Biology subjects

Vu, H. T.

Publications and source records attributed to Vu, H. T..

8 recordsLinked to original sources

bioRxiv2025

A single-cell fixed RNA profiling of liver fibrosis progression and regression reveals SEMA4D and LMCD1 as key mediators of fibrogenesis

Liver fibrosis progression and regression are dynamic processes involving diverse hepatic and immune cell populations. Here, we utilize single-cell fixed RNA profiling (FLEX) of a TAA-induced mouse liver cirrhosis model, with and without a recovery phase, to depict the cellular landscape and molecular mechanisms of fibrosis resolution. The regression phase was characterized by the emergence of pericentral hepatocytes enriched in detoxification and antioxidant genes (e.g., Cyp2e1, Txn1), which secreted Rarres2 to modulate hepatic stellate cell (HSC) function. This was accompanied by the upregulation of scar-resolving genes (Mmp14, Ctsl), restoration of fenestrae in liver sinusoidal endothelial cells, anti-inflammatory phenotypes of Kupffer cells, a decrease in fibrogenic cholangiocyte subsets, and recovery-associated signatures in NK/T cells, B cells, and neutrophils. In contrast, SEMA4D secreted by monocyte-derived macrophages during fibrosis progression activated Plxnb2 HSCs, and its blockade attenuated fibrosis in vivo. Furthermore, LMCD1 was identified as a novel marker for HSC activation and regulation. This single-cell atlas reveals key transcriptional programs and intercellular signaling pathways dependent on the fibrotic condition, offering new therapeutic targets for liver cirrhosis.

cell biology↗

bioRxiv2023

Deciphering the actin structure-dependent preferential cooperative binding of cofilin

The mechanism underlying the preferential and cooperative binding of cofilin and the expansion of clusters toward the pointed-end side of actin filaments remains poorly understood. To address this, we conducted a principal component analysis based on available filamentous actin (F-actin) and C-actin (cofilins were excluded from cofilactin) structures and compared to monomeric G-actin. The results strongly suggest that C-actin, rather than F-ADP-actin, represented the favourable structure for binding preference of cofilin. High-speed atomic force microscopy explored that the shortened bare half helix adjacent to the cofilin clusters on the pointed end side included fewer actin protomers than normal helices. The mean axial distance (MAD) between two adjacent actin protomers along the same long-pitch strand within shortened bare half helices was longer (5.0-6.3 nm) than the MAD within typical helices (4.3-5.6 nm). The inhibition of torsional motion during helical twisting, achieved through stronger attachment to the lipid membrane, led to more pronounced inhibition of cofilin binding and cluster formation than the presence of inorganic phosphate (Pi) in solution. F-ADP-actin exhibited more naturally supertwisted half helices than F-ADP.Pi-actin, explaining how Pi inhibits cofilin binding to F-actin with variable helical twists. We propose that protomers within the shorter bare helical twists, either influenced by thermal fluctuation or induced allosterically by cofilin clusters, exhibit characteristics of C-actin-like structures with an elongated MAD, leading to preferential and cooperative binding of cofilin.

molecular biology↗

bioRxiv2022

Universal chromatin state annotation of the mouse genome

Genome-wide chromatin states learned from integrating genome-wide maps of multiple epigenetic marks within the same cell type have been widely used to generate genome annotations of individual cell types. An alternative strategy based on stacked modeling can provide a single universal chromatin state annotation based jointly on data from many cell types. In human, such an approach was recently demonstrated and the resulting chromatin state annotation, denoted full-stack, was shown to have complementary advantages to per-cell-type annotations. However, an analogous annotation has not been previously available in mouse. Here, we produce a chromatin state annotation for mouse based on 901 datasets assaying 14 chromatin marks in 26 different cell or tissue types. To characterize each chromatin state, we relate the states to other external annotations and compare them to analogously defined states in human. We expect the full-stack chromatin state annotation for mouse will be a useful resource for studying the genome of this key mammalian model organism.

bioinformatics↗

bioRxiv2022

A framework for summarizing chromatin state annotations within and identifying differential annotations across groups of samples

MotivationGenome-wide maps of epigenetic modifications are powerful resources for non-coding genome annotation. Maps of multiple epigenetics marks have been integrated into cell or tissue type-specific chromatin state annotations for many cell or tissue types. With the increasing availability of multiple chromatin state maps for biologically similar samples, there is a need for methods that can effectively summarize the information about chromatin state annotations within groups of samples and identify differences across groups of samples at a high resolution. ResultsWe developed CSREP, which takes as input chromatin state annotations for a group of samples and then probabilistically estimates the state at each genomic position and derives a representative chromatin state map for the group. CSREP uses an ensemble of multi-class logistic regression classifiers to predict the chromatin state assignment of each sample given the state maps from all other samples. The difference of CSREPs probability assignments for two groups can be used to identify genomic locations with differential chromatin state patterns. Using groups of chromatin state maps of a diverse set of cell and tissue types, we demonstrate the advantages of using CSREP to summarize chromatin state maps and identify biologically relevant differences between groups at a high resolution. Availability and implementationThe CSREP source code is openly available under http://github.com/ernstlab/csrep. Contact: jason.ernst@ucla.edu

bioinformatics↗

bioRxiv2021

Plus and minus ends of microtubule respond asymmetrically to kinesin binding by a long range directionally driven allosteric mechanism

Many members in the kinesin superfamily walk predominantly towards the plus end of the micro-tubule (MT) in a hand-over-hand manner. Despite great progress in elucidating the mechanism of stepping kinetics, the origin of stepping directionality is not fully understood. To provide quantitative insights into this important issue, we represent the structures of conventional kinesin (Kin1), MT, and the Kin1-MT complex using the elastic network model, and calculate the residue-dependent responses to a local perturbation in these constructs. Fluctuations in the residues in the {beta} domain of the /{beta}-tubulin are distinct from the domain. Surprisingly, the Kin1-induced asymmetry, which is more pronounced in /{beta}-tubulin in the plus end of MT than in the minus end, propagates spatially across multiple /{beta}-tubulin dimers. Kin1 binding expands the MT lattice by mechanical stresses, resulting in a transition in the cleft of /{beta} tubulin dimer between a closed (CC for closed cleft) state (not poised for Kin1 to bind) to an open (OC for open cleft) binding competent state. The long-range asymmetric responses in the MT, leading to the creation of OC states with high probability in several /{beta} dimers on the plus end of the bound Kin1, is needed for the motor to take multiple steps towards the plus end of the MT. Reciprocally, kinesin binding to the MT stiffens the residues in the MT binding region, induces correlations between switches I and II in the motor, and enhances fluctuations in ADP and the residues in the binding pocket. Our findings explain both the directionality of stepping and MT effects on a key step in the catalytic cycle of Kin1.

biophysics↗

bioRxiv2021

A mammalian methylation array for profiling methylation levels at conserved sequences

Infinium methylation arrays are not available for the vast majority of non-human mammals. Moreover, even if species-specific arrays were available, probe differences between them would confound cross-species comparisons. To address these challenges, we developed the mammalian methylation array, a single custom array that measures 36k CpGs that are well conserved across mammalian species. We designed a set of probes on the array that can tolerate specific cross-species mutations. We annotate the array in over 200 species and report CpG island status and chromatin states in select species. Calibration experiments demonstrate the high fidelity in humans, rats, and mice. The mammalian methylation array has several strengths: it applies to all mammalian species even those that have not yet been sequenced, it provides deep coverage of conserved cytosines facilitating the development epigenetic biomarkers, and it increases the probability that biological insights gained in one species will translate to others.

bioinformatics↗

bioRxiv2020

Universal annotation of the human genome through integration of over a thousand epigenomic datasets

BackgroundGenome-wide maps of chromatin marks such as histone modifications and open chromatin sites provide valuable information for annotating the non-coding genome, including identifying regulatory elements. Computational approaches such as ChromHMM have been applied to discover and annotate chromatin states defined by combinatorial and spatial patterns of chromatin marks within the same cell type. An alternative stacked modeling approach was previously suggested, where chromatin states are defined jointly from datasets of multiple cell types to produce a single universal genome annotation based on all datasets. Despite its potential benefits for applications that are not specific to one cell type, such an approach was previously applied only for small-scale specialized purposes. Large-scale applications of stacked modeling have previously posed scalability challenges. ResultsUsing a version of ChromHMM enhanced for large-scale applications, we applied the stacked modeling approach to produce a universal chromatin state annotation of the human genome using over 1000 datasets from more than 100 cell types, with the learned model denoted as the full-stack model. The full-stack model states show distinct enrichments for external genomic annotations, which we used in characterizing each state. Compared to per-cell-type annotations, the full-stack annotations directly differentiate constitutive from cell type specific activity and is more predictive of locations of external genomic annotations. ConclusionsThe full-stack ChromHMM model provides a universal chromatin state annotation of the genome and a unified global view of over 1000 datasets. We expect this to be a useful resource that complements existing per-cell-type annotations for studying the non-coding human genome.

bioinformatics↗

bioRxiv2020

Multiscale interactions between plant part and a steep environmental gradient determine plant microbial composition in a tropical watershed

Plant microbiomes are shaped by forces working at different spatial scales. Environmental factors determine a pool of potential symbionts while host physiochemical factors influence how those microbes associate with distinct plant tissues. Interactions between these scales, however, are seldom considered. Here we analyze epiphytic microbes from nine Hibiscus tiliaceus trees across a steep environmental gradient within a single Hawaiian watershed. At each location we sampled eight microhabitats: leaves, petioles, axils, stems, roots, and litter from the plant, as well as surrounding air and soil. While the composition of microbial communities is driven primarily by microhabitat, this variable predicted more than twice the compositional variance for bacteria compared to fungi. Fungal community compositional dissimilarity increased more rapidly along the gradient than did bacteria. Additionally, the spatial dynamics of fungal communities differed among plant parts, and these differences influenced the distribution patterns and range size of individual taxa. Within plants, microbes were compositionally nested such that aboveground communities contained a subset of the diversity found belowground. Our findings identify potential differences underlying the mechanisms shaping communities of fungi and bacteria associated with plants, and indicate an interaction between assembly mechanisms working simultaneously on different spatial scales.

microbiology↗