Biology subjects

Pham, T. D.

Publications and source records attributed to Pham, T. D..

10 recordsLinked to original sources

bioRxiv2026

The miR319-targeted TCP transcription factors play crucial roles in the establishment of Arabidopsis thaliana shoot architecture in response to carbon and nitrogen availability.

Shoot branching is a highly plastic developmental process that allows plants to adjust their architecture to environmental conditions, such as carbon and nitrogen availability. Although the class II TCP transcription factor BRANCHED1 is a well-established repressor of shoot branching, the contribution of other TCP factors during this process remains less well understood. Here, we show that the miR319-targeted TCP module promotes shoot branching in Arabidopsis thaliana. Overexpression of miR319 reduced rosette branch production, whereas repression of TCP3 activity or triple knockout (KO) mutation in TCP3, TCP4 and TCP10 inhibited branching. Conversely, expression of a miR319-resistant TCP3 triggered a highly branched phenotype, indicating that TCP3 and related miR319 targets act as positive regulators of shoot branching. Genetic analysis with the strigolactone-deficient max4 mutant showed that strigolactones mediate, at least partly, the reduced branching observed in the miR319 overexpressing line and in the tcp3,4,10 triple mutant. Transcriptomic and DNA-binding analyses indicated indirect effect of TCP3 on strigolactone biosynthesis genes. Instead, miR319 overexpression increased the sensitivity of branching to nitrogen limitation and reduced nitrate uptake, thereby increasing the expression of strigolactone synthesis genes. We further show that carbon starvation reduced the transcription levels of miR319-targeted TCPs, independently of miR319 accumulation, and that TCP3 may connect carbon availability to sugar signalling via HEXOKINASE1. Together, our results identify the miR319-targeted TCP module as a positive regulator of shoot branching that links plant architecture to carbon and nitrogen availability.

plant biology↗

bioRxiv2026

A Unified Spatial AI Framework for Cross-Domain Tissue-State Analysis in Trauma, Oral, and Cardiovascular Pathology

ObjectiveTo develop a cross-domain spatial AI framework for identifying conserved tissue-state organisation across trauma, oral disease, and cardiovascular tissue using spatial transcriptomic data. MethodsFour public spatial transcriptomic datasets spanning wound healing, periodontitis, oral squamous cell carcinoma, and cardiac tissue were integrated using recurrence modelling, graph-based spatial learning, fuzzy tissue-state analysis, and tensor decomposition. Cross-domain coupling, spatial fragmentation, recurrence structure, and permutation-based topological validation were evaluated. ResultsSix conserved fuzzy tissue states were identified, dominated by extracellular matrix remodelling, fibroblast/stromal activation, endothelial signalling, and inflam-matory pathways. Latent embedding analysis demonstrated strong overlap between trauma and oral domains, while cardiovascular tissue exhibited more compact spatial organisation. Oral inflammatory tissue showed the highest fragmentation, whereas cardiovascular tissue demonstrated greater recurrence coherence. Tensor decomposition identified conserved stromal-remodelling programmes across domains. Permutation testing confirmed significantly elevated graph modularity and reduced spatial entropy relative to null distributions. ConclusionThe proposed framework identified conserved spatial tissue-state architecture linking wound healing, oral pathology, and cardiovascular tissue despite differences in tissue origin, pathology, and acquisition technology. SignificanceThese findings demonstrate the potential of spatial AI for investigating conserved stromal and inflammatory microenvironmental organisation across clinically related disease systems and may support spatial biology research in trauma-oral-systemic health.

bioinformatics↗

bioRxiv2026

Deep Learning for Cross-Domain Spatial Transcriptomic Modeling of Tissue Repair

Spatial transcriptomics enables investigation of tissue organization while preserving molecular and spatial information within intact tissues. However, existing computational methods primarily focus on clustering and batch integration and provide limited characterization of higher-order spatial organization and transferable tissuestate dynamics across heterogeneous biological systems. This study introduces a cross-domain spatial transcriptomic framework centered on recurrence-based latent tissuestate analysis, pathological fragmentation quantification, and transferable representation learning between wound repair and tumor-associated microenvironments. Human spatial transcriptomic datasets spanning cutaneous wound healing, oral squamous cell carcinoma, and head and neck squamous cell carcinoma were integrated within a graph-based latent embedding framework. Recurrence analysis was applied within latent transcriptomic space to characterize spatial organization and remodeling dynamics. A pathological fragmentation index quantified intra-tissue spatial disorganization from recurrence structure. The learned latent embeddings achieved a mean silhouette score of 0.79, demonstrating coherent separation of tissue states. Recurrence analysis revealed progressive restoration of spatial organization during wound remodeling, whereas tumor-associated tissues exhibited increased fragmentation and heterogeneous recurrence structure. Independent single-cell RNA-seq reference atlases demonstrated reproducible multicellular enrichment patterns within latent spatial niches. The proposed framework demonstrates that recurrence-inspired latent spatial analysis may provide biologically interpretable characterization of tissue organization and pathological remodeling across heterogeneous biological systems.

bioinformatics↗

bioRxiv2026

Tensor-Derived Similarity Networks for Characterising Spatial Patterns in Colorectal Cancer

Spatial transcriptomics enables the study of gene expression within the spatial context of tissue architecture, offering new opportunities for understanding tumour heterogeneity. This study proposes a tensor-derived similarity network framework for analysing spatial organisation in colorectal cancer. Gene expression data from four patients are represented as spatially structured tensors and decomposed using a low-rank canonical polyadic model to extract latent spatial-molecular features. These features are used to construct similarity networks that characterise spatial relationships between tissue regions. Global network measures, including similarity, density, and spatial heterogeneity, reveal sparse but structured connectivity patterns across all patients. An embedding-permutation framework is introduced to generate randomised spatial configurations while preserving feature distributions. Comparative analysis shows that randomised networks exhibit higher similarity, density, and heterogeneity than real data, indicating that spatial organisation constrains network structure. The results demonstrate that the proposed framework captures meaningful spatial patterns in tumour tissue and provides quantitative measures of spatial heterogeneity. This approach offers a general methodology for analysing spatial transcriptomics data and has potential applications in spatial biomarker discovery and characterisation of tumour architecture.

bioinformatics↗

bioRxiv2025

Resistance to the KRASG12D Inhibitor MRTX1133 is Associated with Increased Sensitivity to BET Inhibition

As many as 90% of human pancreatic ductal adenocarcinoma (PDAC) tumors harbor gain-of-function mutations in the KRAS oncogene. Recently, inhibitors of the most common KRAS mutation, KRASG12D, have entered the clinical arena. However, early evidence suggests that as monotherapy, KRASG12D inhibitors such as MRTX1133 at best provide brief periods of disease stabilization. Hence, there is a growing interest in understanding the mechanisms through which tumors acquire resistance to KRAS inhibition. In the present study, we generated in vitro models of MRTX1133 resistance and subjected parental and drug-resistant cell lines to RNA sequencing. This suggested that MRTX1133-resistant tumor cells undergo a global shift toward histone acetylation. Inhibition of the histone acetyltransferase EP300 reversed the drug-resistant phenotype in vitro, which subsequent RNA sequencing experiments determined was associated with the suppression of pro-survival FOSL1 signaling. Accordingly, siFOSL1 reversed the MRTX1133-resistant phenotype with similar effects on pro-survival signaling. Given the lack of clinically useful EP300 or FOSL1 inhibitors, we next explored whether inhibitors of the acetylation scanning BET proteins would be similarly effective. The addition of BET inhibitors re-sensitized several resistant cell lines to MRTX1133 and impaired FOSL1-mediated survival signaling in vitro. In murine models of MRTX1133-resistant PDAC, BET inhibition cooperated with MRTX1133 to markedly extend overall survival. As BET inhibitors are currently under clinical testing, the combination of MRTX1133 and BET inhibitors warrants further investigation, particularly in tumors that have developed resistance to KRAS inhibition. SIGNIFICANCEHere, we demonstrate that BET inhibition is effective in PDAC with acquired resistance to KRAS inhibitors. As BET inhibitors are under clinical testing, the combination of KRAS and BET inhibitors warrants consideration in PDAC patients. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=195 SRC="FIGDIR/small/653074v1_ufig1.gif" ALT="Figure 1"> View larger version (36K): org.highwire.dtl.DTLVardef@12dc02corg.highwire.dtl.DTLVardef@a3c8e8org.highwire.dtl.DTLVardef@db1b93org.highwire.dtl.DTLVardef@ef65e0_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2024

Rapid Sterilization of Clinical Apheresis Blood Products using Ultra-High Dose Rate Radiation

BACKGROUND AND OBJECTIVESApheresis platelets products and plasma are essential for medical interventions, but both still have inherent risks associated with contamination and viral transmission. Platelet products are vulnerable to bacterial contamination due to storage conditions, while plasma requires extensive screening to minimize virus transmission risks. Here we investigate rapid irradiation to sterilizing doses for bacteria and viruses as an innovative pathogen reduction technology. MATERIALS AND METHODSWe configured a clinical linear accelerator to deliver ultra-high dose rate (6 kGy/min) irradiation to platelet and plasma blood components. Platelet aliquots spiked with 105 CFU of E.coli were irradiated with 0.1-20 kGy, followed by E.coli growth and platelet count assays. COVID Convalescent Plasma (CCP) aliquots were irradiated at a virus-sterilizing dose of 25 kGy and subsequently, RBD- specific antibody binding was assessed. RESULTS1 kGy irradiation of bacteria-spiked platelets reduced E.coli growth by 2.7- log without significant change of platelet count, and 5 kGy or higher produced complete growth suppression. The estimated sterilization (6-log bacterial reduction) dose was 2.3 kGy, corresponding to 31% platelet count reduction. A 25 kGy virus sterilizing dose to CCP produced a 9.2% average drop of RBD-specific IgG binding. CONCLUSIONThis study shows proof-of-concept of a novel rapid blood sterilization technique using a clinical linear accelerator. Promising platelet counts and CCP antibody binding were maintained at bacteria and virus sterilizing doses, respectively. This represents a potential point-of-care blood product sterilization solution. If additional studies corroborate these findings, this may be a practical method for ensuring blood products safety. HIGHLIGHTSO_LI1 kGy irradiation of bacteria-spiked platelets reduced E.coli growth by 2.7-log without significant change of platelet count, and 5 kGy or higher produced complete growth suppression. C_LIO_LIThe estimated sterilization (6-log bacterial reduction) dose was 2.3 kGy, corresponding to 31% platelet count reduction. C_LIO_LIA 25 kGy virus sterilizing dose to CCP produced a 9.2% average drop of RBD- specific IgG binding. C_LI

microbiology↗

bioRxiv2023

A study of genetic variants associated with skin traits in the Vietnamese population

BackgroundMost skin-related traits have been studied from Caucasian genetic background. A comprehensive study on skin-associated genetic effects on under-represented populations like Vietnam is needed to fill the gaps in the field. ObjectivesTo develop a computational pipeline to predict the effect of genetic factors on skin traits using public data (GWAS catalogs and whole genome sequencing (WGS) data of 1000 genomes project-1KGP) and in-house Vietnamese data (WGS and genotyping by SNP array). By using this information we may have a better understanding of the susceptibility of Vietnamese people. MethodsVietnamese cohorts of whole genome sequencing (WGS) of 1008 healthy individuals for the reference and 96 genotyping samples (which do not have any skin cutaneous issues) by Infinium Asian Screening Array-24 v1.0 BeadChip were employed to predict skin-associated genetic variants of 25 skin-related and micronutrients requirement traits in population analysis and correlation analysis. Simultaneously, we compared the landscape of cutaneous issues of Vietnamese people with other populations by assessing their genetic profiles. ResultsThe skin-related genetic profile of Vietnamese cohorts is similar at most with East Asian (JPT: Fst=0.036, CHB: Fst=0.031, CHS: Fst=0.027, CDX: Fst=0.025) in the population study. In addition, we identified pairs of skin traits being at high risk of frequent co-occurrence (such as skin aging and wrinkles (r = 0.45, p =1.50e-5) or collagen degradation and moisturizing (r = 0.35, p = 1.1e-3). ConclusionThis is the first investigation in Vietnam to explore genetic variants of facial skin. These findings could improve inadequate skin-related genetic diversity in the currently published database.

bioinformatics↗

bioRxiv2022

Chance and contingency in B cell evolution limit the similarity of antibody responses to infection across individuals

Antibodies result from the competition of B cell lineages evolving under selection for improved antigen recognition, a process known as affinity maturation. High-affinity antibodies to pathogens such as HIV, influenza, and SARS-CoV-2 are frequently reported to arise from B cells whose receptors, the precursors to antibodies, are encoded by particular immunoglobulin alleles. This raises the possibility that the presence of particular germline alleles in the B cell repertoire is a major determinant of the quality of the antibody response. Alternatively, initial differences in germline alleles propensities to form high-affinity receptors might be overcome by chance events during affinity maturation. We first investigate these scenarios in simulations: when germline-encoded fitness differences are large relative to the rate and effect size variation of somatic mutations, the same germline alleles persistently dominate the response of different individuals. In contrast, if germline-encoded advantages can be easily overcome by subsequent mutations, allele usage becomes increasingly divergent over time, a pattern we then observe in mice experimentally infected with influenza virus. We investigated whether affinity maturation might nonetheless strongly select for particular amino acid motifs across diverse genetic backgrounds, but we found no evidence of convergence to similar CDR3 sequences or amino acid substitutions. These results suggest that although germline-encoded specificities can lead to similar immune responses between individuals, diverse evolutionary routes to high affinity limit the genetic predictability of responses to infection and vaccination. Author SummaryAntibodies arise as B cell receptors encoded by the stochastic recombination of immunoglobulin genes. While those genes evolve over millions of years, the receptors themselves evolve within weeks as B cells compete under selection for improved antigen recognition. This competition shapes the response to infection and vaccination; how much the outcome depends on the initial choice of immunoglobulin genes versus subsequent receptor evolution is an open question that informs the predictability of the immune response and the long-term evolution of immunoglobulins. In simulations, we show that immunoglobulin genes with hardcoded specificity for the antigen can lead to either transient or persistent similarity in the response of different individuals. When the initial advantage is large relative to the effects of mutation, B cells using the same genes consistently dominate the response across individuals. Weaker initial advantages lead to similar responses early on but are later overcome by B cell evolution playing out differently in each individual due to chance events. We observe such increasingly divergent responses in mice infected with influenza virus. While long-term selection might hardcode specificities for particular pathogens on immunoglobulin genes, our results suggest diverse paths to potent antibodies can nonetheless limit the predictability of the response.

immunology↗

bioRxiv2020

Shared B cell memory to coronaviruses and other pathogens varies in human age groups and tissues

Vaccination and infection promote the formation, tissue distribution, and clonal evolution of B cells encoding humoral immune memory. We evaluated convergent antigen-specific antibody genes of similar sequences shared between individuals in pediatric and adult blood, and deceased organ donor tissues. B cell memory varied for different pathogens. Polysaccharide antigen-specific clones were not exclusive to the spleen. Adults convergent clones often express mutated IgM or IgD in blood and are class-switched in lymphoid tissues; in contrast, children have abundant class-switched convergent clones in blood. Consistent with serological reports, pre-pandemic children had class-switched convergent clones to SARS-CoV-2, enriched in cross-reactive clones for seasonal coronaviruses, while adults showed few such clones in blood or lymphoid tissues. These results extend age-related and anatomical mapping of human humoral pathogen-specific immunity. One Sentence SummaryChildren have elevated frequencies of pathogen-specific class-switched memory B cells, including SARS-CoV-2-binding clones.

immunology↗

bioRxiv2020

A single immunization with spike-functionalized ferritin vaccines elicits neutralizing antibody responses against SARS-CoV-2 in mice

Development of a safe and effective SARS-CoV-2 vaccine is a public health priority. We designed subunit vaccine candidates using self-assembling ferritin nanoparticles displaying one of two multimerized SARS-CoV-2 spikes: full-length ectodomain (S-Fer) or a C-terminal 70 amino-acid deletion (S{Delta}C-Fer). Ferritin is an attractive nanoparticle platform for production of vaccines and ferritin-based vaccines have been investigated in humans in two separate clinical trials. We confirmed proper folding and antigenicity of spike on the surface of ferritin by cryo-EM and binding to conformation-specific monoclonal antibodies. After a single immunization of mice with either of the two spike ferritin particles, a lentiviral SARS-CoV-2 pseudovirus assay revealed mean neutralizing antibody titers at least 2-fold greater than those in convalescent plasma from COVID-19 patients. Additionally, a single dose of S{Delta}C-Fer elicited significantly higher neutralizing responses as compared to immunization with the spike receptor binding domain (RBD) monomer or spike ectodomain trimer alone. After a second dose, mice immunized with S{Delta}C-Fer exhibited higher neutralizing titers than all other groups. Taken together, these results demonstrate that multivalent presentation of SARS-CoV-2 spike on ferritin can notably enhance elicitation of neutralizing antibodies, thus constituting a viable strategy for single-dose vaccination against COVID-19.

immunology↗