Biology subjects

Lao, Y.-H.

Publications and source records attributed to Lao, Y.-H..

6 recordsLinked to original sources

bioRxiv2024

Squidiff: Predicting cellular development and responses to perturbations using a diffusion model

Single-cell sequencing has revolutionized our understanding of cellular heterogeneity and responses to environmental stimuli. However, mapping transcriptomic changes across diverse cell types in response to various stimuli and elucidating underlying disease mechanisms remains challenging. Studies involving physical stimuli, such as radiotherapy, or chemical stimuli, like drug testing, demand labor-intensive experimentation, hindering mechanistic insight and drug discovery. Here we present Squidiff, a diffusion model-based generative framework that predicts transcriptomic changes across diverse cell types in response to environmental changes. We demonstrate Squidiffs robustness across cell differentiation, gene perturbation, and drug response prediction. Through continuous denoising and semantic feature integration, Squidiff learns transient cell states and predicts high-resolution transcriptomic landscapes over time and conditions. Furthermore, we applied Squidiff to model blood vessel organoid development and cellular responses to neutron irradiation and growth factors. Our results demonstrate that Squidiff enables in silico screening of molecular landscapes, facilitating rapid hypothesis generation and providing valuable insights for precision medicine.

bioinformatics↗

bioRxiv2024

Human vascular organoids with a mosaic AKT1 mutation recapitulate Proteus syndrome

Vascular malformation, a key clinical phenotype of Proteus syndrome, lacks effective models for pathophysiological study and drug development due to limited patient sample access. To bridge this gap, we built a human vascular organoid model replicating Proteus syndromes vasculature. Using CRISPR/Cas9 genome editing and gene overexpression, we created induced pluripotent stem cells (iPSCs) embodying the Proteus syndrome-specific AKTE17K point mutation for organoid generation. Our findings revealed that AKT overactivation in these organoids resulted in smaller sizes yet increased vascular connectivity, although with less stable connections. This could be due to the significant vasculogenesis induced by AKT overactivation. This phenomenon likely stems from boosted vasculogenesis triggered by AKT overactivation, leading to increased vascular sprouting. Additionally, a notable increase in dysfunctional PDGFR{beta} + mural cells, impaired in matrix secretion, was observed in these AKT-overactivated organoids. The application of AKT inhibitors (ARQ092, AZD5363, or GDC0068) reversed the vascular malformations; the inhibitors effectiveness was directly linked to reduced connectivity in the organoids. In summary, our study introduces an innovative in vitro model combining organoid technology and gene editing to explore vascular pathophysiology in Proteus syndrome. This model not only simulates Proteus syndrome vasculature but also holds potential for mimicking vasculatures of other genetically driven diseases. It represents an advance in drug development for rare diseases, historically plagued by slow progress.

bioengineering↗

bioRxiv2022

Focused ultrasound-mediated brain genome editing

Gene editing in the mammalian brain has been challenging because of the restricted transport imposed by the blood-brain barrier (BBB). Current approaches rely on local injection to bypass the BBB. However, such administration is highly invasive and not amenable to treating certain delicate regions of the brain. We demonstrate a safe and effective gene editing technique by using focused ultrasound (FUS) to transiently open the BBB for the transport of intravenously delivered CRISPR/Cas9 machinery to the brain.

bioengineering↗

bioRxiv2022

Starfysh reveals heterogeneous spatial dynamics in the breast tumor microenvironment

Spatially-resolved gene expression profiling provides valuable insight into tissue organization and cell-cell crosstalk; however, spatial transcriptomics (ST) lacks single-cell resolution. Current ST analysis methods require single-cell RNA sequencing data as a reference for a rigorous interpretation of cell states and do not utilize associated histology images. Significant sample variation further complicates the integration of ST datasets, which is essential for identifying commonalities across tissues or altered cellular wiring in disease. Here, we present Starfysh, the first comprehensive computational toolbox for joint modeling of ST and histology data, dissection of refined cell states, and systematic integration of multiple ST datasets from complex tissues. Starfysh uses an auxiliary deep generative model that incorporates archetypal analysis and any known cell state markers to avoid the need for a single-cell-resolution reference in characterizing known or novel tissue-specific cell states. Additionally, Starfysh improves the characterization of spatial dynamics in complex tissues by leveraging histology images and enables the comparison of niches as spatial "hubs" across tissues. Integrative analysis of primary estrogen receptor-positive (ER+) breast cancer, triple-negative breast cancer (TNBC), and metaplastic breast cancer (MBC) tumors using Starfysh led to the identification of heterogeneous patient- and disease-specific hubs as well as a shared stromal hub with varying spatial orientation. Our results show the ability to delineate the spatial co-evolution of tumor and immune cell states and their crosstalk underlying intratumoral heterogeneity in TNBC and revealed metabolic reprogramming shaping immunosuppressive hubs in aggressive MBC. Starfysh is publicly available (https://github.com/azizilab/starfysh).

bioinformatics↗

bioRxiv2022

An Immune Cell Recirculation-Enabled Microfluidic Array to Study Dynamic Immunotherapeutic Activity in Recapitulated Tumor Microenvironment

The efficacy of immunotherapeutic treatment protocols to enable immune cell mediated treatment of cancer is significantly modulated in the presence of tumor microenvironment (TME) which is a key factor in providing both a physical barrier and immunosuppressive stimuli. Herein, we developed a recirculating, high-throughput microfluidic cell array to capture these crucial players - cytotoxic T cells in circulation, endothelium, and tumor stroma. The system consisted of a three-layered cell array spatially emulating TME, with T cell circulation sustained via fluidic recirculating circuits. This allowed us to study the dynamic TME/circulation system and cancer cell response thereof. The system further revealed that tumor endothelium exhibited a hindrance to T cell infiltration into the breast cancer tumor compartment, which was alleviated when treated with anti-human PD-L1 antibody. The other key stromal component, cancer associated fibroblasts, further attenuated T cell infiltration, and led to reduced apoptosis activity in cancer cells. These results confirm the capability of our tumor-on-a-chip system to recapitulate some key immune cell interactions with the reconstructed TME, along with demon-strating as the feasibility of using this system for high-throughput cancer immunotherapeutic screening.

bioengineering↗

bioRxiv2021

Mapping morphological malformation to genetic dysfunction in blood vessel organoids with 22q11.2 Deletion Syndrome

DiGeorge Syndrome, or 22q11.2 deletion syndrome (22q11.2 DS), is a genetic disorder caused by microdeletions in chromosome 22, impairing the function of endothelial cells (EC) and/or mural cells and leading to deficits in blood vessel development such as abnormal aortic arch morphology, tortuous retinal vessels, and tetralogy of Fallot. The mechanism by which dysfunctional endothelial cells and pericytes contribute to the vasculopathy, however, remains unknown. In this study, we used human blood vessel organoids (VOs) generated from iPSC of 22q11.2 DS patients to model the vascular malformations and genetic dysfunctions. We combined high-resolution lightsheet imaging and single-cell transcriptome analysis to link the genetic profile and vascular phenotype at the single-cell level. We developed a comprehensive analytical methodology by integrating deep learning-mediated blood vessel segmentation, network graph construction, and tessellation analysis for automated morphology characterization. We report that 22q11.2DS VOs demonstrate a smaller size with increased angiogenesis/sprouting, suggesting a less stable vascular network. Overall, clinical presentations of smaller vascular diameter, less connected vasculature, and increased branch points were recapitulated in 22q11.2DS VOs. Single-cell transcriptome profiling showed heterogeneity in both 22q11.2DS and control VOs, but the former demonstrated alterations in endothelial characteristics that are organ-specific and suggest a perturbation in the vascular developmental process. Intercellular communication analysis indicated that the vascular dysfunctions in 22q11.2 deletion were due to a lower cell-cell contact and upregulated extracellular matrix organization involving collagen and fibronectin. Voronoi diagram-based tessellation analysis also indicated that the colocalization of endothelial tubes and mural cells was different between control and 22q11.2 VOs, indicating that alterations in EC and mural interactions might contribute to the deficits in vascular network formation. This study illustrates the utility of VO in revealing the pathogenesis of 22q11.2DS vasculopathy.

bioengineering↗