Biology subjects

Ge, X.

Publications and source records attributed to Ge, X..

At least 73 records · Page 4Linked to original sources

bioRxiv2023

Noise-robust, physical microscopic deconvolution algorithm enabled by multi-resolution analysis regularization

Despite the grand advances in fluorescence microscopy, the photon budget of fluorescent molecules remains the fundamental limiting factor for major imaging parameters, such as temporal resolution, duration, contrast, and even spatial resolution. Computational methods can strategically utilize the fluorescence photons against the imaging noise, to break the abovementioned limits. Here, we propose a multi-resolution analysis (MRA) approach to recharacterize and extract the two main characteristics of fluorescence images: (1) high contrast across the edge, and (2) high continuity along the edge. By regularizing the solution using framelet and curvelet domain sparsity, we develop MRA deconvolution algorithm for fluorescence image, which allows fine detail recovery even with negative signal-to-noise-ratio (SNR), and can provide more than 2-fold physical resolution enhancement with conspicuously fewer artifacts than maximum likelihood estimation (MLE) methods. Furthermore, we develop DeepMRA deconvolution algorithm that can provide computational background inhibition through a bias thresholding mechanism while deconvolving a fluorescence image. Compared with conventional background mitigation schemes, this novel deconvolution canonical form can deal with severer background and better preserve the high-frequency and low-intensity details, which are commonly disrupted by other algorithms. We demonstrate that the MRA and DeepMRA deconvolution algorithms can improve the SNR and resolution of biological images in various microscopies, such as wide-field, confocal, spinning-disk confocal (SD-confocal), light-sheet, structured illumination microscopy (SIM), and stimulated excitation depletion (STED) microscopy.

bioengineering↗

bioRxiv2023

Distinct disease mutations in DNMT3A result in a spectrum of behavioral, epigenetic, and transcriptional deficits

Phenotypic heterogeneity is a common feature of monogenic neurodevelopmental disorders that can arise from differential severity of missense variants underlying disease, but how distinct alleles impact molecular mechanisms to drive variable disease presentation is not well understood. Here, we investigate missense mutations in the DNA methyltransferase DNMT3A associated with variable overgrowth, intellectual disability, and autism, to uncover molecular correlates of phenotypic heterogeneity in neurodevelopmental disease. We generate a DNMT3A P900L/+ mouse model mimicking a disease mutation with mild-to-moderate severity and compare phenotypic and epigenomic effects with a severe R878H mutation. We show that the P900L mutation leads to disease-relevant overgrowth, obesity, and social deficits shared across DNMT3A disorder models, while the R878H mutation causes more extensive epigenomic disruption leading to differential dysregulation of enhancers elements. We identify distinct gene sets disrupted in each mutant which may contribute to mild or severe disease, and detect shared transcriptomic disruption that likely drives common phenotypes across affected individuals. Finally, we demonstrate that core gene dysregulation detected in DNMT3A mutant mice overlaps effects in other developmental disorder models, highlighting the importance of DNMT3A-deposited methylation in neurodevelopment. Together, these findings define central drivers of DNMT3A disorders and illustrate how variable disruption of transcriptional mechanisms can drive the spectrum of phenotypes in neurodevelopmental disease.

neuroscience↗

bioRxiv2023

A novel purity analysis method of bovine milk-derived exosomes by two-dimensional ultra-performance liquid chromatography

Exosomes have been implicated in many biological processes as intercellular communication carriers. Because exosomes are increasingly explored as natural vehicles for cell and gene therapies, and drug delivery applications, it is critical to have high-quality samples. Protein:particle ratio, ELISA, western blotting, polymerase chain reaction, and size-exclusion high-performance liquid chromatography are the main methods that have been extensively applied to analyze exosomes purity in recent years. However, there is currently no well-established method that is convenient for routine quality analysis of small-size impurities in exosomes samples. Here, a size-exclusion high-performance liquid chromatography (SE-HPLC), an ion-exchange high-performance liquid chromatography (IEX-HPLC), and a novel two-dimensional high-performance liquid chromatography (2D-HPLC) method were used to detect the purity of bovine milk-derived exosomes with different processes of exosome isolation in detail. The results showed that the 2D-HPLC method could enhance the accuracy of detecting exosomal purity with higher precision and accuracy of instrumental, reduced personal error and experimental cost, shortened analysis time greatly, and more automation. The 2D-HPLC method is rapid, exhibits high selectivity, and has good sensitivity, thus making it well-suited for application in the pharmaceutical and toxicological analysis of exosomes.

biochemistry↗

bioRxiv2023

Determination of oligomeric organization of membrane proteins from native membranes at nanoscale-spatial and single-molecule resolution

The oligomeric organization of membrane proteins in native cell membranes is a critical regulator of their function. High-resolution quantitative measurements of oligomeric assemblies and how they change under different conditions are indispensable to the understanding of membrane protein biology. We report a single-molecule imaging technique (Native-nanoBleach) to determine the oligomeric distribution of membrane proteins directly from native membranes at an effective spatial resolution of [~]10 nm. We achieved this by capturing target membrane proteins in "native nanodiscs" with their proximal native membrane environment using amphipathic copolymers. We established this method using structurally and functionally diverse membrane proteins with well-established stoichiometries. We then applied Native-nanoBleach to quantify the oligomerization status of a receptor tyrosine kinase (TrkA) and a small GTPase (KRas) under conditions of growth-factor binding or oncogenic mutations, respectively. Native-nanoBleach provides a sensitive, single-molecule platform to quantify membrane protein oligomeric distributions in native membranes at an unprecedented spatial resolution.

biophysics↗

bioRxiv2023

HAPSTR1 localizes HUWE1 to the nucleus to limit stress signaling pathways

HUWE1 is a large, enigmatic HECT domain ubiquitin ligase implicated in the regulation of diverse pathways including DNA repair, apoptosis, and differentiation. How HUWE1 engages its structurally diverse substrates and how HUWE1 activity is regulated are unknown. Using unbiased quantitative proteomics, we identify C16orf72/HAPSTR1 as a dedicated HUWE1 substrate despite HUWE1 targeting substrates in a largely cell type-specific manner. The established physical and genetic interactions between HUWE1 and C16orf72/HAPSTR1 suggest that HAPSTR1 positively regulates HUWE1 function. Here, we show that HAPSTR1 is both a HUWE1 substrate and is required for HUWE1 nuclear localization to facilitate HUWE1 nuclear substrate targeting. HUWE1 or HAPSTR1 loss of function triggers a broad transcriptional stress response. We show that nuclear HUWE1 is both critical for modulating stress signaling pathways, which include p53 and NF-{kappa}B-mediated signaling and required for cell proliferation. Combined, our results define a role for HAPSTR1 in gating critical nuclear HUWE1 functions.

molecular biology↗

bioRxiv2022

Visualization of mitochondrial cristae and mtDNA evolvement and interactions with super-resolution microscopy

Mitochondrial cristae host the respiratory chain complexes composed of mitochondrial DNA (mtDNA)-encoded and nuclear-encoded proteins and are responsible for ATP production. Movement of mtDNA located in the matrix is limited due to blockade by the cristae; yet, the dynamic interaction between the inner membrane and mtDNA remains unknown due to the insufficient spatiotemporal resolution of conventional microscopy and the lack of appropriate in vivo probes targeted to the mitochondrial inner membrane. Here, we developed a novel fluorescence probe to visualize the inner membrane using low-power stimulated emission depletion (STED) microscopy. Dual-color imaging of the inner membrane and mtDNA demonstrated that mtDNA is more likely to spread at mitochondrial tips or branch points under an overall even distribution. Interestingly, exploration of forming this distribution propensity uncovered that the mitochondrial dynamics are closely related to the location of mtDNA, and further insight found that fusion always occurs near mtDNA in order to minimize the pressure for cristae remodeling. In healthy cells, mitochondrial dynamics based on cristae remodeling promotes the even distribution of mtDNA, on the contrary, when cristae structure fails in apoptosis and ferroptosis, leading to mtDNA distribution disorder. Observation of active changes during apoptosis further captured the dynamic process of inner membrane herniation and mtDNA leakage along with cristae remodeling. Under ferroptosis, the mitochondria shrank into ellipsoids and mtDNA converged at the center of mitochondria. The rich dynamics between the cristae and mtDNA, revealed at unprecedented spatiotemporal resolution, show the motive and outgrowth of mtDNA distribution.

biophysics↗

bioRxiv2022

An oral vaccine for SARS-CoV-2 RBD mRNA-bovine milk-derived exosomes induces a neutralizing antibody response in vivo

The severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) that causes the coronavirus disease 2019 (COVID-19) has presented numerous challenges to global health. The vaccines, including lipid-based nanoparticle mRNA, inactivated virus and recombined protein, have been used to prevent SARS-CoV-2 infections in clinics and are immensely helpful against the epidemic. Here, we first present an oral mRNA vaccine based on bovine milk-derived exosomes (milk-exos), which encodes the SARS-CoV-2 receptor binding domain (RBD) as an immunogen. The results indicated that RBD mRNA delivered by milk-derived exosomes can produce secreted RBD peptide in 293 cells in vitro and stimulated neutralizing antibodies against RBD in mice. These results indicated that bovine milk-derived exosome-based mRNA vaccine could serve as a new strategy for preventing SARS-CoV-2 infection. Meanwhile, it also can work as a new oral delivery system for mRNA. One Sentence SummaryOral SARS-CoV-2 mRNA vaccine based on bovine milk-derived exosomes can stimulate neutralizing antibodies in mice.

immunology↗

bioRxiv2022

Open-3DSIM: an Open-source three-dimensional structured illumination microscopy reconstruction platform

With optical section and defocus removal effect, three-dimensional structured illumination microscopy (3DSIM) can get a whole sight of intracellular organelle. Here, Open-3DSIM is reported as an open-source reconstruction platform with double improvement on lateral and axial resolution. MATLAB code, ImageJ version and Exe application are provided for biologists and engineers to maximize its user-friendliness and prompt its further development. Through adaptive parameter estimation and spectrum filter optimization, we demonstrate its superior performance of artifact suppression and defocus elimination over other algorithms on various specimens, under gradient signal-to-noise levels. Moreover, with the capacity to extract the dipole orientation, Open-3DSIM paves a new avenue for interpreting the subcellular structures in six dimensions (xyz{theta}{lambda}t).

bioengineering↗

bioRxiv2022

Functional network organization of the mouse cortex determined by wide-field fluorescence imaging shares some --but not all-- properties revealed with simultaneous fMRI-BOLD

Work in humans and animals shows that the brain can be decomposed into large-scale functional networks. Whereas most studies, especially in humans, use the blood-oxygenation-level-dependent (BOLD) signal, the relationship between BOLD and neuronal activity is complex and incompletely understood. This limits our ability to interpret and apply measures derived from fMRI-BOLD. Here, we employ wide-field Ca2+ imaging simultaneously recorded with fMRI-BOLD in highly-sampled mice expressing GCaMP6f in excitatory neurons. These unique data enabled us to characterize the similarities and differences between networks discoverable by each modality. Importantly, we applied a network partitioning approach that uses a mixed-membership algorithm, which allows brain regions to participate in multiple networks with varying strengths. This contrasts with assuming regions belong to only one network. Our findings demonstrate that (1) most BOLD networks are detected via Ca2+ signals. (2) There is considerable overlapping--as opposed to disjoint--network organization that is evident from both modalities. (3) Large-scale networks determined by Ca2+ signals at low temporal frequencies (0.01 - 0.5 Hz)--as opposed to higher frequencies (0.5 - 5 Hz)--are more similar to those determined by BOLD. (4) Despite many similarities, differences emerge across modes including the spatial distribution of membership diversity (the extent to which regions affiliate with multiple networks). In sum, Ca2+ imaging of excitatory neurons confirms that the mouse cortex is functionally organized into overlapping large-scale networks in a manner that reflects many, but not all, properties observable with simultaneous fMRI-BOLD; affirming the neural origins of patterns of brain organization that are evident in a clinically accessible neuroimaging modality.

neuroscience↗

bioRxiv2022

Exploring the genome and protein space of viruses

Recent metagenomic studies have identified a vast number of viruses. However, the systematic assessment of the true genetic diversity of the whole virus community on our planet remains to be investigated. Here, we explored the genome and protein space of viruses by simulating the process of virus discovery in viral metagenomic studies. Among multiple functions, the power function was found to best fit the increasing trends of virus diversity and was therefore used to predict the genetic space of viruses. The estimate suggests that there are at least 8.23e+08 viral Operational Taxonomic Units (vOTUs) and 1.62e+09 viral protein clusters on Earth when assuming the saturation of the virus genetic space, taking into account the balance of costs and the identification of novel viruses. Its noteworthy that less than 3% of the viral genetic diversity has been uncovered thus far, emphasizing the vastness of the unexplored viral landscape. To saturate the genetic space, a total of 3.08e+08 samples would be required. Analysis of viral genetic diversity by ecosystem yielded estimates consistent with those mentioned above. Furthermore, the estimate of the virus genetic space remained robust when accounting for the redundancy of sampling, sampling time, sequencing platform, and parameters used for protein clustering. This study provides a guide for future sequencing efforts in virus discovery and contributes to a better understanding of viral diversity in nature.

microbiology↗

bioRxiv2022

SurvivalML: an integrative platform for the discovery and exploration of prognostic models in multi-center cancer cohorts

Advances in multi-omics and big-data technologies have led to numerous prognostic signatures aimed at improving current clinicopathological staging systems. Due to the lack of reproducibility and independent confirmation, few signatures have been translated into clinical routine. As high-quality datasets accumulate, identifying robust signatures across multiple independent cohorts becomes possible. Nonetheless, inaccurate data retrieval, different versions of genome annotations, disparate expression distributions, difficult data cleaning, inconsistent clinical information, algorithm selection, and parameter tuning have impeded model development and validation in multi-center datasets. Hence, for the first time, we introduced SurvivalML (https://rookieutopia.com/app_direct/SurvivalML/), a web application for helping develop and validate prognostic models across multi-center datasets. SurvivalML included 37,325 samples (253 eligible datasets) with both transcriptome data and survival information from 21 cancer types, which were renewedly and uniformly re-annotated, normalized, and cleaned. This application provided 10 survival machine-learning algorithms for flexibly training models via tuning essential parameters online and delivered four aspects for model evaluation, including Kaplan-Meier survival analysis, time-dependent ROC, calibration curve, and decision curve analysis. Overall, we believe that SurvivalML can serve as an attractive platform for model discovery from multi-center datasets.

bioinformatics↗

bioRxiv2022

BEST: a web application for comprehensive biomarker exploration on large-scale data in solid tumors

SummaryData mining from RNA-seq or microarray data has become an essential part of cancer biomarker exploration. Certain existing web servers are valuable and broadly utilized, but the meta-analysis of multiple datasets is absent. Most web servers only contain tumor samples from the TCGA database with only one cohort for each cancer type, which also means that the analysis results mainly derived from a single cohort are thin and unstable. Indeed, consistent performance across multiple independent cohorts is the foundation for an excellent biomarker. Moreover, many analytical functions researchers require remain adequately unmet by these tools. Thus, we introduce BEST (Biomarker Exploration for Solid Tumors), a web application for comprehensive biomarker exploration on large-scale data in solid tumors. BEST includes more than 50,000 samples of 27 cancer types. To ensure the comparability of genes between different sequencing technologies and the legibility of clinical traits, we re-annotated transcriptome data based on the GRCh38 patch 13 sequences and unified the nomenclature of clinical traits. BEST delivers fast and customizable functions, including clinical association, survival analysis, enrichment analysis, cell infiltration, immunomodulator, immunotherapy, candidate agents, and genomic alteration. Together, our web server provides multiple cleaned-up independent datasets and diverse analysis functionalities, helping unleash the value of current data resources. It is freely available at https://rookieutopia.com/. The bigger pictureBioinformatics web servers enable researchers without computational programming skills to conduct various bioinformatics analyses. However, most web servers only contain tumor samples from the TCGA database with only one cohort for each cancer type, which also means that the analysis results mainly derived from a single cohort are thin and unstable. Thus, we introduce BEST (Biomarker Exploration for Solid Tumors), a web application for comprehensive biomarker exploration on large-scale data in solid tumors. BEST includes more than 50,000 samples of 27 cancer types that have been uniformly re-annotated based on the GRCh38 patch 13 sequences, which ensures the comparability of genes between different sequencing technologies. BEST also offers prevalent functions including clinical association, survival analysis, enrichment analysis, cell infiltration, immunomodulator, immunotherapy, candidate agents, and genomic alteration. Together, BEST provides a curated database and innovative analytical pipelines to explore cancer biomarkers at high resolution.

genomics↗

bioRxiv2022

Cilium proteomics reveals Numb as a positive regulator of the Hedgehog signaling pathway

The transduction of Hedgehog (Hh) signaling relies on the primary cilium, a cell surface organelle serving as a signaling hub for the cell. Using proximity labeling and quantitative proteomics, we identified Numb as a new ciliary protein that positively regulates Hh signaling. Numb localizes to the ciliary pocket and acts as an endocytic adaptor to incorporate Ptch1 into clathrin-coated vesicles, thereby promoting Ptch1 exit from the cilium, a key step in Hh signaling activation. Numb loss hampers Sonic Hedgehog (Shh)-induced Ptch1 departure from the cilium, resulting in reduced activation of Hh signaling. Numb loss in spinal neural progenitors reduces Shh-induced differentiation into Nkx2.2-positive progenitors, a process reliant on high Hh signaling activity. Genetic ablation of Numb in the developing cerebellum impaired the proliferation of granule cell precursors, a Hh-dependent process, resulting in reduced cerebellar size. This study highlights Numb as a critical regulator of Ptch1 levels in the cilium during Hh signal activation and demonstrates the key role of ciliary pocket-mediated endocytosis in modulating the transduction of cell signaling.

cell biology↗

bioRxiv2022

Visualization of a Limonene Synthesis Metabolon inside Living Bacteria by Hyperspectral SRS Microscopy

Metabolons consisting of cellular structure elements and sequential metabolic enzymes are expected to be involved in diverse biological processes. However, direct visualization of metabolons in prokaryotic cells is still challenging. In this study, we report direct visualization of concentrated subcellular regions of limonene synthesis inside single engineered Escherichia coli by using hyperspectral stimulated Raman scattering (hSRS) microscopy. Equipped with spectral unmixing, hSRS imaging provides a reliable method to quantify intracellular limonene content. In E. coli strains with a complete limonene synthesis pathway, intracellular limonene is found locally concentrated and colocalized with proteins. Furthermore, dual-modality SRS and two-photon fluorescence imaging showed colocalization of limonene and GFP-fused limonene synthase. Significance StatementMonitoring biosynthesis activity at the single-cell level is key to metabolic engineering but is still difficult to achieve in a label-free manner. Using hyperspectral stimulated Raman scattering imaging in the 670-900 cm-1 region, we visualized localized limonene synthesis inside engineered E. coli. The colocalization of limonene and GFP-fused limonene synthase was confirmed by co-registered stimulated Raman scattering and two-photon fluorescence images. Our finding suggests a limonene synthesis metabolon with a polar distribution inside the cells. This finding expands our knowledge of de novo limonene biosynthesis in engineered bacteria and highlights the potential of SRS chemical imaging in metabolic engineering research.

biophysics↗

bioRxiv2022

NFATc1 negatively determines chondrocyte differentiation in articular cartilage progenitors

The origin and differentiation mechanism of articular chondrocytes remain poorly understood. Broadly, the difference in developmental mechanisms of articular and growth-plate cartilage is still less elucidated. Here, we identified that the nuclear factor of activated T-cells cytoplasmic 1 (NFATc1) is a crucial regulator of articular, but not growth-plate, chondrocyte differentiation during development. At the early stage of mouse knee development (embryonic day 13.5), NFATc1-expressing cells were mainly located in the flanking region of the joint interzone. With development, NFATc1-expressing cells generated almost all articular chondrocytes, but not chondrocytes in limb growth-plate primordium. NFATc1-expressing cells displayed prominent capacities for colony formation and multipotent differentiation. Transcriptome analyses revealed a set of characteristic genes in NFATc1-enriched articular cartilage progenitors. Strikingly, the expression of NFATc1 was diminished with articular chondrocyte differentiation, and suppressing NFATc1 expression in articular cartilage progenitors was sufficient to induce spontaneous chondrogenesis while overexpressing NFATc1 suppresses chondrogenesis. Mechanistically, NFATc1 negatively regulated the transcriptional activity of the Col2a1 gene. Thus, our results reveal that NFATc1 characterizes articular, but not growth-plate, cartilage progenitors and negatively determines articular chondrocyte differentiation at least partly through regulating COL2A1 gene transcription.

developmental biology↗

bioRxiv2022

Optical Modulation of Blood-Brain-Tumor Barrier Permeability Enhances Drug Delivery in Diverse Preclinical Glioblastoma Models

Glioblastoma multiforme (GBM) is the most prevalent malignant tumor in the central nervous system. It has diverse phenotypes, including diffuse single-cell infiltration in which the tumor cells co-opt the normal microvasculature, and the neovascularization of an expanding tumor mass. The blood-brain-tumor barrier (BBTB) is a significant obstacle to GBM treatment and restricts entry of most FDA-approved effective oncology drugs. Herein, we report that picosecond laser excitation of vascular-targeted plasmonic gold nanoparticles (AuNPs) can non-invasively and reversibly modulate the BBTB permeability (optoBBTB). OptoBBTB enhances the delivery of paclitaxel (Taxol) in two genetically engineered glioma models (GEMM) that span the spectrum of GBM phenotypes. OptoBBTB followed by Taxol delivery effectively suppresses tumor growth and prolongs the survival time of both GEMM. Moreover, our results raise the possibility that paclitaxel, which is amongst the most widely used oncology drugs because of its proven efficacy but has been abandoned for GBM following its failure to efficacy in early phase clinical trials due to poor blood-brain barrier (BBB) penetration, could now be reconsidered in combination with strategies to increase BBB permeability. In summary, optoBBTB is a novel and effective approach to increase the delivery of therapeutics with limited BBB permeability to treat neoplastic and non-neoplastic brain diseases.

bioengineering↗

bioRxiv2022

vsRNAfinder: a novel method for identifying high-confidence viral small RNAs from small RNA-Seq data

Virus-encoded small RNAs (vsRNA) have been reported to play an important role in viral infection. Unfortunately, there is still a lack of an effective method for vsRNA identification. Herein, we presented vsRNAfinder, a de novo method for identifying high-confidence vsRNAs from small RNA-Seq (sRNA-Seq) data based on peak calling and Poisson distribution and is public available at https://github.com/ZenaCai/vsRNAfinder. vsRNAfinder outperformed two widely-used methods namely miRDeep2 and ShortStack in identifying viral miRNAs with a significantly improved sensitivity. It can also be used to identify sRNAs in animals and plants with similar performance to miRDeep2 and ShortStack. The study would greatly facilitate effective identification of vsRNAs.

bioinformatics↗

bioRxiv2022

A preprocessing and functional connectivity analysis pipeline for mesoscale calcium imaging

To improve bench-to-bedside translation, it is integral that knowledge flow bidirectionally--from animal models to humans, and vice versa. This requires common analytical frameworks, as well as open software and data sharing practices. We share a new pipeline (and test dataset) for the preprocessing of wide-field optical fluorescence imaging data--an emerging mode applicable in animal models--as well as results from a functional connectivity and graph theory analysis inspired by recent work in the human neuroimaging field. The approach is demonstrated using a dataset comprised of two test-cases: (1) data from animals imaged during awake and anesthetized conditions with excitatory neurons labeled, and (2) data from awake animals with different genetically encoded fluorescent labels that target either excitatory neurons or inhibitory interneuron subtypes. Both seed-based connectivity and graph theory measures (global efficiency, transitivity, modularity, and characteristic path-length) are shown to be useful in quantifying differences between wakefulness states and cell populations. Wakefulness state and cell type show widespread effects on canonical network connectivity with variable frequency band dependence. Differences between excitatory neurons and inhibitory interneurons are observed, with somatostatin expressing inhibitory interneurons emerging as notably dissimilar from parvalbumin and vasoactive polypeptide expressing cells. In sum, we demonstrate that our pipeline can be used to examine brain state and cell-type differences in mesoscale imaging data, aiding translational neuroscience efforts. In line with open science practices, we freely release the pipeline and data to encourage other efforts in the community.

neuroscience↗