Biology subjects

Bao, D.

Publications and source records attributed to Bao, D..

8 recordsLinked to original sources

bioRxiv2026

Inferring cascade drivers of VEXAS syndrome by a causal machine learning tool CauNagi

VEXAS syndrome is an adult-onset severe autoinflammatory disease caused by somatic mutations in UBA1, yet the cascade mechanisms linking primitive hematopoietic abnormalities to mature myeloid dysfunctions remain largely unknown. Identifying master regulators of a progressive disease, a black-box process, from complex transcriptomic data also remains challenging. To address this challenge, we developed CauNagi, a computational framework for prioritizing cascade candidate regulators (CCRs). CauNagi integrates a causal representation learning module derived from CausCell with an iterative deep learning backbone adapted from UNAGI; in addition, CauNagi extends these two components with a unique downstream module for CCRs analysis designed to characterize regulatory propagation across hierarchical cellular states. Mechanistically, CauNagi iteratively integrates causal disentangled representation learning with (1) disease-stage cell-state trajectory reconstruction and (2) dynamic regulatory analysis. Benchmarking on single-cell transcriptomic datasets showed that CauNagi preserved cell-type structure in idiopathic pulmonary fibrosis (IPF) and enriched known acute myeloid leukemia(AML)-associated genes among its top-ranked global regulators. When applied to VEXAS syndrome, CauNagi readily revealed inflammatory responses, endoplasmic reticulum stress, and myeloid bias, consistent with the disease features. Furthermore, the CCRs analysis module of CauNagi assisted us in identifying 36 causal drivers, with SPI1, NFKB1, STAT3, and FOS prioritized as high-confidence regulatory hubs linking aberrant myeloid differentiation and inflammatory programs. These findings were further supported by an independent single-cell transcriptomic dataset from a murine VEXAS model. Overall, CauNagi provides a computationally efficient and systematic framework for identifying candidate causal regulators. Beyond hematopoietic diseases, CauNagi may also be applicable to other progressive disorders for which multistage single-cell transcriptomic datasets are available. CauNagi is available at https://github.com/steamed-stuffed-bun/CauNagi.

bioinformatics↗

bioRxiv2026

Neuronal EphB2 signaling drives persistent neuropathic pain following spinal cord injury

Neuropathic pain after spinal cord injury reflects persistent hyperexcitability in the spinal cord dorsal horn, yet the molecular drivers sustaining this maladaptive state are unknown. Using an antibody microarray of dorsal horn tissue from mice six weeks after cervical contusion spinal cord injury, we found persistent upregulation of Eph-ephrin signaling, including increased EphB1, EphB2 and EphB3 expression and phosphorylation. Reversible chemogenetic inhibition of EphB kinase activity, using an EphB1/2/3 analog-sensitive knock-in mouse, selectively reversed established mechanical allodynia without affecting thermal hyperalgesia or motor function and also shifted dorsal horn signaling away from pain sensitization-associated pathways. Among EphB receptors, EphB2 showed the most consistent and robust injury-induced increase in expression within dorsal horn. Although EphB2 transcript levels increased in both dorsal horn neurons and astrocytes, conditional deletion of EphB2 only in dorsal horn neurons, but not in astrocytes, reversed established mechanical allodynia and reduced dorsal horn neuronal activation. These findings identify EphB signaling, and neuronal EphB2 in particular, as a mechanism that actively maintains pain hypersensitivity after spinal cord injury.

neuroscience↗

bioRxiv2026

Myofibroblast lineage mapping and inhibiting subretinal fibrosis by targeting SMAD3 and MRTF pathways via microRNA-24 functional study

Subretinal fibrosis underlies the end-stage pathogenesis of retinal diseases including age-related macular degeneration (AMD). It can disrupt retinal structure and eventually lead to legal blindness by generating contractile force, fibrotic scarring, subretinal hemorrhage, and retinal detachment. Myofibroblasts are the predominant cells critically involved in subretinal fibrosis, however, the cellular contribution to myofibroblasts remains unclear. Here we demonstrate that multiple cell lineages, including macrophages, endothelial cells (EC), retinal pigment epithelial (RPE) cells and pericytes, significantly contribute to myofibroblasts in a laser-induced subretinal fibrosis model. We found microRNA miR-24 is significantly downregulated in the plasma of wet AMD patients. Overexpression of miR-24 represses epithelial-mesenchymal transition (EMT), endothelial-mesenchymal transition (EndMT), and the resulting fibrosis by regulating TGF-{beta}/SMAD3 and PAK4/LIMK2/MRTF pathways. Consistently, a combination of SMAD3 and MRTF inhibitors show superior efficacy to individual inhibitors in repressing fibrosis in vitro and laser-induced subretinal fibrosis in vivo. Together, these suggest the contribution of multiple cell-types in myofibroblast transformation in subretinal fibrosis, and repression of miR-24-regulated TGF-{beta}/SMAD3 and PAK4/LIMK2/MRTF pathways in multiple cell types holds therapeutic potential for treating subretinal fibrosis in AMD and other fibrotic disorders.

molecular biology↗

bioRxiv2025

Mating-Type Imputation (MTI) provides an efficient tool for the mating-type inference of tetrapolar fungi

Mating-type identification is fundamental for the genetic diversity and genetic breeding study in fungi, especially for tetrapolar basidiomycetes, whose mating-types are determined by two multiallelic loci A and B. Traditional mating-type identification of monokaryons relies on manual inference based on their hybridization experiments; however, the process is rather complex, time-consuming and error-prone for large-scale hybridization experiments. In this study, we developed the Mating-Type Imputation (MTI) software for automatic, rapid and accurate monokaryon mating-type inference for tetrapolar fungi using a combinatorial pruning traversal algorithm. Taking the compatibility matrix from 435 hybridization experiments of 30 Flammulina velutipes monokaryons as an example, MTI takes a few minutes to infer the accurate mating-types of all monokaryons, which might take several days for manual inference by experienced investigators. Furthermore, MTI enables us to investigate how false-positives and false-negatives influence mating-type inference results. Using simulated compatibility matrix, we found that MTI could accurately detect potential false-negatives in compatibility and successfully infer the true mating-type combination with limited false-negatives, but the tool could be misled by any false-positives to result in a wrong mating-type combination, indicating that false-positives records in hybridization experiments should be strictly obviated for mating-type inferences. In summary, MTI provides an efficient tool for mating-type inference of tetrapolar fungi, offering technical support for the research paradigm in mating-type studies of edible and medicinal fungi and holding significant theoretical value and broad application prospects in the fields of fungal genetic diversity and breeding studies.

genetics↗

bioRxiv2023

Real-Time Quantification of Cell Mechanics and Functions by Double Resonator Piezoelectric Cytometry -Theory and Study of Cellular Adhesion of HUVECs

Cell mechanics is closely associated with cellular structure and function. However, the inability to measure both cellular force and viscoelasticity of statistically significant number of cells noninvasively remains a challenge for quantitative characterizations of various cellular functions and practical applications. Here a double resonator piezoelectric cytometry (DRPC), using AT and BT cut quartz crystals of the same frequency and surface morphology is developed to simultaneously quantify the cells-generated forces ({Delta}S) and viscoelastic moduli (G', G'') of a population of isolated single cells or cells with different degrees of cell-cell interactions in a non-invasive and real time manner. DRPC captures the dynamic mechanical parameters {Delta}S and G', G'' during the adhesions of human umbilical vein endothelial cells (HUVECs) under different ligand densities of adhesion molecules fibronectin or Arg-Gly-Asp (RGD) modified on the gold surfaces of 9 MHz AT and BT cut quartz crystals, and different seeding densities of HUVECs. It is found that both the ligand density and cell seeding density affect the magnitudes of {Delta}S and G', G'' and their correlations are revealed for the first time by DRPC. The validity of DRPC is further verified by mechanical changes of the cells in response to treatments with cytoskeleton regulators.

biophysics↗

bioRxiv2022

Ratio-based quantitative multiomics profiling using universal reference materials empowers data integration

Multiomics profiling is a powerful tool to characterize the same samples with complementary features orchestrating the genome, epigenome, transcriptome, proteome, and metabolome. However, the lack of ground truth hampers the objective assessment of and subsequent choice from a plethora of measurement and computational methods aiming to integrate diverse and often enigmatically incomparable omics datasets. Here we establish and characterize the first suites of publicly available multiomics reference materials of matched DNA, RNA, proteins, and metabolites derived from immortalized cell lines from a family quartet of parents and monozygotic twin daughters, providing built-in truth defined by family relationship and the central dogma. We demonstrate that the "ratio"-based omics profiling data, i.e., by scaling the absolute feature values of a study sample relative to those of a concurrently measured universal reference sample, were inherently much more reproducible and comparable across batches, labs, platforms, and omics types, thus empower the horizontal (within-omics) and vertical (cross-omics) data integration in multiomics studies. Our study identifies "absolute" feature quantitation as the root cause of irreproducibility in multiomics measurement and data integration, and urges a paradigm shift from "absolute" to "ratio"-based multiomics profiling with universal reference materials.

systems biology↗

bioRxiv2022

Quartet RNA reference materials and ratio-based reference datasets for reliable transcriptomic profiling

As an indispensable tool for transcriptome-wide analysis of differential gene expression, RNA sequencing (RNAseq) has demonstrated great potential in clinical applications. However, the lack of multi-group RNA reference materials of biological relevance and the corresponding reference datasets for assessing the reliability of RNAseq hampers its wide clinical applications wherein the underlying biological differences among study groups are often small. As part of the Quartet Project for quality control and data integration of multiomic profiling, we established four RNA reference materials derived from immortalized B-lymphoblastoid cell lines from four members of a monozygotic twin family. Additionally, we constructed ratio-based transcriptome-wide reference datasets using multi-batch RNAseq datasets, providing "ground truth" for benchmarking. Moreover, Quartet-sample-based quality metrics were developed for assessing reliability of RNAseq technology in terms of intra-batch proficiency and cross-batch reproducibility. The small intrinsic biological differences among the Quartet samples enable sensitive assessment of performance of transcriptomic measurements. The Quartet RNA reference materials combined with the reference datasets can be served as unique resources for assessing data quality and improving reliability of transcriptomic profiling.

genetics↗

bioRxiv2022

Modification Mechanism of Phenol-formaldehyde Resin with Crude Bio-oil by Model Compound Method

To clarify the modification mechanism of bio-oil for phenol-formaldehyde resin with crude bio-oil (BPF), the bio-oil compounds were simplified by model compound method according to the component distribution. The phenol-formaldehyde resin with bio-oil model compounds (BMPF) were prepared and their basic performance, bonding strength and aging characteristics were determined. The changes on the microstructure and chemical bonds of BMPF were also analyzed by scanning electron microscope, Fourier transform infrared spectroscopy, and nuclear magnetic resonance analysis. Results showed that the components of bio-oil had different influence on the performance and microstructure of BMPF, especially phenols. Structural analysis indicated that the phenols and ketones of bio-oil had positive effects on the synthesis of BMPF, while the aldehydes and acids had negative effects. But all components of bio-oil could improve the aging resistance of BMPF inordinately. These results could provide a basis for the modification of BPF.

ecology↗