Biology subjects

Nguyen, T. B.

Publications and source records attributed to Nguyen, T. B..

8 recordsLinked to original sources

bioRxiv2026

TET2-mutant clonal hematopoiesis prevents T-cell exhaustion and suppresses cancer metastasis

Clonal hematopoiesis (CH) is widely regarded as a risk factor for age-associated disease, yet its influence on solid tumor progression remains poorly understood. Here, we uncover an unexpected tumor-suppressive role for TET2-mutant CH in solid tumors. Through an analysis of over 16,000 cancer patients, we demonstrate that TET2 mutations are associated with a significant reduction in metastatic burden. Mechanistically, we show that Tet2 deficiency prevents terminal exhaustion in CD8+ tumor-infiltrating lymphocytes (CD8+ TILs). This resistance is driven by DNA hypermethylation at regulatory elements of the transcription factor Tox, which prevents the induction of the terminal exhaustion program. Consequently, Tet2-deficient CD8+ TILs maintain stem-like, effector-competent states that mediate durable anti-tumor immunity and suppress metastatic outgrowth. Our findings establish TET2-mutant CH as a natural epigenetic constraint on T-cell exhaustion and uncover a mechanistically defined pathway with translational potential for enhancing anti-tumor immune responses.

immunology↗

bioRxiv2024

Evaluation of enzyme activity predictions for variants of unknown significance in Arylsulfatase A

Continued advances in variant effect prediction are necessary to demonstrate the ability of machine learning methods to accurately determine the clinical impact of variants of unknown significance (VUS). Towards this goal, the ARSA Critical Assessment of Genome Interpretation (CAGI) challenge was designed to characterize progress by utilizing 219 experimentally assayed missense VUS in the Arylsulfa-tase A (ARSA) gene to assess the performance of community-submitted predictions of variant functional effects. The challenge involved 15 teams, and evaluated additional predictions from established and recently released models. Notably, a model developed by participants of a genetics and coding bootcamp, trained with standard machine-learning tools in Python, demonstrated superior performance among sub-missions. Furthermore, the study observed that state-of-the-art deep learning methods provided small but statistically significant improvement in predictive performance compared to less elaborate techniques. These findings underscore the utility of variant effect prediction, and the potential for models trained with modest resources to accurately classify VUS in genetic and clinical research.

genetics↗

bioRxiv2023

Aberrant splicing in Huntington's disease via disrupted TDP-43 activity accompanied by altered m6A RNA modification.

Huntingtons disease (HD) is a neurodegenerative disorder caused by a CAG repeat expansion in the first exon of the HTT gene encoding huntingtin. Prior reports have established a correlation between CAG expanded HTT and altered gene expression. However, the mechanisms leading to disruption of RNA processing in HD remain unclear. Here, our analysis of the reported HTT protein interactome identifies interactions with known RNA-binding proteins (RBPs). Total, long-read sequencing and targeted RASL-seq of RNAs from cortex and striatum of the HD mouse model R6/2 reveals increased exon skipping which is confirmed in Q150 and Q175 knock-in mice and in HD human brain. We identify the RBP TDP-43 and the N6-methyladenosine (m6A) writer protein methyltransferase 3 (METTL3) to be upstream regulators of exon skipping in HD. Along with this novel mechanistic insight, we observe decreased nuclear localization of TDP-43 and cytoplasmic accumulation of phosphorylated TDP-43 in HD mice and human brain. In addition, TDP-43 co-localizes with HTT in human HD brain forming novel nuclear aggregate-like bodies distinct from mutant HTT inclusions or previously observed TDP-43 pathologies. Binding of TDP-43 onto RNAs encoding HD-associated differentially expressed and aberrantly spliced genes is decreased. Finally, m6A RNA modification is reduced on RNAs abnormally expressed in striatum from HD R6/2 mouse brain, including at clustered sites adjacent to TDP-43 binding sites. Our evidence supports TDP-43 loss of function coupled with altered m6A modification as a novel mechanism underlying alternative splicing/unannotated exon usage in HD and highlights the critical nature of TDP-43 function across multiple neurodegenerative diseases.

neuroscience↗

bioRxiv2023

A tripartite bacterial-fungal-plant symbiosis in the mycorrhiza-shaped microbiome drives plant growth and mycorrhization

Plant microbiomes play crucial roles in nutrient cycling and plant growth, and are shaped by a complex interplay between plants, microbes, and the environment. The role of bacteria as mediators of the 400-million-year-old partnership between the majority of land plants and, arbuscular mycorrhizal (AM) fungi is still poorly understood. Here we test whether AM hyphae-associated bacteria influence the success of the AM symbiosis. Using partitioned microcosms containing field soil, we discovered that AM hyphae and roots selectively assemble their own microbiome from the surrounding soil. In two independent experiments, we identified several bacterial genera, including Devosia, that are consistently enriched on AM hyphae. Subsequently, we isolated 144 pure bacterial isolates from a mycorrhiza-rich sample of extraradical hyphae and isolated Devosia sp. ZB163 as root and hyphal colonizer. We show that this AM-associated bacterium synergistically acts with mycorrhiza on the plant root to strongly promote plant growth, nitrogen uptake, and mycorrhization. Our results highlight that AM fungi do not function in isolation and that the plant-mycorrhiza symbiont can recruit beneficial bacteria that support the symbiosis.

microbiology↗

bioRxiv2022

SNVformer: An Attention-based Deep Neural Network for GWAS Data

Despite being the widely-used gold standard for linking common genetic variations to phenotypes and disease, genome-wide association studies (GWAS) suffer major limitations, partially attributable to the reliance on simple, typically linear, models of genetic effects. More elaborate methods, such as epistasis-aware models, typically struggle with the scale of GWAS data. In this paper, we build on recent advances in neural networks employing Transformer-based architectures to enable such models at a large scale. As a first step towards replacing linear GWAS with a more expressive approximation, we demonstrate prediction of gout, a painful form of inflammatory arthritis arising when monosodium urate crystals form in the joints under high serum urate conditions, from Single Nucleotide Variants (SNVs) using a scalable (long input) variant of the Transformer architecture. Furthermore, we show that sparse SNVs can be efficiently used by these Transformer-based networks without expanding them to a full genome. By appropriately encoding SNVs, we are able to achieve competitive initial performance, with an AUROC of 83% when classifying a balanced test set using genotype and demographic information. Moreover, the confidence with which the network makes its prediction is a good indication of the prediction accuracy. Our results indicate a number of opportunities for extension, enabling full genome-scale data analysis using more complex and accurate genotype-phenotype association models.

bioinformatics↗

bioRxiv2019

Principles of RNA processing from analysis of enhanced CLIP maps for 150 RNA binding proteins.

A critical step in uncovering rules of RNA processing is to study the in vivo regulatory networks of RNA binding proteins (RBPs). Crosslinking and immunoprecipitation (CLIP) methods enabled mapping RBP targets transcriptome-wide, but methodological differences present challenges to large-scale integrated analysis across datasets. The development of enhanced CLIP (eCLIP) enabled the large-scale mapping of targets for 150 RBPs in K562 and HepG2, creating a unique resource of RBP interactomes profiled with a standardized methodology in the same cell types. Here we describe our analysis of 223 enhanced (eCLIP) datasets characterizing 150 RBPs in K562 and HepG2 cell lines, revealing a range of binding modalities, including highly resolved positioning around splicing signals and mRNA untranslated regions that associate with distinct RBP functions. Quantification of enrichment for repetitive and abundant multi-copy elements reveals 70% of RBPs have enrichment for non-mRNA element classes, enables identification of novel ribosomal RNA processing factors and sites and suggests that association with retrotransposable elements reflects multiple RBP mechanisms of action. Analysis of spliceosomal RBPs indicates that eCLIP resolves AQR association after intronic lariat formation (enabling identification of branch points with single-nucleotide resolution) and provides genome-wide validation for a branch point-based scanning model for 3 splice site recognition. Further, we show that eCLIP peak co-occurrences across RBPs enables the discovery of novel co-interacting RBPs. Finally, we present a protocol for visualization of RBP:RNA complexes in the eCLIP workflow using biotin and standard chemiluminescent visualization reagents, enabling simplified confirmation of ribonucleoprotein enrichment without radioactivity. This work illustrates the value of integrated analysis across eCLIP profiling of RBPs with widely distinct functions to reveal novel RNA biology. Further, our quantification of both mRNA and other element association will enable further research to identify novel roles of RBPs in regulating RNA processing.

genomics↗

bioRxiv2018

Widespread RNA editing dysregulation in Autism Spectrum Disorders

Autism spectrum disorder (ASD) is a genetically complex, clinically heterogeneous neurodevelopmental disease. Recently, our understanding of the molecular abnormalities in ASD has been expanded through transcriptomic analyses of postmortem brains. However, a crucial molecular pathway involved in synaptic development, RNA editing, has not yet been studied on a genome-wide scale. Here, we profiled the global patterns of adenosine-to-inosine (A-to-I) editing in a large cohort of post-mortem ASD brains. Strikingly, we observed a global bias of hypo-editing in ASD brains, common to different brain regions and involving many genes with known neurobiological functions. Through genome-wide protein-RNA binding analyses and detailed molecular assays, we show that the Fragile X proteins, FMRP and FXR1P, interact with ADAR proteins and modulate A-to-I editing. Furthermore, we observed convergent patterns of RNA editing alterations in ASD and Fragile X syndrome, thus establishing RNA editing as a molecular link underlying these two highly related diseases. Our findings support a role for RNA editing dysregulation in ASD and highlight novel mechanisms for RNA editing regulation.

neuroscience↗

bioRxiv2017

A Large-Scale Binding and Functional Map of Human RNA Binding Proteins

Genomes encompass all the information necessary to specify the development and function of an organism. In addition to genes, genomes also contain a myriad of functional elements that control various steps in gene expression. A major class of these elements function only when transcribed into RNA as they serve as the binding sites for RNA binding proteins (RBPs), which act to control post-transcriptional processes including splicing, cleavage and polyadenylation, RNA editing, RNA localization, stability, and translation. Despite the importance of these functional RNA elements encoded in the genome, they have been much less studied than genes and DNA elements. Here, we describe the mapping and characterization of RNA elements recognized by a large collection of human RBPs in K562 and HepG2 cells. These data expand the catalog of functional elements encoded in the human genome by addition of a large set of elements that function at the RNA level through interaction with RBPs.\n\nHighlightsO_LI223 eCLIP datasets for 150 RBPs reveal a wide variety of in vivo RNA target classes.\nC_LIO_LI472 knockdown/RNA-seq profiles of 263 RBPs reveal factor-responsive targets and integration with eCLIP indicates RNA expression and splicing regulatory patterns.\nC_LIO_LI78 RNA Bind-N-Seq profiles of in vitro binding motifs reveal links between in vitro and in vivo binding and indicate that eCLIP peaks that contain in vitro motifs are more strongly associated with regulation.\nC_LIO_LI274 maps of RBP subcellular localization by immunofluorescence indicate widespread organelle-specific RNA processing regulation.\nC_LIO_LI63 ChIP-seq profiles of DNA association suggest broad interconnectivity between chromatin association and RNA processing.\nC_LI

genomics↗