Biology subjects

Li, S.

Publications and source records attributed to Li, S..

At least 595 records · Page 33Linked to original sources

bioRxiv2024

Proteome analysis provides insights into sex differences in Holothuria Scabra

Sex-determining mechanism is still ambiguous for sea cucumber Holothuria scabra which only manifests gonochorism in gonad. In this study, proteomic analysis was employed to delineate sex-related proteins and genes in gonads of H. scabra, subsequently validated through Quantitative real-time polymerase chain reaction (qRT-PCR). A total of 5,313 proteins were identified via proteome sequencing. Among these, 817 proteins exhibited expression in both the ovary and testis, with 445 proteins displaying up-regulation and 372 proteins showing down-regulation. Furthermore, 136 and 69 proteins were identified as ovary-specific and testis-specific Differentially Abundant Proteins (DAPs), respectively. For the validation of 75 DAP coding genes, 9 genes were considered to be reliable. Notably, 25 ovary-bias proteins enriched in ribosome pathway strongly indicated the crucial role of ribosome in ovary. And 5S/18S rRNA ratio in H. Scabra may have potencial to establish a nondestructive method to distinguish sexes unambiguously. This study serves to furnish novel evidence pertaining to sex differences in H. scabra.

molecular biology↗

bioRxiv2024

Lack of dominant-negative activity for tumor-related ZNRF3 missense mutations at endogenous levels

ZNRF3, a negative regulator of {beta}-catenin signaling, removes Wnt receptors from the membrane. Currently, it is unknown which tumor-associated variants can be considered driver mutations and through which mechanisms they contribute to cancer. Here we show that all truncating mutations analyzed at endogenous levels exhibit loss-of-function, with longer variants retaining partial activity. Regarding missense mutations, we show that 27/82 ZNRF3 variants in the RING and R-Spondin domain structures, lead to (partial) loss-of-function/hyperactivation. Mechanistically, defective R-spondin domain variants appear to undergo endoplasmic-reticulum-associated degradation due to protein misfolding. They show reduced stability and fail to reach the membrane correctly, which can be partially restored for several variants by culturing cells at 27{degrees}C. Although RING and R-spondin domain mutations in RNF43/ZNRF3 are often considered to possess dominant-negative oncogene-like activity in cancers, our findings challenge this notion. When representative variants are heterozygously introduced into endogenous ZNRF3, their impact on {beta}-catenin signaling mirrors that of heterozygous knockout, suggesting that the supposed dominant-negative effect is non-existent. In other words, so-called "hyperactivating" ZNRF3/RNF43 mutations behave as classical loss-of-function mutations at endogenous levels. Taken together, our findings provide valuable information on ZNRF3 mutation impact in tumorigenesis and clarify their mechanism of action.

cancer biology↗

bioRxiv2024

Integration of molecular coarse-grained model into geometric representation learning framework for protein-protein complex property prediction

Structure-based machine learning algorithms have been utilized to predict the properties of protein-protein interaction (PPI) complexes, such as binding affinity, which is critical for understanding biological mechanisms and disease treatments. While most existing algorithms represent PPI complex graph structures at the atom-scale or residue-scale, these representations can be computationally expensive or may not sufficiently integrate finer chemical-plausible interaction details for improving predictions. Here, we introduce MCGLPPI, a novel geometric representation learning framework that combines graph neural networks (GNNs) with the MARTINI molecular coarse-grained (CG) model to predict overall PPI properties accurately and efficiently. This framework maps proteins onto a concise CG-scale complex graph, where nodes represent CG beads and edges encode chemically plausible interactions. The GNN-based encoder is tailored to extract high-quality representations from this graph, efficiently capturing the overall properties of the protein complex structure. Extensive experiments on three different downstream PPI property prediction tasks demonstrate that MCGLPPI achieves competitive performance compared with the counterparts at the atom- and residue-scale, but with only a third of the computational resource consumption. Furthermore, the CG-scale pre-training on protein domain-domain interaction structures enhances its predictive capabilities for PPI tasks. MCGLPPI offers an effective and efficient solution for PPI overall property predictions, serving as a promising tool for the large-scale analysis of biomolecular interactions.

bioinformatics↗

bioRxiv2024

Enhancing Gastrodin Production in Yarrowia lipolytica by Metabolic Engineering

Gastrodin, 4-hydroxybenzyl alcohol-4-O-{beta}-D-glucopyranoside, has been widely used in the treatment of neurogenic and cardiovascular diseases. Currently, gastrodin biosynthesis has been achieved in model microorganisms. However, the production levels are insufficient for industrial applications. In this study, we successfully engineered a Yarrowia lipolytica strain to overproduce gastrodin through metabolic engineering. Initially, the engineered strain expressing the heterologous gastrodin biosynthetic pathway, which comprises chorismate lyase, carboxylic acid reductase, phosphopantetheinyl transferase, endogenous alcohol dehydrogenases, and a UDP-glucose dependent glucosyltransferase, produced 1.05 g/L of gastrodin from glucose in a shaking flask. Then, the production was further enhanced to 6.68 g/L with a productivity of 2.23 g/L/day by over-expressing the key node DAHP synthases of the shikimate pathway and alleviating the native tryptophan and phenylalanine biosynthetic pathways. Finally, the best strain, Gd07, produced 13.22 g/L of gastrodin in a 5-L fermenter. This represents the highest reported production of gastrodin in an engineered microorganism to date, marking the first successful de novo production of gastrodin using Y. lipolytica. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=82 SRC="FIGDIR/small/584284v1_ufig1.gif" ALT="Figure 1"> View larger version (25K): org.highwire.dtl.DTLVardef@1eddb6corg.highwire.dtl.DTLVardef@e0bd94org.highwire.dtl.DTLVardef@be472dorg.highwire.dtl.DTLVardef@32fe9d_HPS_FORMAT_FIGEXP M_FIG C_FIG

synthetic biology↗

bioRxiv2024

Survivin in synergy with BAF/SWI complex binds bivalent chromatin regions and activates DNA damage response in CD4+ T cells

This study explores a regulatory role of oncoprotein survivin on the bivalent regions of chromatin (BvCR) characterized by concomitant deposition of trimethylated lysine of histone H3 at position 4 (H3K4me3) and 27 (H3K27me3). Intersect between BvCR and chromatin sequences bound to survivin demonstrated their co-localization on cis-regulatory elements of genes which execute DNA damage control in primary human CD4+ cells. Survivin anchored BRG1-complex to BvCR to repress DNA damage repair genes in IFN{gamma}-stimulated CD4+ cells. In contrast, survivin inhibition shifted the functional balance of BvCR in favor of H3K4me3, which activated DNA damage recognition and repair. Co-expression of BRG1, survivin and IFN{gamma} in CD4+ cells of patients with rheumatoid arthritis identified arthritogenic BRG1hi cells abundant in autoimmune synovia. Immunomodulating drugs inhibited the subunits anchoring BRG1-complex to BvCR, which changed the arthritogenic profile. Together, this study demonstrates the function of BvCR in DNA damage control of CD4+ cells offering an epigenetic platform for survivin and BRG1-complex targeting interventions to combat autoimmunity. SummaryThis study shows that bivalent chromatin regions accommodate survivin which represses DNA repair enzymes in IFN{gamma}-stimulated CD4+ T cells. Survivin anchors BAF/SWI complex to these regions and supports autoimmune profile of T cells, providing novel targets for therapeutic intervention.

immunology↗

bioRxiv2024

Improved functions for non-linear sequence comparison using SEEKR

SEquence Evaluation through k-mer Representation (SEEKR) is a method of sequence comparison that utilizes sequence substrings called k-mers to quantify non-linear similarity between nucleic acid species. We describe the development of new functions within SEEKR that enable end-users to estimate p-values that ascribe statistical significance to SEEKR-derived similarities as well as visualize different aspects of k-mer similarity. We apply the new functions to identify chromatin-enriched long noncoding RNAs (lncRNAs) that harbor XIST-like sequence fragments and show that several of these fragments are bound by XIST-associated proteins. We also highlight the best practice of using RNA-Seq data to evaluate support for lncRNA annotations prior to their in-depth study in cell types of interest.

molecular biology↗

bioRxiv2024

DeepPrep: An accelerated, scalable, and robust pipeline for neuroimaging preprocessing empowered by deep learning

Neuroimaging has entered the era of big data. However, the advancement of preprocessing pipelines falls behind the rapid expansion of data volume, causing significant computational challenges. Here, we present DeepPrep, a pipeline empowered by deep learning and workflow manager. Evaluated on over 55,000 scans, DeepPrep demonstrates a 11-fold acceleration, exceptional scalability, and robustness compared to the current state-of-the-art pipeline, providing a promising solution to meet the scalability requirements of neuroimaging.

neuroscience↗

bioRxiv2024

Structural insights into sphingosine 1-phosphate receptor 4 activation

S1PR4 is one of five subtypes of sphingosine 1-phosphate receptors (S1PRs) that regulate immune cell functioning, with functional distinctions to other subtypes. S1PR1-targeted modulators caused serious cardiac and vascular adverse effects because S1PR1 was expressed throughout the whole body. Since S1PR4 was only expressed in lung and lymphoid cells, S1PR4-targeted modulators might not trigger these side effects. However, the development of S1PR4-specific agonists is greatly hindered because of the lack of activated S1PR4 structure. Here, we resolved cryo-EM structures of activated S1PR4 and revealed the structural mechanism of ligand recognition, receptor activation, and Gi coupling. Our results offered structural templates for the development of selective S1PR4 agonists with improved safety profiles.

biochemistry↗

bioRxiv2024

An injury-induced tissue niche shaped by mesenchymal plasticity coordinates the regenerative and disease response in the lung

Severe lung injury causes basal stem cells to migrate and outcompete alveolar stem cells resulting in dysplastic repair and a loss of gas exchange function. This "stem cell collision" is part of a multistep process that is now revealed to generate an injury-induced tissue niche (iTCH) containing Keratin 5+ epithelial cells and plastic Pdgfra+ mesenchymal cells. Temporal and spatial single cell analysis reveals that iTCHs are governed by mesenchymal proliferation and Notch signaling, which suppresses Wnt and Fgf signaling in iTCHs. Conversely, loss of Notch in iTCHs rewires alveolar signaling patterns to promote euplastic regeneration and gas exchange. The signaling patterns of iTCHs can differentially phenotype fibrotic from degenerative human lung diseases, through apposing flows of FGF and WNT signaling. These data reveal the emergence of an injury and disease associated iTCH in the lung and the ability of using iTCH specific signaling patterns to discriminate human lung disease phenotypes.

cell biology↗

bioRxiv2024

Efficient cloning of genes for wheat yield component traits from QTLs via sequencing of the RIL population

In wheat (Triticum aestivum L.), yield component traits (YCTs) are the most important yield traits. Only several genes for YCTs have been originally cloned. The efficient cloning of genes for YCTs directly from wheat remains a challenge. Here, we proposed a strategy for cloning genes from quantitative trait loci (QTLs) by sequencing of recombinant inbred lines (RILs) (QTL-Seq-RIL). Using the TN18 x LM6 RIL population as an example, we identified 138 candidate unigenes (CUGs) for YCTs from 77 stable QTLs. The average of CUGs per QTL was 1.8, which enabled us to confirm the CUGs directly. We have confirmed seven CUGs, TaIFABPL, TaDdRp, TaRLK, TaTD, TaTFC3, TaKMT and TaSPL17, via the CRISPR/Cas9 system. Of these, six genes were found firstly to regulate YCTs in crops except for TaSPL17. Five CUGs (include TaSPL17) for which orthologous genes have been cloned previously with the same or similar agronomic functions. It is to say, 11 CUGs were preliminarily validated using a single RIL population. QTL-Seq-RIL provides an efficient method for rapid gene cloning using existing RIL populations.

plant biology↗

bioRxiv2024

Delayed cerebrovascular dysfunction and social deficits after traumatic brain injury

Traumatic brain injury (TBI) survivors face debilitating long-term psychosocial consequences, including social isolation and depression. Acute TBI modifies neurovascular physiology and behavior but a gap in our understanding are the chronic physiological implications of altered brain perfusion on behavioral activities, particularly social interactions. We investigated longitudinal functional vascular networks across the brain for 2-months post- TBI and its impact on social behavior. Adult C57/BL6 male mice received a moderate cortical TBI. Behavior (foot-fault, open-field, 3-chamber social preference) was assessed at baseline, 3-, 7-, 14-, 30-, and 60-days post injury (dpi) followed by magnetic resonance imaging (MRI, 9.4T). Anatomical MRI (T2-weighted), dynamic susceptibility contrast (DSC) perfusion weighted MRI (PWI) were acquired at each temporal epoch. After the final 60dpi MRI, animals underwent transcardial perfusion fixation to map angioarchitecture. MRI data were analyzed using standardized protocols followed by cross-correlations between social behavior, cerebral perfusion, and vascular metrics. Social behavior deficits at 60dpi emerged as reduced interaction with a familiar cage-mate (partner). We observed multiphasic decrements in cerebral blood flow (CBF) encompassing lesion and perilesional cortex where acute reductions at 3-14dpi partially recovered by 30dpi, followed by significant reductions in perfusion at 60dpi. The CBF perturbations extended antero-posteriorly from the ipsilateral TBI impact site but also adulterated contralateral brain regions. CBF reductions impacted regions known to regulate social behavior including hippocampus, hypothalamus, and rhinal cortex. Alongside perfusion deficits at 60dpi, social isolation in TBI-mice emerged with a significant decline in preference to spend time with a cage mate. Cortical vascular density was also reduced corroborating the decline in brain perfusion and social interaction. Thus, the novel temporal neurovascular loss, and subsequent recovery followed by chronic decrements are broadly reflected by social interaction perturbations. Our correlations strongly implicate a linkage between vascular density, cerebral perfusion, and social interactions, where early evaluation can potentially predict long-term outcomes. Thus, our study provides a clinically relevant timeline of alterations in functional vascular recovery that can guide research for future therapeutics.

neuroscience↗

bioRxiv2024

Common data models to streamline metabolomics processing and annotation, and implementation in a Python pipeline

To standardize metabolomics data analysis and facilitate future computational developments, it is essential is have a set of well-defined templates for common data structures. Here we describe a collection of data structures involved in metabolomics data processing and illustrate how they are utilized in a full-featured Python-centric pipeline. We demonstrate the performance of the pipeline, and the details in annotation and quality control using large-scale LC-MS metabolomics and lipidomics data and LC-MS/MS data. Multiple previously published datasets are also reanalyzed to showcase its utility in biological data analysis. This pipeline allows users to streamline data processing, quality control, annotation, and standardization in an efficient and transparent manner. This work fills a major gap in the Python ecosystem for computational metabolomics. Author SummaryAll life processes involve the consumption, creation, and interconversion of metabolites. Metabolomics is the comprehensive study of these small molecules, often using mass spectrometry, to provide critical information of health and disease. Automated processing of such metabolomics data is desired, especially for the bioinformatics community with familiar tools and infrastructures. Despite of Pythons popularity in bioinformatics and machine learning, the Python ecosystem in computational metabolomics still misses a complete data pipeline. We have developed an end-to-end computational metabolomics data processing pipeline, based on the raw data preprocessor Asari [1]. Our pipeline takes experimental data in .mzML or .raw format and outputs annotated feature tables for subsequent biological interpretation. We demonstrate the application of this pipeline to multiple metabolomics and lipidomics datasets. Accompanying the pipeline, we have designed a set of reusable data structures, released as the MetDataModel package, which shall promote more consistent terminology and software interoperability in this area.

bioinformatics↗

bioRxiv2024

Hosts Manipulate Lifestyle Switch and Pathogenicity Heterogeneity of Opportunistic Pathogens in the Single-cell Resolution

Host-microbe interactions are virtually bidirectional, but how the host affects their microbiome is poorly understood. Here, we report that the host is a critical modulator to regulate the lifestyle switch and pathogenicity heterogeneity of the opportunistic pathogens Serratia marcescens utilizing the Drosophila and bacterium model system. First, we find that Drosophila larvae efficiently outcompete S. marcescens and typically drive a bacterial switch from pathogenicity to commensalism toward the fly. Furthermore, Drosophila larvae reshape the transcriptomic and metabolic profiles of S. marcescens characterized by a lifestyle switch. More important, the host alters pathogenicity and heterogeneity of S. marcescens in the single-cell resolution. Finally, we find that larvae-derived AMPs are required to recapitulate the response of S. marcescens to larvae. Altogether, our findings provide an insight into the pivotal roles of the host in harnessing the life history and heterogeneity of symbiotic bacterial cells, advancing knowledge of the reciprocal relationships between the host and pathogen.

microbiology↗

bioRxiv2024

Genome-wide Nucleosome Positioning and Associated Features uncovered with Interpretable Deep Residual Networks

Nucleosomes represent elementary building units of eukaryotic chromosomes and consist of DNA wrapped around a histone octamer flanked by linker DNA segments. Nucleosomes are central in epigenetic pathways and their genomic positioning is associated with regulation of gene expression, DNA replication, DNA methylation and DNA repair, among other functions. Building on prior discoveries, that DNA sequences noticeably affect nucleosome positioning, our objective is to identify nucleosome positions and related features across entire genome. Here we introduce an interpretable framework based on the concepts of deep residual networks (NuPose). Trained on high-coverage human experimental MNase-seq data, NuPose is able to learn sequence and structural patterns and their dependencies associated with nucleosome organization in human genome. NuPoSe can be used to identify nucleosomal regions, not covered by experiments, and be applied to unseen data from different organisms and cell types. Our findings point to 43 informative DNA sequence features, most of them constitute tri-nucleotides, di-nucleotides and one tetra-nucleotide. Most features are significantly associated with the structural characteristics, namely, periodicity of nucleosomal DNA and its location with respect to a histone octamer. Importantly, we show that linker DNA features contribute [~]10% to the quality of the prediction model, which together with comprehensive training sets, deep-learning architecture and feature selection may explain the advanced performance of NuPose of 80-89% accuracy.

bioinformatics↗

bioRxiv2024

Coordinated Immune Cell Networks in the Bone Marrow Microenvironment Define the Graft versus Leukemia Response with Adoptive Cellular Therapy

Understanding how intra-tumoral immune populations coordinate to generate anti-tumor responses following therapy can guide precise treatment prioritization. We performed systematic dissection of an established adoptive cellular therapy, donor lymphocyte infusion (DLI), by analyzing 348,905 single-cell transcriptomes from 74 longitudinal bone-marrow samples of 25 patients with relapsed myeloid leukemia; a subset was evaluated by protein-based spatial analysis. In acute myelogenous leukemia (AML) responders, diverse immune cell types within the bone-marrow microenvironment (BME) were predicted to interact with a clonally expanded population of ZNF683+GZMB+ CD8+ cytotoxic T lymphocytes (CTLs) which demonstrated in vitro specificity for autologous leukemia. This population, originating predominantly from the DLI product, expanded concurrently with NK and B cells. AML nonresponder BME revealed a paucity of crosstalk and elevated TIGIT expression in CD8+ CTLs. Our study highlights recipient BME differences as a key determinant of effective anti-leukemia response and opens new opportunities to modulate cell-based leukemia-directed therapy.

cancer biology↗

bioRxiv2024

Endothelial fatty acid-binding proteins contribute to the pathogenesis of pulmonary hypertension

Pulmonary arterial hypertension (PAH) is a devastating disease characterized by obliterative vascular remodeling and persistent increase of vascular resistance, leading to right heart failure and premature death. Understanding the cellular and molecular mechanisms will help develop novel therapeutic approaches for PAH patients. Single-cell RNA sequencing (scRNAseq) analysis found that both FABP4 and FABP5 were highly induced in endothelial cells (ECs) of Egln1Tie2Cre (CKO) mice, which was also observed in pulmonary arterial ECs (PAECs) from idiopathic PAH (IPAH) patients, and in whole lungs of pulmonary hypertension (PH) rats. Plasma levels of FABP4/5 were upregulated in IPAH patients and directly correlated with severity of hemodynamics and biochemical parameters using plasma proteome analysis. Genetic deletion of both Fabp4 and 5 in CKO mice (Egln1Tie2Cre/Fabp4-5-/-, TKO) caused a reduction of right ventricular systolic pressure (RVSP) and RV hypertrophy, attenuated pulmonary vascular remodeling and prevented the right heart failure assessed by echocardiography, hemodynamic and histological analysis. Employing bulk RNA-seq and scRNA-seq, and spatial transcriptomic analysis, we showed that Fabp4/5 deletion also inhibited EC glycolysis and distal arterial programming, reduced ROS and HIF-2 expression in PH lungs. Thus, PH causes aberrant expression of FABP4/5 in pulmonary ECs which leads to enhanced ECs glycolysis and distal arterial programming, contributing to the accumulation of arterial ECs and vascular remodeling and exacerbating the disease.

molecular biology↗

bioRxiv2024

Individualized functional connectivity markers associated with motor and mood symptoms of Parkinson's disease

Parkinsons disease (PD) is a complex neurological disorder characterized by many motor and non-motor symptoms. While most studies focus on the motor symptoms of the disease, it is important to identify markers that underlie different facets of the disease. In this case-control study, we sought to discover reliable, individualized functional connectivity markers associated with both motor and mood symptoms of PD. Using functional MRI, we extensively sampled 166 patients with PD (64 women, 102 men; mean age=61.8 years, SD=7.81) and 51 healthy control participants (32 women, 19 men; mean age=55.68 years, SD=7.62). We found that a model consisting of 44 functional connections predicted both motor (UPDRS-III: Pearson r=0.21, FDR-adjusted p=0.006) and mood symptoms (HAMD: Pearson r=0.23, FDR-adjusted p=0.006; HAMA: Pearson r=0.21, FDR-adjusted p=0.006). Two sets of connections contributed differentially to these predictions. Between-network connections, mainly connecting the sensorimotor and visual large-scale functional networks, substantially contributed to the prediction of motor measures, while within-network connections in the insula and sensorimotor network contributed more so to mood prediction. The middle to posterior insula region played a particularly important role in predicting depression and anxiety scores. We successfully replicated and generalized our findings in two independent PD datasets. Taken together, our findings indicate that sensorimotor and visual network markers are indicative of PD brain pathology, and that distinct subsets of markers are associated with motor and mood symptoms of PD.

neuroscience↗

bioRxiv2024

Dissecting quantitative trait nucleotides by saturation genome editing

Genome editing technologies have the potential to transform our understanding of how genetic variation gives rise to complex traits through the systematic engineering and phenotypic characterization of genetic variants. However, there has yet to be a system with sufficient efficiency, fidelity, and throughput to comprehensively identify causal variants at the genome scale. Here we explored the ability of templated CRISPR editing systems to install natural variants genome-wide in budding yeast. We optimized several approaches to enhance homology-directed repair (HDR) with donor DNA templates, including donor recruitment to target sites, single-stranded donor production by bacterial retrons, and in vivo plasmid assembly. We uncovered unique advantages of each system that we integrated into a single superior system named MAGESTIC 3.0. We used MAGESTIC 3.0 to dissect causal variants residing in 112 quantitative trait loci across 32 environmental conditions, revealing an enrichment for missense variants and loci with multiple causal variants. MAGESTIC 3.0 will facilitate the functional analysis of the genome at single-nucleotide resolution and provides a roadmap for improving template-based genome editing systems in other organisms.

genetics↗