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Chen, X.

Publications and source records attributed to Chen, X..

At least 1,459 records · Page 81Linked to original sources
bioRxiv2019

Generation and quality control of maternal plasma lipidomics data associated with preterm birth

Preterm birth is not only one of the most common causes of infant deaths but also a great risk for them to have severe subsequent health problems. The causes of preterm birth may be due to a combination of genetic and environmental factors, however, it remains largely unknown. Here we report an untargeted lipidomics dataset of plasma specimens from 258 pregnant women at the stage of twelve to twenty-five gestational weeks. Among them, 44 had extremely to very preterm births, 54 had moderate preterm births, 71 had late preterm births and 89 had full-term deliveries. The metabolomic profiling was generated with an UPLC-MS in both the positive and negative mode, and putative identification of all the metabolites was provided by searching against online databases. The quality assessment performed on quality control samples showed that the data is reproducible, robust and reliable. Both the raw data files, the raw and processed data matrix were available on MetaboLights, which may be used as a valuable validation dataset for new findings and a test dataset for novel algorithms.

systems biology↗
bioRxiv2019

Functional divergence of two duplicated Fertilization Independent Endosperm genes in rice with respect to seed development

Fertilization Independent Endosperm (FIE) is an essential member of Polycomb Repression Complex 2 (PRC2) that plays important roles in the developmental regulation of plants. OsFIE1 and OsFIE2 are two FIE homologs in the rice genome. Here, we showed that OsFIE1 probably duplicated from OsFIE2 after the origin of the tribe Oryzeae, but has a specific expression pattern and methylation landscape. During evolution, OsFIE1 underwent a less intensive purifying selection than did OsFIE2. The mutant osfie1 produced smaller seeds and displayed reduced dormancy, indicating that OsFIE1 predominantly functions in late seed development. Ectopic expression of OsFIE1, but not OsFIE2, was deleterious to vegetative growth in a dosage-dependent manner. The newly evolved N-terminal tail of OsFIE1 was probably not the cause of the adverse effects on vegetative growth. The CRISPR/Cas9-derived mutant osfie2 exhibited impaired cellularization of the endosperm, which suggested that OsFIE2 is indispensable for early seed development as a positive regulator of cellularization. Autonomous endosperm was observed in both OsFIE2+- and osfie1/OsFIE2+- but at a very low frequency. Although OsFIE1-PRC2 exhibited H3K27me3 methyltransferase ability in plants, OsFIE1-PRC2 is likely to be less important for development in rice than is OsFIE2-PRC2. Our findings revealed the functional divergence of OsFIE1 and OsFIE2 and shed light on their distinct evolution following duplication.

plant biology↗
bioRxiv2019

Targeting USP9x/SOX2 axis contributes to the anti-osteosarcoma effect of neogambogic acid

SOX2 has been viewed as a critical oncoprotein in osteosarcoma. Emerging evidence show that inducing the degradation of transcription factors such as SOX2 is a promising strategy to make them druggable. Here, we show that neogambogic acid (NGA), an active ingredients in garcinia, significantly inhibited the proliferation of osteosarcoma cells with ubiquitin proteasome-mediated degradation of SOX2 in vitro and in vivo. We further identified USP9x as a bona fide deubiquitinase for SOX2 and NGA directly interacts with USP9x in cells. Moreover, knockdown of USP9x inhibited the proliferation and colony formation of osteosarcoma cells, which could be rescued by overexpression of SOX2. Consistent with this, knockdown of USP9x inhibited the proliferation of osteosarcoma cells in a xenograft mouse model. Collectively, we identify USP9x as the first deubiquitinating enzyme for controlling the stability of SOX2 and USP9x is a direct target for NGA. We propose that targeting the USP9x/SOX2 axis represents a novel strategy for the therapeutic of osteosarcoma and other SOX2 related cancers.

cancer biology↗
bioRxiv2019

Dopamine-dependent loss aversion during effort-based decision-making

From psychology to economics there has been substantial interest in how costs (e.g., delay, risk) are represented asymmetrically during decision-making when attempting to gain reward or to avoid punishment. For example, in decision-making under risk, individuals show a tendency to prefer to avoid punishment than to acquire the equivalent reward (loss aversion). Although the cost of physical effort has received significant recent attention due to the evaluation of motor costs being crucial in our daily decisions, it remains unclear whether loss aversion exists during effort-based decision-making. On the one hand, loss aversion may be hardwired due to asymmetric evolutionary pressure on losses and gains and therefore exists across decision-making contexts. On the other hand, distinct brain regions are involved with different decision costs, making it questionable whether similar asymmetries exist. Here, we demonstrate that young healthy participants exhibit loss aversion during effort-based decision-making by exerting more physical effort in order to avoid punishment than to gain a same-size reward. Next, we show that medicated Parkinsons disease (PD) patients show a reduction in loss aversion compared to age-matched controls. Behavioural and computational analysis revealed that people with PD exerted similar physical effort in return for a reward, but were less willing to produce effort in order to avoid punishment. Therefore, loss aversion is present during effort-based decision-making and can be modulated by altered dopaminergic state. This finding could have important implications for our understanding of clinical disorders that show a reduced willingness to exert effort in the pursuit of reward.\n\nSignificance StatementLoss aversion - preferring to avoid punishment than to acquire equivalent reward - is an important concept in decision-making under risk. However, little is known about whether loss aversion also exists during decisions where the cost is physical effort. This is surprising given that motor cost shapes human behaviour, and a reduced willingness to exert effort is a characteristic of many clinical disorders. Here, we show that healthy individuals exert more effort to minimise punishment than to maximise reward (loss aversion). We also demonstrate that loss aversion is modulated by altered dopaminergic state by showing that medicated Parkinsons disease patients exert similar effort to gain reward but less effort to avoid punishment. Therefore, dopamine-dependent loss aversion is crucial for explaining effort-based decision-making.

animal behavior and cognition↗
bioRxiv2019

Machine Learning for Prioritization of Thermostabilizing Mutations for G-protein Coupled Receptors

Although the three-dimensional structures of G-protein-coupled receptors (GPCRs), the largest superfamily of drug targets, have enabled structure-based drug design, there are no structures available for 87% of GPCRs. This is due to the stiff challenge in purifying the inherently flexible GPCRs. Identifying thermostabilized mutant GPCRs via systematic alanine scanning mutations has been a successful strategy in stabilizing GPCRs, but it remains a daunting task for each GPCR. We developed a computational method that combines sequence, structure and dynamics based molecular properties of GPCRs that recapitulate GPCR stability, with four different machine learning methods to predict thermostable mutations ahead of experiments. This method has been trained on thermostability data for 1231 mutants, the largest publicly available dataset. A blind prediction for thermostable mutations of the Complement factor C5a Receptor retrieved 36% of the thermostable mutants in the top 50 prioritized mutants compared to 3% in the first 50 attempts using systematic alanine scanning.\n\nStatement Of SignifiganceG-protein-coupled receptors (GPCRs), the largest superfamily of membrane proteins play a vital role in cellular physiology and are targets to blockbuster drugs. Hence it is imperative to solve the three dimensional structures of GPCRs in various conformational states with different types of ligands bound. To reduce the experimental burden in identifying thermostable GPCR mutants, we report a computational framework using machine learning algorithms trained on thermostability data for 1231 mutants and features calculated from analysis of GPCR sequences, structure and dynamics to predict thermostable mutations ahead of experiments. This work represents a significant advancement in the development, validation and testing of a computational framework that can be extended to other class A GPCRs and helical membrane proteins.

biophysics↗
bioRxiv2019

BET inhibition induces an anti-apoptotic adaptive response and therapeutic vulnerability to MCL1 inhibitors in breast cancer

The development of effective targeted therapies for the treatment of basal-like breast cancers remains challenging. Here, we demonstrate that BET inhibition induces a multi-faceted adaptive response program leading to MCL1 protein-driven evasion of apoptosis in breast cancers. Consequently, co-targeting MCL1 and BET is highly synergistic in in vitro and in vivo breast cancer models. Drug response and genomics analyses revealed that MCL1 copy number alterations, including low-level gains, are selectively enriched in basal-like breast cancers and associated with effective BET and MCL1 co-targeting. The mechanism of adaptive response to BET inhibition involves upregulation of critical lipid metabolism enzymes including the rate-limiting enzyme stearoyl-CoA desaturase (SCD). Changes in the lipid metabolism are associated with increases in cell motility and membrane fluidity as well as transitions in cell morphology and adhesion. The structural changes in the cell membrane leads to re-localization and activation of HER2/EGFR which can be interdicted by inhibiting SCD activity. Active HER2/EGFR, in turn, induces accumulation of MCL1 protein and therapeutic vulnerability to MCL1 inhibitors. The BET protein, lipid metabolism and receptor tyrosine kinase activation cascade is observed in patient cohorts of basal-like and HER2-amplified breast cancers. The high frequency of MCL1 chromosomal amplifications (>30%) and gains (>50%) in basal-like breast cancers suggests that BET and MCL1 co-inhibition may have therapeutic utility in this aggressive subtype.

cancer biology↗
bioRxiv2019

Rora regulates activated T helper cells during inflammation

The transcription factor Rora has been shown to be important for the development of ILC2 and the regulation of ILC3, macrophages and Treg cells. Here we investigate the role of Rora across CD4+ T cells, both in vitro as well as in the context of several in vivo type 2 infection models. We dissect the function of Rora using overexpression and a CD4-conditional Rora-knockout mouse, as well as a RORA-reporter mouse. We establish the importance of Rora in CD4+ T cells for controlling lung inflammation induced by Nippostrongylus brasiliensis infection, and have measured the effect on downstream genes using RNA-seq. Using a systematic stimulation screen of CD4+ T cells, coupled with RNA-seq, we identify upstream regulators of Rora, most importantly IL-33 and CCL7. Our data suggest that Rora is a negative regulator of the immune system, possibly through several downstream pathways, and is under control of the local microenvironment.

immunology↗
bioRxiv2019

RecO impedes RecG-SSB binding to impair the strand annealing recombination pathway in E.coli

Faithful duplication of genomic DNA relies not only on the fidelity of DNA replication itself, but also on fully functional DNA repair and homologous recombination machinery. We report a molecular mechanism responsible for deciding homologous recombinational repair pathways during replication dictated by binding of RecO and RecG to SSB in E.coli. Using a RecG-yfp fusion protein, we found that RecG-yfp foci appeared only in the {Delta}recG, {Delta}recO and {Delta}recA, {Delta}recO double mutants. Surprisingly, foci were not observed in wild-type {Delta}recG, or double mutants where recG and either recF or, separately recR were deleted. In addition, formation of RecG-yfp foci in the {Delta}recO::kanR required wildtype ssb, as ssb-113 could not substitute. This suggests that RecG and RecO binding to SSB is competitive. We also found that the UV resistance of recO alone mutant increased to certain extent by supplementing RecG. In an ssb-113 mutant, RecO and RecG worked following a different pattern. Both RecO and RecG were able to participate in repairing UV damages when grown at permissive temperature, while they could also be involved in making DNA double strand breaks when grown at nonpermissive temperature. So, our results suggested that differential binding of RecG and RecO to SSB in a DNA replication fork in Escherichia coli.may be involved in determining whether the SDSA or DSBR pathway of homologous recombinational repair is used.\n\nAuthor summarySingle strand DNA binding proteins (SSB) stabilize DNA holoenzyme and prevent single strand DNA from folding into non-B DNA structures in a DNA replication fork. It has also been revealed that SSB can also act as a platform for some proteins working in DNA repair and recombination to access DNA molecules when DNA replication fork needs to be reestablished. In Escherichia coli, several proteins working primarily in DNA repair and recombination were found to participate in DNA replication fork resumption by physically interacting with SSB, including RecO and RecG etc. However the hierarchy of these proteins interacting with SSB in Escherichia coli has not been well defined. In this study, we demonstrated a differential binding of RecO and RecG to SSB in DNA replication was used to establish a RecO-dependent pathway of replication fork repair by abolishing a RecG-dependent replication fork repair. We also show that, RecG and RecO could randomly participate in DNA replication repair in the absence of a functional SSB, which may be responsible for the generation of DNA double strand breaks in an ssb-113 mutant in Escherichia coli.

molecular biology↗
bioRxiv2019

Genome-wide association study provides new insights into the genetic architecture and pathogenesis of heart failure

Heart failure (HF) is a leading cause of morbidity and mortality worldwide1. A small proportion of HF cases are attributable to monogenic cardiomyopathies and existing genome-wide association studies (GWAS) have yielded only limited insights, leaving the observed heritability of HF largely unexplained2-4. We report the largest GWAS meta-analysis of HF to-date, comprising 47,309 cases and 930,014 controls. We identify 12 independent variant associations with HF at 11 genomic loci, all of which demonstrate one or more associations with coronary artery disease (CAD), atrial fibrillation, or reduced left ventricular function suggesting shared genetic aetiology. Expression quantitative trait analysis of non-CAD-associated loci implicate genes involved in cardiac development (MYOZ1, SYNPO2L), protein homeostasis (BAG3), and cellular senescence (CDKN1A). Using Mendelian randomisation analysis we provide new evidence supporting previously equivocal causal roles for several HF risk factors identified in observational studies, and demonstrate CAD-independent effects for atrial fibrillation, body mass index, hypertension and triglycerides. These findings extend our knowledge of the genes and pathways underlying HF and may inform the development of new therapeutic approaches.

genetics↗
bioRxiv2019

Associated habitat and suitability modeling of goldenseal (Hydrastis canadensis L.) in Pennsylvania: explaining and predicting species distribution in a northern edge of range state

Goldenseal (Hydrastis canadensis L.) is a well-known perennial herb indigenous to forested areas in eastern North America. Owing to conservation concerns including wild harvesting for medicinal markets, habitat loss and degradation, and an overall patchy and often inexplicable absence in many regions, there is a need to better understand habitat factors that help determine the presence and distribution of goldenseal populations. In this study, flora and edaphic factors associated with goldenseal populations throughout Pennsylvania--a state near the northern edge of its range--were documented and analyzed to identify habitat indicators and provide possible in situ stewardship and farming (especially forest-based farming) guidance. Additionally, maximum entropy (Maxent) modeling was applied to better predict where suitable habitat might be encountered more broadly and explain species absence from regions of the state (and the northeastern states). Habitat study results identified rich, mesic, woodland sites as being suitable for goldenseal. The most prevalent overstory tree associates on such sites were tulip-poplar (Liriodendron tulipifera L.) and sugar maple (Acer saccharum Marshall), and the most common understory associates were spicebush (Lindera benzoin L.), Virginia creeper (Parthenocissus quinquefolia (L.) Planch.), Jack-in-the-pulpit (Arisaema triphyllum (L.) Schott), mayapple (Podophyllum peltatum L.), wood fern (Drypoteris marginalis (L.) A. Gray), and rattlesnake fern (Botrypus virginianus (L.) Michx.). Loam soils were the most common textural class (average sand, silt, and clay ratio of 50:30:20) with an average pH of 6.2 and high variation in macronutrients. While such sites are widespread in the state, Maxent modeling suggested the present distribution in Pennsylvania is largely restricted by winter temperatures and bedrock type. The latter of these, in turn, is correlated in part with land use legacy (e.g., clearing for farming or livestock grazing), especially in southeast portions of the state.

ecology↗
bioRxiv2019

Diversity and some bioactivities of soil actinomycetes from southwestern China

With the natural medicine exploring, the actinomycetes (actinobacteria) have gotten more and more recognition. 815 soil samples were collected from six areas in the southwestern China. 7063 purified strains of actinomycetes were isolated from these samples by using four media. The 16S rRNA gene sequences of 1998 selected strains of the 7063 were determined, and the phylogenetic analysis was carried out. The diversity of actinomycetes is analyzed. Total 33 genera of actinomycetes as the purified cultivation were identified from these soil samples. 14, 13, 5, 9 and 26 genera of actinobacteria were identified from E, A, B, D, C and F area respectively, and the communities of actinomycetes are very different from each other. The diversity of Xishuangbanna (F area) is the richest, and 26 genera were isolated. That of Emei and Qingcheng Mountain (C area) is monotone, and only five genera were isolated. 158 of 1998 strains (7.9 %) are possible new species. Antimicrobial activities of 1070 selected strains against 11 bacteria and fungi were tested using agar well diffusion method, and biosynthetic genes of type I and II polyketide synthases (PKS I, PKS II), nonribosomal peptide synthase (NRPS) and polygene cytochrome P450 hydroxylase (CYP) of 1036 selected strains were detected by PCR. High rate of antimicrobial activity and the four antibiotic biosynthetic genes existed in these actinomycetes. Results of this study indicates that firstly more unknown actinomycetes can be obtained from soil samples, specially primeval tropical forests. Second, isolation methods for actinomycetes must be continually improved and improved.\n\nImportanceFirst, discarding repeat of a mass of known microbes and compounds is very difficult. Second, pharmaceuticals development can still not overtake the increase of resistance of pathogens to antibiotics, and new diseases continuously and fleetly occur. Soil actinomycetes of these regions are researched few by microbiologist yet. In order to get much more unknown actinomycetes for discovery of new bioactive metabolites, the actinomycetes of forest soil in southwestern China were isolated and identified. Anti-microbial activities and synthetic gene clusters of four kinds of antibiotics of some selected strains were detected.

microbiology↗
bioRxiv2019

Super-resolution Imaging Reveals 3D Structure and Organizing Mechanism of Accessible Chromatin

Access to cis-regulatory elements packaged in chromatin is essential for directing gene expression and cell viability. Here, we report a super-resolution imaging strategy, 3D ATAC-PALM, that enables direct visualization of the entire accessible genome. We found that active chromosomal segments are organized into spatially-segregated accessible chromatin domains (ACDs). Rapid depletion of CTCF or Cohesin (RAD21 subunit) induced enhanced ACD clustering, reduced physical separation between intrachromosomal ACDs, and differentially regulated ACD compaction. Experimental perturbations and polymer modeling suggest that dynamic protein-protein and protein-DNA interactions within ACDs couple with loop extrusion to organize ACD topology. Dysorganization of ACDs upon CTCF or Cohesin loss alters transcription factor binding and target search dynamics in living cells. These results uncover fundamental mechanisms underpinning the formation of 3D genome architecture and its pivotal function in transcriptional regulation.

molecular biology↗
bioRxiv2019

Evaluating Protein Transfer Learning with TAPE

Protein modeling is an increasingly popular area of machine learning research. Semi-supervised learning has emerged as an important paradigm in protein modeling due to the high cost of acquiring supervised protein labels, but the current literature is fragmented when it comes to datasets and standardized evaluation techniques. To facilitate progress in this field, we introduce the Tasks Assessing Protein Embeddings (TAPE), a set of five biologically relevant semi-supervised learning tasks spread across different domains of protein biology. We curate tasks into specific training, validation, and test splits to ensure that each task tests biologically relevant generalization that transfers to real-life scenarios. We bench-mark a range of approaches to semi-supervised protein representation learning, which span recent work as well as canonical sequence learning techniques. We find that self-supervised pretraining is helpful for almost all models on all tasks, more than doubling performance in some cases. Despite this increase, in several cases features learned by self-supervised pretraining still lag behind features extracted by state-of-the-art non-neural techniques. This gap in performance suggests a huge opportunity for innovative architecture design and improved modeling paradigms that better capture the signal in biological sequences. TAPE will help the machine learning community focus effort on scientifically relevant problems. Toward this end, all data and code used to run these experiments are available at https://github.com/songlab-cal/tape.

synthetic biology↗
bioRxiv2019

Transcriptome Dynamics Reveals Progressive Transition from Effector to Memory in CD4+ T cells.

CD4+ T cells are repositories of immune memory, conferring enhanced immunity to many infectious agents. Studies of acute viral and bacterial infection suggest that memory CD4+ T cells develop directly from effectors. However, delineating these dynamic developmental pathways has been challenging. Here, we used high-resolution single-cell RNA-seq and temporal mixture modelling to examine the fate of Th1 and Tfh effector cells during non-lethal Plasmodium infection in mice. We observed linear Th1 and Tfh pathways towards memory, characterized by progressive halving in the numbers of genes expressed, and partial transcriptomic coalescence. Low-level persisting infection diverted but did not block these pathways. We observed in the Th1-pathway a linear transition from Th1 through a Tr1 state to TEM cells, which were then poised for Th1 re-call. The Tfh-pathway exhibited a modest Th1-signature throughout, with little evidence of Tr1 development, and co-expression of TCM and memory Tfh markers. Thus, we present a high-resolution atlas of transcriptome dynamics for naive to memory transitions in CD4+ T cells. We also defined a subset of memory-associated genes, including transcription factors Id2 and Maf, whose expression increased progressively against the background of transcriptomic quiescence. Single-cell ATAC-seq revealed substantial heterogeneity in chromatin accessibility in single effectors, which was extensively, though incompletely reset and homogenized in memory. Our data reveal that linear transitions from effector to memory occur in a progressive manner over several weeks, suggesting opportunities for manipulating CD4+ T cell memory after primary infection.\n\nHighlightsO_LIscRNA-seq reveals progressive transition from effector to memory in CD4+ T cells.\nC_LIO_LITranscriptome dynamics suggest linear not branching models for memory development.\nC_LIO_LIA subset of genes associates with gradual onset of CD4+ T cell memory.\nC_LIO_LITh1/Tfh predisposition varies among clonotypes with identical antigen-specificity.\nC_LIO_LIscATAC-seq uncovers non-coding \"memory\" elements in the genome.\nC_LI

immunology↗
bioRxiv2019

Genome analysis and Hi-C assisted assembly of Elaeagnus angustifolia L., a deciduous tree belonging to Elaeagnaceae

Elaeagnus angustifolia L. is a deciduous tree of the Elaeagnaceae family. It is widely used in the study of abiotic stress tolerance in plants and for the improvement of desertification-affected land due to its characteristics of drought resistance, salt tolerance, cold resistance, wind resistance, and other environmental adaptation. Here, we report the complete genome sequencing using the Pacific Biosciences (PacBio) platform and Hi-C assisted assembly of E. angustifolia. A total of 44.27 Gb raw PacBio sequel reads were obtained after filtering out low-quality data, with an average length of 8.64 Kb. And 39.56 Gb clean reads was obtained, with a sequencing coverage of 75x, and Q30 ratio > 95.46%. The 510.71 Mb genomic sequence was mapped to the chromosome, accounting for 96.94% of the total length of the sequence, and the corresponding number of sequences was 269, accounting for 45.83% of the total number of sequences. The genome sequence study of E. angustifolia can be a valuable source for the comparative genome analysis of the Elaeagnaceae family members, and can help to understand the evolutionary response mechanisms of the Elaeagnaceae to drought, salt, cold and wind resistance, and thereby provide effective theoretical support for the improvement of desertification-affected land.

genetics↗
bioRxiv2019

GIP: A Gene network-based integrative approach for Inferring disease-associated signaling Pathways

Dysregulation or crosstalk of signal transduction pathways contributes to disease development. Despite the initial success of identifying causal links between source and target proteins in simple or well-studied biological systems, it remains challenging to investigate alternative pathways specifically associated with a disease. We develop a Gene network-based integrative approach for Inferring disease-associated signaling Pathways (GIP). Specifically, we identify alternative pathways given source and target proteins. GIP was applied to human breast cancer data. Experimental results showed that GIP identified biologically meaningful pathway modules associated with antiestrogen resistance.

bioinformatics↗
bioRxiv2019

Fate mapping via Ms4a3 expression history traces monocyte-derived cells

Most tissue-resident macrophage (RTM) populations are seeded by waves of embryonic hematopoiesis and are self-maintained independently of a bone-marrow contribution during adulthood. A proportion of RTMs, however, is constantly replaced by blood monocytes and their functions compared to embryonic RTM remains unclear. The kinetics and extent of the contribution of circulating monocytes to RTM replacement during homeostasis, inflammation and disease is highly debated. Here, we identified Ms4a3 as a specific marker expressed by granulocyte-monocyte progenitors (GMPs) and subsequently generated Ms4a3TdT reporter and Ms4a3Cre-RosaTdT fate mapper models to follow monocytes and their progenies. Our Ms4a3Cre-RosaTdT model traced efficiently blood monocytes (97%) and granulocytes (100%), but no lymphocytes or tissue dendritic cells. Using this model, we precisely quantified the contribution of monocytes to the RTM pool during homeostasis and inflammation. The unambiguous identification of monocyte-derived cells will permit future studies of their function under any condition.

immunology↗