research 1) provides important information on the mechanisms that drive changes in the metabolic content of the brain with age and 2) enables the creation of physiologically based pharmacokinetic models for CNS drug distribution across different life stages.

developmental biology↗

bioRxiv2022

Real-time feeding behavior monitoring by electrical penetration graph rapidly reveals host plant susceptibility to crapemyrtle bark scale (Hemiptera: Eriococcidae)

Host range confirmation of invasive hemipterans relies on the evaluation of plant susceptibility though greenhouse or field trials, which are inefficient and time-consuming. When the green industry faces the fast-spreading threat of invasive pests such as crapemyrtle bark scale (Acanthococcus lagerstroemiae), it is imperative to timely identify potential host plants and evaluate plant resistance/susceptibility to pest infestation. In this study, we developed an alternative technology to complement the conventional host confirmation methods. We used electrical penetration graph (EPG) based technology to monitor the A. lagerstroemiae stylet-tip position when it was feeding on different plant tissues in real-time. The frequency and relative amplitude of insect feeding waveforms (recorded by EPG) were extracted by an R programming-based software written to generate eleven feeding parameters for comparative analysis between plant species. The results demonstrated that the occurrences of phloem phase and xylem phase offered conclusive evidence for host plant evaluation. Furthermore, parameters including the percentage of insects capable of accessing phloem tissue, time duration spent on initiating phloem phase and ingesting phloem sap, provided insight into why host plant susceptibility differs among similar plant species. In summary, this study developed a novel real-time diagnostic tool for quick A. lagerstroemiae host confirmation, which laid the essential foundation for effective pest management. Simple SummaryCrapemyrtle bark scale (CMBS; Acanthococcus lagerstroemiae), an invasive polyphagous sap feeder in the United States, has spread across 16 U.S. states in less than two decades, posing potential risks to the Green Industry. Confirming the host range is crucial for effective pest management of invasive insects. However, host range confirmation relying on greenhouse or field trials is often inefficient and time-consuming. In this study, we used the electrical penetration graph (EPG) to monitor the stylet penetration of CMBS in plant tissue in real-time. An R programming-based application was developed to better characterize the insect feeding waveforms recorded by EPG. By analyzing EPG-based feeding parameters, we demonstrated that CMBS have difficulty accessing the phloem tissue (salivation and ingestion) of a resistant plant compared to a susceptible plant. Importantly, we hereby present CMBS typical feeding behaviors on susceptible and non-susceptible plants comparatively, which provides direct evidence for revealing unknown hosts rapidly.

plant biology↗

bioRxiv2021

Discovery of indole-modified aptamers for highly specific recognition of protein glycoforms

Glycosylation is one of the most abundant forms of post-translational modification, and can have a profound impact on a wide range of biological processes and diseases. Unfortunately, efforts to characterize such modifications in the context of basic and clinical research are severely hampered by the lack of affinity reagents that can differentiate protein glycoforms. This lack of reagents is largely due to the challenges associated with generating affinity reagents that can bind to particular glycan epitopes with robust affinity and specificity. In this work, we use a fluorescence-activated cell sorting (FACS)-based approach to generate and screen aptamers with indole-modified bases in an effort to isolate reagents that can differentiate between protein glycoforms. Using this approach, we were able to select multiple aptamers that exhibit strong selectivity for specific glycoforms of two different proteins, with the capacity to discriminate between molecules with identical tertiary structures that differ only in terms of their glycan modifications.

bioengineering↗

bioRxiv2020

Interpreting blood GLUcose data with R package iglu

Continuous Glucose Monitoring (CGM) data play an increasing role in clinical practice as they provide detailed quantification of blood glucose levels during the entire 24-hour period. The R package iglu implements a wide range of CGM-derived metrics for measuring glucose control and glucose variability. The package also allows to visualize CGM data using time-series and lasagna plots. A distinct advantage of iglu is that it comes with a point-and-click graphical user interface (GUI) which makes the package widely accessible to users regardless of their programming experience. Thus, open-source and easy to use iglu package will help advance CGM research and CGM data analyses. R package iglu is publicly available on CRAN and at https://github.com/irinagain/iglu.

bioinformatics↗