Biology subjects

Ji, B.

Publications and source records attributed to Ji, B..

At least 19 recordsLinked to original sources

bioRxiv2026

MRI-compatible 3D Soft Carbon Neural Interface Enabled by Versatile Depth-tunable Laser Drawing

Soft neural interfaces are designed to minimize mechanical mismatch with the brain. However, planar and recessed electrode sites remain locally decoupled from the curved and pulsating cortical surface, degrading the fidelity of neural sensing. Here, we report a 3D soft carbon electrode array, enabled by a depth-tunable laser drawing strategy. This laser-driven workflow achieves versatile fabrication of customizable 3D soft carbon neural interfaces, eliminating the reliance on conventional thin-film microfabrication processes. The fully silicone-based electrode structure realize device-scale conformality, and the 3D soft carbon sites promote a non-penetrating, intimate neural-electrode interface. The CNT-3D array combined superior in-vitro electrochemical and in-vivo recording performance compared with Au-2D and CNT-2D controls. Furthermore, in bilateral rabbit cortex implantation, CNT-3D array retained 80.4% of electrocorticography power after 4 months, versus 11.7% for CNT-2D control. Moreover, the 3D sensing sites significantly suppressed line-frequency harmonics and background noise interference. Subsequently, during magnetic resonance imaging, the CNT-3D array exhibits negligible implant-induced artifacts compared to the conventional Pt-Ir metal array. Overall, this work establishes a laser drawing strategy that extends neural interfaces from macro device-scale conformality to micro site-scale coupling, providing a technological pathway for practical and translational soft neurotechnology.

bioengineering↗

bioRxiv2025

Pseudotimecascade visualizes gene expression cascade in pseudotime analysis

Single-cell transcriptomic technologies enable the reconstruction of dynamic biological processes such as cell development and differentiation. While existing pseudotime methods allow the analysis of temporal expression patterns, they primarily focus on individual genes, overlooking the coordinated programs that drive cellular transitions. We introduce Pseudotimecascade, a tool for visualizing and comparing multi-gene expression cascades along pseudotime. In addition, it links these cascades to biological functions by identifying stage-specific pathways. Applied to hematopoietic stem cell differentiation, Pseudotimecascade highlights regulatory hierarchies and stage-specific processes, offering a deeper understanding of gene programs that govern cell fate decisions. The Pseudotimecascade package is freely available at https://github.com/changxinw/Pseudotimecascade.

bioinformatics↗

bioRxiv2025

AlphaGEM Enables Precise Genome-Scale Metabolic Modelling by Integrating Protein Structure Alignment with deep-learning-based Dark Metabolism Mining

Constructing high-quality genome-scale metabolic models (GEMs) for less-studied species remains challenging. To address this, we developed AlphaGEM, a versatile toolbox leveraging proteome-scale structural alignment and deep-learning-based predictions for efficient genomic mining to generate GEMs ready for applications. Our findings show that the structural alignment or protein-language-model-based prediction (i.e., PLMSearch), could identify more homologous protein relationships than sequence-blast-based alignment, contributing to the accurate profiling of metabolism from target organisms. Additionally, AlphaGEM encompasses an ensemble procedure empowered by multiple deep learning toolboxes to effectively mine the dark metabolic functions encoded by nonhomologous proteins, significantly expanding species-specific metabolic networks. We demonstrate AlphaGEMs accuracy by building GEMs for eukaryotes (e.g., S. pombe, C. albicans) and prokaryotes (e.g., K. pneumoniae, B. subtilis), achieving predictions comparable to manually curated models while outperforming existing tools. AlphaGEM also successfully reconstructs GEMs for M. musculus and C. griseus, showcasing its great potential for uncovering dark metabolism in complex mammals. Lastly, we demonstrate that AlphaGEM could facilitate the automatic GEMs reconstruction for 332 distinct yeast species with high prediction fidelity. In conclusion, AlphaGEM provides unprecedented opportunities for the precise, rapid construction of GEMs across diverse domains, which sets a solid foundation for universal functional analysis of non-model organisms having genome sequences available.

bioinformatics↗

bioRxiv2025

Euktect: Enhanced Eukaryotic Sequence Detection and Classification in Metagenomes via the DNA Language Model

The current taxonomy classification of DNA sequences in metagenomics primarily relies on alignment against reference databases. However, the eukaryotic species in genome databases are not sufficient as there exist numerous unculturable eukaryotes inside metagenomes. These limitations hinder functional and evolutionary analyses of eukaryotes across distinct environmental samples. To overcome these limitations, we created Euktect, a deep-learning-based toolbox for reliable, alignment-free classification of eukaryotic DNA sequences across different phylogenetic levels from metagenome datasets. Euktect achieves high accuracy in extraction of eukaryotic sequences longer than 500bp from the assembled contigs of metagenomes, significantly outperforming existing methods. Furthermore, we developed an algorithm that integrates Euktects predictions with existing tools to refine metagenome-assembled genomes (MAGs), substantially increasing the yield of high-quality eukaryotic MAGs for the downstream analysis. Beyond eukaryotic detection, Euktect incorporates two specialized models: a high-precision classifier for fungal phyla, and a hierarchical classifier that accurately identifies sequences from specific fungal genera (e.g., Candida) in diverse metagenomic samples. Significantly, this framework enables prediction of host disease status (e.g., inflammatory bowel disease) by linking eukaryotic sequence identification to clinical phenotypes through machine learning models. Collectively, Euktect enables accurate reconstruction and functional annotation of eukaryotic genomes from metagenomes at large scale, thereby empowering the comprehensive utilization of sequenced eukaryotic species for downstream evolutionary and clinical research.

bioinformatics↗

bioRxiv2024

Accurate nucleic acid-binding residue identification based on domain-adaptive protein language model and explainable geometric deep learning

Protein-nucleic acid interactions play a fundamental and critical role in a wide range of life activities. Accurate identification of nucleic acid-binding residues helps to understand the intrinsic mechanisms of the interactions. However, the accuracy and interpretability of existing computational methods for recognizing nucleic acid-binding residues need to be further improved. Here, we propose a novel method called GeSite based the domain adaptive protein language model and explainable E(3)-equivariant graph convolution neural network. Prediction results across multiple benchmark test sets demonstrate that GeSite is superior or comparable to state-of-the-art prediction methods. The performance comparison on low structure similarity and newly released test proteins demonstrates the robustness and generalization of the method. Detailed experimental results suggest that the advanced performance of GeSite lies in the well-designed nucleic acid-binding protein adaptive language model. Meanwhile, interpretability analysis exposes the perception of the prediction model on various remote and close functional domains, which is the source of its discernment. The data and source code of GeSite are freely accessible at https://github.com/pengsl-lab/GeSite.

bioinformatics↗

bioRxiv2024

CTCF mutation at R567 causes developmental disorders via 3D genome rearrangement and abnormal neurodevelopment

The three-dimensional genome structure organized by CTCF is required for development. Clinically identified mutations in CTCF have been linked to adverse developmental outcomes. Nevertheless, the underlying mechanism remains elusive. In this investigation, we explored the regulatory roles of a clinically relevant R567W point mutation, located within the 11th zinc finger of CTCF, by introducing this mutation into both murine models and human embryonic stem cell-derived cortical organoid models. Mice with homozygous CTCFR567W mutation exhibited growth impediments, resulting in postnatal mortality, and deviations in brain, heart, and lung development at the pathological and single- cell transcriptome levels. This mutation induced premature stem-like cell exhaustion, accelerated the maturation of GABAergic neurons, and disrupted neurodevelopmental and synaptic pathways. Additionally, it specifically hindered CTCF binding to peripheral motifs upstream to the core consensus site, causing alterations in local chromatin structure and gene expression, particularly at the clustered protocadherin locus. Comparative analysis using human cortical organoids mirrored the consequences induced by this mutation. In summary, this study elucidates the influence of the CTCFR567W mutation on human neurodevelopmental disorders, paving the way for potential therapeutic interventions.

molecular biology↗

bioRxiv2023

Real-Time Structural Biology of DNA and DNA-Protein Complexes on an Optical Microscope

The intricate interplay between DNA and proteins is key for biological functions such as DNA replication, transcription, and repair. To better understand these interactions, it is crucial to develop tools to study DNA-protein complexes with high spatial and temporal resolution. Here, we use the vertical orientation that DNA adopts on graphene and investigate its interactions with proteins via energy transfer from a probe dye to graphene, achieving spatial resolution down to the [A]ngstrom scale. We measured the bending angle of DNA induced by adenine tracts, bulges, abasic sites and the binding of Escherichia coli endonuclease IV with unprecedented precision and millisecond time resolution. Additionally, we observed the translocation of the O6-alkylguanine DNA alkyltransferase along double-stranded DNA, reaching single-base pair resolution and detecting an affinity for adenine tracts. Overall, we foresee that this method will become a widespread tool for the dynamical study of nucleic acid and nucleic acid-protein interactions.

biophysics↗

bioRxiv2023

Augmented Super-Resolution Radial Fluctuations (aSRRF) Pushing the Limits of Structured Illumination Microscopy

Structured illumination microscopy (SIM) is a versatile super-resolution technique known for its compatibility with a wide range of probes and fast implementation. While 3D SIM is capable of achieving a spatial resolution of [~]120 nm laterally and [~]300 nm axially, attempting to further enhance the resolution through methods such as nonlinear SIM or 4-beam SIM introduces complexities in optical configurations, increased phototoxicity, and reduced temporal resolution. Here, we have developed a novel method that combines SIM with augmented super-resolution radial fluctuations (aSRRF) utilizing a single image through image augmentation. By applying aSRRF reconstruction to SIM images, we can enhance the SIM resolution to [~]50 nm isotopically, without requiring any modifications to the optical system or sample acquisition process. Additionaly, we have incorporated the aSRRF approach into an ImageJ plugin and demonstrated its versatility across various fluorescence microscopy images, showcasing a remarkable two-fold resolution increase.

cell biology↗

bioRxiv2022

Cell remote mechanics regulates large-spatial matrix modeling with dynamic simulations

Tissues are often isotropic and heterogeneous organizations, which developmental processes are coordinated by cells and extracellular matrix modeling. Cells have the capability of modeling matrix in distance, however, the biophysical mechanism is largely unknown. We investigated underlying mechanism of large collagen I (COL) fibrillary modeling by cell mechanics with designed arrays of cell clusters. By incorporating dynamic contractions, Molecular Dynamics simulations yielded highly matching isotropic outcomes with observed COL clustering in experiments from variable geometrical arrays without spatial limitation. Further designed single polygons from triangles to hexagons resulted in predicted structural assembly which showed maintained spatial balance. Cell cytoskeletal integrity (actin filaments, microtubules), actomyosin contractions, and endoplasmic reticulum calcium channels were essential for remote fiber inductions, while membrane mechanosensitive integrin and Piezo showed coordinative role in regulating the fiber assembly. The study provides new insights on cell mechanics-induced isotropic matrix modeling with dynamic large-spatial scales and the associated cellular mechanism. The assembled biomechanical scaffolds with pre-designs may lead to applications in micro-tissue engineering. This work implicates heterogeneous tissue structures maybe partially derived from isotropic cell mechanics.

biophysics↗

bioRxiv2022

Systems analysis of metabolic responses to a mixed meal test in an obese cohort reveals links between tissue metabolism and the gut microbiota

Individuals with prediabetes and type 2 diabetes mellitus (T2DM) have poor ability to adapt to diet-triggered perturbations. We investigated global metabolic responses to a mixed meal test (MMT) in morbidly obese individuals with different diabetic status by performing plasma metabolomic profiling. Abnormal metabolism of carbohydrates, (branched-chain) amino acids, fatty acids and acylcholines in individuals with (pre)diabetes was observed. Moreover, differences in metabolic responses were associated with altered fecal metagenomics and transcriptomes of liver, jejunum and adipose tissues, which revealed a modified gut microbiome and multi-tissue metabolism in individuals having insulin resistance. Finally, using integrative machine learning models, we built a predictive model based on metabolomics data after 2h MMT, and identified possible new biomarkers for glycemic control including N-acetylaspartate and phenylalanine-derived metabolites that may be useful for diagnosis, intervention and prevention of T2DM.

systems biology↗

bioRxiv2021

Non-invasive imaging of tau-targeted probe uptake by whole brain multi-spectral optoacoustic tomography

AimAbnormal tau accumulation plays an important role in tauopathy diseases such as Alzheimers disease and Frontotemporal dementia. There is a need for high-resolution imaging of tau deposits at the whole brain scale in animal models. Here, we demonstrate non-invasive whole brain imaging of tau-targeted PBB5 probe in P301L model of 4-repeat tau at 130 m resolution using volumetric multi-spectral optoacoustic tomography (vMSOT). MethodsThe binding properties of PBB5 to 4-repeat K18 tau and A{beta}42 fibrils were assessed by using Thioflavin T assay and surface plasmon resonance assay. We identified the probe PBB5 suitable for vMSOT tau imaging. The imaging performance was first evaluated using postmortem human brain tissues from patients with Alzheimers disease, corticobasal degeneration and progressive supranuclear palsy. Concurrent vMSOT and epi-fluorescence imaging of in vivo PBB5 targeting (i.v.) was performed in P301L and wild-type mice. Ex vivo measurements on excised brains along with multiphoton microscopy and immunofluorescence staining of tissue sections were performed for validation. The spectrally-unmixed vMSOT data was registered with MRI atlas for volume-of-interest analysis. ResultsPBB5 showed specific binding to recombinant K18 tau fibrils, Alzheimers disease brain tissue homogenate by competitive binding against [11C]PBB3 and to tau deposits (AT-8 positive) in post-mortem corticobasal degeneration and progressive supranuclear palsy brain. i.v. administration of PBB5 in P301L mice led to retention of the probe in tau-laden cortex and hippocampus in contrast to wild-type animals, as also confirmed by ex vivo vMSOT, epi-fluorescence and multiphoton microscopy results. ConclusionvMSOT with PBB5 facilitates novel 3D whole brain imaging of tau in P301L animal model with high-resolution for future mechanistic studies and monitoring of putative treatments targeting tau.

neuroscience↗

bioRxiv2020

Ppard is Essential in Acceleration of Pancreatic Ductal Adenocarcinoma Development by High-Fat Diet in Mutant Kras Mice

Pro-obesity high-fat diet is linked with an increased incidence of pancreatic cancers, but the molecular underpinnings of this association remain poorly understood. Here, we report that PPARD is upregulated in pancreatic intraepithelial neoplasia lesions (PanINs) at early stages of pancreatic tumorigenesis in humans and mutant Kras mice. Transgenic overexpression of Ppard in pancreatic epithelial cells drastically accelerates the development and progression of pancreatic ductal adenocarcinoma in mutant Kras mice when activated by feeding the mice with a high-fat diet or a diet containing GW501516 (50 mg/kg), a selective PPARD agonist. In contrast, pancreatic Ppard genetic deletion significantly suppressed the promotion of pancreatic tumorigenesis by these diets. Mechanistically, we found that this Ppard hyperactivation in pancreatic epithelial cells of mutant Kras mice increased production of chemokines and cytokines (e.g., CcI2, CcI4-5, CxcI5 and II6), leading to the robustly increased recruitment of myeloid-derived suppressor cells and macrophages into pancreata, which fostered an immune suppressive microenvironment and subsequently accelerated pancreatic ductal adenocarcinoma development and progression. Our findings demonstrate that PPARD plays an essential role in the promotion of pancreatic tumorigenesis by a high-fat diet. Targeted inhibition of PPARD activation is a potential interventive strategy for pancreatic cancer prevention and therapy.

cancer biology↗

bioRxiv2020

Tracking tau fibrillogenesis and consequent primary phagocytosis of neurons mediated by microglia in a living tauopathy model

Fibrillary tau pathologies have been implicated in Alzheimers and allied neurodegenerative diseases, while mechanisms by which neurons bearing tau tangles die remain enigmatic. To address this issue, we pursued tau and related key pathologies macroscopically by PET and MRI and microscopically by intravital two-photon laser optics. Time-course macroscopic assays of tau transgenic mice demonstrated intimate associations of tau deposition and increase of an inflammatory microglial marker, translocator protein (TSPO), with regional brain atrophy. Longitudinal microscopy of these mice revealed a rapid turnover of tau lesions resulting from continuous generation of new tau aggregates followed by loss of neurons and their fibrillar contents. This technology also allowed the capturing of the disappearance of tangle-bearing neurons several days after being engulfed by activated microglia. Notably, a therapeutic TSPO ligand profoundly suppressed the mobility and phagocytotic activity of microglia and improved neuronal survival in this model, supporting the involvement of primary phagocytosis of viable neurons by microglia in tau-primed neuronal death. Finally, partial depletion of microglia revealed roles of immune factors, MFG-E8 and C1q, as eat-me signals for an immediate attraction of phagocytic microglia towards the elimination of tangle-loaded neurons.

neuroscience↗

bioRxiv2020

Codon-optimized FAM132b prevents diet-induced obesity by modulating adrenergic response and insulin action

FAM132b, also known as myonectin, has been identified as a myokine produced by exercise. It is a secreted protein precursor that belongs to the adipolin/erythroferrone family, and has hormone activity in circulation to regulate cellular iron homeostasis and lipid metabolism via unknown receptors. Here, adeno-associated viral vectors (AAV9) were engineered to induce overexpression of FAM132b with 2 codon mutations (A136T and P159A). Treatment of mice under high-fat diet feeding with FAM132b gene transfer resulted in marked reductions in body weight, fat depot, adipocytes size, glucose intolerance and insulin resistance. Moreover, FAM132b overproduction reduced glycemic response to epinephrine (EPI) in whole body and increased lipolytic response to EPI in adipose tissues. This adrenergic response of adipose tissue led to the result that gene transfer reduced glycogen utilization and increased fat consumption in skeletal muscle during exercise. FAM132b knockdown by shRNA significantly increased glycemic response to EPI in vivo and reduced adipocytes response to EPI and adipose tissue browning. Structural analysis suggested that FAM132b mutants delivered by AAV9 may form a weak bond with ADRB2, and potentially bind to insulin against insulin receptor by blocking the receptor binding sites on insulin B-chain. Our study underscores the potential of FAM132b gene therapy with codon optimization to treat obesity by modulating adrenergic response and interfering insulin action. SignificanceWe show here that AAV9-mediated expression of FAM132b with A136T and P159A is a safe and effective therapeutic strategy for improving glucose homeostasis. This is the first demonstration of a therapeutic effect on metabolic disorders in mice with FAM132b codon optimization. These therapeutic effects indicate that FAM132b gene transfer with selective codon mutants in vivo might be a valid therapy for diabetes that can be extended to other metabolic disorders.

molecular biology↗

bioRxiv2020

Double-transmembrane domain reduces fusion rate by increasing lipid-protein mismatch

SNARE is the essential mediator of membrane fusion that highly relies on the molecular structure of SNAREs. For instance, the protein syntaxin-1 involving in neuronal SNAREs, has a single transmembrane domain (sTMD) leading to fast fusion, while the syntaxin 17 has a V-shape double TMDs (dTMDs), taking part in the autophagosome maturation. However, it is not clear how the TMD structure influences the fusion process. Here, we demonstrate that the dTMDs significantly reduce fusion rate compared with the sTMD by using an in vitro reconstitution system. Through theoretical analysis, we reveal that the V-shape dTMDs can significantly increase protein-lipid mismatch, thereby raising the energy barrier of the fusion, and that increasing the number of SNAREs can reduce the energy barrier or protein-lipid mismatch. This study provides a physical-chemical mechanistic understanding of SNARE-regulated membrane fusion.

biophysics↗

bioRxiv2020

Integrated metabolic modeling, culturing and transcriptomics explains enhanced virulence of V. cholerae during co-infection with ETEC

Gene essentiality is altered during polymicrobial infections. Nevertheless, most studies rely on single-species infections to assess pathogen gene essentiality. Here, we use genome-scale metabolic models to explore the effect of co-infection of the diarrheagenic pathogen Vibrio cholerae (V. cholerae) with another enteric pathogen, enterotoxigenic E. coli (ETEC). Model predictions showed that V. cholerae metabolic capabilities were increased due to ample cross-feeding opportunities enabled by ETEC. This is in line with increased severity of cholera symptoms known to occur in patients with dual-infections by the two pathogens. In vitro co-culture systems confirmed that V. cholerae growth is enhanced in co-cultures relative to single-cultures. Further, expression levels of several V. cholerae metabolic genes were significantly perturbed as shown by dual RNAseq analysis of its co-cultures with different ETEC strains. A decrease in ETEC growth was also observed, probably mediated by non-metabolic factors. Single gene essentiality analysis predicted conditionally-independent genes that are essential for the pathogen’s growth in both single- and co-infection scenarios. Our results reveal growth differences that are of relevance to drug targeting and efficiency in polymicrobial infections.Importance Most studies proposing new strategies to manage and treat infections have been largely focused on identifying druggable targets that can inhibit a pathogen’s growth when it is the single cause of infection. In vivo, however, infections can be caused by multiple species. This is important to take into account when attempting to develop or use current antibacterials since their efficacy can change significantly between single and co-infections. In this study, we used genome-scale metabolic models (GEMs) to interrogate the growth capabilities of Vibrio cholerae (V. cholerae) in single and co-infections with enterotoxigenic E. coli (ETEC), which co-occur in large fraction of diarrheagenic patients. Co-infection model predictions showed that V. cholerae growth capabilities are enhanced in presence of ETEC relative to V. cholerae single-infection, through cross-fed metabolites made available to V. cholerae by ETEC. In vitro, co-cultures of the two enteric pathogens further confirmed model predictions showing an increased growth of V. cholerae in co-culture relative to V. cholerae single-cultures while ETEC growth was suppressed. Dual RNAseq analysis of the co-cultures also confirmed that the transcriptome of V. cholerae is distinct during co-infection compared to single infection scenarios where processes related to metabolism were significantly perturbed. Further, in silico gene-knock out simulations uncovered discrepancies in gene essentiality for V. cholerae growth between single and co-infections. Integrative model-guided analysis thus identified druggable targets that would be critical for V. cholerae growth in both single and co-infections, thus designing inhibitors against those targets would provide a broader spectrum coverage against cholera infections.View Full Text

systems biology↗

bioRxiv2020

Bayesian genome scale modelling identifies thermal determinants of yeast metabolism

The molecular basis of how temperature affects cell metabolism has been a long-standing question in biology, where the main obstacles are the lack of high-quality data and methods to associate temperature effects on the function of individual proteins as well as to combine them at a systems level. Here we develop and apply a Bayesian modeling approach to resolve the temperature effects in genome scale metabolic models (GEM). The approach minimizes uncertainties in enzymatic thermal parameters and greatly improves the predictive strength of the GEMs. The resulting temperature constrained yeast GEM uncovered enzymes that limit growth at superoptimal temperatures, and squalene epoxidase (ERG1) was predicted to be the most rate limiting. By replacing this single key enzyme with an ortholog from a thermotolerant yeast strain, we obtained a thermotolerant strain that outgrew the wild type, demonstrating the critical role of sterol metabolism in yeast thermosensitivity. Therefore, apart from identifying thermal determinants of cell metabolism and enabling the design of thermotolerant strains, our Bayesian GEM approach facilitates modelling of complex biological systems in the absence of high-quality data and therefore shows promise for becoming a standard tool for genome scale modeling.

systems biology↗

bioRxiv2019

Deschloroclozapine: a potent and selective chemogenetic actuator enables rapid neuronal and behavioral modulations in mice and monkeys

The chemogenetic technology Designer Receptors Exclusively Activated by Designer Drugs (DREADDs) affords remotely reversible control of cellular signaling, neuronal activity and behavior. Although the combination of muscarinic-based DREADDs with clozapine-N-oxide (CNO) has been widely used, sluggish kinetics, metabolic liabilities, and potential off-target effects of CNO represent areas for improvement. Here we provide a new high affinity and selective agonist deschloroclozapine (DCZ) for muscarinic-based DREADDs. Positron emission tomography revealed that DCZ selectively bound to and occupied DREADDs in both mice and monkeys. Systemic delivery of low doses of DCZ (1 or 3 g/kg) enhanced neuronal activity via hM3Dq within minutes in mice and monkeys. Intramuscular injections of DCZ (100 g/kg) reversibly induced spatial working memory deficits in monkeys expressing hM4Di in the prefrontal cortex. DCZ represents the most potent, selective, metabolically stable and fast-acting DREADD agonist reported with utility in both mice and non-human primates for a variety of applications.

neuroscience↗