Biology subjects

Lan, X.

Publications and source records attributed to Lan, X..

At least 37 records · Page 2Linked to original sources

bioRxiv2024

Increased functional integration of emotional control network in late adulthood

Emotional wellbeing has often been shown to improve across the adult lifespan. The corresponding effects, however, in the emotion regulation brain networks remain underexplored. By utilizing large-scale datasets such as the Human Connectome Project (HCP-Aging, N=621, 349 females) and Cambridge Centre for Ageing and Neuroscience (Cam-CAN, N=333, 155 females), we were able to investigate how emotion regulation networks functional topography differs across the entire adult lifespan. Based on previous meta-analytic work that identified four large-scale functional brain networks involved in emotion generation and regulation, we investigated the association between the integration of these emotion regulation networks and measures of mental wellbeing with age in the HCP-Aging dataset. We found an increased functional integration of the emotional control network among older adults, which was replicated using the Cam-CAN dataset. Further we found that the interoceptive network, which is mediating emotion generative and regulative processes and carries our introspective and reflective functions, is less integrated in higher age. Our study highlights the importance of identifying topological changes in the functional emotion network architecture across the lifespan, as it allows for a better understanding of functional brain network changes that accompany emotional aging. HighlightsO_LIWe aimed to identify age-related differences in the functional integration of large-scale emotion regulation brain networks across the adult lifespan, and its implications for well-being. C_LIO_LIFrontal emotion control network showed increased while interoception network showed decreased functional integration with higher age in the HCP-Aging dataset. C_LIO_LIIncreased integration of emotion control network was replicated and validated in the Cam-CAN dataset. C_LI

neuroscience↗

bioRxiv2024

Mechanistic dissection of the CHD4 enhancers reveals cooperative functions among the homotypic ZNF410 clustered motifs

Transcription factors often regulate numerous target genes. However, ZNF410 controls only a single gene, CHD4, in human erythroid cells by its highly restricted chromatin occupancy to the CHD4 locus via two clusters of ZNF410 binding motifs. Here, we uncover that ZNF410 controls chromatin accessibility and activity of the two CHD4 enhancer regions. Combining CRISPR/Cas9 genomic deletion with CRISPRi approaches, we demonstrate that both enhancer regions additively contribute to CHD4 gene expression. Mutations of the di-adenine nucleotides within the ZNF410 binding motif fully disrupt ZNF410-DNA interaction. Luciferase assays, ChIP-seq, and ATAC-seq studies reveal that the homotypic clustered motifs within the CHD4 enhancers are recognized by ZNF410 in a collaborative fashion. Especially, the three ZNF410 motifs located in the 3 end of the distal enhancer act as "switch motifs" to control the chromatin accessibility and activity of the whole distal enhancer region. Together, our findings expose a complex functional hierarchy of motifs, where clustered motifs bound by the same transcription factor cooperate to fine-tune the expression of target gene. HighlightsO_LIZNF410 maintains the accessibility of the CHD4 enhancer regions C_LIO_LIThe two enhancer elements additively modulate CHD4 gene expression C_LIO_LIThe dinucleotide "AA" is the key bases within ZNF410 binding motif C_LIO_LIZNF410 binds to homotypic clustered motifs in a cooperative manner C_LI

molecular biology↗

bioRxiv2023

Hypoxia impacts small intestinal organoid stemness and differentiation

Comprised of several cell types functioning differently, the small intestinal epithelial cells perform their functions and synergistically maintain homeostasis in the first part of the mammalian intestine. Due to the uneven distribution of the vessel, the oxygen level exhibits a gradient decreasing pattern in the normal intestine and becomes aberrant in some intestinal diseases. In this work, we find certain levels of hypoxia simulated by cobaltous chloride (CoCl2) caused an increase in the secretive cell types and a decrease in the absorptive cell types in vitro cultured mouse small intestinal organoids. Importantly, the intestinal stem cell amount is impacted which leads to attenuated epithelial regeneration. Our study highlights the cell-type-specific alterations under the hypoxia insult, which gives possible therapeutic hints for hypoxia-relevant gastrointestinal diseases.

cancer biology↗

bioRxiv2023

Utilizing Non-Invasive Prenatal Test Sequencing Data Resource for Human Genetic Investigation

Non-invasive prenatal testing (NIPT) employs ultra-low-pass sequencing of maternal plasma cell-free DNA to detect fetal trisomy. With exceptional sensitivity, specificity, and safety, NIPT has gained global adoption, exceeding ten million tests, establishing it as one of the largest human genetic resources. This resource holds immense potential for exploring population genetic variations and their correlations with phenotypes. Here, we present comprehensive methods tailored for analyzing large, low-depth NIPT genetic datasets, involving customized algorithms and software for genetic variation detection, genotype imputation, and genome-wide association analysis. Through evaluations, we demonstrate that, when integrated with appropriate probabilistic models and population-specific haplotype reference panels, accurate allele frequency estimation and high genotype imputation accuracy (0.8 to 0.9) are achievable for genetic variants with alternative allele frequencies between 0.01 and 0.05, at sequencing depths of 0.1x to 0.25x. Additionally, we attained an R-square exceeding 0.9 for estimating genetic effect sizes across various sequencing platforms. These findings establish a robust theoretical and practical foundation for leveraging NIPT data in advancing medical genetic studies, not only in realms of maternal and child health, but also for long-term health outcomes. HighlightsO_LIIntroduction of probabilistic model integration for analyzing large-scale, low-pass non-invasive prenatal test (NIPT) sequencing data C_LIO_LIEvaluation of protocols for variant detection, genotype imputation, and genome-wide association analyses with NIPT data C_LI

bioinformatics↗

bioRxiv2023

Lymphotoxin-β Promotes Bone Colonization and Osteolytic Outgrowth of Indolent Bone Metastatic cells of Breast Cancer

Bone metastatic relapse is a lethal consequence of breast cancer, occurring years after initial diagnosis. By analyzing single-cell transcriptomes of bone-seeding tumor cells and in vivo barcoded cDNA library screening, LT{beta} (lymphotoxin-{beta}) is identified as a key factor highly expressed in early-stage bone metastatic cells, associated with poor bone metastasis-free survival, and capable of promoting dormancy reactivation in multiple breast cancer models. Mechanistically, tumor-derived LT{beta} activates NF-{kappa}B2 signaling in osteoblasts to express CCL2/5, facilitating tumor cell seeding and accelerating osteoclastogenesis. Both processes contribute to the reactivation of dormancy and metastatic outgrowth. Blocking LT{beta} signaling with a decoy receptor significantly suppressed bone colonization and metastatic progression, whereas clinical sample analysis revealed significantly higher LT{beta} expression in bone metastases than in primary tumors. Our findings highlight LT{beta} as a bone niche-induced factor that promotes tumor cell seeding and dormancy reactivation, underscoring its potential as a therapeutic target for preventing bone metastatic relapse in patients with breast cancer.

cell biology↗

bioRxiv2023

High-throughput and genome-scale targeted mutagenesis using CRISPR in a non-model multicellular organism, Bombyx mori

Large-scale genetic mutant libraries are powerful approaches to interrogating genotype-phenotype correlations and identifying genes responsible for certain environmental stimuli, both of which are the central goal of life science study. We produced the first large-scale CRISPR/Cas9-induced library in a non-model multicellular organism, Bombyx mori. We developed a piggyBac-delivered binary genome editing strategy, which can simultaneously meet the requirements of mixed microinjection, efficient multi-purpose genetic operation, and preservation of growth-defect lines. We constructed a single-guide RNA (sgRNA) plasmid library containing 92,917 sgRNAs targeting promoters and exons of 14,645 protein-coding genes, established 1726 transgenic sgRNA lines following microinjection of 66,650 embryos, and generated 300 mutant lines with diverse phenotypic changes. Phenomic characterization of mutant lines identified a large set of genes responsible for visual phenotypic or economically valuable trait changes. Next, we performed pooled context-specific positive screens for tolerance to environmental pollute cadmium exposure, and identified KWMTBOMO12902 as a strong candidate gene for breeding applications in sericulture industry. Collectively, our results provide a novel and versatile approach for functional B. mori genomics, and a powerful resource for identifying key candidate genes potential for improving various economic traits. This study also demonstrates the effectiveness, practicality, and convenience of large-scale mutant libraries in other non-model organisms.

genomics↗

bioRxiv2023

COMSE: Analysis of Single-Cell RNA-seq Data Using Community Detection Based Feature Selection

Single-cell RNA sequencing enables studying cells individually, yet high gene dimensions and low cell numbers challenge the analysis. And only a subset of the genes detected are involved in the biological processes underlying cell-type specific functions. We present COMSE, an unsupervised feature selection framework using community detection to capture informative genes from scRNA-seq data. COMSE identified cell substates with high resolution, as demonstrated by its capacity in distinguishing cells at different stages of the cell cycle. Evaluations based on real and simulated scRNA-seq datasets showed COMSE outperformed methods even at high dropout rates in cell clustering. We also demonstrate that by identifying communities of genes associated with batch effects, COMSE differentiates biological differences from batch effects, thereby enabling integrated analysis of scRNA-seq datasets generated with different platforms.

bioinformatics↗

bioRxiv2023

VitTCR: A deep learning method for peptide recognition prediction

The identification of the interaction between T-cell receptors (TCRs) and immunogenic peptides is important for the development of novel cancer immunotherapies and vaccines. However, experimentally determining whether a TCR recognizes a peptide is still time- and labour-consuming. In this study, we introduced VitTCR, a predictive model based on the architecture of the vision transformer (ViT), designed to forecast TCR-peptide interactions. Prior to prediction, VitTCR converts the TCR-peptide interactions into a numerical tensor named AtchleyMaps using Atchley factors. Subsequently, VitTCR takes AtchleyMaps as inputs and predicts whether an interaction between a TCR and a peptide exists. Through comprehensive evaluations, we demonstrate that VitTCR surpasses other published methods in classifying TCR-peptide pairs, exhibiting superior performance in terms of the area under the receiver operating characteristic (AUROC) and the area under the precision-recall curve (AUPR). To determine the focal contact point between TCRs and peptides, we obtained a positional bias weight matrix (PBWM) from the empirical amino acid (AA) contact probabilities derived from 83 structurally resolved pMHC-TCR complexes. The comparison of VitTCR with and without the integration of the PBWM revealed significant enhancements in the performance of the model. Moreover, the predicted probabilities generated by VitTCR exhibit significant correlations with immunological factors such as the clonal expansion and activation percentages of T cells. This further supports the efficacy of VitTCR in capturing biologically meaningful TCR-peptide interactions. In conclusion, VitTCR provides a useful computational tool for the prediction of TCR-peptide interactions, thereby contributing to our understanding in this field.

bioinformatics↗

bioRxiv2023

Reconstructing cellular differentiation networks and identifying cell fate-determining features with CIBER

Trajectory inference methods are frequently used for cell fate analysis, however, most of them are similarity-based and lack an understanding of the causality underlying differentiation processes. Here, we present CIBER, a Causal Inference-Based framework for the Evaluation of feature effects and the Reconstruction of cellular differentiation networks. CIBER provides a novel paradigm for dissecting cell state transitions other than trajectory inference and differential analysis. It is a versatile framework that can be applied to various types of data, including transcriptomic, epigenomic and microarray data. It can identify both known and potential cell-lineage structures with minimal prior knowledge. By integrating the CIBER-learned network with structural causal model and applying in silico perturbation as inventions, we generated an effect matrix that quantifies the impact of different features on each differentiation branch. Using this effect matrix, CIBER can identify crucial features involved in haematopoiesis, even if these features show no significant difference in expression between lineages. Moreover, CIBER can predict novel regulation associations and provide insight into the potential mechanism underlying the influence of transcription factors on biological processes. To validate CIBERs capabilities, we conducted in vivo experiments on Bcl11b, a non-differentially expressed transcription factor identified by CIBER. Our results demonstrate that dysfunction of Bcl11b leads to a bias towards myeloid lineage differentiation at the expense of lymphoid lineage, which is consistent with our predictions.

systems biology↗

bioRxiv2022

Disabling of ARC1 through CRISPR/CAS9 leads to a complete breakdown of self-incompatibility responses in Brassica napus

Self-incompatibility (SI) is a genetic mechanism utilized by many flowering plants to promote outcrossing by recognizing and rejecting self-pollen. While the molecular mechanisms controlling SI can differ in various families, plants in the Brassicaceae family have been found to regulate SI through a S-haplotype-specific receptor-ligand interaction. The recognition of self-pollen leads to the activation of ARMADILLO-REPEAT-CONTAINING1 (ARC1), an E3 ligase which is thought to degrade the compatibility factors required for pollen germination, thus resulting in SI. However, the role of ARC1 in SI in the Brassicaceae family has been disputed within the scientific community. While various studies demonstrate that the manipulation of ARC1 and its downstream targets can break-down the SI response, others show that the SI phenotype can be imparted to self-compatible cultivars without the ARC1 gene. This study investigated the involvement of ARC1 in SI through the generation of loss-of-function ARC1 mutants using CRISPR-Cas9 in B. napus. Loss of ARC1 resulted in complete breakdown of SI in two different S-haplotypes providing strong evidence for the essential nature of ARC1 for mounting a successful SI response.

plant biology↗

bioRxiv2021

The first sheep graph pan-genome reveals the spectrum of structural variations and their effects on different tail phenotypes

Structural variations (SVs) are a major contributor to genetic diversity and phenotypic variations, but their prevalence and functions in domestic animals are largely unexplored. Here, we assembled 26 haplotype-resolved genome assemblies from 13 genetically diverse sheep using PacBio HiFi sequencing. We constructed a graph-based ovine pan-genome and discovered 142,422 biallelic insertions and deletions, 7,028 divergent alleles and 13,419 multiallelic variations. We then used a graph-based approach to genotype the biallelic SVs in 684 individuals from 45 domestic breeds and two wild species. Integration with RNA-seq data allows to identify candidate expression-associated SVs. We demonstrate a direct link of SVs and phenotypes by localizing the putative causative insertion in HOXB13 gene responsible for the long-tail trait and identifying multiple large SVs associated with the fat-tail. Beyond generating a benchmark resource for ovine structural variants, our study highlights that animal genetic research will greatly benefit from using a pan-genome graph rather than a single reference genome.

genomics↗

bioRxiv2021

Screening and Identification of Lassa Virus Endonuclease-targeting Inhibitors from a Fragment-based Drug Development Library

Lassa virus (LASV) belongs to the Old World genus Mammarenavirus, family Arenaviridae, and order Bunyavirales. Arenavirus contains a segmented negative-sense RNA genome, which is in line with the bunyavirus and orthomyxoviruses. The segmented negative-sense RNA viruses utilize a cap-snatching strategy to provide primers cleavaged from the host capped mRNA for viral mRNA transcription. As a similar strategy and the conformational conservation shared with these viruses, the endonuclease (EN) would serve as an attractive target for developing broad-spectrum inhibitors. Using the LASV minigenome (MG) system, we screened a fragment-based drug development library and found three candidates (F1204, F1781, and F1597) inhibited MG activity. All three candidates also inhibited the prototype arenavirus Lymphocytic choriomeningitis virus (LCMV) MG activity. Furthermore, the investigation revealed that two benzotriazole compounds (F1204 and F1781) effectively inhibited authentic LCMV and severe fever with thrombocytopenia syndrome virus (SFTSV) infections. The combination of either compound with an arenavirus entry inhibitor had significant synergistic antiviral effects. Moreover, both F1204 and F1781 were found to exert the binding ability of LASV EN with binding affinity at the micromolar level. These findings provide a basis for developing benzotriazole compounds as potential candidates for the treatment of segmented negative-sense RNA virus infections. ImportanceCap-snatching is the mRNA transcription strategy shared by all the segmented, negative-sense RNA viruses. Using a fragment-based drug development (FBDD) library, we tried to screen out the backbone compound to inhibit the endonuclease activity and thus block this kind of virus infection. Two benzotriazole compounds, F1204 and F1781, were identified to inhibit the Lassa virus (LASV) minigenome activity by targeting the LASV EN.

microbiology↗

bioRxiv2021

Screening of Botanical Drugs against SARS-CoV-2 Entry

An escalating pandemic caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is impacting global health. Specific treatment options for diseases caused by SARS-CoV-2 are largely lacking. Herein, we used a pseudotype virus (pv) bearing the SARS-CoV-2 S glycoprotein to screen a botanical drug library to identify an agent against SARS-CoV-2 entry. All the four hits, including angeloylgomisin O, schisandrin B, procyanidin, and oleanonic acid, were identified for effective inhibition of SARS-CoV-2 S pv entry in the micromolar range. A mechanistic study revealed that these four agents inhibit SARS-CoV-2 S pv entry by blocking S-mediated membrane fusion. Furthermore, angeloylgomisin O, schisandrin B, and oleanonic acid inhibited authentic SARS-CoV-2 with a high selective index (SI). We also showed that all the four hits could also inhibit the entry of pv of Middle East respiratory syndrome coronavirus (MERS-CoV) and newly emerged SARS-CoV-2 variants (D614G, K417N/E484K/N501Y/D614G). In drug combination studies performed in cellular antiviral assays, angeloylgomisin O and schisandrin B displayed synergistic effects in combination with remdesivir. These results indicated that angeloylgomisin O, schisandrin B, procyanidin, and oleanonic acid can inhibit SARS-CoV-2 and that they are potential therapeutic agents for COVID-19.

microbiology↗

bioRxiv2021

Reversible blood-brain barrier opening utilizing the membrane active peptide melittin in vitro and in vivo

The blood-brain barrier (BBB) tightly controls entry of molecules and cells into the brain, restricting the delivery of therapeutics. Blood-brain barrier opening (BBBO) utilizes reversible disruption of cell-cell junctions between brain microvascular endothelial cells to enable transient entry into the brain. Development of BBBO techniques has been hindered by a lack of physiological models for in vitro study. Here, we utilize an in vitro tissue-engineered microvessel model to demonstrate that melittin, a membrane active peptide present in bee venom, supports BBBO. From endothelial and neuronal viability studies, we identify the accessible concentration range for BBBO. We then use a tissue-engineered model of the human BBB to optimize dosing and elucidate the mechanism of opening. Melittin and other membrane active variants transiently increase paracellular permeability via disruption of cell-cell junctions. In mice, we demonstrate a minimum clinically effective intra-arterial dose of 3 M{middle dot}min melittin, which is reversible within one day and neurologically safe. Melittin-induced BBBO represents a novel platform for delivery of therapeutics into the brain.

bioengineering↗

bioRxiv2021

RNAi screening reveals requirement for PDGFRβ in JEV infection.

Mosquito-borne Japanese encephalitis virus (JEV) causes serious illness worldwide and is associated with high morbidity and mortality. To identify potential host therapeutic targets, a high-throughput receptor tyrosine kinase small interfering RNA library screening was performed with recombinant JEV particles. Platelet-derived growth factor receptor beta (PDGFR{beta}) was identified as a hit after two rounds of screening. Knockdown of PDGFR{beta} blocked JEV infection, and trans-complementation of PDGFR{beta} could partly restore its infectivity. The PDGFR{beta} inhibitor imatinib, which has been approved for the treatment of malignant metastatic cancer, protected mice against JEV-induced lethality by decreasing the viral load in the brain, while abrogating the histopathological changes associated with JEV infection. These findings demonstrated that PDGFR{beta} is important in viral infection and provided evidence for the potential to develop imatinib as a therapeutic intervention against JEV infection.

microbiology↗

bioRxiv2020

Functional Characterization of a Lassa Virus Fusion Inhibitors Adaptive Mutant

Lassa virus (LASV) glycoprotein complex (GPC) contains retained stable-signal peptide (SSP), GP1, and GP2. SSP interacts with GP2 and provides an interface targeted by numerous fusion inhibitors. Serially passaging of LASV with inhibitors allowed some adaptive mutants to be obtained of which most had mutations located in the transmembrane (TM) domain of GP2. In the current study, we focused on the F446L mutant, which is reported to confer resistance to ST-series inhibitors. We found that F446L conferred cross-resistance to structurally distinct inhibitors. Furthermore, F446L increased the fusion activities of LASV and Mopeia virus GPC, elevating the pH threshold for fusion of LASV and promoting fusion of MOPV at neutral pH. F446L exerted little effect on the pseudotype viral growth profile or thermostability. By introducing other residues to the conserved F446 locus, it was found that this site was less compatible with a similar tyrosine residue and was intolerable to charged residues. These results help characterize the fusion inhibitor target located in the TM domain of GP2, which should be useful for drug and vaccine design. IMPORTANCEThe LASV SSP-GP2 interface provides an Achilles heel that is targeted by numerous inhibitors. However, the emergence of resistant viruses is a major concern for direct antiviral drugs. In this study, we investigated the F446L mutant located in the GPC TM domain to determine the relationship between drug resistance, membrane fusion activity, viral growth kinetics, and thermostability. These results will be helpful in monitoring drug-resistant variants, as well as the advancement of drug and vaccine design.

microbiology↗

bioRxiv2020

The wheat 55K SNP-based exploration of loci for spikelet number per spike from a tetraploid wheat (Triticum turgidum L.) recombinant inbred line population derived from a Chinese landrace Ailanmai and a wild emmer accession

The spikelet number per spike (SNS) is a primary factor determining wheat yield. Common wheat breeding reduces the genetic diversity among elite germplasm resources, leading to a detrimental effect on future wheat production. It is, therefore, necessary to explore new genetic resources for SNS to increase wheat yield. A tetraploid landrace Ailanmai x wild emmer wheat recombinant inbred line (RIL) population was used to construct a genetic map using the wheat 55K single nucleotide polymorphism (SNP) array. The linkage map containing 1150 bin markers with a total genetic distance of 2411.8 cM was obtained. Based on phenotypic data from eight environments and best linear unbiased prediction (BLUP) values, five quantitative trait loci (QTL) for SNS were identified, explaining 6.71-29.40% of the phenotypic variation. Two of them, QSns.sau-AM-2B.3 and QSns.sau-AM-3B.2, were detected as the major and novel QTL. Their effects were further validated in two additional F2 populations using tightly linked Kompetitive Allele-Specific PCR (KASP) markers. Potential candidate genes within the physical intervals of corresponding QTL were predicted to participate in inflorescence development and spikelet formation. Genetic associations between SNS and other agronomic traits were also detected and analyzed. This study demonstrates the feasibility of wheat 55K SNP array developed for common wheat in genetic mapping of tetraploid population and shows the potential application of wheat related species in wheat improvement programs.

genetics↗

bioRxiv2020

ZNF410 uniquely activates the NuRD component CHD4 to silence fetal hemoglobin expression

Metazoan transcription factors typically regulate large numbers of genes. Here we identify via a CRISPR-Cas9 genetic screen ZNF410, a pentadactyl DNA binding protein that in human erythroid cells directly and measurably activates only one gene, the NuRD component CHD4. Specificity is conveyed by two highly evolutionarily conserved clusters of ZNF410 binding sites near the CHD4 gene with no counterparts elsewhere in the genome. Loss of ZNF410 in adult-type human erythroid cell culture systems and xenotransplant settings diminishes CHD4 levels and derepresses the fetal hemoglobin genes. While previously known to be silenced by CHD4, the fetal globin genes are exposed here as among the most sensitive to reduced CHD4 levels. In vitro DNA binding assays and crystallographic studies reveal the ZNF410-DNA binding mode. ZNF410 is a remarkably selective transcriptional activator in erythroid cells whose perturbation might offer new therapeutic opportunities in the treatment of hemoglobinopathies. HighlightsO_LIA CRISPR screen implicates ZNF410 in fetal globin gene repression C_LIO_LIThe CHD4 gene is the singular direct ZNF410 target in erythroid cells C_LIO_LIThe fetal globin genes are exquisitely sensitive to CHD4 levels C_LIO_LIFive C2H2 zinc fingers of ZNF410 recognize the major groove of a 14 base pair sequence C_LI

molecular biology↗