Biology subjects

Qi, Y.

Publications and source records attributed to Qi, Y..

At least 91 records · Page 5Linked to original sources

bioRxiv2024

Human Motor Cortex Encodes Complex Handwriting Through a Sequence of Primitive Neural States

How the human motor cortex (MC) orchestrates sophisticated fine movements such as handwriting remains a puzzle1-3. Here, we investigate this question through Utah array recordings from human MC hand knob, during imagined handwriting of Chinese characters (306 characters tested, 6.3 {+/-} 2.0 strokes per character). We find MC programs the writing of complicated characters by sequencing a small set of primitive states: The directional tuning of motor neurons remains stable within each primitive state but strongly varies across states. Furthermore, the occurrence of a primitive state is encoded by a separate set of neurons not directly involved in movement control. By automatically identifying the primitive states and corresponding neuronal tuning properties, we can reconstruct a recognizable writing trajectory for each character (84% improvement in reconstruction accuracy compared with baseline). Our findings unveil that skilled, sophisticated movements are decomposed into a sequence of primitive movements that are programmed through state-specific neural configurations, and this hierarchical control mechanism sheds new light on the design of high-performance brain-computer interfaces.

neuroscience↗

bioRxiv2024

BERTE：High-precision hierarchical classification of transposable elements by a transfer learning method with BERT pre-trained model and convolutional neural network

Transposable Elements (TEs) are abundant repeat sequences found in living organisms. They play a pivotal role in biological evolution and gene regulation and are intimately linked to human diseases. Existing TE classification tools can classify classes, orders, and superfamilies concurrently, but they often struggle to effectively extract sequence features. This limitation frequently results in subpar classification results, especially in hierarchical classification. To tackle this problem, we introduced BERTE, a tool for TE hierarchical classification. BERTE encoded TE sequences into distinctive features that consisted of both attentional and cumulative k-mer frequency information. By leveraging the multi-head self-attention mechanism of the pre-trained BERT model, BERTE transformed sequences into attentional features. Additionally, we calculated multiple k-mer frequency vectors and concatenate them to form cumulative features. Following feature extraction, a parallel Convolutional Neural Network (CNN) model was employed as an efficient sequence classifier, capitalizing on its capability for high-dimensional feature transformation. We evaluated BERTEs performance on filtered datasets collected from 12 eukaryotic databases. Experimental results demonstrated that BERTE could improve the F1-score at different levels by up to 21% compared to current state-of-the-art methods. Furthermore, the results indicated that not only could BERT better characterize TE sequences in feature extraction, but also that CNN was more efficient than other popular deep learning classifiers. In general, BERTE classifies TE sequences with greater precision. BERTE is available at https://github.com/yiqichen-2000/BERTE.

bioinformatics↗

bioRxiv2024

Comprehensive Hierarchical Classification of Transposable Elements based on Deep Learning

Transposable elements (TEs) are DNA sequences capable of translocating within a genome. They constitute a substantial portion of eukaryotic genomes and play significant roles in genome evolution and gene regulation. The correct classification of these repetitive elements is essential to investigate their potential impact on genomes. Despite the existence of several tools for TE classification, they often neglect the importance of simultaneously utilizing global and local information for TE-type identification, resulting in suboptimal performance. Furthermore, these tools are not user-friendly due to the complex installation processes and numerous dependencies. In this study, we introduced a novel framework, CREATE, which leverages the strengths of Convolutional and Recurrent Neural NEtworks, combined with Attention mechanisms, for efficient TE classification. Given the tree-like structure of TE groups, we separately trained nine models within the class hierarchy. Benchmarking experiments showed that CREATE significantly outperformed other TE classification tools. The source code and demo data for CREATE are available at https://github.com/yangqi-cs/CREATE. To facilitate TE annotation for researchers, we have developed a web platform, named WebDLTE, based on the CREATE framework. This platform employs GPU-accelerated pre-trained deep learning models for real-time TE classification and offers the most comprehensive collection of TEs for download. The web interface can be accessed at https://www.webdlte.nwpu.edu.cn.

bioinformatics↗

bioRxiv2024

Critical analysis of polycyclic tetramate macrolactam biosynthetic cluster phylogeny and functional diversity

Polycyclic tetramate macrolactams (PTMs) are bioactive natural products commonly associated with certain actinobacterial and proteobacterial lineages. These molecules have been the subject of numerous structure-activity investigations since the 1970s. New members continue to be pursued in wild and engineered bacterial strains, and advances in PTM biosynthesis suggests their outwardly simplistic biosynthetic gene clusters (BGCs) belie unexpected product complexity. Towards addressing the origins of this complexity and understanding its influence on PTM discovery, we engaged in a combination of bioinformatics to systematically classify PTM BGCs, and PTM-targeted metabolomics to compare the products of select BGC types. By comparing groups of producers and BGC mutants, we exposed knowledge gaps that complicate bioinformatics-driven product predictions. In sum, we provide new insights into the evolution of PTM BGCs while systematically accounting for the PTMs discovered thus far. The combined computational and metabologenomic findings presented here should prove useful for guiding future discovery. IMPORTANCEPolycyclic tetramate macrolactam (PTM) pathways are frequently found within the genomes of biotechnologically-important bacteria, including Streptomyces and Lysobacter spp. Their molecular products are typically bioactive, having substantial agricultural and therapeutic interest. Leveraging bacterial genomics for the discovery of new related molecules is thus desirable, but drawing accurate structural predictions from bioinformatics alone remains challenging. This difficulty stems from a combination of previously underappreciated biosynthetic complexity and remaining knowledge gaps, compounded by a stream of yet-uncharacterized PTM biosynthetic loci gleaned from recently sequenced bacterial genomes. We engaged in the following study to create a useful framework for cataloging historic PTM clusters, identifying new cluster variations, and tracing evolutionary paths for these molecules. Our data suggests new PTM chemistry remains discoverable in nature. However, our metabolomic and mutational analyses emphasize practical limitations to genomics-based discovery by exposing hidden complexity.

microbiology↗

bioRxiv2024

Transcriptome Analysis Identifies An ASD-Like Phenotype In Oligodendrocytes And Microglia From C58/J Amygdala That Is Dependent On Sex and Sociability

BackgroundAutism Spectrum Disorder (ASD) is a group of neurodevelopmental disorders with higher incidence in males and is characterized by atypical verbal/nonverbal communication, restricted interests that can be accompanied by repetitive behavior, and disturbances in social behavior. This study investigated brain mechanisms that contribute to sociability deficits and sex differences in an ASD animal model. MethodsSociability was measured in C58/J and C57BL/6J mice using the 3-chamber social choice test. Bulk RNA-Seq and snRNA-Seq identified transcriptional changes in C58/J and C57BL/6J amygdala within which DMRseq was used to measure differentially methylated regions in amygdala. ResultsC58/J mice displayed divergent social strata in the 3-chamber test. Transcriptional and pathway signatures revealed immune-related biological processes differ between C58/J and C57BL/6J amygdala. Hypermethylated and hypomethylated genes were identified in C58/J versus C57BL/6J amygdala. snRNA-Seq data in C58/J amygdala identified differential transcriptional signatures within oligodendrocytes and microglia characterized by increased ASD risk gene expression and predicted impaired myelination that was dependent on sex and sociability. RNA velocity, gene regulatory network, and cell communication analysis showed diminished oligodendrocyte/microglia differentiation. Findings were verified using bulk RNA-Seq and demonstrated oxytocins beneficial effects on myelin gene expression. LimitationsOur findings are significant. However, limitations can be noted. The cellular mechanisms linking reduced oligodendrocyte differentiation and reduced myelination to an ASD phenotype in C58/J mice need further investigation. Additional snRNA-Seq and spatial studies would determine if effects in oligodendrocytes/microglia are unique to amygdala or if this occurs in other brain regions. Oxytocins effects need further examination to understand its potential as an ASD therapeutic. ConclusionsOur work demonstrates the C58/J mouse models utility in evaluating the influence of sex and sociability on the transcriptome in concomitant brain regions involved in ASD. Our single-nucleus transcriptome analysis elucidates potential pathological roles of oligodendrocytes and microglia in ASD. This investigation provides details regarding regulatory features disrupted in these cell types, including transcriptional gene dysregulation, aberrant cell differentiation, altered gene regulatory networks, and changes to key pathways that promote microglia/oligodendrocyte differentiation. Our studies provide insight into interactions between genetic risk and epigenetic processes associated with divergent affiliative behavior and lack of positive sociability.

neuroscience↗

bioRxiv2024

Protecting Allogeneic Pancreatic Islet Grafts by Engineered Veto

In todays clinical practice, general immune suppression regimens are used to prevent transplant rejection. Though highly effective, they impair a patients protection against infectious challenges. Strategies are being sought that prevent graft rejection without inhibiting beneficial immune functions. One such approach is based on the classical veto effect that employs donor-derived CD8+ T cells to inhibit cellular immune responses. Yet, allogeneic grafts may only be partially protected by classical veto as CD8+ T cells may fail to remove organ-specific alloreactive T cells. To induce transplant specific immune unresponsiveness, if not tolerance, it may be necessary to endow grafted tissues with veto. Adenoviral vectors were designed that expressed the CD8 -chain as transgene and thus conferred the immune inhibitory veto function to cells of grafted tissues. In the present model, adenoviral vector vectors protected transduced allogeneic pancreatic islets from rejection in fully immune competent recipients. These studies demonstrated that a tissue-engineering approached could be used to create universally acceptable transplants.

immunology↗

bioRxiv2024

RBM7 deficiency promotes breast cancer metastasis by coordinating MFGE8 splicing switch and NF-kB pathway

Aberrant alternative splicing is well-known to be closely associated with tumorigenesis of various cancers. However, the intricate mechanisms underlying breast cancer metastasis driven by deregulated splicing events remain largely unexplored. Here, we unveiled that RBM7 is decreased in lymph node and distant organ metastases of breast cancer as compared to primary lesions and low expression of RBM7 is correlated with the reduced disease-free survival of breast cancer patients. Breast cancer cells with RBM7 depletion exhibited an increased potential for lung metastasis compared to scramble control cells. The absence of RBM7 stimulated breast cancer cell migration, invasion, and angiogenesis. Mechanistically, RBM7 controlled the splicing switch of MFGE8, favoring the production of the predominant isoform of MFGE8, MFGE8-L. This resulted in the attenuation of STAT1 phosphorylation and alterations in cell adhesion molecules. MFGE8-L exerted an inhibitory effect on the migratory and invasive capability of breast cancer cells, while the truncated isoform MFGE8-S, which lack the second F5/8 type C domain had the opposite effect. In addition, RBM7 negatively regulates the NF-{kappa}B cascade and an NF-{kappa}B inhibitor could obstruct the increase in HUVEC tube formation caused by RBM7 silencing. Clinically, we noticed a positive correlation between RBM7 expression and MFGE8 exon7 inclusion in breast cancer tissues, providing new mechanistic insights for molecular-targeted therapy in combating breast cancer.

cancer biology↗

bioRxiv2023

ProtPipe: A Multifunctional Data Analysis Pipeline for Proteomics and Peptidomics

Mass spectrometry (MS) is a technique widely employed for the identification and characterization of proteins, personalized medicine, systems biology and biomedical applications. By combining MS with different proteomics approaches such as immunopurification MS, immunopeptidomics, and total protein proteomics, researchers can gain insights into protein-protein interactions, immune responses, cellular processes, and disease mechanisms. The application of MS-based proteomics in these areas continues to advance our understanding of protein function, cellular signaling, and complex biological systems. Data analysis for mass spectrometry is a critical process that includes identifying and quantifying proteins and peptides and exploring biological functions for these proteins in downstream analysis. To address the complexities associated with MS data analysis, we developed ProtPipe to streamline and automate the processing and analysis of high-throughput proteomics and peptidomics datasets. The pipeline facilitates data quality control, sample filtering, and normalization, ensuring robust and reliable downstream analysis. ProtPipe provides downstream analysis including identifying differential abundance proteins and peptides, pathway enrichment analysis, protein-protein interaction analysis, and MHC1-peptide binding affinity. ProtPipe generates annotated tables and diagnostic visualizations from statistical postprocessing and computation of fold-changes across pairwise conditions, predefined in an experimental design. ProtPipe is well-documented open-source software and is available at https://github.com/NIH-CARD/ProtPipe, accompanied by a web interface.

bioinformatics↗

bioRxiv2023

Small-molecule activators of a bacterial signaling pathway inhibit virulence

The Burkholderia genus encompasses multiple human pathogens, including potential bioterrorism agents, that are often extensively antibiotic resistant. The FixLJ pathway in Burkholderia is a two-component system that regulates virulence. Previous work showed that fixLJ mutations arising during chronic infection confer increased virulence while decreasing the activity of the FixLJ pathway. We hypothesized that small-molecule activators of the FixLJ pathway could serve as anti-virulence therapies. Here, we developed a high-throughput assay that screened over 28,000 compounds and identified 11 that could specifically active the FixLJ pathway. Eight of these compounds, denoted Burkholderia Fix Activator (BFA) 1-8, inhibited the intracellular survival of Burkholderia in THP-1-dervived macrophages in a fixLJ-dependent manner without significant toxicity. One of the compounds, BFA1, inhibited the intracellular survival in macrophages of multiple Burkholderia species. Predictive modeling of the interaction of BFA1 with Burkholderia FixL suggests that BFA1 binds to the putative ATP/ADP binding pocket in the kinase domain, indicating a potential mechanism for pathway activation. These results indicate that small-molecule FixLJ pathway activators are promising anti-virulence agents for Burkholderia and define a new paradigm for antibacterial therapeutic discovery.

microbiology↗

bioRxiv2023

Sequence-based drug design using transformers

Protein-ligand interactions play central roles in biological processes and are of key importance in drug design. Deep learning-based approaches are emerging as cost-effective alternatives to high-throughput experimental methods for the screening of large libraries of ligands. Here, to predict the binding affinity between proteins and small molecules, we introduce Ligand-Transformer, a deep learning framework based on the AlphaFold2 transformer architecture. We applied Ligand-Transformer to screen inhibitors targeting the mutant EGFRLTC kinase, identifying compounds with low nanomolar potency. We then used this approach to predict the conformational population shifts induced by ABL kinase inhibitors. To show the applicability of Ligand-Transformer to disordered proteins, we explored the binding of small molecules to the Alzheimers A{beta} peptide, identifying compounds that delayed its aggregation. Overall, Ligand-Transformer illustrates the potential of transformers in accurately predicting the interactions of small molecules with both ordered and disordered proteins, thus uncovering molecular mechanisms and facilitating the initial steps in drug discovery.

bioinformatics↗

bioRxiv2023

Landscape of Large-Scale Somatic Genomic Insertions in Non-Small Cell Lung Carcinoma Revealed by Nanopore Sequencing

Previous NSCLC genomic studies were mostly based on the next-generation sequencing of short reads, which is an efficient approach for identifying single nucleotide variants and small indels but ineffective for identifying structural variants, especially large-scale insertions. Here, we studied 151 lung adenocarcinoma (LUAD) and 106 lung squamous cell carcinoma (LUSC) samples and paired blood samples using nanopore sequencing technology. We developed a rigorous computational pipeline and characterized the landscape of large-scale somatic insertions in NSCLC. Combining other omics data, we report three findings: 1. we identified an LUSC-enriched somatic simple repeat expansion shared by approximately 40% of LUSC patients that regulates PTPRZ1 gene expression through distal enhancers; 2. the somatic insertion of transposable elements (TEs) in NSCLC were mostly complex TEs consisting of multiple TE elements; and 3. the insertion of short interspersed nuclear elements, especially from the Alu family in young lineages, is a frequent somatic mutation type that shapes the transcriptome of NSCLC through the expression of these elements.

genomics↗

bioRxiv2023

The role of neutrophil typing in homeostatic resilience protective model of inflammatory preconditioning

Sepsis is a systemic inflammatory response syndrome (SIRS) characterized by a dysregulated host response to infection that results in organ dysfunction. The response of neutrophils to early inflammation is critical, interferon regulatory factors 4 (IRF4) and interferon regulatory factors 5 (IRF5) are expressed in most cell types of the immune system, but the relationship between the role of IRF4 and IRF5 in preconditioning-protected septic peritonitis mouse model and neutrophils response remains unknown. In this study, we used an E.coli-induced septic peritonitis mouse model and zebrafish model to explore the relationship between neutrophil inflammation and IRF subtype changes in the process of septic peritonitis. Mechanistically, we found that the protein complex formed by polymorphonuclear neutrophils (PMN) and IRF5/MyD88 can secrete pro-inflammatory factors and directly kill invading bacteria. Author SummaryNumerous animal and clinical sepsis studies have shown that markedly impaired recruitment of neutrophils to sites of infection and failure to clear bacteria contribute to excessive inflammation and increased mortality in sepsis. In our previous work, we established an Escherichia coli (E.coli) lethal septic peritonitis model and a preconditioning-protected septic peritonitis mouse model. In the early stage of septic peritonitis, a large number of PMN infiltrate the peritoneal cavity, which produces an inflammatory response to invasive bacteria. In this study, the switching process between pro-inflammatory and anti-inflammatory attracted our attention. Our research shows that IRF5-IRF4 regulatory axis leads to a PMN phenotype switch in sepsis and the expression of IRF5 and IRF4 was related to PMN pro-inflammatory (N1 type) and anti-inflammatory (N2 type) phenotypes, respectively.

immunology↗

bioRxiv2023

Consensus Tree under the Ancestor-Descendant Distance is NP-hard

Due to uncertainty in tumor phylogeny inference from sequencing data, many methods infer multiple, equally-plausible phylogenies for the same cancer. To summarize the solution space [T] of tumor phylogenies, consensus tree methods seek a single best representative tree S under a specified pairwise tree distance function. One such distance function is the ancestor-descendant (AD) distance d (T, T'), which equals the symmetric difference of the transitive closures of the edge sets E (T) and E (T'). Here, we show that finding a consensus tree S for tumor phylogenies [T] that minimizes the total AD distance {sum}T [isin][T] d (S, T) is NP-hard.

cancer biology↗

bioRxiv2023

Visualizing translating dynamics in situ at high spatial and temporal resolution in eukaryotic cells

Many protein complexes are highly dynamic in cells, characterizing their conformational changes in cells is crucial for unraveling their functions. In this report, using cryo-electron microscopy, 451,700 ribosome particles from Saccharomyces cerevisiae cell lamellae were obtained to solve the 60S region to 2.9 [A] resolution by in situ single particle analysis. Over 20 distinct conformations were identified by 3D classification with resolutions typically higher than 4 [A]. These conformations were used to reconstruct a complete elongation cycle of eukaryotic translation with elongation factors. We found that compact eEF2 anchors to the partially rotated ribosome after subunit rolling, and hypothesize that it stabilizes the local conformation for peptidyl transfer. Moreover, an open eEF3 binding to a fully rotated ribosome was observed, whose conformational change was coupled with head swiveling and body back-rotation of the 40S subunit.

biophysics↗

bioRxiv2023

African swine fever virus I196L is a virulence determinant and its deletant induces robust protection in Domestic pig

The worldwide pandemic of African swine fever virus (ASFV) has a profound impact on the global pig industry. ASFV is a complex multilayered structure and the functions of unknown genes are being revealed. Here we deleted I196L from virulent ASFV SY18 with different length and obtained two recombinant viruses. The replication efficiency of the two recombinant viruses were similar but significantly lower than parental SY18. The pigs all survived the two recombinant viruses with 106.0TCID50 except one pig occurred sudden death and the suvived pigs all resisted the challenge without fever after intramuscularly injecting a lethal dose (102.0TCID50) of ASFV SY18. The recombinant viruses induced a strong anti-p54 humoral immune response. Meanwhile, the pigs also inevitably appeared moderate to high viremia throughout the observation period and presented a gradually downward trend. The results show that deleting I196L gene is a potential and effective vaccine that protects pigs from ASFV. IMPORTANCEThe worldwide outbreak of African swine fever (ASF) cannot be effectively prevented due to no availably commercial vaccine. Many different types of vaccine candidates are researched and reported, which is a hopeful trend to develop safety and efficacy vaccine. Here we report on an unknown functional gene, I196L, which affects the virulence and replication of ASFV. When I196L was deleted from ASFV SY18, the recombinant virus decreased virulence and resisted the challenge of parental strain. This is a novel, effective, potential live attenuated vaccine (LAVs) for ASF.

immunology↗

bioRxiv2023

Essential Function of Membrane-Bound Transcription Factor MYRF in Promoting Transcription of miRNA lin-4 during C. elegans Development

Precise developmental timing control is essential for organism formation and function, but its mechanisms are unclear. In C. elegans, the microRNA lin-4 critically regulates developmental timing by post-transcriptionally downregulating the larval-stage-fate controller LIN-14. However, the mechanisms triggering the activation of lin-4 expression toward the end of the first larval stage remain unknown. We demonstrate that the transmembrane transcription factor MYRF-1 is necessary for lin-4 activation. MYRF-1 is initially localized on the cell membrane, and its increased cleavage and nuclear accumulation coincide with lin-4 expression timing. MYRF-1 regulates lin-4 expression cell-autonomously and hyperactive MYRF-1 can prematurely drive lin-4 expression in embryos and young first-stage larvae. The tandem lin-4 promoter DNA recruits MYRF-1GFP to form visible loci in the nucleus, suggesting that MYRF-1 directly binds to the lin-4 promoter. Our findings identify a crucial link in understanding developmental timing regulation and establish MYRF-1 as a key regulator of lin-4 expression.

developmental biology↗

bioRxiv2023

Molecular tuning of sea anemone stinging

Jellyfish and sea anemones fire single-use, venom-covered barbs to immobilize prey or predators. We previously showed that the anemone Nematostella vectensis uses a specialized voltage-gated calcium (CaV) channel to trigger stinging in response to synergistic prey-derived chemicals and touch (Weir et al., 2020). Here we use experiments and theory to find that stinging behavior is suited to distinct ecological niches. We find that the burrowing anemone Nematostella uses uniquely strong CaV inactivation for precise control of predatory stinging. In contrast, the related anemone Exaiptasia diaphana inhabits exposed environments to support photosynthetic endosymbionts. Consistent with its niche, Exaiptasia indiscriminately stings for defense and expresses a CaV splice variant that confers weak inactivation. Chimeric analyses reveal that CaV{beta} subunit adaptations regulate inactivation, suggesting an evolutionary tuning mechanism for stinging behavior. These findings demonstrate how functional specialization of ion channel structure contributes to distinct organismal behavior.

physiology↗

bioRxiv2023

Dendritic voltage imaging reveals biophysical basis of associative plasticity rules

Dendrites on neurons support nonlinear electrical excitations, but the computational significance of these events is not well understood. We developed molecular, optical, and analytical tools to map sub-millisecond voltage dynamics throughout the dendritic trees of CA1 pyramidal neurons under diverse optogenetic and synaptic stimulus patterns, in acute brain slices. We observed history-dependent spike back-propagation in distal dendrites, driven by locally generated Na+ spikes (dSpikes). Dendritic depolarization created a transient window for dSpike propagation, opened by A-type KV channel inactivation, and closed by slow NaV inactivation. Collisions of dSpikes with synaptic inputs triggered calcium channel and N-methyl-D-aspartate receptor (NMDAR)-dependent plateau potentials, with accompanying complex spikes at the soma. This hierarchical ion channel network acts as a spike-rate accelerometer, providing an intuitive picture of how dendritic excitations shape associative plasticity rules.

neuroscience↗