Biology subjects

Pham, N.

Publications and source records attributed to Pham, N..

14 recordsLinked to original sources

bioRxiv2026

Tumor Microenvironment Modulates Lineage Plasticity in Lung Squamous Cell Carcinoma

Lung squamous cell carcinoma (LUSC) is the second most common type of lung cancer, yet therapeutic options remain limited. A deeper understanding of its biology and molecular pathogenesis is essential for developing new treatment strategies. Here, we investigated the mechanisms of phenotypic plasticity in LUSC by comparing organoid-derived orthotopic lung models (ODOLs) and subcutaneous xenograft models (ODXs). ODXs showed greater tumor growth, squamous differentiation, and extracellular matrix (ECM) organization compared to ODOLs. Transcriptomic analyses revealed upregulation of multiple HIF1 and SOX2 target genes together with enhanced hypoxia signaling in ODXs. CRISPR/Cas9-mediated HIF1-knockout ODXs showed reduced SOX2 expression, tumor growth, and ECM organization, whereas SOX2-knockout ODXs reduced tumor growth without affecting HIF1 and ECM organization. These results indicate that HIF1 regulates squamous lineage maintenance through SOX2 and ECM remodeling. Spatial transcriptomics revealed enrichment of basal cell-like and squamous-differentiated tumor states in ODXs, whereas ODOLs displayed less differentiated phenotypes. These findings identify the tumor microenvironment as a critical determinant of lineage plasticity in LUSC and provide mechanistic insight into how hypoxia shapes tumor differentiation.

Cancer Biology↗

bioRxiv2026

FXR and BET signaling orchestrate to protect β cells

In both type 1 and type 2 diabetes (T1D and T2D), insulin-producing {beta} cells undergo progressive dysfunction due to inflammation, leading to impaired glucose responsiveness, dedifferentiation, and cell loss. While bile acid (BA) dysregulation under diabetic conditions is known to influence metabolic and inflammatory pathways, its mechanistic role in {beta} cell regulation remains incompletely defined1-3. Here we show that bile acid sensor Farnesoid X receptor (FXR) and Bromodomain and Extra-Terminal motif (BET) signaling cooperatively regulates {beta} cell inflammatory response and {beta} cell identity. We identified the physiological protein-protein interaction between FXR and the bromodomain-containing protein 4 (BRD4) as a regulatory axis that protects against {beta} cell dysfunction. We show that FXR activation by Fexaramine (Fex) together with BRD4 inhibition by JQ1 synergistically suppressed IL-1{beta}-induced inflammation while also improving {beta} cell identity and insulin secretion in both db/db model and high-fat diet (HFD) plus multi low-dose streptozotocin (MLD-STZ) model of diabetes. Importantly, this cooperative effect is abolished in {beta} cell-specific FXR knockout ({beta}FXRKO) mice, establishing that FXR is required for the functional synergy between these pathways in vivo. Mechanistically, structure-guided modeling and mutational analyses identified a direct interaction between FXR and the BD2 domain of BRD4, depending on specific lysine acetylation sites. Additionally, inhibition of the BD2 domain of BET combined with FXR activation markedly improved {beta} cell survival in human T1D and T2D models established from human pluripotent stem cell (hPSC)-derived islet-like organoids (HILOs). Collectively, these findings establish a BA-bromodomain axis as a transcriptional interface linking metabolic signaling and chromatin regulation, and highlight FXR-BET targeting as a promising strategy to counter progressive {beta} cell failure in diabetes.

molecular biology↗

bioRxiv2026

A pooled screening approach reveals bacterial chemoreceptors for short-chain carboxylic acids

Bacterial chemotaxis is a key process in host colonization and virulence, mediated by large repertoires of chemoreceptors. Despite their physiological and ecological importance, mapping these chemoreceptors to their cognate metabolic ligands remains a major challenge due to the vast number of potential interactions. To address this, we developed a pooled screening assay that enriches functional chemoreceptors from a gene library. Using this approach, we identified a previously uncharacterized group of chemoreceptors in Pseudomonas species with Cache_3-Cache_2 domains that sense short-chain C3 carboxylic acids. Sequence and computational structural analyses revealed that these chemoreceptors exhibit domain features similar to a recently reported C1 formate chemoreceptor despite substantial sequence divergence. Functional assays of representative chemoreceptors confirmed robust chemotactic responses to C3 carboxylic acids, with limited responses to formate. Integrating structural and molecular dynamics analyses suggests that increased binding pocket size and altered flexibility, relative to the formate chemoreceptor, facilitate recognition of larger C3 carboxylic acid ligands. Together, our approach provides a simple and scalable framework for mapping ligand-chemoreceptor interactions and enables systematic characterization across diverse metabolites.

microbiology↗

bioRxiv2025

Denoising 7T Structural MRI with Conditional Generative Diffusion Models

Purpose7T MRI offers ultra-high resolution and improved sensitivity for iron deposition in neurodegenerative disorders, but commonly used acquisitions are long and hence challenging, especially for elderly subjects. Efficiently denoising a short acquisition to achieve the image quality of a longer acquisition would be of translational benefit. Materials and MethodsWe introduce a conditional diffusion model derived from generative AI (a 7T Conditional Diffusion Model, 7TCDM) that was trained on native single-acquisition 2D reconstructions and referenced multi-repetition images to guide the denoising process and improve SNR and contrast. 7TCDM model was tested on 2D T2-weighted gradient-echo imaging from 19 participants, including healthy controls and individuals with mild cognitive impairment or Alzheimers disease (AD). 7TCDMs performance was assessed using Mean Squared Error (MSE), Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Index Measure (SSIM), and comprehensive reader studies. ResultsReferencing the multi-repetition ground truth, 7TCDM improved the single-acquisition original image by 29.1% in MSE, 5.8% in PSNR, and 9.4% in SSIM, and outperformed convolutional neural network-based models in all metrics. Expert rater evaluations confirmed superior image quality, with significantly enhanced detail and contrast preservation in regions such as the hippocampi, white matter lesions, and small cortical veins. The model also demonstrated robust performance in both the concurrently acquired and publicly available 3D multi-echo gradient echo acquisitions, which the model was not trained on. ConclusionsThe 7T Conditional Diffusion Model provides high-quality denoised images from shorter scans, increasing the feasibility of scanning patients in shorter times while preserving essential anatomical and pathological details.

neuroscience↗

bioRxiv2024

WRAD core perturbation impairs DNA replication fidelity promoting immunoediting in pancreatic cancer

It is unclear how cells counteract the potentially harmful effects of uncoordinated DNA replication in the context of oncogenic stress. Here, we identify the WRAD (WDR5/RBBP5/ASH2L/DPY30) core as a modulator of DNA replication in pancreatic ductal adenocarcinoma (PDAC) models. Molecular analyses demonstrated that the WRAD core interacts with the replisome complex, with disruption of DPY30 resulting in DNA re-replication, DNA damage, and chromosomal instability (CIN) without affecting cancer cell proliferation. Consequently, in immunocompetent models, DPY30 loss induced T cell infiltration and immune-mediated clearance of highly proliferating cancer cells with complex karyotypes, thus improving anti-tumor efficacy upon anti-PD-1 treatment. In PDAC patients, DPY30 expression was associated with high tumor grade, worse prognosis, and limited response to immune checkpoint blockade. Together, our findings indicate that the WRAD core sustains genome stability and suggest that low intratumor DPY30 levels may identify PDAC patients who will benefit from immune checkpoint inhibitors.

cancer biology↗

bioRxiv2023

An engineered tumor organoid model reveals cellular identity and signaling trajectories underlying translocation RCC.

Translocation renal cell carcinoma (tRCC) is a rare, aggressive type of kidney cancer primarily occurring in children. They are genetically defined by translocations involving MiT/TFE gene family members, TFE3 or, in rare cases, TFEB. The biology underlying tRCC development remains poorly understood, partly due to the lack of representative experimental models. Here, we utilized human kidney organoids, or tubuloids, to engineer a tRCC model by expression of one of the most common MiT/TFE fusions, SFPQ-TFE3. Fusion expressing tubuloids adopt a tRCC-like phenotype and gene expression signature in vitro and grow as clear cell RCC upon xenotransplantation in mice. Genome-wide binding analysis reveals that SFPQ-TFE3 reprograms gene expression signatures by aberrant, gain-of-function genome-wide DNA binding. Combining these analyses with single-cell mRNA readouts reveals an epithelium-to-mesenchymal differentiation trajectory underlying tRCC transformation, potentially caused by deregulated Wnt signaling. Our study demonstrates that SFPQ-TFE3 expression is sufficient to transform kidney epithelial cells into tRCC and defines the trajectories underlying malignant transformation, thereby facilitating the development of new therapeutic interventions.

cancer biology↗

bioRxiv2022

Different B cell activation patterns in asymptomatic and symptomatic COVID-19 patients

Early and persistent defects in B cell subsets such as memory B cells were shown to be correlated with poor outcomes in COVID-19 patients. This research aimed to develop a molecular pathway model to understand the B cell development in COVID-19. A B cell transcriptomics dataset, obtained from COVID-19 patients, was analyzed on the resulting pathway model to study B cell activation. The pathway showed two distinct gene expression profiles between asymptomatic and symptomatic patients. In asymptomatic patients, there is an increase in transcript levels of antiviral interferon-stimulated genes such as ISG15, IFITM1, and NEAT1 and a driving gene for the extrafollicular pathway CXCR4 indicating a formation of plasmablast. In symptomatic patients, the results suggest an inhibition occurring at the germinal center hinting at a reduction in memory B cell production. Transcripts of driver gene CXCR5 involved in germinal center development is one of the most downregulated genes. This could contribute to the shortage in the formation of memory B cells in COVID-19. Concluding, in SARS-CoV-2 infection, B cells follow different activation routes in asymptomatic and symptomatic patients. In this study, we constructed a pathway that allowed us to analyze and interpret activation patterns of B cells in COVID-19 patients and their link to disease severity. Importantly, the pathway and approach can be reused for further research in COVID-19 or other diseases.

immunology↗

bioRxiv2022

A versatile and interoperable computational framework for the analysis and modeling of COVID-19 disease mechanisms

The COVID-19 Disease Map project is a large-scale community effort uniting 277 scientists from 130 Institutions around the globe. We use high-quality, mechanistic content describing SARS-CoV-2-host interactions and develop interoperable bioinformatic pipelines for novel target identification and drug repurposing. Community-driven and highly interdisciplinary, the project is collaborative and supports community standards, open access, and the FAIR data principles. The coordination of community work allowed for an impressive step forward in building interfaces between Systems Biology tools and platforms. Our framework links key molecules highlighted from broad omics data analysis and computational modeling to dysregulated pathways in a cell-, tissue- or patient-specific manner. We also employ text mining and AI-assisted analysis to identify potential drugs and drug targets and use topological analysis to reveal interesting structural features of the map. The proposed framework is versatile and expandable, offering a significant upgrade in the arsenal used to understand virus-host interactions and other complex pathologies.

systems biology↗

bioRxiv2022

Single-cell transcriptomic atlas reveals increased regeneration in diseased human inner ears

Mammalian inner ear hair cell loss leads to permanent hearing and balance dysfunction. In contrast to the cochlea, vestibular hair cells of the murine utricle have some regenerative capacity. Whether human utricular hair cells regenerate remains unknown. Here we procured live, mature utricles from organ donors and vestibular schwannoma patients, and present a validated single-cell transcriptomic atlas at unprecedented resolution. We describe previously unknown markers of 25 sensory and non-sensory cell types, with genes of hair cell and supporting cell subtypes displaying striking divergence between mice and humans. We further uncovered transcriptomes unique to hair cell precursors, which we validated to be 14-fold more robust in vestibular schwannoma utricles, representing ongoing regeneration in humans. Lastly, trajectory analysis of the supporting cell-hair cell axis revealed 5 distinct patterns of dynamic gene expression and associated pathways, including mTOR signaling and synaptogenesis. Our dataset constitutes a foundational resource, accessible via a web-based interface, serving to advance knowledge of the normal and diseased human inner ears and tools to stimulate human inner ear regeneration.

cell biology↗

bioRxiv2020

BBrowser: Making single-cell data easily accessible

BioTurings BBrowser is a software solution that helps scientists effectively analyze single-cell omics data. It combines big data with big computation and modern data visualization to create a unique platform where scientists can interact and obtain important biological insights from the massive amounts of single-cell data. BBrowser has three main components: a curated single-cell database, a big-data analytics layer, and a data visualization module. BBrowser is available for download at: https://bioturing.com/bbrowser/download.

bioinformatics↗

bioRxiv2020

Mechanisms preventing Break-Induced Replication during repair of two-ended DNA double-strand breaks

DNA synthesis during homologous recombination (HR) is highly mutagenic and prone to template switches. Two-ended DNA double strand breaks (DSBs) are usually repaired by gene conversion with a short patch of DNA synthesis, thus limiting the mutation load to the vicinity of the DSB. Single-ended DSBs are repaired by Break-Induced Replication (BIR) that involve extensive and mutagenic DNA synthesis spanning even hundreds of kilobases. It remains unknown how mutagenic BIR is suppressed at two-ended DSBs. Here we demonstrate that BIR is suppressed at two-ended DSBs by several proteins coordinating the usage of both DSB ends: ssDNA annealing protein Rad52 and Rad59, D-loop unwinding helicase Mph1, and DSB ends tethering Mre11-Rad50-Xrs2 complex. Finally, BIR is also suppressed when a normally heterochromatic repair template is silenced by Sir2. These findings suggest several mechanisms restricting mutagenic BIR during repair of two-ended DSBs.

genetics↗

bioRxiv2018

Consistency, Inconsistency and Ambiguity of Metabolite Names in Biochemical Databases Used for Genome Scale Metabolic Modelling

Genome scale metabolic models (GEMs) are manually curated repositories describing the metabolic capabilities of an organism. GEMs have been successfully used in different research areas, ranging from systems medicine to biotechnology. However, the different naming conventions (namespaces) of databases used to build GEMs limit model reusability and prevent the integration of existing models. This problem is known in the GEM community but its extent has not been analyzed in depth. In this study, we investigate the name ambiguity and the multiplicity of non-systematic identifiers and we highlight the (in)consistency in their use in eleven biochemical databases of biochemical reactions and the problems that arise when mapping between different namespaces and databases. We found that such inconsistencies can be as high as 83.1%, thus emphasizing the need for strategies to deal with these issues. Currently, manual verification of the mappings appears to be the only solution to remove inconsistencies when combining models. Finally, we discuss several possible approaches to facilitate (future) unambiguous mapping.

bioinformatics↗

bioRxiv2018

Real-time tracking of complex ubiquitination cascades using a fluorescent confocal on-bead assay

The ubiquitin-proteasome system (UPS) controls the stability, localization and/or activity of the proteome. However, the identification and characterization of complex individual ubiquitination cascades and their modulators remains a challenge. Here, we report a broadly applicable, multiplexed, miniaturized on-bead technique for real-time monitoring of various ubiquitination-related enzymatic activities. The assay, termed UPS-confocal fluorescence nanoscanning (UPS-CONA), employs a substrate of interest immobilized on a micro-bead and a fluorescently labelled ubiquitin which, upon enzymatic conjugation to the substrate, is quantitatively detected on the bead periphery by confocal imaging. UPS-CONA is suitable for studying individual enzymatic activities, including various E1, E2 and HECT-type E3 enzymes, and for monitoring multi-step reactions within ubiquitination cascades in a single experimental compartment. We demonstrate the power of the UPS-CONA technique by simultaneously following ubiquitin transfer from Ube1 through Ube2L3 to E6AP. We applied this multi-step setup to investigate the selectivity of five ubiquitination inhibitors reportedly targeting different classes of ubiquitination enzymes. Using UPS-CONA, we have identified a new activity of a small molecule E2 inhibitor, BAY 11-7082, and of a HECT E3 inhibitor, heclin, towards the Ube1 enzyme. As a sensitive, quantitative, flexible and reagent-efficient method with a straightforward protocol, UPS-CONA constitutes a powerful tool for interrogation of ubiquitination-related enzymatic pathways and their chemical modulators, and is readily scalable for large experiments.

biochemistry↗

bioRxiv2017

Detecting Drug-Target Binding In Cells Using Fluorescence Activated Cell Sorting Coupled With Mass Spectrometry Analysis

The assessment of drug-target engagement for determining the efficacy of a compound inside cells remains challenging, particularly for difficult target proteins. Existing techniques are more suited to soluble protein targets. Difficult target proteins include those with challenging in vitro solubility, stability or purification properties that preclude target isolation. Here, we report a novel technique that measures intracellular compound-target complex formation, as well as cellular permeability, specificity and cytotoxicity - the Toxicity-Affinity-Permeability-Selectivity (TAPS) technique. The TAPS assay is exemplified here using human kynurenine 3-monooxygenase (KMO), a challenging intracellular membrane protein target of significant current interest. TAPS confirmed target binding of known KMO inhibitors inside cells. We conclude that the TAPS assay can be used to facilitate intracellular hit validation on most, if not all intracellular drug targets.

pharmacology and toxicology↗