Biology subjects

zhang, z.

Publications and source records attributed to zhang, z..

17 recordsLinked to original sources

bioRxiv2026

Spatialsnake: a flexible workflow for spatial transcriptomics analysis across platforms

Background: Spatial transcriptomics technologies measure gene expression at different spatial resolutions and generate diverse data outputs. Existing workflows support a range of platforms and analyses, but combining methods and extending analyses to selected populations or tissue regions can require additional scripts and repeated data preparation. Findings: We developed Spatialsnake, a flexible workflow built on SpatialData and Snakemake for analysing processed outputs from Visium, Visium HD, Stereo-seq, Xenium and MERFISH. A common command-line interface supports single- and multi-sample analysis, with adjustable parameters and saved intermediate results. Users can select populations, tissue regions or distance-based neighborhoods, repeat clustering and annotation, and map refined labels back to the full dataset. Additional modules support cell-type composition estimation, spatial-domain identification, cell-cell communication inference, regulon analysis and sample-level comparisons. We demonstrate these functions using mouse-brain Visium and colorectal cancer Visium HD datasets. Joint analysis of three colorectal cancer sections retained 1,527,987 bins and enabled further analysis of 223,632 epithelial bins, linking epithelial subpopulation annotations to their locations within the complete tissue. Conclusions: Spatialsnake provides a unified workflow for spatial transcriptomics analysis across sequencing- and imaging-based platforms. Its flexible analysis modules support both whole-tissue analysis and further investigation of selected cell populations and tissue regions.

bioinformatics↗

bioRxiv2026

An electron-bifurcating hydrogenase-like activity associated with mitochondrial Complex I under hypoxia in vascular plants

Abstract Molecular hydrogen (H2) evolution by higher plants under oxygen limitation was reported more than six decades ago, yet its origin, biochemical basis and physiological significance have remained unresolved. Here, we localize this activity to a mitochondrial, Complex I-associated electron-transfer system. Mitochondrial fractions from etiolated Vigna radiata hypocotyls accumulated H2 under hypoxia and mildly acidic conditions. H2 accumulation was nearly abolished by rotenone and was sensitive to perturbations of Complex II, quinone-pool turnover, terminal oxidases and protonmotive force. NADH-generating substrates and succinate-fumarate supplementation stimulated H2 accumulation, while metabolic profiling linked H2 production to succinate and NADH accumulation. Cumulative H2 production exceeded the measured NADH pool by approximately two orders of magnitude, requiring sustained NADH regeneration. These findings support a division-of-labour model involving coexisting mature Complex I and CI*, a Complex I assembly or remodeling state. TCA-cycle dehydrogenation and succinate-driven reverse electron transfer (RET) through mature Complex I replenish the matrix NADH pool, whereas CI* consumes NADH through an H2-evolving branch, regenerating NAD. This model identifies a potential conditional redox function for CI* and an electron outlet coupled to continuous NADH cycling. Unlike mammalian RET, which can generate pronounced reactive oxygen species (ROS), diversion of reducing equivalents into H2 could attenuate the corresponding ROS signature, potentially helping explain the elusive physiological evidence for plant RET. The data establish a RET-compatible supply route, not direct reverse electron flux. Structural and computational analyses support an FMN-Fe-S branched mechanism whose catalytic steps remain unverified. More broadly, Complex I assembly may not merely build the respiratory machinery; under specific physiological conditions, its intermediate states may reshape electron fate, exposing latent hydrogenase-related chemistry associated with Complex I's evolutionary ancestry.

biochemistry↗

bioRxiv2025

Dissecting organoid-bacteria interaction highlights decreased contractile force as a key factor for heart infection

Bacterial endocarditis is a fatal cardiovascular disease exacerbated by weakened heart contraction, yet the direct impact of cardiac contractility on bacterial adhesion remains elusive. Here, we present a novel quantitative physics model integrating finite element analysis and live-cell imaging to uncover their strong correlation. Using this model, we quantified the real-time force magnitude generated by organoid-type cardiac microtissue derived from healthy donors and dilated cardiomyopathy patients - mimicking normal and suppressed heart contractility, respectively - to the approaching bacteria in a real fluidic system. The data revealed that weakened cardiac contractility facilitated bacterial invasion of the myocardium. Verifying this finding in a mouse transverse aortic constriction model demonstrated that increasing heart contraction efficiently mitigated bacterial invasion, with a 25% increase in heart contractility reducing endocarditis risk by 80%. Our findings demonstrate that patient-derived cardiac organoids provide a physiologically relevant platform for studying bacterial infections in vitro, offering high clinical fidelity. This platform establishes a valuable tool for drug screening and the development of novel therapeutic strategies.

bioengineering↗

bioRxiv2024

AKR1C mediates the acquired resistance to T-Dxd in a HER-2 positive gastric cancer line

Trastuzumab deruxtecan (T-Dxd), an anti-HER2 antibody-drug conjugate, has significantly enhanced clinical outcomes for patients as a HER2-directed therapy compared to previous standards of care. However, acquired resistance is always a concern, necessitating further investigation into the underlying resistance mechanism. In this study, we successfully established T-Dxd-resistant cell line (N87-R) by exposing HER2-positive N87 gastric cancer cells to increasing concentrations of T-Dxd, and demonstrated its resistance phenotype both in vitro and in vivo. While there were no changes in HER2 expression or T-Dxd binding in N87-R, a signature of drug metabolism genes were found upregulated, among which AKR1C played a critical role in the resistance mechanism. The resistance phenotype of N87-R cells was mitigated by both siRNA-mediated knockdown of AKR1C and pharmacological inhibition of its enzymatic activity. Our preclinical study underscores the critical role of AKR1C function in mediating T-Dxd resistance and suggests potential therapeutic innovation for combating T-Dxd resistance.

cancer biology↗

bioRxiv2024

Ligand-independent c-Met activation by HHLA2 drives hepatocellular carcinoma and predicts c-MET inhibitor efficacy

The HGF/c-Met signaling pathway facilitates the initiation, progression, and metastasis of hepatocellular carcinoma (HCC). c-Met activation, however, is complex and not solely dependent on HGF, hindering targeted therapy development. This study identifies a critical oncogenic role for HHLA2, a B7 family member, in HCC and highlights its potential as a therapeutic target. We demonstrate that HHLA2 directly interacts with and activates c-Met through N-glycosylation, triggering sustained signaling and promoting aggressive HCC features. Mechanistically, we identified the pro-tumorigenic role of HHLA2 required downstream upregulation of MMP9 and VEGFA, both implicated in tumor progression. In multiple mouse models, HHLA2 overexpression accelerated tumor progression, metastasis, and reduced liver NK cell infiltration, all of which were reversed by c-Met inhibition. In a cohort of 176 HCC patients, HHLA2 expression strongly correlated with c-Met phosphorylation, advanced tumor stage, and poor prognosis. Importantly, HHLA2 expression predicted sensitivity to c-Met inhibitors in cell lines and patient-derived organoids and could be detected in patient serum, suggesting its potential as a prognostic biomarker. Collectively, our findings reveal an HHLA2-mediated mechanism of c-Met activation and provide a strong rationale for targeting the HHLA2-c-Met axis as a novel therapeutic strategy, with HHLA2 serving as a potential prognostic biomarker. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=173 SRC="FIGDIR/small/622557v1_ufig1.gif" ALT="Figure 1"> View larger version (26K): org.highwire.dtl.DTLVardef@8b10dforg.highwire.dtl.DTLVardef@b43dorg.highwire.dtl.DTLVardef@394c4aorg.highwire.dtl.DTLVardef@1bfbc8c_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2024

scIDPMs: Single-cell RNA-seq imputation using diffusion probabilistic models

Single-cell RNA sequencing (scRNA-seq) technology is a high-throughput sequencing analysis method that enables the sequencing of mRNA in individual cells, thereby facilitating a more precise understanding of cellular gene expression and metabolic products. This approach reveals cell function and characteristics, making it widely applicable in biological research. However, scRNA-seq data often suffers from false zero values known as dropout events due to limitations in sequencing technology. These dropout events not only mask true gene expression levels but also significantly impact downstream analysis accuracy and reliability. To address this challenge, numerous computational approaches have been proposed for imputing missing gene expression values. Nevertheless, existing imputation methods struggle to fully capture the distribution of dropout values due to the high sparsity of scRNA-seq data and the complexity and randomness associated with gene expression patterns. Recently, probabilistic diffusion models have emerged as deep generative models capable of accurately restoring probability density distributions in domains such as image and audio processing. In this paper, we propose a method called scIDPMs, which utilizes conditional diffusion probabilistic models to impute scRNA-seq data. scIDPMs first identifies dropout sites based on the characteristics of cellular gene expression and then infers the dropout values by conditioning on the available gene expression values, which provide context information for the dropout values. To effectively capture the global features of gene expression profiles, scIDPMs employs a deep neural network with an attention mechanism to optimize the objective function. The performance of scIDPMs was evaluated using both simulated and real scRNA-seq datasets, and compared with eight other imputation methods. The experimental results clearly demonstrated that, in comparison to alternative approaches, scIDPMs exhibited exceptional performance in recovering biologically meaningful gene expression values and enhancing various downstream analyses.

bioinformatics↗

bioRxiv2023

BL-Hi-C reveals the 3D genome structure of Brassica crops with high efficiency and sensitivity

High-throughput chromatin conformation capture (Hi-C) technologies can be used to investigate the three-dimensional genomic structure of plants. However, complex protocol and high background noise in Hi-C hinder its practical application in plant 3D genomics. Here, we took the approach of modified Bridge Linker Hi-C technology (BL-Hi-C) to explore plant 3D landscape. We modified the BL-Hi-C method by simplifing nuclei extraction step. By using Brassica rapa and Brassica oleracea, BL-Hi-C showed higher signal value and lower background noise than Hi-C. The high sensitivity of BL-Hi-C was further demonstrated by its capacity to identify gene loops involving BrFLC1, BrFLC2 and BrFLC3 which were undetectable in Hi-C. BL-Hi-C also showed promising performance with input as low as 100 mg leaf tissue. By analyzing of the generated data from BL-Hi-C, we found that the simulated 3D genome structure of B. rapa leaf cells was Bouquet configuration. Our results showed that the modified BL-Hi-C is a powerful tool for the investigation of plants genomic organization, gene regulation, and genome assembly. IN A NUTSHELL Background3D genome structure play a critical role in regulating spatiotemporal gene expression. However, there is a lack of simple, efficient and sensitive Hi-C technique in plants. QuestionHow to study plant 3D genomics more simple and efficientHow to detect plant chromatin loops more sensitive? FindingsWe showed that BL-Hi-C is more simple, efficient and sensitive than coventional Hi-C by using Brassica rapa and Brassica oleracea. Furthermore, BL-Hi-C demonstrated its high sensitivity by detecting gene loops involving BrFLC1, BrFLC2, and BrFLC3 which could not be detected by Hi-C. In addition, BL-Hi-C demonstrated promising performance with inputs as low as 100 mg leaf tissue. By analyzing BL-Hi-C data, we found that the simulated 3D genome structure of B. rapa leaf cells was Bouquet configuration. Next stepsHow chromatin loops are formed and regulated gene expression are key questions to be answered in plants. Our dataset of BL-Hi-C will enable future investigations to improve our understanding of chromatin loops.

genomics↗

bioRxiv2023

A glutamatergic DRN-VTA pathway for neuropathic pain and comorbid depression-like behavior modulation

Chronic pain causes both physical suffering and comorbid mental disorders such as depression. However, the neural circuits and molecular mechanisms underlying these maladaptive behaviors remain elusive. Here, we report a pathway from vesicular glutamate transporter3 neurons in the dorsal raphe nucleus to dopamine neurons in the ventral tegmental area (VGluT3DRN[->]DAVTA), of which population activity in response to innocuous mechanical stimuli and sucrose consumption, is respectively inhibited and attenuated by chronic neuropathic pain. Mechanistically, neuropathic pain dampens VGluT3DRN[->]DAVTA glutamatergic transmission and DAVTA neural excitability. VGluT3DRN[->]DAVTA activation alleviates neuropathic pain and comorbid depression-like behavior (CDB) by releasing glutamate, which subsequently promotes DA release in the nucleus accumbens medial shell (NAcMed) and produces analgesia and antidepressant effects via D2 and D1 receptors, respectively. In addition, VGluT3DRN[->]DAVTA inhibition produces pain-like hypersensitivity and depression-like behavior in healthy mice. These findings reveal a novel VGluT3DRN[->]DAVTA[->]D2/D1NAcMed pathway in establishing and modulating chronic pain and comorbid depressive-like behavior.

neuroscience↗

bioRxiv2022

ATM-Mediated Translocation of RanBPM Regulates DNA Damage Response by Stabilizing p21 in Non-Small Cell Lung Cancer Cells

Non-small cell lung cancer (NSCLC) is the leading cause of cancer-induced deaths around the world, and platinum-based chemotherapy remains a standard-of-care for most patients with advanced NSCLC. DNA damage response (DDR) induced by platinum or Etoposide activated a panel of cell cycle-regulatory proteins including p21 through p53 pathway. In this present study, we found that the level of p21 or RanBPM is lower in NSCLC than non-malignant tissues and has a highly positive correlation, which is negatively correlated with the survival of patients. We further revealed that RanBPM protein physically interacts with p21, RanBPM deubiquitinates p21 by recruiting a deubiquitinase USP11 to maintain protein stability of p21. Furthermore, RanBPM regulates DNA damage response (DDR) in a p21-dependent manner, and DNA damage promotes the translocation of RanBPM into the nucleus and regulates p21 protein stability through ATM-mediated pathways. We for the first time revealed a novel mechanism of p21 protein stability regulated by RanBPM, and the novel roles of RanBPM in the regulation of DDR.

cancer biology↗

bioRxiv2022

Ultra Low Power, Event-Driven Data Compression of Multi-Unit Activity

Recent years have demonstrated the feasibility of using intracortical Brain-Machine Interfaces (iBMIs), by decoding thoughts, for communication and cursor control tasks. iBMIs are increasingly becoming wireless due to the risk of infection and mechanical failure, typically associated with percutaneous connections. The wireless communication itself, however, increases the power consumption further; with the total dissipation being strictly limited due to safety heating limits of cortical tissue. Since wireless power is typically proportional to the communication bandwidth, the output Bit Rate (BR) must be minimised. Whilst most iBMIs utilise Multi-Unit activity (MUA), i.e. spike events, and this in itself significantly reduces the output BR (compared to raw data), it still limits the scalability (number of channels) that can be achieved. As such, additional compression for MUA signals are essential for fully-implantable, high-information-bandwidth systems. To meet this need, this work proposes various hardware-efficient, ultra-low power MUA compression schemes. We investigate them in terms of their BRs and hardware requirements as a function of various on-implant conditions such as MUA Binning Period (BP) and number of channels. It was found that for BPs [≤] 10 ms, the delta-asynchronous method had the lowest total power and reduced the BR by almost an order of magnitude relative to classical methods (e.g. to approx. 151 bps/channel for a BP of 1 ms and 1000 channels on-implant.). However, at larger BPs the synchronous method performed best (e.g. approx. 29 bps/channel for a BP of 50 ms, independent of channel count). As such, this work can guide the choice of MUA data compression scheme for BMI applications, where the BR can be significantly reduced in hardware efficient ways. This enables the next generation of wireless iBMIs, with small implant sizes, high channel counts, low-power, and small hardware footprint. All code and results have been made publicly available.

bioengineering↗

bioRxiv2022

Hardware evaluation of spike detection algorithmstowards wireless brain machine interfaces

The current trend for implantable Brain Machine Interfaces (BMIs) is to increase the channel count, towards next generation devices that improve on information transfer rate. This however increases the raw data bandwidth for wired or wireless systems that ultimately impacts the power budget (and thermal dissipation). On-implant feature extraction and/or compression are therefore becoming essential to reduce the data rate, however the processing power is of concern. One common feature extraction technique for intracortical BMIs is spike detection. In this work, we have empirically compared the performance, resource utilization, and power consumption of three hardware efficient spike emphasizers, Non-linear Energy Operator (NEO), Amplitude Slope Operator (ASO) and Energy of Derivative (ED), and two common statistical thresholding mechanisms (using mean or median). We also propose a novel median approximation to address the issue of the median operator not being hardware-efficient to implement. These have all been implemented and evaluated on reconfigurable hardware (FPGA) to estimate their hardware efficiency in an ultimate ASIC design. Our results suggest that ED with average thresholding provides the most hardware efficient (low power/resource) choice, while using median has the advantage of improved detection accuracy and higher robustness on threshold multiplier settings. This work is significant because it is the first to implement and compare the hardware and algorithm trade-offs that have to be made before translating the algorithms into hardware instances to design wireless implantable BMIs.

bioengineering↗

bioRxiv2022

Selecting an effective amplitude threshold for neural spike detection

This paper assesses and challenges whether commonly used methods for defining amplitude thresholds for spike detection are optimal. This is achieved through empirical testing of single amplitude thresholds across multiple recordings of varying SNR levels. Our results suggest that the most widely used noise-statistics-driven threshold can suffer from parameter deviation in different noise levels. The spike-noise-driven threshold can be an ideal approach to set the threshold for spike detection, which suffers less from the parameter deviation and is robust to sub-optimal settings.

bioengineering↗

bioRxiv2022

Establishment of a hypoxia ischemia reperfusion brain damagemodel in neonatal rats

ObjectiveRice-Vannucci model has been widely used as HIE (Hypoxic ischemic encephalopathy) animal model in the past forty years, but it does not mimic reperfusion injury that occurs during HIE. The aim of the present study was to establish a new neonatal rat model by simulating hypoxia ischemia reperfusion brain damage (HIRBD) through "common carotid artery (CCA) muscle bridge". MethodsSixty 7-day-old male Sprague-Dawley rats were randomly assigned to group A (HIRBD groups, n=36), group B (Rice-Vannucci group, n=12), and group C (sham-operated group, n=12). Rats in group A were assigned to 3 subgroups (A1-A3, 12 animals/subgroup). Dynamic changes in cerebral blood flow (CBF) were evaluated by the laser speckle imaging system. The status of the CCA was observed under a stereomicroscope. Changes in body weight, gross morphology as well as pathological sections of brain tissue were examined to evaluate the feasibility of the model. ResultsThe results indicated that CCA muscle bridge successfully blocked the CBF. CBF was restored after removal of the CCA muscle bridge in HIRBD groups. The CCA was in good condition after removing the muscle bridge, and blood supply was not affected. Changes in body weight, gross morphology and pathological sections of brain tissue indicated that ischemia reperfusion induced by the CCA muscle bridge method caused varying degrees of brain damage. ConclusionCCA muscle bridge method is effective for establishing a reliable, stable, and reproducible neonatal rat model for study of HIRBD.

neuroscience↗

bioRxiv2021

Nrf2 mediated ER-phagy protects against oxidative damage in intervertebral disc degeneration

Intervertebral disc degeneration (IDD) increases the risk of low back pain (LBP). Oxidative stress may induce cellular damage and contribute to various diseases including IDD. Endoplasmic reticulum autophagy (ER-phagy) is a specific type of autophagy, its role in oxidative stress induced damage as well as in IDD is unknown. This study explores the role of ER-phagy in oxidative damage in intervertebral disc nucleus pulposus cells (NPCs), as well as the Nrf2/FAM134B axis in ER-phagy regulation and IDD therapy. We found ER-phagy was decreased in NPCs during oxidative stress; while FAM134B may promote ER-phagy and alleviate oxidative stress induced ER-stress and apoptosis. In addition, the nuclear transcription factor Nrf2 may promote the expression of FAM134B as well as ER-phagy, and suppress ER-stress and apoptosis in NPCs. Furthermore, overexpression of FAM134B and Nrf2 could effectively attenuate the progression of IDD in rats in vivo. These results suggest Nrf2/FAM134B mediated ER-phagy may combat oxidative damage in cells; meanwhile, ER-phagy as well as Nrf2 could be potential therapeutic targets for IDD. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=114 SRC="FIGDIR/small/469451v1_ufig1.gif" ALT="Figure 1"> View larger version (44K): org.highwire.dtl.DTLVardef@188b390org.highwire.dtl.DTLVardef@1c4e4f6org.highwire.dtl.DTLVardef@193fe77org.highwire.dtl.DTLVardef@12770e2_HPS_FORMAT_FIGEXP M_FIG C_FIG

cell biology↗

bioRxiv2020

A robust and automated algorithm that uses single-channel spike sorting to label multi-channel Neuropixels data

This paper describes preliminary work towards an automated algorithm for labelling Neuropixel data that exploits the fact that adjacent recording sites are spatially oversampled. This is achieved by combining classical single channel spike sorting with spatial spike grouping, resulting in an improvement in both accuracy and robustness. This is additionally complemented by an automated method for channel selection that determines which channels contain high quality data. The algorithm has been applied to a freely accessible dataset, produced by Cortex Lab, UCL. This has been evaluated to have a accuracy of over 77% compared to a manually curated ground truth.

bioengineering↗

bioRxiv2020

Identification of key candidate genes and pathways in axial Spondyloarthritis through integrated bioinformatics analysis

BackgroundRadiographic axial Spondyloarthritis (r-axSpA) is the prototypic form of seronegative spondyloarthritis (SpA). In the present study, we evaluated the key genes related with r-axSpA, and then elucidated the possible molecular mechanisms of r-axSpA. Material/MethodsThe gene expression GSE13782 was downloaded from the GEO database contained five proteoglycan-induced spondylitis mice and three naive controls. The differentially expressed genes (DEGs) were identified with the Bioconductor affy package in R. Gene Ontology (GO) enrichment and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were built with the DAVID program followed by construction of a protein-protein interaction (PPI) network performed with Cytoscape. WebGestalt was performed to construct transcriptional regulatory network and microRNAs-target regulatory networks. RT-PCR and immunohistochemical staining were performed to testify the expression of hub genes, transcription factors (TFs) and microRNAs. ResultsA total of 230 DEGs were identified. PPI networks were constructed by mapping DEGs into STRING, in which 20 hub proteins were identified. KEGG pathway analyses revealed that the chemokine, NOD-like receptor, IL-17, and TNF signalling pathways were altered. GO analyses revealed that DEGs were extensively involved in the regulation of cytokine production, the immune response, the external side of the plasma membrane, and G-protein coupled chemoattractant receptor activity. The results of RT-PCR and immunohistochemical staining demonstrated that the expression of DEGs, TFs and microRNAs in our experiment were basically consistent with the predictions. ConclusionsThe results of this study offer insight into the pathomechanisms of r-axSpA and provide potential research directions.

molecular biology↗

bioRxiv2018

Intraflagellar transport protein 74 is essential for mouse spermatogenesis and male fertility by regulating axonemal microtubule assembly in mice

IFT74 is a component of the core intraflagellar transport (IFT) complex, a bidirectional movement of large particles along the axoneme microtubules for cilia formation. In this study, we investigated its role in sperm flagella formation and discovered that mice deficiency in IFT74 in male germ cells were infertile associated with low sperm counts and immotile sperm. The few developed spermatozoa displayed misshaped heads and short tails. Transmission electron microscopy revealed abnormal flagellar axoneme in the seminiferous tubules where sperm are made. Clusters of unassembled microtubules were present in the spermatids. Testicular expression levels of IFT27, IFT57, IFT81, IFT88 and IFT140 were significantly reduced in the mutant mice, with the exception of IFT20 and IFT25. The levels of ODF2 and SPAG16L proteins were also not changed. However, the processed AKAP4 protein, a major component of the fibrous sheath, a unique structure of sperm tail, was significantly reduced. Our study demonstrates that IFT74 is essential for mouse sperm formation, probably through assembly of the core axoneme and fibrous sheath, and highlights a potential genetic factor (IFT74) that contributes to human infertility in men.

developmental biology↗