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Biology subjects

Xing, L.

Publications and source records attributed to Xing, L..

At least 37 records · Page 2Linked to original sources
bioRxiv2023

Post-translational regulation of Platelet-derived growth factor receptor β is critical for fracture repair in aged mice

Increased protein ubiquitination was observed in fracture callus and particularly in aged mice. Treatment of proteasome inhibitor enhanced fracture repair in young and mice by increasing the number of mesenchymal progenitor cells (MPCs). However, the protein targets of proteasome inhibitor are still not known. Ub-proteomics identifies the top ub-proteins in MPCs and osteoblasts. Among them, PDGFR{beta} plays important roles both in osteogenesis and angiogenesis, which were reduced in callus of aged mice. We examine the dramatic decrease of PDGFR{beta} protein level, increased Ub-PDGFR{beta}, but mild decrease of mRNA in callus of aged mice, suggesting dys-regulated protein modification is the major cause of decreased PDGFR{beta} level. Decreased PDGFR{beta} results in the failure of PDGF-BB enhanced MPCs proliferation and fracture repair in aged mice. Co-treatment with proteasome inhibitor rescues the ability of PDGF-BB on MPC proliferation and fracture repair. Our findings not only discover the protein target of proteasome inhibitor in MPCs, but importantly connect the compromised effect of PDGF treatment on diseases with PDGFR{beta} proteasomal degradation. We open a new avenue for the treatment of fracture repair in elderly with the combination of PDGF-BB and proteasome inhibitor.

cell biology↗
bioRxiv2023

Senescent cells impair fracture repair through elevating ubiquitin-proteasome system activity in aged mice.

Senescent cells accumulate in multiple tissues with aging. Depletion of senescent cells benefits the aging related disease, such as aging bone fracture. However, the molecular mechanisms by which senescent cells regulate their neighboring bone cells are still not well-known. We reported that proteasome inhibitor enhanced fracture repair in aged mice. Senescent cells are major source of chronic inflammatory cytokines, which in turn induced protein ubiquitination. We reported that PDGFR{beta} was one of the highly ubiquitinated proteins in mesenchymal progenitors (MPCs) and TGF{beta} was the most increased SASP. In the current study, we found TGF{beta} induced PDGFR{beta} ubiquitination and proteasomal degradation through its E3 ligases. TGF{beta} neutralizing antibody blocked the inhibited callus derived MPC growth and increased Ub-PDGFR{beta} by senescent cells, which could be further prevented PDGFR{beta} inhibitor. These findings suggested senescent cells derived TGF{beta} impaired fracture repair in aged mice through elevating ubiquitination of PDGFR{beta}. The discovery of TGF{beta}-PDGFR{beta} pathway triggered by senescent cells opens avenues for optimizing treatment strategies for aging related disease by combination with the ligand of PDGFR{beta}.

cell biology↗
bioRxiv2023

A resource for probing influences of perinatal factors on neurodevelopment in 3-10-years-old Chinese children

Adverse perinatal factors can disrupt the normal development of the brain, with potential long-term impacts on childrens overall development. Currently, the neuropathological mechanisms by which these factors lead to various neurodevelopmental disorders (NDDs) remain largely unknown. An open resource that integrate perinatal factors with brain and mental health development is essential for investigating NDD-related aetiology. In this Data Descriptor, we introduce a multicentre database containing information on perinatal factors that influence childrens brain-mind development, namely, periCBD, that combines neuroimaging and behavioural phenotypes with perinatal factors associated with a high incidence of NDDs at county/region/central district hospitals. PeriCBD was designed to establish a platform for the investigation of individual differences in brain-mind development among children aged 3-10 years are associated with perinatal factors. Ultimately, our goal was to develop an early prediction and screening model for NDDs that leverages normative data to facilitate NDD aetiology research. Herein, we provide a systematic overview of the data acquisition/cleaning/quality control/sharing, processes of periCBD and present preliminary brain-mind associations.

neuroscience↗
bioRxiv2023

Longer mandible or nose? Co-evolution of feeding organs in early elephantiforms

The long-trunked elephantids underwent a significant evolutionary stage characterized by an exceptionally elongated mandible. The initial elongation and subsequent regression of the long mandible, along with its co-evolution with the trunk, present an intriguing issue that remains incompletely understood. Through comparative functional and eco-morphological investigations, as well as feeding preference analysis, we reconstructed the feeding behavior of major groups of longirostrine elephantiforms. In the Platybelodon clade, the rapid evolutionary changes observed in the narial region, strongly correlated with mandible and tusk characteristics, suggest a crucial evolutionary transition where feeding function shifted from the mandible to the trunk, allowing proboscideans to expand their niches to more open regions. This functional shift further resulted in elephantids relying solely on their trunks for feeding. Our research provides insights into how unique environmental pressures shape the extreme evolution of organs, particularly in large mammals that developed various peculiar adaptations during the late Cenozoic global cooling trends.

paleontology↗
bioRxiv2023

Artificial Intelligence Helps to Predict Recurrence and Mortality for Prostate Cancer using Histology Images

Besides grading, deep learning could improve expert consensus to predict prostate cancer (PCa) recurrence. We developed a novel PCa recurrence prediction system based on artificial intelligence (AI). We validated it using multi-institutional and international datasets comprising 2,647 PCa patients with at least a 10-year follow-up. Survival analyses were performed and goodness-of-fit of multivariate models was evaluated using partial likelihood ratio tests, Akaikes test, or Bayesian information criteria to determine the superiority of our system over existing grading systems. Comprehensive survival analyses demonstrated the effectiveness of our AI- system in categorizing PCa into four distinct risk groups. The system was independent and superior to the existing five grade groups for malignancies. A high consensus level was observed among five blinded genitourinary pathology experts in ranking images according to our prediction system. Therefore, AI may help develop an accurate and clinically interpretable PCa recurrence prediction system, facilitating informed decision-making for PCa patients.

pathology↗
bioRxiv2023

Self-supervised deep learning of gene-gene interactions for improved gene expression recovery

Single-cell RNA sequencing (scRNA-seq) has emerged as a powerful tool to gain biological insights at the cellular level. However, due to technical limitations of the existing sequencing technologies, low gene expression values are often omitted, leading to inaccurate gene counts. The available methods, including state-of-the-art deep learning techniques, are incapable of imputing the gene expressions reliably because of the lack of a mechanism to explicitly consider the underlying biological knowledge of the system. Here we tackle the problem in two steps to exploit the gene-gene interactions of the system: (i) we reposition the genes in such a way that their spatial configuration reflects their interactive relationships; and (ii) we use a self-supervised 2D convolutional neural network to extract the contextual features of the interactions from the spatially configured genes and impute the omitted values. Extensive experiments with both simulated and experimental scRNA-seq datasets are carried out to demonstrate the superior performance of the proposed strategy against the existing imputation methods.

genomics↗
bioRxiv2022

Multi-omics Analysis Identifies IgG2b Class-Switching with ALCAM-CD6 Co-Stimulation in Lymph Nodes During Advanced Inflammatory-Erosive Arthritis

Defective lymphatic drainage and B-cell translocation into joint-draining lymph node sinuses are pathogenic phenomena in patients with severe rheumatoid arthritis (RA). However, the molecular mechanisms underlying this lymphatic dysfunction remain poorly understood. Here, by utilizing spatial and single-cell transcriptomics in tumor necrosis factor transgenic (TNF-Tg) mice, we characterized functional genomic changes in popliteal lymph nodes (PLNs) of "Early" and "Advanced" RA to determine the mechanisms orchestrating B-cell differentiation. We first show that Ighg2b expression localized to Marco+ sinuses and negatively correlated with bone volumes in ipsilateral joints. We further reveal that Advanced PLNs exhibited a concomitant accumulation of iron-laden macrophages and T-cells. Mechanistically, crosstalk between ALCAM+ macrophages and CD6+ T-cells was identified as a co-stimulatory pathway promoting IgG2b class-switching. These findings were validated by immunohistochemistry, flow cytometry, ELISPOT, and clinical correlates. Collectively, we propose that ALCAM-CD6 co-stimulation activates T cells, initiating IgG2b class-switching and plasma cell differentiation in RA flare.

immunology↗
bioRxiv2022

Root twisting drives halotropism via stress-induced microtubule reorientation

Plants have evolved signaling mechanisms that guide growth away from adverse environments that can cause yield losses. Root halotropism is a sodium-specific negative tropism that is crucial for surviving and thriving under high salinity. Although root halotropism was discovered some years ago, the underlying molecular and cellular mechanisms remain unknown. Here, we show that abscisic acid (ABA)-mediated root twisting determines halotropism in Arabidopsis. An ABA-activated SnRK2 protein kinase (SnRK2.6) phosphorylates the microtubule-associated protein SP2L at Ser406, which induces a change in the anisotropic cell expansion at the root transition zone that located between the apical meristem and basal elongation zone, and is required for root twisting during halotropsim. Salt stress triggers SP2L-mediated cortical microtubule reorientation in cells at the transition zone, which guides cellulose microfibril patterns. Our findings outline the cellular and molecular mechanisms of root halotropism and indicate that anisotropic cell expansion through MT-reorientation and microfibril deposition have a central role in mediating tropic responses.

plant biology↗
bioRxiv2022

Single-cell RNA sequencing reveals dysregulation of spinal cord cell types in a several spinal muscular atrophy mouse model

Although spinal muscular atrophy (SMA) is a motor neuron disease caused by the loss of survival of motor neuron (SMN) proteins, there is growing evidence that non-neuronal cells play important roles in SMA pathogenesis. However, transcriptome alterations occurring at the single-cell level in SMA spinal cord remain unknown, preventing us from fully comprehending the role of specific cells. Here, we performed single-cell RNA sequencing of the spinal cord of a severe SMA mouse model, and identified ten cell types as well as their differentially expressed genes. Using CellChat, we found that cellular communication between different cell types in the spinal cord of SMA mice was significantly reduced. A dimensionality reduction analysis revealed 29 cell subtypes and their differentially expressed gene. A subpopulation of vascular fibroblasts showed the most significant change in the SMA spinal cord at the single-cell level. This subpopulation was drastically reduced, possibly causing vascular defects and resulting in widespread protein synthesis and energy metabolism reductions in SMA mice. This study reveals for the first time a single-cell atlas of the spinal cord of mice with severe SMA, and sheds new light on the pathogenesis of SMA.

neuroscience↗
bioRxiv2022

5' transgenes drive leaky expression of 3' transgenes in inducible bicistronic vectors

Molecular cloning techniques enabling contemporaneous expression of two or more protein-coding sequences in a cell type of interest provide an invaluable tool for understanding the molecular regulation of cellular functions. DNA recombination employing the Cre-lox system is commonly used as a molecular switch for inducing the expression of recombinant proteins encoded within a bicistronic cassette. In such an approach, the two protein-coding sequences are separated by a 2A peptide or internal ribosome entry site (IRES), and expression is designed to be strictly Cre-dependent by using a lox-STOP-lox cassette or flip-excision (FLEX) switch. However, low-level or leaky expression of recombinant proteins is often observed in the absence of Cre activity, potentially compromising the utility of this approach. To investigate the mechanism of leaky gene expression, we generated pCAG-lox-GFP-STOP-lox-Transgene A-2A-Transgene B vectors, which are designed to express nuclear-targeted GFP in the absence of Cre, and express both transgenes A and B after Cre-mediated recombination. We found that cells transfected with these bicistronic vectors exhibited low-level Cre-independent expression specifically of the transgene positioned 3' of the 2A peptide. We observed similar results in vivo by viral transduction of the adult mouse cerebral cortex with AAV-mutagenesis of putative transcription factor binding sites that the 5' transgene confers promoter-like activity that drives expression of the 3' transgene. Finally, we demonstrate that inclusion of an additional lox-STOP-lox cassette between the 2A sequence and 3' transgene dramatically reduces the extent of Cre-independent leaky gene expression. Our findings highlight that caution should be applied to the use of Cre-dependent bicistronic constructs when tight regulation of transgene expression is desired and provide a guide to preventing leaky gene expression when the expression of more than one protein is required.

molecular biology↗
bioRxiv2022

Longer metaphase and fewer chromosome segregation errors in modern human than Neandertal brain development

Since the ancestors of modern humans separated from those of Neandertals, around one hundred amino acid substitutions spread to essentially all modern humans. The biological significance of these changes is largely unknown. Here, we examine all six such amino acid substitutions in the three proteins known to have key roles in kinetochore function and chromosome segregation and to be highly expressed in the stem cells of the developing neocortex. When we introduce these modern human-specific substitutions in the mouse, three substitutions in two of these proteins, KIF18a and KNL1, cause a prolongation of metaphase and a reduction in chromosome segregation errors in apical progenitors of the developing neocortex. Conversely, the ancestral substitutions cause a reduction in metaphase length and an increase in chromosome segregation errors in human brain organoids. Our data also show that, in these aspects, Neandertals were more similar to chimpanzees than to modern humans. Thus, the fidelity of chromosome segregation during neocortex development improved in modern humans after their divergence from Neandertals.

neuroscience↗
bioRxiv2022

SARS-CoV-2 triggers Golgi fragmentation via downregulation of GRASP55 to facilitate viral trafficking

The COVID-19 pandemic is caused by SARS-CoV-2, an enveloped RNA virus. Despite extensive investigation, the molecular mechanisms for its assembly and secretion remain largely elusive. Here, we show that SARS-CoV-2 infection induces global alterations of the host endomembrane system, including dramatic Golgi fragmentation. SARS-CoV-2 virions are enriched in the fragmented Golgi. Disrupting Golgi function with small molecules strongly inhibits viral infection. Significantly, SARS-CoV-2 infection down-regulates GRASP55 but up-regulates TGN46 protein levels. Surprisingly, GRASP55 expression reduces both viral secretion and spike number on each virion, while GRASP55 depletion displays opposite effects. In contrast, TGN46 depletion only inhibits viral secretion without affecting spike incorporation into virions. TGN46 depletion and GRASP55 expression additively inhibit viral secretion, indicating that they act at different stages. Taken together, we show that SARS-CoV-2 alters Golgi structure and function to control viral assembly and secretion, highlighting the Golgi as a potential therapeutic target for blocking SARS-CoV-2 infection.

cell biology↗
bioRxiv2022

SERM: a self-consistent deep learning solution forrapid and accurate gene expression recovery

Single cell RNA sequencing (scRNA-seq) is a promising technique to determine the states of individual cells and classify novel cell subtypes. Computationally, the processing of scRNA-seq data presents a daunting challenge because of the noisy nature and humongous size and dimensionality of the data. Compromised solution by omitting the genes with low expression is commonly taken in current scRNA-seq analysis, which leads to inaccurate gene counts. In this paper, we introduce a broadly applicable data-driven gene expression recovery framework, referred to as the self-consistent expression recovery machine (SERM), to impute the missing gene expression. Using deep learning, SERM first learns from a subset of the noisy gene expression data to estimate the underlying data distribution. SERM then recovers the overall gene expression data by imposing a self-consistency on the gene expression matrix, thus ensuring that the expression levels are similarly distributed in different parts of the matrix. We show that SERM significantly improves the accuracy of gene imputation with at least 100-fold increase in computational efficiency in comparison to the state-of-the-art techniques. Thus SERM promises to provide an urgently needed computational solution for rapid and accurate recovery of big genomic expression data. SERM is available as a web-based computational tool (https://www.analyxus.com/compute/serm) and its source codes can be found in https://github.com/xinglab-ai/self-consistent-expression-recovery-machine.

bioinformatics↗
bioRxiv2021

The Siberian wild apple, Malus baccata (L.) Borkh., is an additional contributor to the genomes of cultivated European and Chinese apples

It is crucial to understand domestication to unravel the evolutionary processes that shape the divergence of populations. Differences in life-history traits have probably led to marked differences in the mode and speed of evolution between trees and annuals, particularly the extent of crop-wild gene flow during domestication. Apple is an iconic tree and major fruit crop grown worldwide. The contribution of wild apple species to the genetic makeup of the cultivated apple genome remains a topic of intense investigations. We used population genomics in combination with SNPs to investigate the contributions of the two known wild apple relatives, Malus sylvestris and Malus sieversii, and a supposed contributor, Malus baccata, to European and Chinese rootstock and dessert genomes, with a focus on the extent of wild-crop gene flow during apple domestication. We showed that the European dessert and rootstock apples form a specific gene pool, whereas the Chinese dessert and rootstock apples were a mixture of three wild gene pools. Coalescent-based inferences and gene flow estimates indicated that M. baccata is an additional contributor to the genome of both European and Chinese cultivated apples through wild-to-crop introgressions. We also confirmed previous results on the contribution of M. sylvestris to the cultivated apple genome, and provided insights into the origin of the apple rootstock. This study further demonstrates the role of gene flow during apple domestication, as seen in other woody perennials, and show that domestication of the apple tree involved several wild apple species.

evolutionary biology↗
bioRxiv2021

The ataxia protein sacsin is required for integrin trafficking and synaptic organization

Autosomal recessive spastic ataxia of Charlevoix-Saguenay (ARSACS) is caused by mutations in SACS, which manifest as a childhood-onset cerebellar ataxia. Cellular ARSACS phenotypes include mitochondrial dysfunction, intermediate filament (IF) disorganization, and loss of Purkinje neurons. It is unclear how the loss of SACS causes these deficits, or why they manifest as cerebellar ataxia. We employed a multi-omics approach to characterize molecular and cellular deficiencies in SACS knockout (KO) cells. We identified alterations in microtubule structure and dynamics, protein trafficking, and mislocalization of synaptic and focal adhesion proteins. Targeting PTEN, a negative regulator of focal adhesions, rescued several cellular phenotypes in SACS KO cells. We found sacsin interacts with proteins implicated in vesicle transport, including HSP proteins, and interactions between structural and cell adhesion proteins were diminished in SACS KO cells. In all, this study suggests that trafficking and localization of synaptic adhesion proteins is a causal molecular deficiency in ARSACS.

cell biology↗
bioRxiv2021

A graph-theoretical approach to DNA similarity analysis

One of the very active research areas in bioinformatics is DNA similarity analysis. There are several approaches using alignment-based or alignment-free methods to analyze similarities/dissimilarities between DNA sequences. In this work, we introduce a novel representation of DNA sequences, using n-ary Cartesian products of graphs for arbitrary positive integers n. Each of the component graphs in the representing Cartesian product of each DNA sequence contain combinatorial information of certain tuples of nucleotides appearing in the DNA sequence. We further introduce a metric space structure to the set of all Cartesian products of graphs that represent a given collection of DNA sequences in order to be able to compare different Cartesian products of graphs, which in turn signifies similarities/dissimilarities between DNA sequences. We test our proposed method on several datasets including Human Papillomavirus, Human rhinovirus, Influenza A virus, and Mammals. We compare our method to other methods in literature, which indicates that our analysis results are comparable in terms of time complexity and high accuracy, and in one dataset, our method performs the best in comparison with other methods.

genomics↗
bioRxiv2021

Integrative COVID-19 Biological Network Inference with Probabilistic Core Decomposition

The SARS-CoV-2 coronavirus is responsible for millions of deaths around the world. To help contribute to the understanding of crucial knowledge and to further generate new hypotheses relevant to SARS-CoV-2 and human protein interactions, we make use of the information abundant Biomine probabilistic database and extend the experimentally identified SARS-CoV-2-human protein-protein interaction (PPI) network in silico. We generate an extended network by integrating information from the Biomine database, the PPI network, and other experimentally validated results. To generate novel hypotheses, we focus on the high-connectivity sub-communities that overlap most with the integrated experimentally validated results in the extended network. Therefore, we propose a new data analysis pipeline that can efficiently compute core decomposition on the extended network and identify dense subgraphs. We then evaluate the identified dense subgraph and the generated hypotheses in three contexts: literature validation for uncovered virus targeting genes and proteins, gene function enrichment analysis on subgraphs, and literature support on drug repurposing for identified tissues and diseases related to COVID-19. The majority types of the generated hypotheses are proteins with their encoding genes and we rank them by sorting their connections to the integrated experimentally validated nodes. In addition, we compile a comprehensive list of novel genes, and proteins potentially related to COVID-19, as well as novel diseases which might be comorbidities. Together with the generated hypotheses, our results provide novel knowledge relevant to COVID-19 for further validation.

bioinformatics↗