Biology subjects

Hoang, L.

Publications and source records attributed to Hoang, L..

9 recordsLinked to original sources

bioRxiv2026

QuantiTrack: A unified software to study protein dynamics in living cells

Linking the spatiotemporal dynamics of proteins in live cells to biological function is a fundamental challenge in biology. Single molecule tracking (SMT) has emerged as a powerful technique to investigate protein dynamics at the single molecule level. However, SMT analysis often requires expertise in biophysical modeling and programming, and integrating results from different analyses can be challenging. To address these barriers, we developed QuantiTrack: a MATLAB-based SMT analysis software with a simple graphical user interface. This provides a much-needed end-to-end solution where a user can load a movie, detect and track single molecules, and perform complementary downstream analyses within a standardized workflow. QuantiTrack includes quantitative metrics for selecting detection and tracking parameters and troubleshooting experimental design, and includes a detailed step-by-step User Guide. We used simulations to demonstrate how signal intensity, labeling density, and motion blur affect detection and tracking fidelity. Using multi-state simulations, we further benchmarked complementary methods to identify distinct mobility states from heterogeneous trajectory populations. Finally, we applied QuantiTrack to real experimental data where we address how the glucocorticoid receptor (GR), a hormone-regulated transcription factor, responds to treatment and washout of its cognate hormone. Hormone washout results in rapid (in minutes) downregulation of GR target genes to basal levels. By integrating complementary analyses within QuantiTrack, we showed that hormone washout substantially reduced the bound fraction of GR, its occupancy in the mobility state associated with GR activation, and dwell times. Together, these analyses showcase QuantiTrack as an integrated platform for extracting biologically meaningful measurements from single molecule trajectories.

biophysics↗

bioRxiv2026

Enhancing volumetric microscopy with blind computational correction of spatially variant aberrations using neural field representation

Studying biological processes across multi-millimeter scales requires imaging systems that combine high spatial resolution with a large field of view (FOV). However, optical aberrations degrade image quality, particularly in large-FOV systems where distortions gradually worsen toward the periphery. Existing methods for correcting field-dependent aberrations are limited and often impractical. Hardware-based solutions such as adaptive optics demand additional components and sample manipulation, increasing system complexity and experimental burden. Computational approaches, while promising, typically rely on exhaustive point spread function (PSF) calibration or large training datasets, restricting their applicability. We introduce a self-supervised algorithm that simultaneously estimates spatially varying aberrations and reconstructs 3D sample structure from a single blurred image--without PSF calibration or training data. Our method was implemented on optically cleared mouse hippocampal neurons and cortical vasculature imaged with oblique plane microscopy (OPM), as well as in vivo mouse retinal vasculature captured with adaptive optics scanning laser ophthalmoscopy (AOSLO), where PSF calibration is infeasible. The algorithm predicts and corrects aberrations across multi-millimeter FOVs, enhances contrast in low signal-to-noise regions, and reveals critical structural details in neuronal and vascular systems that are obscured in raw images. This approach enables high-resolution, large-scale imaging without hardware modifications, expanding the accessibility of advanced microscopy techniques.

bioinformatics↗

bioRxiv2025

Versatile high-speed volumetric imaging from microscopic to macroscopic scale by self-adaptive oblique plane microscopy

There is an increasing need for large-scale high-speed volumetric recording in complex multi-cellular model systems to define dynamic processes. Oblique plane microscopy (OPM) provides a solution that features oblique illumination, rapid optical scanning, and remote focusing to achieve real-time 4D microscopy. OPM implements light sheet imaging via a single primary objective lens, making the entire space below the objective accessible for large specimens, such as living mouse brain. Yet it is challenging to adopt OPM beyond a microscopic scale (i.e. size < 1mm), limiting its broad applications. Here we present a self-adaptive OPM that leverages Abbes sine condition to unlock its flexibility across a range of field-of-views (FOVs) (up to 8 mm2) and resolutions (down to 2.2 {micro}m3). This versatility enables brain-wide single neuron volumetric calcium imaging in behaving larval zebrafish (1x0.4 mm2 FOV at 5 Hz) and capillary blood cell tracking in living mouse brain (>3x3 mm2 FOV) with a sweeping 0.32 mm wide volume section at 100 Hz. In optically cleared mouse brain, the flexibility allows a screen-and-zoom capability by sequentially imaging the whole brain at low-and-high magnifications to locate and resolve subcellular structures such as dendritic tress and spines. By offering a switchable imaging resolution, volume, and speed, the self-adaptive OPM achieves a versatile platform for studying a wide range of multi-cellular model system, whether in vivo or fixed and optically cleared.

bioengineering↗

bioRxiv2025

Bile acids target an exposed cavity in the glucocorticoid receptor modulating receptor self-assembly, chromatin binding and transcriptional activity

The glucocorticoid receptor (GR) is an essential transcription factor that controls metabolism and homeostasis. Glucocorticoids (GCs) activate the GR upon occupying the internal ligand-binding pocket (LBP) of its ligand-binding domain (GR-LBD), which has been the focus of most previous structure-function studies. Synthetic GCs such as dexamethasone are widely used to treat inflammatory diseases, but their chronic use results in major side effects, whose molecular underpinnings remain unresolved. Here we present a thorough analysis of the topography of GR-LBD and its ability to bind small-molecule compounds, especially cholesterol derivatives. We show that one important class of steroids, bile acids, bind to previously unidentified and highly conserved, surface-exposed cavities on GR-LBD. We show that bile acids affect GR turnover and self-assembly in living cells, modulating receptor transcriptional activity. These findings reveal a previously unrecognized mechanism of GR regulation, with implications for the design of GCs with novel mechanisms of action. TeaserBile acids modulate the activity of the glucocorticoid receptor upon binding to an exposed allosteric pocket thereby influencing transcriptional regulation and receptor self-assembly in living cells.

molecular biology↗

bioRxiv2025

Knowledge Discovery in Datasets of Proteomics by Systems Modeling in Translational Research on Pancreatic Cancer

Knowledge discovery in databases (KDD) can contribute to translational research, also known as translational medicine, by bridging the gap between in vitro and in vivo studies and clinical applications. Here, we propose a systems modeling workflow for KDD. This framework includes data collection of composition model (various research models) and processing model (proteomics) and analytical model (bioinformatics, artificial intelligence/machine leaning and pattern evaluation), knowledge presentation, and feedback loops for hypothesis generation and validation. We applied this workflow to study pancreatic ductal adenocarcinoma (PDAC). Through this approach, we identified the common proteins between human PDAC and various research models in vitro (cells, spheroids and organoids) and in vivo (mouse mice). Accordingly, we hypothesized potential translational targets on hub proteins and the related signaling pathways, PDAC specific proteins and signature pathways, and high topological proteins. Thus, we suggest that this systems modeling workflow can be a valuable method for KDD, facilitating knowledge discovery in translational targets in general and in particular to PADA in this case.

systems biology↗

bioRxiv2024

Subtle methodological variations substantially impact correlation test results in ecological time series

Correlation analyses using ecological time series can indicate phenomena such as interspecific interactions or an environmental factor that affects several populations. However, methodological choices in these analyses can significantly impact the results, potentially leading to spurious correlations or missed true associations. In this study, we explore how different decisions affect the performance of statistical tests for correlations between pairs of time series in simulated two-species ecosystems. We show that when performing nonparametric "surrogate data" tests, both the choice of statistic and the method of generating the null distribution can affect true positive and false positive rates. We also show how seemingly closely related methods of accounting for lagged correlation produce vastly different false positive rates. For methods that establish a null model by simulating the dynamics of one of the two species, we show that the choice of species simulated can influence test behavior. Additionally, we identify scenarios where the outcomes of analyses can be highly sensitive to the initial conditions of an ecosystem, even under simple mathematical models. Our results indicate the importance of thoughtful consideration and documentation of the statistical choices investigated here. To make this work broadly accessible, we include visual explanations of most methods tested in an appendix.

bioinformatics↗

bioRxiv2023

The evolutionary conserved choroid plexus sustains the homeostasis of brain ventricles in zebrafish

The choroid plexus produces cerebrospinal fluid (CSF) by transport of electrolytes and water from the vasculature to the brain ventricles. The choroid plexus plays additional roles in brain development and homeostasis by secreting neurotrophic molecules, and by serving as a CSF-blood barrier and immune interface. Prior studies have identified transporters on the epithelial cells that transport water and ions into the ventricles and tight junctions involved in the CSF-blood barrier. Yet, how the choroid plexus epithelial cells maintain the brain ventricle system and control brain physiology remain unresolved. To provide novel insights into the physiological roles of the choroid plexus, we use juvenile and adult zebrafish as model systems. Upon histological and transcriptomic analyses, we first identified that the zebrafish choroid plexus is highly conserved with the mammalian choroid plexus and that it expresses all transporters necessary for CSF secretion. Using novel genetic lines, we also identified that the choroid plexus secretes proteins into the CSF. Next, we generated a transgenic line allowing us to ablate specifically the epithelial cells in the choroid plexus. Using the ablation system, we identified a reduction of the ventricular sizes, but no alterations of the CSF-blood barrier. Altogether, our findings identified that the zebrafish choroid plexus is evolutionarily conserved and critical for maintaining the size and homeostasis of the brain ventricles. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=163 HEIGHT=200 SRC="FIGDIR/small/565468v1_ufig1.gif" ALT="Figure 1"> View larger version (42K): org.highwire.dtl.DTLVardef@1594039org.highwire.dtl.DTLVardef@877b99org.highwire.dtl.DTLVardef@c3834forg.highwire.dtl.DTLVardef@1e1f787_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIThe zebrafish choroid plexus has similar anatomical features with the mammalian choroid plexus. C_LIO_LIThe expression of choroid plexus transporters involved in CSF secretion is evolutionarily conserved across vertebrates. C_LIO_LIGeneration of a novel choroid plexus specific driver line shows that the choroid plexus epithelial cells secrete proteins into CSF. C_LIO_LIAblation of the choroid plexus decreases the size of the brain ventricles. C_LI

neuroscience↗

bioRxiv2020

Prevalence of pathogenic variants in DNA damage response genes in patients undergoing cancer risk assessment and reporting a personal history of early-onset renal cancer

PurposePathogenic variants (PVs) in a number of genes are known to increase the risk of hereditary renal cancer (hRC). However, many early-onset RC (eoRC) patients undergoing genetic testing lack PVs in hRC genes; thus, their genetic risk remains undefined. To determine if PVs in DNA damage response (DDR) genes are enriched in a convenience sample of eoRC patients undergoing genetic testing. Materials and MethodsRetrospective review of results for 844 unselected eoRC patients, undergoing genetic testing with a multi-gene cancer panel by Ambry Genetics [between July 2012 and December 2016]. The patients were tested with CancerNext and/or CancerNext Expanded panels for a variety of indications. Identified PVs were compared with patient characteristics. ResultsMean age of RC diagnosis was 48 years [range 24-60]. In addition to eoRC, 57.9% patients tested reported at least one additional cancer; breast cancer being the most common (40.1% of females, 2.5% of males). PVs in cancer risk genes were identified in 12.8% of patients--3.7% in RC-specific genes, and 8.55% in DDR genes. DDR gene PVs were most commonly identified in CHEK2, BRCA1/2, and ATM. Among the 2.1% of patients with a BRCA1/2 PV, <50% reported a personal history of hereditary breast/ovarian-associated cancer. No association between age of RC diagnosis, and prevalence of PVs in RC-specific or DDR genes was observed. ConclusionsMulti-gene panel testing including DDR genes may provide a more comprehensive risk assessment in unselected eoRC patients, and their families. Validation in larger datasets is needed to characterize the association with eoRC.

genetics↗

bioRxiv2018

Palbociclib and fulvestrant act in synergy to modulate central carbon metabolism in breast cancer cells

Palbociclib, is a selective inhibitor of cyclin-dependent kinases 4 and 6 and used as a first-line treatment for patients with estrogen receptor positive breast cancer. It has been shown that patients have improved progression-free survival when treated in combination with fulvestrant, an estrogen receptor antagonist. However, the mechanisms for this survival advantage are not known. We sought to analyze metabolic and transcriptomic changes in MCF-7 adenocarcinoma breast cancer cells following single and combined treatments to determine if selective metabolic pathways are targeted during combination therapy. Our results showed that individually, the drugs caused metabolic disruption to the same metabolic pathways, however fulvestrant additionally attenuated the pentose phosphate pathway and the production of important coenzymes. A comprehensive effect was observed when the drugs were applied together, confirming the combinatory therapy's synergism in the cell model. This study highlights the power of merging high-dimensional datasets to unravel mechanisms involved in cancer metabolism and therapy.\n\nHighlights{circ} First study employing multi-omics to investigate combined therapy on breast cancer cells\n{circ}Fulvestrant attenuates the pentose phosphate pathway and coenzyme production\n{circ}Synergism of palbociclib and fulvestrant was confirmed in vitro\n{circ}Altered key pathways have been identified\n\n\neTOC BlurbJohnson et al. applied an innovative multi-omics approach to decipher metabolic pathways affected by single versus combination dosing of palbociclib and fulvestrant in estrogen receptor positive breast cancer. Key metabolites and genes were correlated within metabolic pathways and shown to be involved in the drugs' synergism.

biochemistry↗