Biology subjects

Yang, B.

Publications and source records attributed to Yang, B..

At least 127 records · Page 7Linked to original sources

bioRxiv2024

Turnover of RNA-binding Proteins and MicroRNAs by intrinsically disordered region-directed ZSWIM8 ubiquitin ligase during brain development

Widely present in mammalian proteomes, intrinsically disordered regions (IDRs) in proteins play important biological functions by conferring structural flexibility and mediating biomolecular interactions. IDR-containing proteins, including many RNA-binding proteins (RBPs), are prone to misfolding and aggregation and must be constantly monitored. Here we show that the conserved ZSWIM8-type Cullin-RING ubiquitin ligase (CRLZSWIM8) is a master regulator of such proteins during brain development. ZSWIM8 selects its substrates via an IDR-dependent mechanism, and deletion of ZSWIM8 causes aberrant accumulation of numerous RBPs including AGO2 and ELAV1 in neonatal brains. Furthermore, AGO2 ubiquitination by ZSWIM8 is triggered by microRNA binding, leading to target-directed microRNA degradation (TDMD) of MiR7. Dysregulation of MiR7 in the absence of ZSWIM8 results in defects in oligodendrocyte maturation and functions. Together, our findings have demonstrated that, by utilizing variable target-recognition strategies, ZSWIM8 controls the abundance of conformationally flexible RBPs and miRNA metabolism that are essential for brain development. TeaserA conserved ubiquitin ligase controls the quality of disordered proteins to ensure brain development.

developmental biology↗

bioRxiv2024

CAT Bridge: an efficient toolkit for compound-transcript association mining from multi-omics data

BackgroundWith advancements in sequencing and mass spectrometry technologies, multi-omics data can now be easily acquired for understanding complex biological systems. Nevertheless, substantial challenges remain in determining the association between gene-metabolite pairs due to the non-linear and multifactorial interactions within cellular networks. The complexity arises from the interplay of multiple genes and metabolites, often involving feedback loops and time-dependent regulatory mechanisms that are not easily captured by traditional analysis methods. FindingsHere, we introduce Compounds And Transcripts Bridge (abbreviated as CAT Bridge, available at https://catbridge.work), a free user-friendly platform for longitudinal multi-omics analysis to efficiently identify transcripts associated with metabolites using time-series omics data. To evaluate the association of gene-metabolite pairs, CAT Bridge is a pioneering work benchmarking a set of statistical methods spanning causality estimation and correlation coefficient calculation for multi-omics analysis. Additionally, CAT Bridge features an artificial intelligence (AI) agent to assist users interpreting the association results. ConclusionsWe applied CAT Bridge to experimentally obtained Capsicum chinense (chili pepper) and public human and Escherichia coli (E. coli) time-series transcriptome and metabolome datasets. CAT Bridge successfully identified genes involved in the biosynthesis of capsaicin in C. chinense. Furthermore, case study results showed that the convergent cross mapping (CCM) method outperforms traditional approaches in longitudinal multi-omics analyses. CAT Bridge simplifies access to various established methods for longitudinal multi-omics analysis, and enables researchers to swiftly identify associated gene-metabolite pairs for further validation.

bioinformatics↗

bioRxiv2023

Identification of a Novel Ferroptosis Inducer with Dual Modulatory Effects on GPX4 Activity and Stability

Ferroptosis is a unique form of intracellular iron-dependent cell death that differs from apoptosis, necrosis, and autophagy. GPX4, an antioxidant defense enzyme, plays a pivotal role as regulator of ferroptosis. Extensive researches suggest that targeting GPX4 holds promise for cancer therapy. However, the current GPX4 inhibitors face challenges due to unfavorable drug-like properties, which hinder their progress in clinical development. In this study, we identified a novel inhibitor called MI-2, demonstrating potent ferroptosis-inducing capacity. Mechanistically, MI-2 effectively inhibits the activity of GPX4 by direct interaction. Furthermore, MI-2 promotes the degradation of GPX4 through its well-established target, MALT1. In multiple cancer models, MI-2 has demonstrated synergistic effects when combined with sorafenib or regorafenib, resulting in enhanced ferroptosis induction. These findings highlight the dual modulatory effects of MI-2 on GPX4 activity and stability, offering a promising starting point for the development of drug-like GPX4 inhibitors with translational potential.

cell biology↗

bioRxiv2023

Loss-of-function mutation in the polyamine transporter gene OsLAT5 as a selectable marker for genome editing

Genome editing by TALENs, CRISPR/Cas, base or prime editing have become routine tools. During stable plant transformation, the gene coding for the editing enzyme, e.g., Cas9, the guide RNAs (gRNAs), alongside a selectable marker are integrated into the nuclear genome. Identification of successful transformants relies on selectable or screenable markers, typically genes providing resistance to antibiotics or herbicides. Selectable markers use a substantial portion of the T-DNA, hence reducing transfer efficiency by limiting the effective number of TALENs or guide/pegRNAs that can be used in parallel. Moreover, marker genes are frequently subject to gene silencing. Here, we generated loss-of-function mutations in PUT/LAT-type polyamine transporter family genes to confer resistance to the phytotoxin methylviologen (MV) as a method for selection. As a proof of concept, CRISPR/Cas9 vectors with gRNAs were constructed to target three close homologs OsLAT1, OsLAT5, and OsLAT7. We show that loss of OsLAT5 (also known as OsPUT3 or OsPAR1) function was sufficient to confer resistance to MV in rice seeds, seedlings and calli, validating the editing approach of OsLAT5 to obtain a selectable marker. We discuss the potential of incorporating a gRNA cassette (for OsLAT5) as a selectable marker and a reporter for successful genome editing for optimizing editing protocols.

plant biology↗

bioRxiv2023

Prediction of DNA i-Motifs Via Machine Learning

i-Motifs (iMs), are secondary structures formed in cytosine-rich DNA sequences and are involved in multiple functions in the genome. Although putative iM forming sequences are widely distributed in the human genome, the folding status and strength of putative iMs vary dramatically. Much previous research on iM has focused on assessing the iM folding properties using biophysical experiments. However, there are no dedicated computational tools for predicting the folding status and strength of iM structures. Here, we introduce a machine learning pipeline, iM-Seeker, to predict both folding status and structural stability of DNA iMs. The programme iM-Seeker incorporates a Balanced Random Forest classifier trained on genome-wide iMab antibody-based CUT&Tag sequencing data to predict the folding status and an Extreme Gradient Boosting regressor to estimate the folding strength according to both literature biophysical data and our in-house biophysical experiments. iM-Seeker predicts DNA iM folding status with a classification accuracy of 81% and estimates the folding strength with coefficient of determination (R2) of 0.642 on the test set. Model interpretation confirms that the nucleotide composition of the C-rich sequence significantly affects iM stability, with a positive correlation with sequences containing cytosine and thymine and a negative correlation with guanine and adenine. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=140 SRC="FIGDIR/small/571121v1_ufig1.gif" ALT="Figure 1"> View larger version (31K): org.highwire.dtl.DTLVardef@11f4398org.highwire.dtl.DTLVardef@18eb7e9org.highwire.dtl.DTLVardef@cc49c6org.highwire.dtl.DTLVardef@1ff91a8_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

bioRxiv2023

Neuropeptide Signaling Is Required To Implement A Line Attractor Encoding A Persistent Internal Behavioral State

Internal states drive survival behaviors, but their neural implementation is not well understood. Recently we identified a line attractor in the ventromedial hypothalamus (VMH) that represents an internal state of aggressiveness. Line attractors can be implemented by recurrent connectivity and/or neuromodulatory signaling, but evidence for the latter is scant. Here we show that neuropeptidergic signaling is necessary for line attractor dynamics in this system, using a novel approach that integrates cell type-specific, anatomically restricted CRISPR/Cas9-based gene editing with microendoscopic calcium imaging. Co-disruption of receptors for oxytocin and vasopressin in adult VMH Esr1+ neurons that control aggression suppressed attack, reduced persistent neural activity and eliminated line attractor dynamics, while only modestly impacting neural activity and sex- or behavior-tuning. These data identify a requisite role for neuropeptidergic signaling in implementing a behaviorally relevant line attractor. Our approach should facilitate mechanistic studies in neuroscience that bridge different levels of biological function and abstraction.

neuroscience↗

bioRxiv2023

Microglia facilitate and stabilize the response to general anesthesia

General anesthesia leads to a loss of consciousness and an unarousable state in patients. Although general anesthetics are widely used in clinical practice, their underlying mechanisms remain elusive. The potential involvement of nonneuronal cells is unknown. Microglia are important immune cells in the central nervous system (CNS) that play critical roles in CNS function and dysfunction. We unintentionally observed delayed anesthesia induction and early anesthesia emergence in microglia-depleted mice. We found that microglial depletion differentially regulates neuronal activities by suppressing the neuronal network of anesthesia-activated brain regions and activating emergence-activated brain regions. Thus, microglia facilitate and stabilize the anesthesia status. This influence is not mediated by dendritic spine plasticity. Instead, it relies on the activation of microglial P2Y12 and subsequent calcium influx, which facilitates the general anesthesia response. Together, we elucidate the regulatory role of microglia in general anesthesia, extending our knowledge of how nonneuronal cells modulate neuronal activities.

neuroscience↗

bioRxiv2023

Harnessing the endogenous Type I-C CRISPR-Cas system for genome editing in Bifidobacterium breve

Bifidobacterium breve, one of the main bifidobacterial species colonizing the human gastrointestinal tract in early life, has received extensive attention for its purported beneficial effects on human health. However, exploration of the mode of action of such beneficial effects exerted by B. breve is cumbersome due to the lack of effective genetic tools, which limits its synthetic biology application. Given the widespread presence of endogenous CRISPR-Cas systems in B. breve, the current study developed an endogenous CRISPR-based gene editing toolkit for genetic manipulation of B. breve. Deletion of the gene coding uracil phosphoribosyl-transferase (upp) was achieved in two different B. breve strains using this system. In addition, translational termination of uracil phosphoribosyl-transferase was successfully achieved in B. breve FJSWX38M7 by single-base substitution of the upp gene and insertion of three stop codons. The gene encoding linoleic acid isomerase (bbi) in B. breve, being a characteristic trait, was deleted after plasmid curing, which rendered it unable to convert linoleic acid into conjugated linoleic acid, demonstrating the feasibility of successive editing. This study expanded the gene manipulation toolkit of B. breve and provides a reference for functional genome editing and analysis using an endogenous CRISPR-Cas system in Bifidobacterium. ImportanceThe lack of effective genetic tools for Bifidobacterium breve is an obstacle to studying the molecular mechanisms of its health-promoting effects, hindering the development of next-generation probiotics. Here, we introduce a gene editing method based on the endogenous CRISPR-Cas system, which can achieve gene deletion, single base substitution, gene insertion and continuous gene editing in B. breve. This study will promote the excavation of functional genes and elucidation of molecular mechanisms of B. breve.

molecular biology↗

bioRxiv2023

Gut microbial genomes with paired isolates from China signify probiotic and cardiometabolic effects

The gut microbiome displays significant genetic differences between populations while systematic characterization of the genomic landscape of the gut microbiome in Asia populations remains limited. Here, we present the Chinese gut microbial reference (CGMR) set, comprising 101,060 high quality metagenomic assembled genomes (MAGs) of 3,707 non-redundant species paired with 1,376 live isolates from a national wide collection of 3,234 fecal samples across China. This improved reference set contains 987 novel species compared with existing resources worldwide. By associating MAGs with geographic and phenotypic characteristics, we observed regional-specific coexisting MAGs and MAGs with probiotic and cardiometabolic functionalities. We further conducted mice experiments to confirm the probiotic effects of two Faecalibacterium intestinalis isolates in alleviating constipation, the cardiometabolic influences of three Bacteroides fragilis_A isolates in obesity, and the functional potential of isolates from the two new species belonging to the genera Parabacteroides and Lactobacillus in host lipids metabolism. Our study not only expands the current microbial genomes with paired isolates but also demonstrates their probiotic and cardiometabolic effects on hosts, contributing to the mechanistic understanding of host-microbe interactions and the translation of microbiome-based personalized therapies.

microbiology↗

bioRxiv2023

Engineering an artificial catch bond using mechanical anisotropy

Catch bonds are a rare class of protein-protein interactions where the bond lifetime increases under an external pulling force. Here, we report how modification of anchor geometry generates catch bonding behavior for the mechanostable Dockerin G:Cohesin E (DocG:CohE) adhesion complex found on human gut bacteria. Using AFM single-molecule force spectroscopy in combination with bioorthogonal click chemistry, we mechanically dissociated the complex using five precisely controlled anchor geometries. When tension was applied through residue #13 on CohE and the N-terminus of DocG, the complex behaved as a two-state catch bond, while in all other tested pulling geometries, including the native configuration, it behaved as a slip bond. We used a kinetic Monte Carlo model with experimentally derived parameters to simulate rupture force and lifetime distributions, achieving strong agreement with experiments. Single-molecule FRET measurements further demonstrated that the complex does not exhibit dual binding mode behavior at equilibrium but unbinds along multiple pathways under force. Together, these results show how mechanical anisotropy and anchor point selection can be used to engineer artificial catch bonds.

biophysics↗

bioRxiv2023

Olfactory learning in Drosophila requires O-GlcNAcylation of mushroom body ribosomal subunits

O-GlcNAcylation is a dynamic post-translational modification that diversifies the proteome. Its dysregulation is associated with neurological disorders that impair cognitive function, and yet identification of phenotype-relevant candidate substrates in a brain-region specific manner remains unfeasible. By combining an O-GlcNAc binding activity derived from Clostridium perfringens OGA (CpOGA) with TurboID proximity labeling in Drosophila, we developed an O-GlcNAcylation profiling tool that translates O-GlcNAc modification into biotin conjugation for tissue-specific candidate substrates enrichment. We mapped the O-GlcNAc interactome in major brain regions of Drosophila and found that components of the translational machinery, including many ribosomal subunits, were abundantly O-GlcNAcylated in the mushroom body, the computational center of the Drosophila brain. Hypo-O-GlcNAcylation induced by ectopic expression of active CpOGA in the mushroom body decreased local ribosomal activity, leading to olfactory learning deficits that could be rescued by increasing ribosome biogenesis. Our study reveals that O-GlcNAcylation contributes to the links between protein synthesis and cognitive function in the brain learning center, and provides a useful tool for future dissection of tissue-specific functions of O-GlcNAcylation in Drosophila.

cell biology↗

bioRxiv2023

Tree diversity increases forest temperature buffering

Global warming is increasing the frequency and intensity of climate extremes. Forests may buffer such extreme events by creating their own microclimate below their canopy via cooling hot and insulating against cold macroclimate air temperatures. This buffering capacity of forests may be increased by tree diversity and may itself maintain forest functioning and biodiversity. However, despite its relevance for many ecosystem processes, the effect of tree diversity on temperature buffering is largely unexplored. Here, we show that tree species richness consistently increases forest temperature buffering across daily, monthly, and annual scales over six years. This finding is based on data from a large-scale tree diversity experiment covering a species richness gradient of 1 to 24 tree species. We found that species richness strengthened both components of forest temperature buffering: the attenuation of hot and of cold macroclimate air temperatures, with the cooling effect being more pronounced. The buffering effect of tree species richness was mediated by canopy density and structural diversity, assessed as leaf area index and stand structural complexity index, respectively. Safeguarding and planting diverse forests may thus mitigate negative effects of global warming and climate extremes on ecosystem functions and communities below the tree canopy.

ecology↗

bioRxiv2023

SpaRx: Elucidate single-cell spatial heterogeneity of drug responses for personalized treatment

Spatial cellular heterogeneity contributes to differential drug responses in a tumor lesion and potential therapeutic resistance. Recent emerging spatial technologies such as CosMx SMI, MERSCOPE, and Xenium delineate the spatial gene expression patterns at the single cell resolution. This provides unprecedented opportunities to identify spatially localized cellular resistance and to optimize the treatment for individual patients. In this work, we present a graph-based domain adaptation model, SpaRx, to reveal the heterogeneity of spatial cellular response to drugs. SpaRx transfers the knowledge from pharmacogenomics profiles to single-cell spatial transcriptomics data, through hybrid learning with dynamic adversarial adaption. Comprehensive benchmarking demonstrates the superior and robust performance of SpaRx at different dropout rates, noise levels, and transcriptomics coverage. Further application of SpaRx to the state-of-art single-cell spatial transcriptomics data reveals that tumor cells in different locations of a tumor lesion present heterogenous sensitivity or resistance to drugs. Moreover, resistant tumor cells interact with themselves or the surrounding constituents to form an ecosystem for drug resistance. Collectively, SpaRx characterizes the spatial therapeutic variability, unveils the molecular mechanisms underpinning drug resistance, and identifies personalized drug targets and effective drug combinations. Key PointsO_LIWe have developed a novel graph-based domain adaption model named SpaRx, to reveal the heterogeneity of spatial cellular response to different types of drugs, which bridges the gap between pharmacogenomics knowledgebase and single-cell spatial transcriptomics data. C_LIO_LISpaRx is developed tailored for single-cell spatial transcriptomics data and is provided available as a ready-to-use open-source software, which demonstrates high accuracy and robust performance. C_LIO_LISpaRx uncovers that tumor cells located in different areas within tumor lesion exhibit varying levels of sensitivity or resistance to drugs. Moreover, SpaRx reveals that tumor cells interact with themselves and the surrounding microenvironment to form an ecosystem capable of drug resistance. C_LI

bioinformatics↗

bioRxiv2023

Well-ST-seq: cost-effective spatial transcriptomics at cellular level and high RNA capture efficiency

Spatial transcriptomic technologies are promising tools to reveal fine anatomical profiles of tissues. As for the methodologies based on barcoded probe arrays, improving the balance among probe barcoding complexity and cost, gene capture sensitivity, and spatial resolution can accelerate the spreading of spatial transcriptomic in basic science and clinical work. Here, based on miniaturized microfluidic and microarray technologies, we constructed a spatially cellular-level RNA-capture probe arrays. Owing to the predetermined and cost-effective probe fixation characteristics of the methodology, the consumable cost and fabrication time of the probe array can be reduced to $1.21/mm2 and approximately 2 hours, and the preparation process does not rely on large precision instruments. Moreover, the efficiency of the transcript captured by the probe array is even comparable to conventional single-cell RNA sequencing. Based on this technology, we achieved the spatial transcriptome expression mapping and gained insight into spatial cell heterogeneity of the mouse hippocampus.

genomics↗

bioRxiv2023

Eye Blinks as a Visual Processing Stage

Humans blink their eyes frequently during normal viewing, more often than it seems necessary for keeping the cornea well lubricated. Since the closure of the eyelid disrupts the image on the retina, eye blinks are commonly assumed to be detrimental to visual processing. However, blinks also provide luminance modulations rich in spatial information to neural pathways highly sensitive to temporal changes. Here we report that the luminance transients from blinks enhance visual sensitivity. By coupling high-resolution eye-tracking in human observers with modeling of blink transients and spectral analysis of visual input signals, we show that blinking increases the power of retinal stimulation and that this effect significantly enhances visibility despite the time lost in exposure to the external scene. We further show that, as predicted from the spectral content of input signals, this enhancement is selective for stimuli at low spatial frequencies and occurs irrespective of whether the luminance transients are actively generated or passively experienced. These findings indicate that, like eye movements, blinking acts as a computational tool in a visual processing strategy that uses motor behavior to reformat spatial information in the temporal domain.

neuroscience↗

bioRxiv2023

Building a genetic and epigenetic predictive model of breast cancer intrinsic subtypes using large-scale data and hierarchical structure learning

Breast cancer subtyping is a difficult clinical and scientific challenge. The prevalent Prediction Analysis of Microarray of 50 genes (PAM50) system and its Immunohistochemistry (IHC) surrogate showed significant inconsistencies. This is because of the limited training samples, highly variable molecular features and in-efficient strategies used in these classifiers. The rapid development of early screening technologies, especially in the field of circulating tumor DNA, has also challenged the subtyping of breast cancer at the DNA level. By integrating large-scale DNA-level data and using a hierarchical structure learning algorithm, we developed Unified Genetic and Epigenetic Subtyping (UGES), a new intrinsic subtype classifier. The benchmarks showed that the use of all classes of DNA alterations worked much better than single classes, and that the multi-step hierarchical learning is crucial, which improves the overall AUC score by 0.074 compared to the one-step multi-classification method. Based on these insights, the ultimate UGES was trained as a three-step classifier on 50831 DNA features of 2065 samples, including mutations, copy number aberrations, and methylations. UGES achieved overall AUC score 0.963, and greatly improved the clinical stratification of patients, as each stratas survival difference became statistically more significant p-value=9.7e-55 (UGES) vs 2.2e-47 (PAM50). Finally, UGES identified 52 subtype-level DNA biomarkers that can be targeted in early screening technology to significantly expand the time window for precision care. The analysis code is freely available at https://github.com/labxscut/UGES.

bioinformatics↗

bioRxiv2023

Identifying gastric cancer molecular subtypes by integrating DNA-based hierarchical classification strategy and clinical stratification

BackgroundMolecular subtyping has been introduced to better understand the genetic landscape of gastric cancer (GC), but current subtyping methods only had limited success because of the mixed use of molecular features, a lack of strategy optimization, and the limited availability of GC samples. The community urgently calls for a precise, and easily adoptable subtyping method to enable DNA-based early screening and treatment. MethodsBased on TCGA subtypes, we developed a novel classifier, termed Hierarchical DNA-based Classifier for Gastric Cancer Molecular Subtyping (HCG), leveraging all DNA-level alterations as predictors, including gene mutations, copy number aberrations and methylations. By adding the closely related esophageal adenocarcinomas (EA) dataset, we expanded the TCGA GC dataset for training and testing HCG (n=453). We optimized HCG with three hierarchical strategies evaluated by their overall accuracy using Lasso-Logistic regression, and by their clinical stratification capacity using multivariate survival analysis. We used difference tests to identify subtype-specific DNA alteration biomarkers based on HCG defined subtypes. ResultsOur HCG classifier achieved an overall AUC score of 0.95 and significantly improved the clinical stratification of patients (overall p-value=0.032). 25 subtype-specific DNA alterations were identified by difference tests, including high level of mutations in SYNE1, ITGB4 and COL22A1 genes for the MSI subtype, high level of methylations of ALS2CL, KIAA0406 and RPRD1B genes for the EBV subtype. ConclusionsHCG is an accurate and robust classifier for DNA-based GC molecular subtyping with high-performing clinical stratification capacity. The training and test datasets and analysis programs of HCG are available at https://github.com/labxscut/HCG.

bioinformatics↗

bioRxiv2023

Lipid-anchored Proteasomes Control Membrane Protein Homeostasis

Protein degradation in eukaryotic cells is mainly carried out by the 26S proteasome, a macromolecular complex not only present in the cytosol and nucleus but also associated with various membranes. How proteasomes are anchored to the membrane and the biological meaning thereof have been largely unknown in higher organisms. Here we show that N-myristoylation of the Rpt2 subunit is a general mechanism for proteasome-membrane interaction. Loss of this modification in the Rpt2-G2A mutant cells leads to profound changes in the membrane-associated proteome, perturbs the endomembrane system and undermines critical cellular processes such as cell adhesion, endoplasmic reticulum-associated degradation (ERAD) and membrane protein trafficking. Rpt2G2A/G2A homozygous mutation is embryonic lethal in mice and is sufficient to abolish tumor growth in a nude mice xenograft model. These findings have defined an evolutionarily conserved mechanism for maintaining membrane protein homeostasis and underscored the significance of compartmentalized protein degradation by myristoyl-anchored proteasomes (MAPs) in health and disease.

biochemistry↗