Biology subjects

Mary, H.

Publications and source records attributed to Mary, H..

6 recordsLinked to original sources

bioRxiv2025

An integrated platform for high-throughput phenospace learning of 3D multilineage organoid systems

Complex multilineage organoid systems lack quantitative phenotyping methods preserving spatial architecture at high throughput. Current approaches compromise biological complexity, spatial resolution, or robust homogeneous multilineage assembly. We establish an integrated experimental-computational platform for high-throughput spatial phenotyping of multilineage organoids through developing a modular tumoroid culture system incorporating pancreatic ductal adenocarcinoma (PDAC) cells and cancer-associated fibroblasts (CAFs) in 384-well format with multiplexed whole-mount imaging. We developed Phenocoder, a machine learning framework combining conditional variational autoencoders with spatial graph analysis to extract multiscale organoid features. Rigorous validation demonstrates robust performance in PDAC tumoroids. The platform identifies pathway modulators that disrupt the fibrotic microenvironment and discovers stroma-dependent vulnerabilities, undetectable in monocultures. Extending to immuno-competent tumoroids, we assess fibrosis modulators in combination with T cell bispecific antibodies, identifying treatments that enhance immune cell proliferation and infiltration inducing cancer cell death, validated in patient-derived explants. This platform establishes a generalizable framework for multilineage organoid phenotyping.

cancer biology↗

bioRxiv2025

Modeling viral and bacterial infections in human lung organotypic systems reveals strain specific host responses

In this study, we developed novel lung organoid-on-chip models that elucidate differential human tissue response to various strains of respiratory pathogens: Streptococcus pneumoniae and SARS-CoV-2. We show that human fetal-derived distal lung epithelial cells are readily expandable in 3D as organoids, thereby providing a highly sustainable source of lung progenitor cells. These 3D organoid progenitors can then be induced to produce airway and alveolar organoids on microfluidic devices. Upon challenge with Streptococcus pneumoniae, a bacterium known to cause pneumonia, a rapid and strain-dependent colonization was observed at the epithelial surface of alveolar chips. We also assessed SARS-CoV-2 infection in the alveoli-on-chip system and observed that the Delta variant exhibited greater infectivity as compared to the Omicron BA.5. Both SARS-CoV-2 variants induced potent interferon responses and triggered the expression of different interferon-stimulated genes. Our results demonstrate that strain-specific host defense mechanisms can be recapitulated in human-organoid-based microfluidic systems, paving the way for the use of such platforms for more targeted assessments of human response to novel emergent pathogen strains. HighlightsO_LIHuman fetal epithelial lung stem cells can be expanded as multipotent organoids and differentiated into both airway or alveolar organoids C_LIO_LIMultipotent lung organoids efficiently produce functional epithelia of small airway or alveoli when grown on-chip. C_LIO_LIStreptococcus pneumoniae inoculation in alveoli-on-chip mimics the early stages of bacterial colonization in lung epithelia C_LIO_LIAlveoli on-chip system recapitulates variant-specific interactions. SARS-CoV-2 Delta replicates but not Omicron BA.5. C_LIO_LIRobust interferon response upon SARS-CoV-2 infection shows Alveoli on-chip can model innate immune responses. C_LI

bioengineering↗

bioRxiv2024

Clostridioides difficile binary toxin CDT induces biofilm-like persisting microcolonies

Clinical symptoms of Clostridioides difficile infection (CDI) range from diarrhea to pseudomembranous colitis. A major challenge in managing CDI is the high rate of relapse. Several studies correlate production of CDT binary toxin by clinical strains of Clostridioides difficile with higher relapse rates. Although the mechanism of action of CDT on host cells is known, its exact contribution to CDI is still unclear. To understand the physiological role of CDT during CDI, we established two hypoxic relevant intestinal models, Transwell and Microfluidic Intestine-on-Chip systems. Both were challenged with the epidemic strain UK1 CDT+ and its isogenic CDT- mutant. We report that CDT binary toxin induces mucin-associated microcolonies that increase C. difficile colonization and display biofilm-like properties by enhancing C. difficile resistance to vancomycin but not to fidaxomicin, a biofilm disrupting antibiotic. Importantly, biofilm- like CDT-dependent microcolonies were also observed in the caecum and colon of infected mice. Hence, our study shows that CDT toxin induces biofilm-like microcolonies, increasing C. difficile colonization and persistence.

microbiology↗

bioRxiv2024

Recapitulating memory B cell responses in a Lymphoid Organ-Chip to evaluate mRNA vaccine boosting strategies

Predicting the immunogenicity of candidate vaccines in humans remains a challenge. To address this issue, we developed a Lymphoid Organ-Chip (LO chip) model based on a microfluidic chip seeded with human PBMC at high density within a 3D collagen matrix. Perfusion of the SARS-CoV-2 Spike protein mimicked a vaccine boost by inducing a massive amplification of Spike-specific memory B cells, plasmablast differentiation, and Spike-specific antibody secretion. Features of lymphoid tissue, including the formation of activated CD4+ T cell/B cell clusters and the emigration of matured plasmablasts, were recapitulated in the LO chip. Importantly, myeloid cells were competent at capturing and expressing mRNA vectored by lipid nanoparticles, enabling the assessment of responses to mRNA vaccines. Comparison of on-chip responses to Wuhan monovalent and Wuhan/Omicron bivalent mRNA vaccine boosts showed equivalent induction of Omicron neutralizing antibodies, pointing at immune imprinting as reported in vivo. The LO chip thus represents a versatile platform suited to the preclinical evaluation of vaccine boosting strategies.

immunology↗

bioRxiv2022

A meta-analysis of genome-wide association studies identifies new genetic loci associated with all-cause and vascular dementia

Dementia is multifactorial with Alzheimer (AD) and vascular (VaD) pathologies making the largest contributions. Genome-wide association studies (GWAS) have identified over 70 genetic risk loci for AD but the genomic determinants of other dementias, including VaD remain understudied. We hypothesize that common forms of dementia will share genetic risk factors and conducted the largest GWAS to date of "all-cause dementia" (ACD) and examined the genetic overlap with VaD. Our dataset includes 809,299 individuals from European, African, Asian, and Hispanic ancestries with 46,902 and 8,702 cases of ACD and VaD, respectively. We replicated known AD loci at genome-wide significance for both ACD and VaD and conducted bioinformatic analyses to prioritize genes that are likely functionally relevant, and shared with closely related traits and risk factors. For ACD, novel loci identified were associated with energy transport (SEMA4D), neuronal excitability (ANO3), amyloid deposition in the brain (RBFOX1), and MRI markers of small vessel disease (HBEGF). Novel VaD loci were associated with hypertension, diabetes, and neuron maintenance (SPRY2, FOXA2, AJAP1, and PSMA3). Our study identified genetic risks underlying all-cause dementia, demonstrating overlap with neurodegenerative processes, vascular risk factors (Type-II diabetes, blood pressure, lipid) and cerebral small vessel disease. These novel insights could lead to new prevention and treatment strategies for all dementias.

genetics↗

bioRxiv2019

Kappa (κ): Analysis of Curvature in Biological Image Data using B-splines

Curvature is a central morphological feature of tissues, cells, and sub-cellular structures. A challenge for computational biology is to measure the curvature of these structures from biological image data. We present an open-source Fiji plugin for measuring curvature using B-splines. The plugin is named Kappa after the Greek symbol for curvature,{kappa} . Kappa is semi-automated: users create an initialization curve by a point-click method, and the initialization curve is fit to the underlying data using an iterative minimization algorithm. We demonstrate Kappas applicability on images of cytoskeletal filaments in vitro, the cell wall of budding yeast, and whole worms moving in an agar dish. In order to verify the accuracy and precision of Kappa, we created a bank of synthetic images of known curvature using sine waves and golden spirals, which we digitized with different signal-to-noise ratios (SNR), pixel sizes, and point-spread functions (PSF). For synthetic images with characteristics similar to real data, the measured curvatures of those images show a high correlation with the theoretical curvatures. Our fitting algorithms perform better with higher SNR, smaller pixel sizes, and especially PSFs equivalent to super-resolution microscopy data (surprise, surprise). Kappa is freely available under the MIT license for simple integration into Fiji-based workflows. The source code and documentation can be found on GitHub at https://github.com/brouhardlab/Kappa.

bioinformatics↗