Biology subjects

Wu, X.

Publications and source records attributed to Wu, X..

At least 415 records · Page 23Linked to original sources

bioRxiv2022

Optimization and deoptimization of codons in SARS-CoV-2 and the implications for vaccine development

The spread of Coronavirus Disease 2019 (COVID-19), caused by the SARS-CoV-2 coronavirus, has progressed into a global pandemic. To date, thousands of genetic variants have been identified across SARS-CoV-2 isolates from patients. Sequence analysis reveals that the codon usage of viral sequences decreased over time but fluctuated from time to time. In this study, through evolution modeling, we found that this phenomenon might result from the virus preference for mutations during transmission. Using dual luciferase assays, we further discovered that the deoptimization of codons on viruses might weaken protein expression during the virus evolution, indicating that the choice of codon usage might play important role in virus fitness. Finally, given the importance of codon usage in protein expression and particularly for mRNA vaccine, we designed several omicron BA.2.12.1 and BA.4/5 spike mRNA vaccine candidates based on codon optimization, and experimentally validated their high levels of expression. Our study highlights the importance of codon usage in virus evolution and mRNA vaccine development.

evolutionary biology↗

bioRxiv2022

Structural basis for intrinsic transcription termination

Efficient and accurate termination is required for gene transcription in all living organisms. Cellular RNA polymerases (RNAP) in both bacteria and eukaryotes can terminate their transcription through a factor-independent termination pathway (called intrinsic termination transcription in bacteria), in which RNAP recognizes terminator sequences, stops nucleotide addition, and releases nascent RNA spontaneously. Here we report a set of single-particle cryo-EM structures of E. coli transcription intrinsic termination complexes representing key intermediate states of the event. The structures show how RNAP pauses at terminator sequences, how the terminator RNA hairpin folds inside RNAP, and how RNAP rewinds the transcription bubble to release RNA and then DNA. These macromolecular snapshots define a structural mechanism for bacterial intrinsic termination and a pathway for RNA release and DNA collapse relevant for factor-independent termination by all RNA polymerases.

molecular biology↗

bioRxiv2022

A view of the pan-genome of domesticated cowpea (Vigna unguiculata Walp.)

Cowpea, Vigna unguiculata L. Walp., is a diploid warm-season legume of critical importance as both food and fodder in sub-Saharan Africa. This species is also grown in Northern Africa, Europe, Latin America, North America, and East to Southeast Asia. To capture the genomic diversity of domesticates of this important legume, de novo genome assemblies were produced for representatives of six sub-populations of cultivated cowpea identified previously from genotyping of several hundred diverse accessions. In the most complete assembly (IT97K-499-35), 26,026 core and 4,963 noncore genes were identified, with 35,436 pan genes when considering all seven accessions. GO-terms associated with response to stress and defense response were highly enriched among the noncore genes, while core genes were enriched in terms related to transcription factor activity, and transport and metabolic processes. Over 5 million SNPs relative to each assembly and over 40 structural variants >1 Mb in size were identified by comparing genomes. Vu10 was the chromosome with the highest frequency of SNPs, and Vu04 had the most structural variants. Noncore genes harbor a larger proportion of potentially disruptive variants than core genes, including missense, stop gain, and frameshift mutations; this suggests that noncore genes substantially contribute to diversity within domesticated cowpea. Article SummaryThis study reports annotated genome assemblies of six cowpea accessions. Together with the previously reported annotated genome of IT97K-499-35, these constitute a pan-genome resource representing six subpopulations of domesticated cowpea. Annotations include genes, variant calls for SNPs and short indels, larger presence or absence variants, and inversions. Noncore genes are enriched for loci involved in stress response and harbor many genic variants with potential effects on coding sequence.

genomics↗

bioRxiv2022

The effector recognition by synthetic sensor NLR receptors requires the concerted action of multiple interfaces within and outside the integrated domain

Plant sensor nucleotide-binding leucine-rich repeat (NLR) receptors detect pathogen effectors through their integrated domains (IDs). The RGA5 sensor NLR recognizes its corresponding effectors AVR-Pia and AVR1-CO39 from the blast fungus Magnaporthe oryzae through direct binding to its heavy metal-associated (HMA) ID to trigger the RGA4 helper NLR-dependent resistance in rice. Here we report a mutant of RGA5 named RGA5HMA5 that confers complete resistance in transgenic rice plants to the M. oryzae strains expressing the noncorresponding effector AVR-PikD. RGA5HMA5 carries three engineered interfaces, two of which lie in the HMA ID and the other in the C-terminal Lys-rich stretch tailing the ID. However, the RGA5 variants having one or two of the three interfaces, including replacing all the Lys residues with Glu residues in the Lys-rich stretch, failed to activate RGA4-dependent cell death of rice protoplasts. Altogether, this work demonstrates that sensor NLRs require a concerted action of multiple surfaces within and outside the IDs to both recognize noncorresponding effectors and activate helper NLR-mediated resistance, and has implications in structure-guided designing of sensor NLRs.

plant biology↗

bioRxiv2022

Distinct encoding and post-encoding representational formats contribute to episodic sequence memory formation

In episodic encoding, an unfolding experience is rapidly transformed into a memory representation that binds separate episodic elements into a memory form to be later recollected. However, it is unclear how brain activity changes over time to accommodate the encoding of incoming information. This study aimed to investigate the dynamics of the representational format that contributed to memory formation of sequential episodes. We combined Representational Similarity Analysis and multivariate decoding approaches on EEG data to compare whether "category-level" or "item-level" representations supported memory formation during the online encoding of a picture triplet sequence and offline, in the period that immediately followed encoding. The findings revealed a gradual integration of category-level representation during the online encoding of the picture sequence and a rapid item-based neural reactivation of the encoded sequence at the episodic offset. However, we found that only memory reinstatement at episodic offset was associated with successful memory retrieval from long term memory. These results suggest that post-encoding memory reinstatement is crucial for the rapid formation of unique memory for episodes that unfold over time. Overall, the study sheds light on the dynamics of representational format changes that take place during the formation of episodic memories.

neuroscience↗

bioRxiv2022

Tumor landscape of epithelial ovarian cancer highlights that EGR1 drives tumor invasion at single-cell resolution

Identifying underlying molecular mechanisms and biomarkers of epithelial ovarian carcinoma (EOC) proliferation and metastasis remains challenging. Patients of EOC are usually diagnosed at an advanced stage and the availability of invasion-related targets is limited. Herein, we explored the single-cell RNA sequencing (scRNA-seq) dataset of EOC and defined tumor physiological reprograming compared to bulk RNA-seq. The energy metabolism and anti-apoptotic pathway was found as critical contributors to intratumor heterogeneity. Moreover, hypoxia, oxidative phosphorylation (OXPHOS) and glycolysis were positively correlated, which have biologically activity trajectories during epithelial mesenchymal transition (EMT). The HMGH1, EGR1 and RUNX1 were found to be critical inducers of the EMT process in EOC. Experimental validation revealed that suppressed EGR1 decreased the expression of FAS and HSPG2 and associating with EMT progression in EOC. In tumor microenvironment (TME), CAFs were found have significant contribution to tumor immune infiltration and metastasis and accumulation of CAFs was associated with poorer patient survival. In conclusion, physiological features and molecular mechanisms in the TME of EOC were revealed and provided effective targets for the suppression of tumor metastasis.

bioinformatics↗

bioRxiv2022

Contextual incongruency triggers memory reinstatement and the disruption of neural stability

Schemas, or internal representation models of the environment, are thought to be central in organising our everyday life behaviour by giving stability and predictiveness to the structure of the world. However, when an element from an unfolding event mismatches the schema-derived expectations, the coherent narrative is interrupted and an update to the current event model representation is required. Here, we asked whether the perceived incongruence of an item from an unfolding event and its impact on memory relied on the disruption of neural stability patterns preceded by the neural reactivation of the memory representations of the just-encoded event. Our study includes data from 3 different experiments whereby participants encoded images of target objects preceded by trial-unique sequences of events depicting daily routine. We found that neural stability patterns gradually increased throughout the ongoing exposure to a schema-consistent episodic narrative and that the brain stability pattern was interrupted when the encoding of an object of the event was lowly congruent within the ongoing schema representation. We found that the decrease in neural stability for low-congruence items was best seen at [~]1000 ms from object encoding onset when compared to high-congruence items and that this effect was preceded by an enhanced N400 ERP and an increased degree of neural reactivation of the just-encoded episode for low-congruence items. Current results offer new insights into the neural mechanisms and their temporal orchestration that are engaged during online encoding of schema-consistent episodic narratives and the detection of incongruencies.

neuroscience↗

bioRxiv2022

In vivo functional genomics identifies essentiality of potassium homeostasis in medulloblastoma

The identification of cancer maintenance genes--driver genes essential to tumor survival--is fundamental for developing effective cancer therapy. Transposon-based insertional mutagenesis screens can identify cancer driver genes broadly but not discriminate maintenance from progression or initiation drivers, which contribute to cancer phenotypes and tumorigenesis, respectively. We engineered a nested, double-jumping transposon system to first dysregulate gene expression during tumorigenesis and then restore gene expression following tumor induction, allowing for genome-wide screening of maintenance essentiality in vivo. In a mouse model of medulloblastoma, the most common pediatric malignancy, insertion and remobilization of this nested transposon uncovers potassium channel genes as recurrent maintenance drivers. In human medulloblastoma, KCNB2 is the most overexpressed potassium channel across Group 3, Group 4, and SHH subgroups, and Kcnb2 knockout in mice diminishes the replicative potential of medulloblastoma-propagating cells to mitigate tumor growth. Kcnb2 governs potassium homeostasis to regulate plasma membrane tension-gated EGFR signaling, which drives proliferative expansion of medulloblastoma-propagating cells. Thus, our novel transposon system reveals potassium homeostasis as essential to tumor maintenance through biomechanical modulation of membrane signaling.

cancer biology↗

bioRxiv2022

A unified model for the surveillance of translation in diverse noncoding sequences

Translation is pervasive outside of canonical coding regions, occurring in lncRNAs, UTRs, and introns. While the resulting polypeptides are often non-functional, translation in noncoding regions is nonetheless necessary for the birth of new coding regions. The mechanisms underlying the surveillance of translation in diverse noncoding regions and how escaped polypeptides evolve new functions remain unclear. Intriguingly, noncoding sequence-derived functional peptides often localize to membranes. Here, we show that the intrinsic nucleotide bias in the noncoding genome and in the genetic code frequently results in polypeptides with a hydrophobic C-terminal tail, which is captured by the ribosome-associated BAG6 membrane protein triage complex for either proteasomal degradation or membrane targeting. In contrast, canonical proteins have evolved to deplete C-terminal hydrophobic residues. Our results uncovered a fail-safe mechanism for the surveillance of unwanted translation from diverse noncoding regions and suggest a possible biochemical route for the preferential membrane localization of newly evolved proteins. HighlightsO_LITranslation in diverse noncoding regions is mitigated by proteasomal degradation C_LIO_LIC-terminal hydrophobicity is a hallmark of noncoding sequence derived polypeptides C_LIO_LIA genome-wide CRISPR screen identified the BAG6 membrane protein triage pathway C_LIO_LIRibosome-associated BAG6 complex targets C-terminal hydrophobicity for degradation C_LI

molecular biology↗

bioRxiv2022

stAPAminer: Mining Spatial Patterns of Alternative Polyadenylation for Spatially Resolved Transcriptomic Studies

Alternative polyadenylation (APA) contributes to transcriptome complexity and gene expression regulation, which has been implicated in various cellular processes and diseases. Single-cell RNA-seq (scRNA-seq) has led to the profile of APA at the single-cell level, however, the spatial information of cells is not preserved in scRNA-seq. Alternatively, spatial transcriptomics (ST) technologies provide opportunities to decipher the spatial context of the transcriptomic landscape within single cells and/or across tissue sections. Pioneering studies on ST have unveiled potential spatially variable genes and/or splice isoforms, however, the pattern of APA usages in spatial contexts remains unappreciated. Here, we developed a toolkit called stAPAminer for mining spatial patterns of APA from spatial barcoded ST data. APA sites were identified and quantified from the ST data. Particularly, an imputation model based on K-nearest neighbors algorithm was designed for recovering APA signals. Then APA genes with spatial patterns of APA usage variation were identified. By analyzing the well-established ST data of mouse olfactory bulb (MOB), we present a detailed view of spatial APA usage across morphological layers of MOB with stAPAminer. We complied a comprehensive list of genes with spatial APA dynamics and obtained several major spatial expression patterns representing spatial APA dynamics in different morphological layers. Extending this analysis to two additional replicates of the MOB ST data, we found that spatial APA patterns of many genes are reproducible among replicates. stAPAminer employs the power of ST for exploring transcriptional atlas of spatial APA patterns with spatial resolution, which is available at https://github.com/BMILAB/stAPAminer.

bioinformatics↗

bioRxiv2022

Prior-guided Individualized Thalamic Parcellation based on Local Diffusion Characteristics using Deep Learning

As a gateway for projections entering and exiting the cerebral cortex, the human thalamus processes information from sensory to cognition relevant to various neuropsychiatric disorders. It is composed of dozens of nuclei, which have been difficult to identify with clinical MR sequences. However, delineating thalamic nuclei accurately at an individual level is essential for precise neuromodulation treatment. Here, we not only identified the fine-grained thalamic nuclei using local diffusion properties in vivo but also employed a deep learning strategy to achieve highly reproducible individual-level parcellation. Using High-quality diffusion MRI (dMRI), we first constructed a fine-grained group thalamus atlas based on thalamic local diffusion features. Then, the high-probability core area of the group thalamus atlas was wrapped into the native space as prior guidance for individualized thalamus construction. Finally, we trained the semi-supervised multiple classification models to accurately construct the individualized thalamus atlas with single-subject local diffusion characteristics. Compared to group atlas registration and single-subject clustering strategies, our individualized thalamus atlas combines population commonality and individual specificity and is superior in depicting the individual thalamic nuclei boundaries. Besides, our atlas provides a more conspicuous capacity to capture the individual specificity of thalamic nuclei. Through the evaluation by 3.0T\7.0T and test-retest dMRI datasets, the proposed high-probability group prior guided individualized thalamus construction pipeline is robust and repeatable in different magnetic field strengths and scanning batches. In addition, the individual parcellation of the thalamic nuclei has a good correspondence with the histological atlas and captured both higher group consistency and inter-subjects variations, which could be a valuable solution for precision clinical treatment.

neuroscience↗

bioRxiv2022

A Survey on Methods for Predicting Polyadenylation Sites from DNA Sequences, Bulk RNA-seq, and Single-cell RNA-seq

Alternative polyadenylation (APA) plays important roles in modulating mRNA stability, translation, and subcellular localization, and contributes extensively to shaping eukaryotic transcriptome complexity and proteome diversity. Identification of poly(A) sites (pAs) on a genome-wide scale is a critical step toward understanding the underlying mechanism of APA-mediated gene regulation. A number of established computational tools have been proposed to predict pAs from diverse genomic data. Here we provided an exhaustive overview of computational approaches for predicting pAs from DNA sequences, bulk RNA-seq data, and single-cell RNA-seq (scRNA-seq) data. Particularly, we examined several representative tools using RNA-seq and scRNA-seq data from peripheral blood mononuclear cells and put forward operable suggestions on how to assess the reliability of pAs predicted by different tools. We also proposed practical guidelines on choosing appropriate methods applicable to diverse scenarios. Moreover, we discussed in depth the challenges in improving the performance of pA prediction and benchmarking different methods. Additionally, we highlighted outstanding challenges and opportunities using new machine learning and integrative multi-omics techniques and provided our perspective on how computational methodologies might evolve in the future for non-3 UTR, tissue-specific, cross-species, and single-cell pA prediction.

bioinformatics↗

bioRxiv2022

Metformin Alleviates Arthrofibrosis in Rat via Fibroblast Metabolic Reprogramming and Lactate-Mediated Macrophage Polarization

BackgroundEmerging studies have suggested an essential role of fibroblast metabolic reprogramming in the pathogenesis of arthrofibrosis. The metabolic modulator metformin appears to be a therapeutic candidate for fibrotic disorders. However, whether metformin could alleviate arthrofibrosis has not been defined. In this study we have determined if treatment with metformin has the beneficial effect on arthrofibrosis and its underlying mechanism. MethodsArticular capsule samples were collected from patients with/without arthrofibrosis to perform gene and protein expression analysis. Arthrofibrosis animal model was established to examine the anti-fibrotic effect of metformin. Cell culture experiments were conducted to determine the mechanism by which metformin inhibits fibroblast activation. ResultsWe found that glycolysis was upregulated in human fibrotic articular capsules. In an arthrofibrosis animal model, intra-articular injection of metformin mitigated inflammatory reactions, downregulated expression of both fibrotic and glycolytic markers, improved range of motion of the joint, and reduced capsular fibrosis and thickening. At the cellular level, metformin inhibited the activation of fibroblasts and mitigated the abundant influx of glucose into activated fibroblasts. Interestingly, metformin prompted a metabolic shift from oxidative phosphorylation to aerobic glycolysis in activated fibroblasts, resulting in the anti-fibrotic effect of metformin. ConclusionMetformin decreased glycolysis, causing a metabolic shift toward aerobic glycolysis in activated fibroblasts and has beneficial effect on the treatment of arthrofibrosis. The translational potential of this articleThe finding of this study demonstrated the therapeutic effect of metformin on arthrofibrosis and defined novel targets for the treatment of articular fibrotic disorders.

cell biology↗

bioRxiv2022

HCP5 prevents ubiquitination-mediated UTP3 degradation to inhibit apoptosis by activating c-Myc transcriptional activity

Inducing cancer cell apoptosis through cytotoxic reagents is the main therapeutic strategy for diverse cancer types. However, several antiapoptotic factors impede curative cancer therapy by driving cancer cells to resist cytotoxic agent-induced apoptosis, thus leading to refractoriness and relapse. To define critical antiapoptotic factors that contribute to chemoresistance in esophageal squamous cell carcinoma (ESCC), we generated two pairs of parental and apoptosis-resistant cell models through cisplatin (DDP) induction and then performed whole-transcriptome sequencing. We identified the long noncoding RNA (lncRNA) histocompatibility leukocyte antigen complex P5 (HCP5) as the chief culprit for chemoresistance. Mechanistically, HCP5 interacts with UTP3 small subunit processome component (UTP3) and prevents UTP3 degradation from E3 ligase tripartite motif containing 29 (TRIM29)-mediated ubiquitination. UTP3 then recruits c-Myc to activate vesicle-associated membrane protein 3 (VAMP3) expression. Activated VAMP3 suppresses caspase-dependent apoptosis and eventually leads to chemoresistance. Accordingly, the expression level of the HCP5/UTP3/c-Myc/VAMP3 axis in chemoresistant patients is significantly higher than that in chemosensitive patients. Thus, our study demonstrated that the HCP5/UTP3/c-Myc/VAMP3 axis plays an important role in the inhibition of cancer cell apoptosis and that HCP5 can be a promising chemosensitive target for cancer treatment.

cancer biology↗

bioRxiv2022

SARS-CoV-2 S protein antagonizes type I interferon downstream signal pathway through interacting and attenuating phosphorylation of STAT1/STAT2

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) may keep patients in a clinically asymptomatic state by blocking cellular innate antiviral immunity, but the molecular mechanism remains unclear. Here, we screened the viral proteins of SARS-CoV-2 and found that the spike (S) protein inhibits the activation of interferon-stimulated genes (ISGs) and even reduces the expression of these genes to below background values. Mechanistically, the S protein interacted with STAT1, STAT2, and IRF9 and impedes the phosphorylation of STAT1/STAT2, thus preventing the formation of the interferon-stimulating gene factor 3 (ISGF3) complex and inhibiting the downstream production of Interferon-stimulated genes (ISGs). Remarkably, we also have found that the inhibitory mechanism of the S protein was conservative among SARS-CoV-2 variants and other human coronaviruses, including SARS-CoV, MERS-CoV, HCoV-229E, HCoV-NL63, and HCoV-HKU1. Truncation studies indicated that the most conserved S2 domain played a major inhibitory role. Altogether, our findings unveil a new mechanism by which SARS-CoV-2 S protein attenuated the hosts antiviral immune response and provide new insights into the pathogenic mechanism of coronavirus.

microbiology↗

bioRxiv2022

Development and Application of a Novel Simple Sequence Repeat Mining Algorithm Based on Regular Expression

Simple sequence repeats (SSRs) are molecular genetic markers that are powerful tools in genomics studies; SSR markers are routinely mined as a part of genetic workflows. Here, we developed a novel SSR mining algorithm based on regular expression that can reduce the complexity of commonly used SSR mining software. We used the following SSR mining regular expression: ({i, j}?) (\1) {k}, where i and j denote the minimum and maximum lengths of the motifs of the SSR sequence, respectively, and k is the minimum number of repeat motifs. From this SSR mining algorithm, we developed an SSR sequence analysis software (named "regexSSRw") that is capable of mining eligible SSR loci from FASTA format sequences; regexSSRw can be accessed at https://github.com/renm79/rgxSSRw. This SSR mining algorithm can aid a range of applications, from being used by programmers in the development of SSR mining software to being implemented by scholars into their SSR marker workflow.

bioinformatics↗

bioRxiv2022

Discovery of a new class of reversible TEA-domain transcription factor inhibitors with a novel binding mode

The TEA domain (TEAD) transcription factor forms a transcription co-activation complex with the key downstream effector of the Hippo pathway, YAP/TAZ. TEAD-YAP controls the expression of Hippo-responsive genes involved in cell proliferation, development, and tumorigenesis. Hyperactivation of TEAD-YAP activities is observed in many human cancers, and is associated with cancer cell proliferation, survival and immune evasion. Therefore, targeting the TEAD-YAP complex has emerged as an attractive therapeutic approach. We previously reported that the mammalian TEAD transcription factors (TEAD1-4) possess auto-palmitoylation activities and contain an evolutionarily conserved palmitate-binding pocket (PBP), which allows small molecule modulation. Since then, several reversible and irreversible inhibitors have been reported by binding to PBP. Here, we report a new class of TEAD inhibitors with a novel binding mode. Representative analog TM2 shows potent inhibition of TEAD auto-palmitoylation both in vitro and in cells. Surprisingly, the co-crystal structure of the human TEAD2 YAP-binding domain (YBD) in complex with TM2 reveals that TM2 adopts an unexpected binding mode by occupying not only the hydrophobic PBP, but also a new side binding pocket formed by hydrophilic residues. RNA-seq analysis shows that TM2 potently and specifically suppresses TEAD-YAP transcriptional activities. Consistently, TM2 exhibits strong anti-proliferation effects as a single agent or in combination with a MEK inhibitor in YAP-dependent cancer cells. These findings establish TM2 as a promising small molecule inhibitor against TEAD-YAP activities and provide new insights for designing novel TEAD inhibitors with enhanced selectivity and potency.

biochemistry↗

bioRxiv2022

Single-cell Ca2+ parameter inference reveals how transcriptional states inform dynamic cell fates

Single-cell genomic technologies offer vast new resources with which to study cells, but their potential to inform parameter inference of cell dynamics has yet to be fully realized. Here we develop methods for Bayesian parameter inference with data that jointly measure gene expression and Ca2+ dynamics in single cells. We propose to share information between cells via transfer learning: for a sequence of cells, the posterior distribution of one cell is used to inform the prior distribution of the next. In application to intracellular Ca2+ signaling dynamics, we fit the parameters of a dynamical model for thousands of cells with variable single-cell responses. We show that transfer learning accelerates inference with sequences of cells regardless of how the cells are ordered. However, only by ordering cells based on their transcriptional similarity can we distinguish Ca2+ dynamic profiles and associated marker genes from the posterior distributions. Inference results reveal complex and competing sources of cell heterogeneity: parameter covariation can diverge between the intracellular and intercellular contexts. Overall, we discuss the extent to which single-cell parameter inference informed by transcriptional similarity can quantify relationships between gene expression states and signaling dynamics in single cells.

systems biology↗