Biology subjects

Nguyen, H.-N.

Publications and source records attributed to Nguyen, H.-N..

15 recordsLinked to original sources

bioRxiv2026

CALFP-MHC: Interpretable Pan-Allelic Prediction of Peptide-MHC Binding and Presentation Using Chemically Grounded Fingerprints and Contrastive Learning

Identifying which peptides bind major histocompatibility complex (MHC) molecules is central to vaccine design, neoantigen prioritization, and precision immunotherapy. Existing deep learning predictors largely encode amino acids as discrete symbols, thereby missing the residue-level chemistry driving molecular recognition. Performance also tends to degrade under class imbalance, for rare alleles, and on peptide- MHC combinations outside the training distribution. We developed CALFP-MHC, a framework that encodes each amino acid as a set of complementary cheminformatics fingerprints capturing functional groups, atomic connectivity, and substructural features, and combines positional encoding with supervised contrastive pre-training to organize the latent space by binding class before fine-tuning a binary classifier. Peptide-MHC interactions are modeled through a hybrid convolutional-transformer backbone. In a large-scale computational benchmark covering [~]18.7 million peptide-MHC pairs across 112 HLA class I and 53 class II alleles, CALFP-MHC achieved AUCs of 0.93-0.97 and PPVs of 0.66-0.94. Critically, performance remained above AUC 0.90 even at a 200:1 negative-to-positive ratio, where competing tools frequently collapsed toward chance. On independent experimental data containing 3,627 class I and 520 class II MS/MS-confirmed ligands and 570 validated neoantigens, the model maintained strong discrimination, correctly prioritizing immunogenic peptides and MHC-presented ligands. Attention and integrated-gradient analyses recovered established anchor positions (P2 and P{Omega} for class I, P1, P4, P6, and P9 for class II) and highlighted chemically interpretable functional groups consistent with known binding determinants. CALFP-MHC demonstrates that grounding residue representations in molecular chemistry, rather than sequence symbols alone, improves both robustness and interpretability in peptide-MHC binding prediction.

immunology↗

bioRxiv2026

DETECTION OF BIOSYNTHETIC GENE CLUSTERS FROM METAGENOME OF NATURAL HONEY COLLECTED IN VIETNAM

The antimicrobial properties of natural honey are partly attributed to bioactive secondary metabolites produced by its associated microbial communities, yet the biosynthetic capacity of these communities remains poorly characterized. Here, we applied a metagenomic approach to investigate the biosynthetic gene cluster (BGC) diversity of bacteria associated with Apis cerana honey from the Northwest mountainous region of Vietnam - a biogeographically distinct and underexplored ecosystem. A total of 366 BGCs spanning 38 compound classes were identified, with terpenes, nonribosomal peptide synthetases (NRPS), and ribosomally synthesized and post-translationally modified peptides (RiPPs) being the most prevalent. Strikingly, 304 BGCs (>83%) lacked close matches in the MIBiG reference database, indicating a high degree of biosynthetic novelty relative to previously characterized natural product repertoires. Among the identified clusters, an azole-containing RiPP BGC recovered from a metagenome-assembled genome (MAG) assigned to Atlantibacter hermannii was predicted to exhibit strong antibacterial activity, with a probability score of 74.5%, representing a prioritized target for heterologous expression and bioactivity validation. These findings establish the Apis cerana honey microbiome as a tractable and largely untapped reservoir for applied microbial research, with direct implications for the discovery of novel antimicrobial agents from underexplored environmental niches. ImportanceAntimicrobial resistance represents one of the most pressing challenges in modern medicine, driving urgent demand for novel bioactive compounds from underexplored microbial sources. Honey-associated bacterial communities are recognized contributors to the antimicrobial properties of natural honey, yet their biosynthetic capacity remains poorly characterized at the metagenomic level. This study demonstrates that the microbiome of Apis cerana honey from a biogeographically distinct region of Vietnam harbors extensive and largely novel biosynthetic gene cluster diversity, with over 83% (304/366) of identified BGCs lacking database references. These findings position honey microbiomes as a tractable and underutilized reservoir for applied microbial research, with direct relevance to the discovery of new antimicrobial agents. The identification of a candidate antibacterial RiPP BGC in Atlantibacter hermannii provides a concrete target for future cultivation-based and heterologous expression studies, bridging metagenomic discovery with applied biotechnological pipelines.

microbiology↗

bioRxiv2026

Oxidant-mediated activation and inhibition of LRRC8C and LRRC8D channel currents require N-terminal and Transmembrane 1 pore domains

Leucine Rich Repeat Containing 8C (LRRC8C) anion channels modulate NADPH oxidase 1 activity and allow extracellular superoxide influx promoting inflammatory signaling. Here we studied chimeric 8C/8D channels and identified oxidant-dependent current modulation within the N-terminus (NT) and first transmembrane domain (TM1). Chloramine-T (ChlT) elicited inhibitory and activating current responses, whereas other redox agents had comparatively little impact. ChlT moderately inhibited wild-type (WT) 8C current and abrogated block by DCPIB. Substitution of the 8D NT (8D1-22) conferred ChlT-dependent current activation, as did 8D2-4, 8D5-11, I2F, and I2Y substitution. M48T (distal TM1) substitution enhanced WT 8C current inhibition and impaired activation in NT mutants. An M48D mutation diminished 8C current block by DCPIB by [~]50%. WT 8D currents were potently inhibited by ChlT. Substitution of the 8C first extracellular loop (EL1) weakened inhibition, while 8C EL1 + TM145-49 substitution produced ChlT-mediated current activation. 8C45-49 or T48M substitutions in 8D resulted in rapid disruption and loss of initial current inhibition, and a progressive increase of non-rectifying current. These results provide evidence that NT2-4, particularly I2/F2, in combination with M48 are primary determinants of activating vs. inhibitory current modulation by ChlT. M48 oxidation limits 8C inhibition and is required for activating responses, while T48 and 8D EL1 promote 8D signature current inhibition. ChlT exposure disrupts subsequent or preexisting channel block by DCPIB, consistent with a common site of interaction. Thus, factors that alter NT pore stability and mobility may regulate inhibition vs. activation of LRRC8C by redox stress.

cell biology↗

bioRxiv2025

Smooth muscle LRRC8A knockout reduces superoxide influx, inflammation, senescence and atherosclerosis

BackgroundLeucine Rich Repeat Containing 8A (LRRC8A) anion channels (VRACs) associate with NADPH oxidase 1 (Nox1) and support extracellular superoxide (O2{middle dot}-) production, inflammation, and contractility in vascular smooth muscle cells (VSMCs). We proposed previously that VRACs also support influx of O2{middle dot}- to localize cytoplasmic redox signals. MethodsWe assayed O2{middle dot}- influx, assessed changes in mRNA expression (RNAseq), and tested multiple phenotypes of cultured LRRC8A knockout (KO) VSMCs. Aortic atherosclerotic burden and inflammation, and mesenteric vascular reactivity were compared between wild type (WT) apolipoprotein E null (ApoE-/-) mice and VSMC-specific LRRC8A KO, ApoE-/- mice. ResultsKO cells were less permeable to extracellular O2{middle dot}-, produced less mitochondrial O2{middle dot}-, and experienced less oxidant stress (GSH/GSSG, lipid peroxidation, Nrf2 activity) than WT. RNAseq and reporter assays demonstrated reduced pro-inflammatory (NF-{kappa}B and Hif1) transcription. KO cells also under-expressed multiple senescence markers and had longer telomeres. Inflammation causes a metabolic shift from oxidative phosphorylation (OCR) to glycolysis (ECAR). Both pathways were less active in KO cells, as was expression of glycolytic enzymes. Mitochondrial membrane potential was lower in KO cells, but ADP/ATP and NADP+/NADPH were unaltered, suggesting lower energy demand. Consistent with this, proliferation and migration were both reduced in KO cells. Protein-protein interaction analysis of RNAseq data (PPI Hub) identified Epidermal Growth Factor Receptor (EGFR) signaling. Resting phosphorylation of EGFR (pY1068) and AKT (pS473 and pT308) were all reduced in KO cells, as was and EGF-induced pY1068 and pS308. Following 15 weeks of exposure to a high fat diet (42%) VSMC-specific LRRC8A-/- and 8A+/-, ApoE-/- mice had reduced atherosclerotic lesion area, aortic senescence ({beta}-Gal), inflammation (ICAM, VCAM) and proliferation marker (PCNA) expression compared to WT, ApoE-/- controls. Mesenteric artery vasomotor function was also preserved, and the abundance of MYPT1 and CPI17 was lower in KO vessels. Uptake of oxidized LDL (OxLDL) was significantly reduced in KO VSMCs and impaired by VRAC block in WT cells. ConclusionsLoss of LRRC8A reduced O2{middle dot}- influx, oxidative stress, inflammation and senescence, lowers energy demand, and in the setting of hypercholesterolemia impaired uptake of oxidized LDL and abrogated atherosclerosis. VSMC VRACs may be novel targets of vascular anti-inflammatory therapy. Novelty and SignificanceO_ST_ABSWhat Is Known?C_ST_ABSO_LIChronically inflamed vascular smooth muscle cells (VSMCs) are critical drivers of atherosclerotic plaque development. C_LIO_LIIn VSMCs, Nox1-derived superoxide drives redox signaling that promotes inflammation, phenotypic switching, and senescence. C_LIO_LILRRC8A family volume-regulated anion channels (VRACs) physically associate with Nox1 and support TNF-induced ROS production, receptor endocytosis, NF-{kappa}B activation, and proliferation. C_LIO_LIHypercholesterolemia causes VSMC inflammation via oxidized LDL (OxLDL) activation of scavenger receptors (e.g., LOX-1, CD36) that stimulate oxidant production and EGFR/PI3K-Akt-NF-{kappa}B signaling. C_LI What New Information Does This Article Contribute?O_LILRRC8A channels support influx of extracellular superoxide which impacts cytosolic redox status, metabolism and Nrf2, HIF-1, and NF-{kappa}B activity. C_LIO_LILoss of LRRC8A reprograms VSMCs into a low-oxidative-stress, low-energy-demand state, characterized by diminished proliferation and migration, attenuated senescence, and preservation of telomere length. C_LIO_LILoss of LRRC8A inhibits EGF-stimulated EGFR and Akt phosphorylation and uncouples oxidant-dependent growth factor signaling from downstream inflammatory and metabolic remodeling. C_LIO_LIVSMC-specific LRRC8A knockout or heterozygosity in hypercholesterolemic ApoE-/- mice reduces aortic inflammation and senescence, reduces atherosclerotic lesion burden, and preserves mesenteric artery vasomotor function. C_LIO_LILRRC8A/VRAC activity is necessary for uptake of oxidized but not native LDL in VSMCs. C_LIO_LILRRC8A is a novel regulator of scavenger receptor-dependent lipoprotein handling and a potential therapeutic target to uncouple oxidant signaling from VSMC lipid overload and inflammation in the vessel wall. C_LI

physiology↗

bioRxiv2025

Smooth muscle LRRC8A knockout preserves vascular function in AngII hypertension

Angiotensin II (AngII) causes hypertension and vascular inflammation both directly and indirectly via cytokines. In vascular smooth muscle cells (VSMCs) AngII and TNF activate NADPH oxidase 1 (Nox1) to produce superoxide. TNF receptors associate with Nox1 and Leucine Rich Repeat Containing 8A (LRRC8A) anion channels to modulate inflammation, as well as contractility in a RhoA-dependent manner. VSMC-specific LRRC8A knockout (KO) mesenteric arteries are protected from TNF-induced injury and vasodilated better. We hypothesized that LRRC8A KO would preserve vascular function and decrease blood pressure (BP) in AngII-infused mice. Wild type (WT) and LRRC8A KO mice received AngII infusions for 14 days. Systolic BP was not different, but KO mice had more BP "dipping" during inactive periods and dipping was preserved after AngII. Contraction of KO mesenteric vessels to AngII itself was not altered, however after AngII exposure the function of KO aortic and mesenteric vessels was less impaired as reflected by less augmented contraction to norepinephrine and serotonin and preserved relaxation to acetylcholine and sodium nitroprusside. Western blotting revealed increased soluble guanylate cyclase alpha and reduced CPI-17 in hypertensive KO aortae. Consistent with the presence of lower Rho kinase activity in KO VSMCs, phosphorylation of Ezrin/Radixin/Moesin (ERM) and Cofilin was reduced. Aortic wall/lumen was not different between hypertensive WT and KO mice, but AngII caused less proliferation (lower PCNA), and less induction of antioxidant enzymes and senescence markers in KO vessels. Thus, while AngII-induced contraction does not require LRRC8A, these channels support the associated inflammatory response which modifies BP dipping.

physiology↗

bioRxiv2024

Supervised non-negative matrix factorization on cell-free DNA fragmentomic features enhances early cancer detection

BackgroundCell-free circulating DNA (cfDNA) fragments exhibit non-random patterns in their length (FLEN), end-motif (EM), and distance to nucleosome position (ND). While these cfDNA features have shown promise as inputs for machine learning and deep learning models in early cancer detection, most studies utilize them as raw inputs, overlooking the potential benefits of pre-processing to extract cancer-specific features. This study aims to enhance cancer detection accuracy by developing a novel approach to feature extraction from cfDNA fragmentomics. MethodsWe implemented a supervised non-negative matrix factorization (SNMF) algorithm to generate embedding vectors capturing cancer-specific signals within cfDNA fragmentomic features. These embeddings served as input for a machine learning model to classify cancer patients from healthy individuals. ResultsWe validated our framework using two datasets: an in-house cohort of 431 cancer patients and 442 healthy individuals (dataset 1), and a published cohort comprising 90 hepatocellular carcinoma (HCC) patients and 103 individuals with cirrhosis or hepatitis B (dataset 2). In dataset 1, we achieved an AUC of 94% in pan-cancer detection. In dataset 2, our framework achieved an AUC of 100% for HCC vs healthy classification, 99% for HCC vs non-HCC patients classification, and 96% for identifying HCC patients among a mixed group of non-HCC patients and healthy donors. ConclusionThis study demonstrates the efficiency of SNMF-transformed features in improving both pan-cancer detection and specific HCC detection. Our approach offers a significant advancement in leveraging cfDNA fragmentomics for early cancer detection, potentially enhancing diagnostic accuracy in clinical settings.

bioinformatics↗

bioRxiv2024

epiTCR-KDA: Knowledge Distillation model on Dihedral Angles for TCR-peptide prediction

MotivationAntigen recognition by T-cell receptors (TCRs) triggers cascades of immune responses. Successful predictions of the TCR and antigen (as peptide) bindings therefore signify the advancements in immunotherapy. However, most of current TCR-peptide interaction predictors fail to predict unseen data. This limitation may be derived from the conventional usage of TCR and/or peptide sequences as input, which may not adequately reflect their structural characteristics. Therefore, incorporating the TCR and peptide structural information into the prediction model to improve the generalizability is necessary. ResultsWe presented epiTCR-KDA as a new predictor of TCR-peptide binding that utilises structural information, specifically the dihedral angles between the residues of both the peptide and the TCR. This structural descriptor was integrated into a model constructed using knowledge distillation to enhance its generalizability. The epiTCR-KDA demonstrated competitive prediction performance, with an AUC of 0.99 for seen data and AUC of 0.86 for unseen data. Across multiple public datasets, epiTCR-KDA consistently outperformed other predictors, such as epiTCR, NetTCR, BERTrand, TEIM-Seq, TEINet, and ImRex, maintaining a median AUC of 0.9 (ranging from 0.82 to 0.91). Further analysis of epiTCR-KDA performance indicated that the cosine similarity of the dihedral angle vectors between the unseen testing data and training data is crucial for its stable performance. In conclusion, our epiTCR-KDA model, with its capacity to predict for unseen data, has brought us one step closer toward the development of a highly effective pipeline for affordable antigen-based immunotherapy. Availability and implementationepiTCR-KDA is available on GitHub (https://github.com/ddiem-ri-4D/epiTCR-KDA)

bioinformatics↗

bioRxiv2023

Tissue of origin detection for cancer tumor using low-depth cfDNA samples through combination of tumor-specific methylation atlas and genome-wide methylation density in graph convolutional neural networks

BackgroundCell free DNA (cfDNA)-based assays hold great potential in detecting early cancer signals yet determining the tissue-of-origin (TOO) for cancer signals remains a challenging task. Here, we investigated the contribution of a methylation atlas to TOO detection in low depth cfDNA samples. MethodsWe constructed a tumor-specific methylation atlas (TSMA) using whole-genome bisulfite sequencing (WGBS) data from five types of tumor tissues (breast, colorectal, gastric, liver and lung cancer) and paired white blood cells (WBC). TSMA was used with a non-negative least square matrix factorization (NNLS) deconvolution algorithm to identify the abundance of tumor tissue types in a WGBS sample. We showed that TSMA worked well with tumor tissue but struggled with cfDNA samples due to the overwhelming amount of WBC-derived DNA. To construct a model for TOO, we adopted the multi-modal strategy and used as inputs the combination of deconvolution scores from TSMA with other features of cfDNA. ResultsOur final model comprised of a graph convolutional neural network using deconvolution scores and genome-wide methylation density features, which achieved an accuracy of 69% in a held-out validation dataset of 239 low-depth cfDNA samples. ConclusionsIn conclusion, we have demonstrated that our TSMA in combination with other cfDNA features can improve TOO detection in low-depth cfDNA samples.

cancer biology↗

bioRxiv2023

The T Cell Receptor beta Chain Repertoire of Tumor Infiltrating Lymphocytes Improves Neoantigen Prediction and Prioritization

In the realm of cancer immunotherapy, the meticulous selection of neoantigens plays a fundamental role in enhancing personalized treatments. Traditionally, this selection process has heavily relied on predicting the binding of peptides to human leukocyte antigens (pHLA). Nevertheless, this approach often overlooks the dynamic interaction between tumor cells and the immune system. In response to this limitation, we have developed an innovative prediction algorithm rooted in machine learning, integrating T cell receptor {beta} chain (TCR{beta}) profiling data from colorectal cancer (CRC) patients for a more precise neoantigen prioritization. TCR{beta} sequencing was conducted to profile the TCR repertoire of tumor-infiltrating lymphocytes (TILs) from 28 CRC patients. The data unveiled both intra-tumor and inter-patient heterogeneity in the TCR{beta} repertoires of CRC patients, likely resulting from the stochastic utilization of V and J segments in response to neoantigens. Our novel combined model integrates pHLA binding information with pHLA-TCR binding to prioritize neoantigens, resulting in heightened specificity and sensitivity compared to models using individual features alone. The efficacy of our proposed model was corroborated through ELISpot assays on long peptides, performed on four CRC patients. These assays demonstrated that neoantigen candidates prioritized by our combined model outperformed predictions made by the established tool NetMHCpan. This comprehensive assessment underscores the significance of integrating pHLA binding with pHLA-TCR binding analysis for more effective immunotherapeutic strategies.

cancer biology↗

bioRxiv2023

Improvement in Neoantigen Prediction via Integration of RNA Sequencing Data for Variant Calling

Neoantigen-based immunotherapy has emerged as a promising strategy for improving the life expectancy of cancer patients. This therapeutic approach heavily relies on accurate identification of cancer mutations using DNA sequencing (DNAseq) data. However, current workflows tend to provide a large number of neoantigen candidates, of which only a limited number elicit efficient and immunogenic T-cell responses suitable for downstream clinical evaluation. To overcome this limitation and increase the number of high-quality immunogenic neoantigens, we propose integrating RNA sequencing (RNAseq) data into the mutation identification step in the neoantigen prediction workflow. In this study, we characterize the mutation profiles identified from DNAseq and/or RNAseq data in tumor tissues of 25 patients with colorectal cancer (CRC). We detected only 22.4% of variants shared between the two methods. In contrast, RNAseq-derived variants displayed unique features of affinity and immunogenicity. We further established that neoantigen candidates identified by RNAseq data significantly increased the number of highly immunogenic neoantigens (confirmed by ELISpot) that would otherwise be overlooked if relying solely on DNAseq data. In conclusion, this integrative approach holds great potential for improving the selection of neoantigens for personalized cancer immunotherapy, ultimately leading to enhanced treatment outcomes and improved survival rates for cancer patients.

immunology↗

bioRxiv2023

LRRC8A anion channels modulate vasodilation via association with Myosin Phosphatase Rho Interacting Protein (MPRIP)

BackgroundIn vascular smooth muscle cells (VSMCs), LRRC8A volume regulated anion channels (VRACs) are activated by inflammatory and pro-contractile stimuli including tumor necrosis factor alpha (TNF), angiotensin II and stretch. LRRC8A physically associates with NADPH oxidase 1 (Nox1) and supports its production of extracellular superoxide (O2-*). Methods and ResultsMice lacking LRRC8A exclusively in VSMCs (Sm22-Cre, KO) were used to assess the role of VRACs in TNF signaling and vasomotor function. KO mesenteric vessels contracted normally to KCl and phenylephrine, but relaxation to acetylcholine (ACh) and sodium nitroprusside (SNP) was enhanced compared to wild type (WT). 48 hours of ex vivo exposure to TNF (10ng/ml) markedly impaired dilation to ACh and SNP in WT but not KO vessels. VRAC blockade (carbenoxolone, CBX, 100 M, 20 min) enhanced dilation of control rings and restored impaired dilation following TNF exposure. Myogenic tone was absent in KO rings. LRRC8A immunoprecipitation followed by mass spectroscopy identified 35 proteins that interacted with LRRC8A. Pathway analysis revealed actin cytoskeletal regulation as the most closely associated function of these proteins. Among these proteins, the Myosin Phosphatase Rho-Interacting protein (MPRIP) links RhoA, MYPT1 and actin. LRRC8A-MPRIP co-localization was confirmed by confocal imaging of tagged proteins, Proximity Ligation Assays, and IP/western blots which revealed LRRC8A binding at the second Pleckstrin Homology domain of MPRIP. siLRRC8A or CBX treatment decreased RhoA activity in cultured VSMCs, and MYPT1 phosphorylation at T853 was reduced in KO mesenteries suggesting that reduced ROCK activity contributes to enhanced relaxation. MPRIP was a target of redox modification, becoming oxidized (sulfenylated) after TNF exposure. ConclusionsInteraction of Nox1/LRRC8A with MPRIP/RhoA/MYPT1/actin may allow redox regulation of the cytoskeleton and link Nox1 activation to both inflammation and vascular contractility.

physiology↗

bioRxiv2022

SPITFIR(e): A supermaneuverable algorithm for restoring 2D-3D fluorescence images and videos,and background subtraction

While fluorescent microscopy imaging has become the spearhead of modern biology as it is able to generate long-term videos depicting 4D nanoscale cell behaviors, it is still limited by the optical aberrations and the photon budget available in the specimen and to some extend to photo-toxicity. A direct consequence is the necessity to develop flexible and "off-road" algorithms in order to recover structural details and improve spatial resolution, which is critical when pushing the illumination to the low levels in order to limit photo-damages. Moreover, as the processing of very large temporal series of images considerably slows down the analysis, special attention must be paid to the feasibility and scalability of the developed restoration algorithms. To address these specifications, we present a very flexible method designed to restore 2D-3D+Time fluorescent images and subtract undesirable out-of-focus background. We assume that the images are sparse and piece-wise smooth, and are corrupted by mixed Poisson-Gaussian noise. To recover the unknown image, we consider a novel convex and non-quadratic regularizer Sparse Hessian Variation) defined as the mixed norms which gathers image intensity and spatial second-order derivatives. This resulting restoration algorithm named SPITFIR(e) (SParse fIT for Fluorescence Image Restoration) utilizes the primal-dual optimization principle for energy minimization and can be used to process large images acquired with varied fluorescence microscopy modalities. It is nearly parameter-free as the practitioner needs only to specify the amount of desired sparsity (weak, moderate, high). Experimental results in lattice light sheet, stimulated emission depletion, multifocus microscopy, spinning disk confocal, and wide-field microscopy demonstrate the generic ability of the SPITFIR(e) algorithm to efficiently reduce noise and blur, and to subtract undesirable fluorescent background, while avoiding the emergence of deconvolution artifacts.

bioinformatics↗

bioRxiv2021

Oxidant-Resistant LRRC8A/C Anion Channels Support Superoxide Production by Nox1

Tumor necrosis factor- (TNF) activates NADPH Oxidase 1 (Nox1) in vascular smooth muscle cells (VSMCs), producing superoxide (O2*-) required for subsequent signaling. LRRC8 family proteins A-E comprise volume-regulated anion channels (VRACs). The required subunit LRRC8A physically associates with Nox1, and VRAC activity is required for Nox activity and the inflammatory response to TNF. LRRC8 channel currents are modulated by oxidants, suggesting that oxidant sensitivity and proximity to Nox1 may play a physiologically relevant role. In VSMCs, LRRC8C knockdown (siRNA) recapitulated the effects of siLRRC8A, inhibiting TNF-induced extracellular and endosomal O2*- production, receptor endocytosis, NF-{kappa}B activation, and proliferation. In contrast, siLRRC8D potentiated NF-{kappa}B activation. Nox1 co-immunoprecipitated with 8C and 8D, and co-localized with 8D at the plasma membrane and in vesicles. We compared VRAC currents mediated by homomeric and heteromeric 8C and 8D channels expressed in HEK293 cells. The oxidant chloramine T (ChlorT, 1 mM) weakly inhibited LRRC8C, but potently inhibited 8D currents. ChlorT exposure also greatly reduced subsequent current block by DCPIB, implicating external sites of oxidation. Substitution of the extracellular loop domains (EL1, EL2) of 8D onto 8C conferred significantly stronger ChlorT-dependent inhibition. 8A/C channel activity is thus more effectively maintained in the oxidized microenvironment expected to result from Nox1 activation at the plasma membrane. Increased ratios of 8D:8C expression may potentially depress inflammatory responses to TNF. LRRC8A/C channel downregulation represents a novel strategy to reduce TNF-induced inflammation. Key PointsO_LILRRC8A-containing anion channels associate with Nox1 and regulate superoxide production and TNF signaling. Here we show that .LRRC8C and 8D also co-immunoprecipitate with Nox1 in vascular smooth muscle cells. C_LIO_LILRRC8C knockdown inhibited TNF-induced O2*- production, receptor endocytosis, NF-{kappa}B activation, and proliferation while LRRC8D knockdown enhanced NF-{kappa}B activation. Significant changes in LRRC8 isoform expression in human atherosclerosis and psoriasis suggest compensation for increased inflammation. C_LIO_LIThe oxidant chloramine-T (ChlorT, 1 mM) weakly ([~]25%) inhibited 8C currents but potently ([~]80%) inhibited 8D currents. Substitution of the two extracellular loop (EL) domains of 8D onto 8C conferred significantly stronger ChlorT-dependent inhibition. C_LIO_LIChlorT also impaired current block by DCPIB, which occurs through interaction with EL1, further implicating external sites of oxidation. C_LIO_LI8A/C channels most effectively maintain activity in an oxidized microenvironment, as is expected to result from Nox1 activity at the plasma membrane. C_LI

cell biology↗

bioRxiv2020

Genetic landscape of recessive diseases in the Vietnamese population from large-scale clinical exome sequencing

PurposeAccurate profiling of population-specific recessive diseases is essential for the design of cost-effective carrier screening programs. However, minority populations and ethnic groups, including Vietnamese, are still under-represented in existing genetic studies. Here we reported the first comprehensive study of recessive diseases in the Vietnamese population. MethodsClinical exome sequencing (CES) data of 4,503 disease-associated genes obtained from a cohort of 985 Vietnamese individuals was analyzed to identify pathogenic variants, associated diseases and their carrier frequencies in the population. ResultsEighty-five recessive diseases were identified in the Vietnamese population, among which seventeen diseases had carrier frequencies of at least 1% (1 in 100 individuals). Three diseases were especially prevalent in the Vietnamese population with carrier frequencies of 2-12 times higher than in other East Asia or the world populations, including Beta-thalassemia (1 in 25), citrin deficiency (1 in 33) and phenylketonuria (1 in 40). Seven novel pathogenic and three likely pathogenic variants associated with nine recessive diseases were also discovered. ConclusionsThe comprehensive profile of recessive diseases identified in this study shall enable the design of cost-effective carrier screening programs specific to the Vietnamese population. The newly discovered pathogenic variants may also exist in other populations at extremely low frequencies, thus representing a valuable resource for future research. Our study has demonstrated the advantage of population-specific genetic studies to advance the knowledge and practice of medical genetics.

genetics↗

bioRxiv2019

Genetic profiling of 2,683 Vietnamese genomes from non-invasive prenatal testing data

The under-representation of several ethnic groups in existing genetic databases and studies have undermined our understanding of the genetic variations and associated traits or diseases in many populations. Cost and technology limitations remain the challenges in performing large-scale genome sequencing projects in many developing countries, including Vietnam. As one of the most rapidly adopted genetic tests, non-invasive prenatal testing (NIPT) data offers an alternative untapped resource for genetic studies. Here we performed a large-scale genomic analysis of 2,683 pregnant Vietnamese women using their NIPT data and identified a comprehensive set of 8,054,515 single-nucleotide polymorphisms, among which 8.2% were new to the Vietnamese population. Our study also revealed 24,487 disease-associated genetic variants and their allele frequency distribution, especially 5 pathogenic variants for prevalent genetic disorders in Vietnam. We also observed major discrepancies in the allele frequency distribution of disease-associated genetic variants between the Vietnamese and other populations, thus highlighting a need for genome-wide association studies dedicated to the Vietnamese population. The resulted database of Vietnamese genetic variants, their allele frequency distribution, and their associated diseases presents a valuable resource for future genetic studies.

genomics↗