Biology subjects

Jeong, M.

Publications and source records attributed to Jeong, M..

18 recordsLinked to original sources

bioRxiv2026

Genome-wide LD scores enable robust heritability and genetic correlation estimation from summary statistics across genetic ancestries

Our knowledge of human complex trait architecture across diverse populations remains limited. Estimating SNP heritability and genetic correlation from GWAS summary statistics - successful in revealing genetic architecture in homogeneous cohorts - is challenging in structured and admixed populations due, in part, to the difficulty of representing long-range LD. We present SUMMIT, a statistical framework that combines genome-wide LD scores, efficiently estimated using random projections, with GWAS summary statistics to estimate genome-wide and annotation-specific heritability and genetic correlation. In simulations that explore diverse aspects of genetic architecture across European (EUR), South Asian (SAS), and admixed African-European cohorts (AFR) in the UK Biobank (UKB), SUMMIT had increased accuracy and reduced bias compared to prior methods, with the largest gains in non-European ancestries reflecting improved modeling of long-range LD. Across 40 UKB traits, SUMMIT produced estimates of genome-wide common-SNP heritability (h_g^2) and heritability enrichments in genomic annotations that were broadly concordant across ancestries with the SUMMIT h_g^2 estimates more closely matching recent whole-genome sequencing based estimates. SUMMIT substantially improved genetic correlation analysis recovering more significant findings across ancestries (23 SAS and 3 AFR at FDR < 0.05 compared with none and two for cov-LDSC) with the non-European discoveries showing concordant effects in Europeans suggesting that, like heritability, global patterns of pleiotropy are largely shared across ancestries. By combining accurate genome-wide LD and efficient moment estimation, SUMMIT enables investigation into how heritability and genetic correlation vary across populations and genomic annotations, including in structured and admixed cohorts, at the genome-wide, annotation-specific, and cross-trait levels.

genomics↗

bioRxiv2026

Cross-Species Efficacy of Combinatorial Gene Therapy for Osteoarthritis and Correction of Neuro-Inflammatory Pain Mechanisms

Osteoarthritis is a leading cause of chronic pain and disability, which lacks disease-modifying treatment. Given the complex multi-tissue and multifactorial drivers behind disease progression, effective treatments will require simultaneously targeting several mechanisms underlying joint degeneration and pain. Here, we developed and evaluated a combinatorial gene therapy, consisting of a high-capacity adenoviral vector carrying two therapeutic genes to target distinct pathological mechanisms: inflammation (IL-1Ra) and chondrocyte health (PRG4). Intra-articular delivery of this treatment improved functional, structural, and pain outcomes in murine and equine osteoarthritis models. In addition, treatment normalized inflammatory environments in joint tissues, as well as in the dorsal root ganglia (DRG) known to harbor joint-innervating sensory neurons. Moreover, gene therapy reversed OA-induced molecular signatures of neural hyperexcitability, suggesting amelioration of peripheral sensitization. Collectively, these findings support combinatorial gene therapy as a promising treatment for osteoarthritis, while identifying neuroinflammatory signatures for correction of disease progression and pain. One Sentence SummaryA single intra-articular injection of a combinatorial gene therapy slows OA progression and reduces pain in small and large animal models.

systems biology↗

bioRxiv2026

Overlapping MHC class I/II Epitopes Program cDC1-like Differentiation of Monocyte-Derived Dendritic Cells via mTORC1 Signaling Inhibition

Viral infection polarizes monocyte-derived dendritic cells (moDC) to initiate type 1 immunity. The availability of overlapping (homologous) MHC class I and II epitopes, an occurrence frequently and primarily associated with intracellular infection, significantly enhances this process; however, the underlying mechanism(s) are unclear. We demonstrate that moDC loaded with homologous MHC epitopes acquire a cDC1-like phenotype in a process governed by mTORC1. mTORC1 pathway inhibition leads to NF-{kappa}B-mediated expression of IL-12 and other type I immune polarizing genes. The observed cDC1-like gene signature was also significantly enhanced in clinical moDC vaccine products made through methodologies that enforced class I and II antigenic homology. Collectively, these findings reveal a novel and previously unrecognized mechanism of immune governance that might also be exploited in cancer immunotherapy. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=167 SRC="FIGDIR/small/716309v1_ufig1.gif" ALT="Figure 1"> View larger version (41K): org.highwire.dtl.DTLVardef@15475borg.highwire.dtl.DTLVardef@ffe5fborg.highwire.dtl.DTLVardef@53c761org.highwire.dtl.DTLVardef@46c4ef_HPS_FORMAT_FIGEXP M_FIG C_FIG

immunology↗

bioRxiv2026

A biobank-scale method for learning modulators of gene-environment interaction underlying human complex traits from multiple environmental exposures

It is increasingly recognized that genetic effects on complex traits and diseases are shaped by environmental context. Biobanks that measure diverse environmental exposures alongside genotypes and phenotypes at scale enable systematic study of gene-environment (GxE) interactions. Existing approaches, however, are limited in their ability to accurately model polygenic GxE involving many exposures across genome-wide genetic variants. It is unclear which exposure combinations are relevant for a given trait while distinguishing true interactions from environment-dependent heteroskedastic noise. To address these challenges, we develop Efficient multi-eNvironmental Gene-environment Interaction iNference Estimator (ENGINE), a supervised variance-component framework that learns an embedding that combines multiple environmental exposures while jointly estimating additive, GxE, and heteroskedastic noise components. To enable biobank-scale inference, ENGINE makes a single pass over the genotype matrix to cache genotype-dependent summaries, then assembles normal-equation components and gradients at each iteration. In simulations, ENGINE controls type I error rates, achieves high power, and accurately recovers the environmental embedding while remaining efficient at biobank-scale. Applied to five complex traits paired with lifestyle exposures in N = 291,273 unrelated white British individuals and M = 454,207 common SNPs (MAF> 0.01) from the UK Biobank, ENGINE recovered GxE variance that was on average 1.4-fold larger than that captured by a single exposure and 5.5-fold larger than that captured by the first principal component of the exposures.

genetics↗

bioRxiv2025

Comprehensive gene heritability estimation reveals the genetic architecture of rare coding variants underlying complex traits

Whole-exome sequencing (WES) enables high-resolution interrogation of the contribution of rare coding variants to complex trait variation. However, existing methods for heritability estimation attributed to rare-coding variants are often limited by the effects of linkage disequilibrium (LD) and by the sparse nature of rare variant data. We introduce FLEX (Fast, LD-aware Estimation of eXome-wide and gene-level heritability), a scalable and flexible framework for estimating and partitioning heritability across genes or sets of genes using WES data. FLEX integrates all coding variants- from common to ultra-rare - within a unifled model and corrects for LD-induced effects to improve the accuracy of heritability estimates. In addition, FLEX supports both individual-level and summary statistic data and is computationally efflcient for biobank-scale datasets. Through extensive simulations, we show that FLEX is well-calibrated while providing accurate heritability estimates. We applied FLEX to WES data across N = 153, 351 unrelated European ancestry individuals and 20 quantitative traits in the UK Biobank. We identifled 64 gene-trait pairs with signiflcant gene-level heritability (p < 0.05/18, 624 accounting for the number of protein-coding genes tested), among which rare coding variants explained 38% of gene-level heritability, on average. Compared to heritability estimates from genome-wide imputed SNPs, incorporation of rare and ultra-rare coding variants led to a 24.8% increase in heritability on average, while effect sizes at rare and ultra-rare variants are substantially larger ({approx} 18x on average). Partitioning across variant effect annotations, we flnd that predicted loss-of-function variants had stronger individual effects than missense variants (24% on average) while missense variants accounted for a greater share of rare coding heritability. Together, FLEX provides an adaptable and accurate approach for quantifying gene-level heritability, advancing our understanding of the genetic architecture of complex traits, and facilitating the discovery of trait-relevant genes.

genetics↗

bioRxiv2025

Distinct modes of dopamine modulation on striatopallidal synaptic transmission

Dopamine (DA) affects voluntary movement by modulating basal ganglia function. In the classical model, DA depletion leads to overactivity of the indirect pathway and excessively inhibits the thalamus, resulting in hypokinesia. The contribution of DA on striatopallidal synapses, an initial hub in the indirect pathway connecting the striatum to the external globus pallidus (GPe), remains poorly understood because of the sparse DA innervation. Here, we combine optogenetic projection targeting, whole cell patch clamp recordings in acute brain slices from mice, and computational modeling to overcome this limitation. We show that DA activates D2R receptors (D2Rs) and D4 receptors (D4Rs) differentially in distinct GPe subregions. In a pinwheel-like fashion, dorsolateral and ventromedial GPe expresses high levels of D2Rs, which exert presynaptic inhibition, while in dorsomedial and ventrolateral GPe D4Rs cause postsynaptic inhibition. DA depletion by 6-OHDA (6-hydroxydopamine) reverses the region- specific effect of DA, shifting it in the opposite direction and contributing to hypokinesia. These findings reveal the mechanism by which the different modality information conveyed spatially through the indirect pathway is differentially modulated by DA at striatopallidal synapses.

neuroscience↗

bioRxiv2025

The N-terminal order-disorder transition is a critical determinant for a metamorphosis of IscU

IscU, a key scaffold protein mediating the biogenesis of iron-sulfur (Fe-S) clusters, exhibits metamorphic characteristics crucial for its versatile and efficient function. Previous studies have demonstrated that IscU has two interconverting conformations: the structured state (S-state) and the disordered state (D-state), each contributing to its distinct functionality and interaction network. Despite its physiological importance, the precise mechanism underpinning the maintenance of IscUs unique structural heterogeneity has remained elusive. In this study, we used computational and experimental approaches to reveal that the N-terminal order-disorder plays a critical role in the metamorphic modulation of IscU. We found that the N-terminal region displays greater structural plasticity, which is linked to other regions of IscU through coevolutionary relationships. Moreover, we demonstrated that the degree of orderliness in the N-terminal region correlates positively with the stabilization of IscUs S-state and negatively with its affinity for HscA. This indicates that the flexibility in the N-terminal region is finely tuned to optimize IscUs physiological efficiency and efficacy. Finally, our data suggest that a peptide mimicking the N-terminal motif can modulate IscUs metamorphic properties, suggesting a novel therapeutic potential for related pathogenic processes.

biochemistry↗

bioRxiv2024

Morphological and Molecular Phylogenetic Characterization of Three New Marine Goniomonad Species

Goniomonads are commonly found heterotrophic biflagellates in both marine and freshwater environments. Despite the high genetic diversity inferred from 18S rDNA data, many goniomonad species remain undescribed. In this study, we established a total of 21 marine goniomonad culture strains, and from these, describe three new species by using light microscopy, electron microscopy, and 18S rDNA phylogeny. Molecular sequence analyses suggest the presence of several distinct sub-lineages within the marine goniomonad clade. Two of these are Goniomonas ulleungensis sp. nov. and G. lingua sp. nov., which are similar in size, flagellar length, appendage & orientation and by having a tongue-like protrusion at the anterior. The two species can be differentiated by the periplast plate pattern with G. ulleungensis displaying one additional plate on the right side. G. duplex sp. nov. differed from these two species by having two unequal flagella with the longer one trailing posteriorly and having the opposite cell orientation when skidding. Comparative analyses of five marine goniomonad species showed that genetically distinct goniomonad groups can be delineated by morphological data as well, and of several morphological features that are of taxonomic utility, the periplast plate pattern, observable by SEM, is particularly informative in goniomonad taxonomy.

evolutionary biology↗

bioRxiv2024

Development of covalent probes to capture Legionella pneumophila effector enzymes

Upon infection of host cells, Legionella pneumophila releases a multitude of effector enzymes into the cells cytoplasm that hijack a plethora of cellular activities, including the hosts ubiquitination pathways. Effectors belonging to the SidE-family are involved in non-canonical serine phosphoribosyl ubiquitination of host substrate proteins contributing to the formation of a Legionella-containing vacuole that is crucial in the onset of Legionnaires disease. This dynamic process is reversed by effectors called Dups that hydrolyse the phosphodiester in the phosphoribosyl ubiquitinated protein. We installed reactive warheads on chemically prepared ribosylated ubiquitin to generate a set of probes targeting these Legionella enzymes. In vitro tests on recombinant DupA revealed that a vinyl sulfonate warhead was most efficient in covalent complex formation. Mutagenesis and x-ray crystallography approaches were used to identify the site of covalent crosslinking to be an allosteric cysteine residue. The subsequent application of this probe highlights the potential to selectively enrich the Dup enzymes from Legionella-infected cell lysates.

cell biology↗

bioRxiv2024

Scalable summary statistics-based heritability estimation method with individual genotype level accuracy

SNP heritability, the proportion of phenotypic variation explained by genotyped SNPs, is an important parameter in understanding the genetic architecture underlying various diseases and traits. Methods that aim to estimate SNP heritability from individual genotype and phenotype data are limited by their ability to scale to Biobank-scale datasets and by the restrictions in access to individual-level data. These limitations have motivated the development of methods that only require summary statistics. While the availability of publicly accessible summary statistics makes them widely applicable, these methods lack the accuracy of methods that utilize individual genotypes. Here we present a SUMmary statistics-based Randomized Haseman-Elston regression (SUM-RHE), a method that can estimate the SNP heritability of complex phenotypes with accuracies comparable to approaches that require individual genotypes, while exclusively relying on summary statistics. SUM-RHE employs Genome-Wide Association Study (GWAS) summary statistics and statistics obtained on a reference population, which can be efficiently estimated and readily shared for public use. Our results demonstrate that SUM-RHE obtains estimates of SNP heritability that are substantially more accurate compared to other summary statistic methods and on par with methods that rely on individual-level data.

genomics↗

bioRxiv2023

FetoML: Interpretable predictions of the fetotoxicity of drugs based on machine learning approaches

Pregnant females may use medications to manage health problems that develop during pregnancy or that they had prior to pregnancy. However, using medications during pregnancy has a potential risk to the fetus. Assessing the fetotoxicity of drugs is essential to ensure safe treatments, but the current process is challenged by ethical issues, time, and cost. Therefore, the need for in silico models to efficiently assess the fetotoxicity of drugs has recently emerged. Previous studies have proposed successful machine learning models for fetotoxicity prediction and even suggest molecular substructures that are possibly associated with fetotoxicity risks or protective effects. However, the interpretation of the decisions of the models on fetotoxicity prediction for each drug is still insufficient. This study constructed machine learning-based models that can predict the fetotoxicity of drugs while providing explanations for the decisions. For this, permutation feature importance was used to identify the general features that the model made significant in predicting the fetotoxicity of drugs. In addition, features associated with fetotoxicity for each drug were analyzed using the attention mechanism. The predictive performance of all the constructed models was significantly high (AUROC: 0.854-0.974, AUPR: 0.890-0.975). Furthermore, we conducted literature reviews on the predicted important features and found that they were highly associated with fetotoxicity. We expect that our model will benefit fetotoxicity research by providing an evaluation of fetotoxicity risk for drugs or drug candidates, along with an interpretation of that prediction. Author summaryDrugs are often necessary for the treatment of diseases in pregnant females. However, some drugs can potentially cause fetotoxicities, such as teratogenicity and abortion. Therefore, it is essential to study fetotoxicity, but traditional toxicity testing demands time, money, and labor. To modernize these testing methods, in silico approaches for predicting the fetotoxicity of drugs are emerging. The proposed models so far have successfully predicted the fetotoxicity of drugs and proposed some fetotoxicity-related substructures, but the interpretation of the models determination is still insufficient. In this study, we proposed FetoML to predict the fetotoxicity of drugs based on machine learning and provide the substructures that the model focused on in predicting fetotoxicity for each drug. We confirmed the significant predictive performance and interpretability of the model through a quantitative performance evaluation and literature review. We expect FetoML to benefit fetotoxicity studies of drugs by modernizing the paradigm of fetotoxicity testing and providing insights to researchers.

systems biology↗

bioRxiv2023

Genetic and transcriptomic analysis of hyphal constriction based on a novel assay method in the rice blast fungus

An ability of fungi to undergo hyphal constriction is important for fungal ecology and diseases. In the rice blast fungus, Magnaporthe oryzae, hyphal constriction is required to traverse host cell junctions through pit fields. However, little is known about genetic underpinnings of hyphal constriction, except the requirement of a mitogen-activated protein kinase, Pmk1. Here we demonstrate that a simple in vitro assay based on nitrocellulose membrane allows investigation of the genetic basis for hyphal constriction. Using the assay, we found that the constriction limit of M. oryzae hypha lies between 0.22 and 0.3 m, and that a histone modification might be involved in hyphal constriction. RNA-seq experiments combining our assay and {Delta}pmk1 showed that hyphal constriction relies on transcriptional changes of genes implicated primarily in membrane and cell wall-related cellular processes in Pmk1-dependent and/or Pmk1-independent manner. Furthermore, our assays with diverse fungal species suggest correlation between hyphal constriction and fungal lifestyles. Our study reveals that hyphal constriction can be induced without host-derived cues and provides molecular and evolutionary insights into a fundamental process to infection of host plant.

microbiology↗

bioRxiv2023

Structural insights into ubiquitin chain cleavage by Legionella ovarian tumor deubiquitinases

Although ubiquitin is found only in eukaryotes, several pathogenic bacteria and viruses possess proteins that hinder the host ubiquitin system. Legionella, a gram-negative intracellular bacterium, possesses an ovarian tumor (OTU) family of deubiquitinases (Lot DUBs). Herein, we describe the molecular characteristics of Lot DUBs. We elucidated the structure of LotA OTU1 domain and revealed that entire Lot DUBs possess a characteristic extended helical lobe (EHL) that is not found in other OTU-DUBs. The structural topology of EHL is the same throughout the Lot family, and it provides an S1' ubiquitin-binding site. Moreover, the catalytic triads of Lot DUBs resemble those of the A20-type OTU-DUBs. Furthermore, we revealed a unique mechanism by which LotA OTU domains cooperate together to distinguish the length of the chain and preferentially cleaves longer K48-linked polyubiquitin chains. The LotA OTU1 domain itself cleaves K6-linked ubiquitin chains, while it is also essential for assisting the cleavage of longer K48-linked polyubiquitin chains by the OTU2 domain. Thus, this study provides novel insights into the structure and mechanism of action of Lot DUBs.

biochemistry↗

bioRxiv2022

Vitamin A-treated NK cells reduce IFN-γ production and support regulatory T cell differentiation

Natural killer (NK) cells are innate cytotoxic lymphocytes that contribute to immune responses against stressed, transformed or infected cells. NK cell effector functions are regulated by microenvironmental factors, including cytokines, metabolites and nutrients. Vitamin A is an essential micronutrient that plays an indispensable role in embryogenesis and development, but was also reported to regulate immune responses. However, the role of vitamin A in regulating NK cell functions remains poorly understood. Here, we show that the most prevalent vitamin A metabolite, all-trans retinoic acid (atRA), induces transcriptional and functional changes in NK cells leading to altered metabolism and reduced IFN-{gamma} production in response to a wide range of stimuli. atRA-exposed NK cells display a reduced ability to support dendritic cell (DC) maturation and to eliminate immature DCs. Moreover, they support the polarization and proliferation of regulatory T cells. These results imply that in vitamin A-enriched environments, NK cells can acquire regulatory-like functions and might promote tolerogenic immunity and/or immunosuppression.

immunology↗

bioRxiv2022

AhR-mediated activation of innate lymphocytes restrains tissue-resident memory-like CD8+ T cell responses during contact hypersensitivity

Allergic contact dermatitis (ACD) and the mouse model of hapten-induced contact hypersensitivity (CHS) are inflammatory skin responses triggered by the repeated exposure to exogenous allergens and haptens. ACD and CHS effector responses have been extensively studied, but the regulatory mechanisms that control inflammation and determine the kinetics of its resolution are still incompletely understood. In addition, although CHS can be mediated by both innate and adaptive effector cells in a non-redundant manner, leading to distinct skin pathologies, their interplay during the course of inflammation remains so far unaddressed. Here, we show that NKp46+ innate lymphoid cells (ILCs) limit the extent of CHS inflammation by modulating the CD8+ TRM immune compartment. This regulatory effect of ILCs depends on the expression of the ligand-induced transcription factor aryl-hydrocarbon receptor (AhR). AhR-deficiency in NKp46+ ILCs did not affect the memory response to hapten, but led to spatial propagation and amplification of inflammatory response in the skin. This phenotype correlated with increased numbers of Ifng-producing CD8+ TRM-like cells and neutrophilic infiltration in the skin. Our study thereby demonstrates a novel AhR-driven innate-adaptive immune interplay in regulating skin inflammation.

immunology↗

bioRxiv2022

Liver sinusoidal endothelial cells orchestrate NK cell recruitment and activation in acute inflammatory liver injury

In both steady-state and during endotoxicosis, liver sinusoidal endothelial cells (LSECs) can rapidly clear lipopolysaccharide (LPS) from the bloodstream. They are located along blood sinusoids of the liver, and establish intimate contact with circulating and tissue-resident immune cells. However, their role in regulating immune responses during LPS-induced endotoxicosis remains poorly understood. Here, we show that LSECs play a dual role in regulating inflammatory responses, acting as modulators of NK cell pro-inflammatory output and as major producers of immune cell-attracting chemokines. We demonstrate that LSECs switch their chemokine expression pattern driven by LPS and IFN-{gamma}, resulting in the production of the myeloid-attracting chemokine CCL2 and the lymphoid-attracting chemokine CXCL10, which accumulate in the serum of LPS-challenged animals. In livers of LPS-injected mice, monocytes and Kupffer cells expressed highest amounts of the pro-inflammatory cytokine Il12a and Il18 transcripts, while NK cells expressed the highest amounts of Ifng. NK cell exposure to LSECs in vitro led to global transcriptomic changes, and primed NK cells to produce higher amounts of IFN-{gamma} in response to IL-12 and IL-18. LSECs required exposure to IFN-{gamma} for Cxcl10 expression, and Cxcl10 gene-deletion in endothelial cells abrogated NK cell accumulation in the liver after LPS treatment. Thus, our data indicate that LSECs occupy a unique temporal and spatial position acting as central regulators that respond to both LPS and immune-derived inflammatory signals, and fuel a positive feedback loop of immune cell attraction and activation in the inflamed liver tissue. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=96 SRC="FIGDIR/small/500206v1_ufig1.gif" ALT="Figure 1"> View larger version (20K): org.highwire.dtl.DTLVardef@653c53org.highwire.dtl.DTLVardef@5ba4bdorg.highwire.dtl.DTLVardef@9caad8org.highwire.dtl.DTLVardef@1945eb5_HPS_FORMAT_FIGEXP M_FIG C_FIG

immunology↗

bioRxiv2022

Exercise reprograms the inflammatory landscape of multiple stem cell compartments during mammalian aging

Exercise has the ability to rejuvenate stem cells and improve tissue homeostasis and regeneration in aging animals. However, the cellular and molecular changes elicited by exercise have not been systematically studied across a broad range of cell types in stem cell compartments. To gain better insight into the mechanisms by which exercise affects niche and stem cell function, we subjected young and old mice to aerobic exercise and generated a single cell transcriptomic atlas of muscle, neural and hematopoietic stem cells with their niche cells and progeny. Complementarily, we also performed whole transcriptome analysis of single myofibers from these animals. We identified common and unique pathways that are compromised across these tissues and cell types in aged animals. We found that exercise has a rejuvenating effect on subsets of stem cells, and a profound impact in the composition and transcriptomic landscape of both circulating and tissue resident immune cells. Exercise ameliorated the upregulation of a number of inflammatory pathways as well as restored aspects of cell-cell communication within these stem cell compartments. Our study provides a comprehensive view of the coordinated responses of multiple aged stem cells and niche cells to exercise at the transcriptomic level.

cell biology↗

bioRxiv2021

Effects of Platycodon grandiflorum on Gut Microbiota and Immune System of Immunosuppressed Mouse

Platycodon grandiflorum (PG) has been used as a traditional remedy to control immune related diseases. However, there is limited information about its immune stimulating effects on the immunosuppressed model. The main bioactive components such as saponins are known to con-tribute to controlling immune activity. Thus, we developed an aged red PG (PGS) with 2.6 times of platycodin D, one of the saponins. We treated PG and PGS (PG-diets) to immunosuppressed mice via cyclophosphamide (CPA) injection. After 2weeks of the supplement, 16S rRNA sequencing was performed to investigate the effects of PG-diets on the gut microbiota and immune system in the immune suppressed model. PG-diets groups showed an increased abundance of microorganism in immune-deficient mice compared to the control NC group, indicating PG-diets have a distinct effect on microbial communities. Detection of specific genera related to the immune related biomarkers in PG-diets groups can support their effects on the immune system. Especially, the Akkermansia showed a significant decrease of abundance in response to the CPA treatment in the NC group at the genus level, but its abundance increased in response to the PG-diets treatment in the PG-diets groups. We also found that the modulation of gut microbiome by PG-diets was correlated with body weight as one of important immune biomarkers, though not much difference was found between PG and PGS effects. The results demonstrate that PG-diets may improve the health benefits of immune suppressed mice by altering the gut microbiome.

microbiology↗