Biology subjects

Fan, X.

Publications and source records attributed to Fan, X..

At least 235 records · Page 13Linked to original sources

bioRxiv2019

The 14q32.31 DLK1-DIO3 MIR300 tumor suppressor promotes leukemogenesis by inducing cancer stem cell quiescence and inhibiting NK cell anti-cancer immunity.

Drug-resistance of tumor-initiating cells, impaired NK cell immune-response, PP2A loss-of-function and aberrant miRNA expression are cancer features resulting from microenvironmental- and tumor-specific signals. Here we report that genomic-imprinted MIR300 is a cell context-independent dual function tumor suppressor which is upregulated in quiescent leukemic stem (LSC) and NK cells by microenvironmental signals to induce quiescence and impair immune-response, respectively, but inhibited in CML and AML proliferating blasts to prevent PP2A-induced apoptosis. MIR300 anti-proliferative and PP2A-activating functions are differentially activated through dose-dependent CCND2/CDK6 and SET inhibition, respectively. LSCs escape PP2A-mediated apoptosis through TUG1 lncRNA that uncouples and limits MIR300 functions to cytostasis by regulating unbound-MIR300 levels. Halting MIR300 homeostasis restores NK cell activity and suppresses leukemic but not normal hematopoiesis by eradicating nearly all LSCs. Thus, MIR300 tumor suppressor activity is essential and therapeutically important for LSC-driven leukemias.

cancer biology↗

bioRxiv2019

TWIST1 homo- and heterodimers orchestrate specificity control in embryonic stem cell lineage differentiation and craniofacial development

The extensive array of bHLH transcription factors and their combinations as dimers underpin the diversity of molecular function required for cell type specification during embryogenesis. The bHLH factor TWIST1 plays pleiotropic roles during development. However, which combinations of TWIST1 dimers are involved and what impact each dimer imposes on the gene regulation network controlled by TWIST1 remain elusive. In this work, proteomic profiling of human-TWIST1 expressing cell lines and transcriptome analysis of mouse cranial mesenchyme have revealed that TWIST1 homodimer and heterodimers with TCF3, TCF4 and TCF12 E-proteins are the predominant dimer combinations. Dimers formation or their balance are altered by disease-causing mutations in TWIST1 helix domains, which may account for the defective differentiation of the craniofacial mesenchyme observed in patients. Functional analyses of the loss and gain of TWIST1-E-protein dimer activity have revealed previously unappreciated roles in guiding lineage differentiation of embryonic stem cells: TWIST1-E-protein heterodimers activate the differentiation of mesoderm and neural crest cells which is accompanied by epithelial-to-mesenchymal transition, while TWIST1 homodimers maintain the stem cells in a progenitor state and block entry to the endoderm lineage.

developmental biology↗

bioRxiv2019

A robust benchmark for germline structural variant detection

New technologies and analysis methods are enabling genomic structural variants (SVs) to be detected with ever-increasing accuracy, resolution, and comprehensiveness. Translating these methods to routine research and clinical practice requires robust benchmark sets. We developed the first benchmark set for identification of both false negative and false positive germline SVs, which complements recent efforts emphasizing increasingly comprehensive characterization of SVs. To create this benchmark for a broadly consented son in a Personal Genome Project trio with broadly available cells and DNA, the Genome in a Bottle (GIAB) Consortium integrated 19 sequence-resolved variant calling methods, both alignment- and de novo assembly-based, from short-, linked-, and long-read sequencing, as well as optical and electronic mapping. The final benchmark set contains 12745 isolated, sequence-resolved insertion and deletion calls [≥]50 base pairs (bp) discovered by at least 2 technologies or 5 callsets, genotyped as heterozygous or homozygous variants by long reads. The Tier 1 benchmark regions, for which any extra calls are putative false positives, cover 2.66 Gbp and 9641 SVs supported by at least one diploid assembly. Support for SVs was assessed using svviz with short-, linked-, and long-read sequence data. In general, there was strong support from multiple technologies for the benchmark SVs, with 90 % of the Tier 1 SVs having support in reads from more than one technology. The Mendelian genotype error rate was 0.3 %, and genotype concordance with manual curation was >98.7 %. We demonstrate the utility of the benchmark set by showing it reliably identifies both false negatives and false positives in high-quality SV callsets from short-, linked-, and long-read sequencing and optical mapping.

genomics↗

bioRxiv2019

Nuclear actin regulates inducible transcription by enhancing RNA polymerase II clustering

Gene expression in response to external stimuli underlies a variety of fundamental cellular processes. However, how the transcription machinery is regulated under these scenarios is largely unknown. Here, we discover a novel role of nuclear actin in inducible transcriptional regulation using next-generation transcriptome sequencing and super-resolution microscopy. The RNA-seq data reveal that nuclear actin is required for the establishment of the serum-induced transcriptional program. Using super-resolution imaging, we found a remarkable enhancement of RNA polymerase II (Pol II) clustering upon serum stimulation and this enhancement requires the presence of nuclear actin. To study the molecular mechanisms, we firstly observed that Pol II clusters co-localized with the serum-response genes and nuclear actin polymerized in adjacent to Pol II clusters upon serum stimulation. Furthermore, N-WASP and Arp2/3 are reported to interact with Pol II, and we demonstrated N-WASP is required for serum-enhanced Pol II clustering. Importantly, using an optogenetic tool, we revealed that N-WASP phase-separated with the carboxy-terminal domain of Pol II and nuclear actin. In addition to serum stimulation, we found nuclear actin also essential in enhancing Pol II clustering upon interferon-{gamma} treatment. Taken together, our work unveils nuclear actin promotes the formation of transcription factory on inducible genes, acting as a general mechanism underlying the rapid response to environmental cues.

cell biology↗

bioRxiv2019

Laser Recording of Subcellular Neuron Activities

Advances in imaging and recording of neural activities with a single neuron resolution have played a significant role in understanding neurological diseases in the past decade. Conventional methods relying on patch-clamp and electrodes are regarded as invasive, whereas fluorescence-based imaging tools are useful but still suffer from a low signal-to-noise ratio and low sensitivity. Here we developed a novel optical imaging and recording system by employing laser emissions to record the action potentials in single neurons and neuronal networks caused by subtle transients (Ca2+ concentration) in primary neurons in vitro with a subcellular and single-spike resolution. By recording the laser emissions from neurons, we discovered that lasing emissions could be biologically modulated by intracellular activities and extracellular stimulation with >100-fold improvement in detection sensitivity over traditional fluorescence-based measurement. Finally, we showed that ultrasound can wirelessly activate neurons adsorbed with piezoelectric BaTiO3 nanoparticles, in which the neuron laser emissions were modulated by ultrasound. Our findings show that ultrasound stimulation can significantly increase the lasing intensity and neuron network response. This work not only opens the door to laser emission recording of intracellular dynamics in neuronal networks but may provide an ultra-sensitive detection method for brain-on-chip applications, optogenetics, and neuro-analysis.

bioengineering↗

bioRxiv2019

Clinical pattern of antibiotic overuse and misuse in primary healthcare hospitals in the southwest of China

PurposeOveruse and misuse of antibiotics are the primary risk factors for antibiotics resistance. Inadequate professional competence of primary care physicians might exacerbate these problems in China. This retrospective study aims to document the clinical pattern of antibiotics use and its overuse and misuse rates in rural primary care institutions, and to evaluate the association between antibiotics use and characteristics of the physicians and their patients.\n\nMethodsMedical records from 16 primary care hospitals in rural areas of Guizhou province, China were obtained from the Health Information System in 2018. Classification of incorrect and/or unnecessary use, escalated use and combined antibiotics use was based on the Guiding Principle of Clinical Use of Antibiotics (2015, China) and the standard of USA Centers for Disease Control and Prevention. Generalized Estimating Equations were employed to determine predictive factors for inappropriate antibiotics use.\n\nResultsA total of 74,648 antibiotics prescriptions were retrieved. Uncomplicated respiratory infection was the most common disease accounting for 58.6% of all prescriptions. The main antibiotic group used was penicillins (51.5%) followed by cephalosporins and macrolides (14% each). Of 57,009 patient visits, only 8.7% of the antibiotic prescriptions were appropriate. Combined, escalated, and incorrect and/or unnecessary antibiotics use was found in 7.8%, 6.2% and 77.3% of patient visits, respectively, of which 28.7% were given intravenously. Antibiotics misuse was significantly more likely among newly employed physicians with lower levels of professional education. Adult patients and those who had public insurance had a higher risk of being prescribed incorrect and/or unnecessary antibiotics.\n\nConclusionOveruse of antibiotics for uncomplicated respiratory infection and use of cephalosporins, macrolides and injection antibiotics in primary care are the major problems of clinical practice in rural areas of Guizhou.

epidemiology↗

bioRxiv2019

Rapid breath analysis for acute respiratory distress syndrome diagnostics using a portable 2-dimensional gas chromatography device

Acute respiratory distress syndrome (ARDS) is the most severe form of acute lung injury, responsible for high mortality and long-term morbidity. As a dynamic syndrome with multiple etiologies its timely diagnosis is difficult as is tracking the course of the syndrome. Therefore, there is a significant need for early, rapid detection and diagnosis as well as clinical trajectory monitoring of ARDS. Here we report our work on using human breath to differentiate ARDS and non-ARDS causes of respiratory failure. A fully automated portable 2-dimensional gas chromatography device with high peak capacity, high sensitivity, and rapid analysis capability was designed and made in-house for on-site analysis of patients breath. A total of 85 breath samples from 48 ARDS patients and controls were collected. Ninety-seven elution peaks were separated and detected in 13 minutes. An algorithm based on machine learning, principal component analysis (PCA), and linear discriminant analysis (LDA) was developed. As compared to the adjudications done by physicians based on the Berlin criteria, our device and algorithm achieved an overall accuracy of 87.1% with 94.1% positive predictive value and 82.4% negative predictive value. The high overall accuracy and high positive predicative value suggest that the breath analysis method can accurately diagnose ARDS. The ability to continuously and non-invasively monitor exhaled breath for early diagnosis, disease trajectory tracking, and outcome prediction monitoring of ARDS may have a significant impact on changing practice and improving patient outcomes.

bioengineering↗

bioRxiv2019

Aberrant Clonal Hematopoiesis Following Lentiviral Transduction of HSPC in a Rhesus Macaque

Lentiviral vectors (LV) have been used for the delivery of genes into hematopoietic stem and progenitor cells (HSPC) in clinical trials worldwide. LV, in contrast to retroviral vectors, have not been associated with insertion site-associated malignant clonal expansions, and thus have been considered safer. Here, however, we present a case of markedly abnormal dysplastic clonal hematopoiesis impacting the erythroid, myeloid and megakaryocytic lineages in a rhesus macaque transplanted with HSPCs that were transduced with a LV containing a strong retroviral murine stem cell virus (MSCV) constitutive promoter-enhancer in the LTR. 9 insertions were mapped in the abnormal clone, resulting in overexpression and aberrant splicing of several genes of interest, including the cytokine stem cell factor and the transcription factor PLAG1. This case represents the first clear link between a lentiviral insertion-induced clonal expansion and a clinically abnormal transformed phenotype following transduction of normal primate or human HSPC, and are thus concerning, and suggest that strong constitutive promoters should not be included within LV vectors.

molecular biology↗

bioRxiv2019

An improved control efficacy against tobacco bacterial wilt by an engineered Pseudomonas mosselii expressing the ripAA gene from phytopathogenic Ralstonia solanacearum

The environmental bacterium Pseudomonas mosselii produces antagonistic secondary metabolites with inhibitory effects on multiple plant pathogens, including Ralstonia solanacearum, the causal agent of bacterial wilt. In this study, an engineered P. mosselii strain was generated to express R. solanacearum ripAA, which determines incompatible interactions with tobacco plants. The ripAA gene together with its native promoter was integrated into the P. mosselii chromosome. The resulting strain showed no difference in antimicrobial activity against R. solanacearum. Promoter-LacZ fusion and RT-PCR experiments demonstrated that the ripAA gene was transcribed in culture media. Compared with that of the wild type, the engineered strain reduced the disease index by 9.1% for bacterial wilt on tobacco plants. A transcriptome analysis was performed to identify differentially expressed genes in tobacco plants, and the results revealed that ethylene-and jasmonate-dependent defense signaling pathways were induced. These data demonstrated that the engineered P. mosselii expressing ripAA enables improved biological control against tobacco bacterial wilt by the activation of host defense responses.\n\nImportanceNowadays, the use of biocontrol agents is more and more popular in agriculture, but they cannot replaced of chemical agents mostly, due to the poorer control effect. So the study about how to improve the efficacy of biocontrol agents become necessary and urgent. We increase the efficacy against plant pathogen through introducing an avirulence gene from plant pathogen into the biocontrol agent based on \"gene to gene\" hypothesis. The new engineered strain can improve the systemic resistance and elicit primary immune response of plants. Our research not only provides a new strategy for genetic modification of biocontrol agent, a number of avirulence gene from pathogen or plant can be tested to be expressed in different biocontrol agents to antagonize plant disease, but also help the study of interaction between phythopathogenic avirulence gene and host.

microbiology↗

bioRxiv2018

Construction of an index system for big data application in health care enterprises: A study based on the Delphi method

This study explored the theory of medical enterprise management and big data. Based on the Delphi method, two rounds of expert opinions were consulted on the capability of a health care enterprise big data application index system covering 11 dimensions, 46 first-level indicators and 111 second-level indicators. The index system includes two categories of input and capacity. The input category includes five dimensions: human resources, material resources, financial resources, government policies, and social service system or social environment. The capabilities category includes six dimensions: data integration capabilities, service capabilities, data analysis capabilities, information security, profitability, and innovation capabilities. This index system aims to appraise the application capability of big data scientifically and systematically, and fills the gaps of such research in China so far, which has positive significance for further research in the future.

scientific communication and education↗

bioRxiv2018

The long noncoding RNA Hand2as orchestrates heart development through regulation of precise expression of HAND2

Rigorous exploration and dissection of potential actions and effects of long noncoding RNA (lncRNA) in animals remain challenging. Here using multiple knockout mouse models and single-cell RNA sequencing, we demonstrate that the divergent lncRNA Hand2as has a key, complex modulatory effect on the expression of its neighboring gene HAND2 and subsequently on heart development and function, largely independent of Hand2as transcription and transcripts. Full-length deletion of Hand2as in mouse causes moderate yet prevalent upregulation of HAND2 in hundreds of cardiac cells, resulting in profound biological consequences, including dysregulated cardiac gene programs, congenital heart defects and perinatal lethality. We propose a cis-functional role for the Hand2as locus in dampening HAND2 expression to restrain cardiomyocyte proliferation, thereby orchestrating a balanced development of cardiac cell lineages. This study highlights the need for complementary genetic and single-cell approaches to delineate the function and primary molecular effects of an lncRNA in animals.\n\nImpact statementThe long noncoding RNA Hand2as critically controls the precise expression of its neighboring gene HAND2, thereby balancing cardiac lineages and expression programs that are essential for heart development and function.

developmental biology↗

bioRxiv2018

Pervasive translation of circular RNAs driven by short IRES-like elements

Although some circular RNAs (circRNAs) were found to be translated through IRES-driven mechanism, the scope and functions of circRNA translation are unclear because endogenous IRESs are rare. To determine the prevalence and mechanism of circRNA translation, we developed a cell-based system to screen random sequences and identified 97 overrepresented hexamers that drive cap-independent circRNA translation. These IRES-like short elements are significantly enriched in endogenous circRNAs and sufficient to drive circRNA translation. We further identified multiple trans-acting factors that bind these IRES-like elements to initiate translation. Using mass-spectrometry data, hundreds of circRNA-coded peptides were identified, most of which have low abundance due to rapid degradation. As judged by mass-spectrometry, 50% of translatable endogenous circRNAs undergo rolling circle translation, several of which were experimentally validated. Consistently, mutations of the IRES-like element in one circRNA reduced its translation. Collectively, our findings suggest a pervasive translation of circRNAs, providing profound implications in translation control.

molecular biology↗

bioRxiv2018

Single particle cryo-EM reconstruction of 52 kDa streptavidin at 3.2 Angstrom resolution

The fast development of single particle cryo-EM has made it more feasible to obtain the 3D structure of well-behaved macromolecules with molecular weight higher than 300 kDa at ~3 [A] resolution. It remains a challenge to obtain high resolution structure of molecules smaller than 100 kDa using single particle cryo-EM, mainly due to the low contrast of the molecules embedded in vitreous ice. In this work, we applied the Cs-corrector-VPP coupled cryo-EM to study 52 kDa streptavidin (SA) protein supported on a thin layer of graphene film and embedded in vitreous ice. We were able to solve both the apo-SA and biotin-bound SA at near-atomic resolution using single particle cryo-EM. We demonstrated that the method is capable to determine the structure of molecule as small as 39 kDa and potentially even smaller molecules. Furthermore, we found that using the graphene film to avoid the adsorption to the air-water interface is critical to maintain the proteins high-resolution structural information.

biophysics↗

bioRxiv2018

Global analysis of N6-methyladenosine functions and its disease association using deep learning and network-based methods

N6-methyladenosine (m6A) is the most abundant methylation, existing in >25% of human mRNAs. Exciting recent discoveries indicate the close involvement of m6A in regulating many different aspects of mRNA metabolism and diseases like cancer. However, our current knowledge about how m6A levels are controlled and whether and how regulation of m6A levels of a specific gene can play a role in cancer and other diseases is mostly elusive. We propose in this paper a computational scheme for predicting m6A-regulated genes and m6A-associated disease, which includes Deep-m6A, the first model for detecting condition-specific m6A sites from MeRIP-Seq data with a single base resolution using deep learning and a new network-based pipeline that prioritizes functional significant m6A genes and its associated diseases using the Protein-Protein Interaction (PPI) and gene-disease heterogeneous networks. We applied Deep-m6A and this pipeline to 75 MeRIP-seq human samples, which produced a compact set of 709 functionally significant m6A-regulated genes and nine functionally enriched subnetworks. The functional enrichment analysis of these genes and networks reveal that m6A targets key genes of many critical biological processes including transcription, cell organization and transport, and cell proliferation and cancer-related pathways such as Wnt pathway. The m6A-associated disease analysis prioritized five significantly associated diseases including leukemia and renal cell carcinoma. These results demonstrate the power of our proposed computational scheme and provide new leads for understanding m6A regulatory functions and its roles in diseases.\n\nAuthor summaryThe goal of this work is to identify functional significant m6A-regulated genes and m6A-associated diseases from analyzing an extensive collection of MeRIP-seq data. To achieve this, we first developed Deep-m6A, a CNN model for single-base m6A prediction. To our knowledge, this is the first condition-specific single-base m6A site prediction model that combines mRNA sequence feature and MeRIP-Seq data. The 10-fold cross-validation and test on an independent dataset showthat Deep-m6A outperformed two sequence-based models. We applied Deep-m6A followed by network-based analysis using HotNet2 and RWRH to 75 human MeRIP-Seq samples from various cells and tissue under different conditions to globally detect m6A-regulated genes and further predict m6A mediated functions and associated diseases. This is also to our knowledge the first attempt to predict m6A functions and associated diseases using only computational methods in a global manner on a large number of human MeRIP-Seq samples. The predicted functions and diseases show considerable consistent with those reported in the literature, which demonstrated the power of our proposed pipeline to predict potential m6A mediated functions and associated diseases.

bioinformatics↗

bioRxiv2018

Targeting RyR2 with a phosphorylation site-specific nanobody Reverses Dysfunction of Failing Cardiomyocytes in Rat

Chronic PKA phosphorylation of RyR2 has been shown to increased diastolic SR Ca2+ leak and lead to cardiac dysfunction. Since the change of phosphorylation level of RyR2 is a biomarker of failing heart, we attempted to verify the hypothesis that intracellular gene delivery of a RyR2 targeting phosphorylation site-specific nanobody could preserve contractility of failing myocardium. In present study, we acquired the RyR2-specific nanobodies from a phage display library which are variable domains of camellidae heavy chain-only antibodies (VHH). One of the monoclonal nanobodies, AR185, inhibiting RyR2 phosphorylation in an in vitro assay was then chosen for further investigation. We investigated the potential of adeno-associated virus (AAV)-9-mediated cardiac expression of AR185 against post-ischemic heart failure. Adeno-associated virus gene delivery elevated the intracellular expression AR185 protein in the ischemic heart failure model of rats, and this treatment normalized the systolic and diastolic dysfunction of the failing myocardium in vivo and in vitro by reversing myocardial Ca2+ handling. Furthermore, AR185 gene transfer to failing cardiomyocytes reduced the frequency of sarcoplasmic reticulum (SR) calcium leak, thereby restoring the attenuated intracellular calcium transients and SR calcium load. Moreover, AR185 gene transfer inhibited PKA phosphorylation of RyR2 in failing cardiomyocytes. Our results provided strong pre-clinical experimental evidence of the cardiac expression of RyR2 nanobody with AAV9 vectors as a promising therapeutic strategy for ischemic heart failure.

pathology↗

bioRxiv2018

Transcriptional regulation of voltage-gated sodium channels contributes to GM-CSF induced pain

Granolocyte-macrophage colony stimulating factor (GM-CSF) induces production of granulocyte and macrophage populations from the hematopoietic progenitor cells; it is one of the most common growth factors in the blood. GM-CSF is also involved in bone cancer pain development by regulating tumor-nerve interactions, remodeling of peripheral nerves and sensitization of damage-sensing (nociceptive) nerves. However, the precise mechanism for GM-CSF-dependent pain is unclear. In this study, we found that GM-CSF is highly expressed in human malignant osteosarcoma. Rats implanted with bone cancer cells develop mechanical and thermal hyperalgesia but antagonizing GM-CSF in these animals significantly reduced such hypersensitivity. Nociceptor-specific voltage gated Na+ channels Nav1.7, Nav1.8 and Nav1.9 were found to be selectively up-regulated in rat DRG neurons treated with GM-CSF, which resulted in enhanced excitability. GM-CSF activated the Jak2 and Stat3 signaling pathway which promoted the transcription of Nav1.7-1.9 in DRG neurons. Accordingly targeted knocking down either Nav1.7-1.9 or Jak2/Stat3 in DRG neurons alleviated the hyperalgesia in rats. Our findings describe a new bone cancer pain mechanism and provide a new insight into the physiological and pathological functions of GM-CSF.

neuroscience↗

bioRxiv2018

Detecting Large Indels Using Optical Map Data

Optical Maps (OM) provide reads that are very long, and thus can be used to detect large indels not detectable by the shorter reads provided by sequence-based technologies such as Illumina and PacBio. Two existing tools for detecting large indels from OM data are BioNano Solve and OMSV. However, these two tools may miss indels with weak signals. We propose a local-assembly based approach, OMIndel, to detect large indels with OM data. The results of applying OMIndel to empirical data demonstrate that it is able to detect indels with weak signal. Furthermore, compared with the other two OM-based methods, OMIndel has a lower false discovery rate. We also investigated the indels that can only be detected by OM but not Illumina, PacBio or 10X, and we found that they mostly fall into two categories: complex events or indels on repetitive regions. This implies that adding the OM data to sequence-based technologies can provide significant progress towards a more complete characterization of structural variants (SVs). The algorithm has been implemented in Perl and is publicly available on https://bitbucket.org/xianfan/optmethod.

bioinformatics↗

bioRxiv2018

Predict plant-derived xenomiRs from plant miRNA sequences using random forest and one-dimensional convolutional neural network models

BackgroundAn increasing number of studies reported that exogenous miRNAs (xenomiRs) can be detected in animal bodies, however, some others reported negative results. Some attributed this divergence to the selective absorption of plant-derived xenomiRs by animals.\n\nResultsHere, we analyzed 166 plant-derived xenomiRs reported in our previous study and 942 non-xenomiRs extracted from miRNA expression profiles of four species of commonly consumed plants. Employing statistics analysis and cluster analysis, our study revealed the potential sequence specificity of plant-derived xenomiRs. Furthermore, a random forest model and a one-dimensional convolutional neural network model were trained using miRNA sequence features and raw miRNA sequences respectively and then employed to predict unlabeled plant miRNAs in miRBase. A total of 241 possible plant-derived xenomiRs were predicted by both models. Finally, the potential functions of these possible plant-derived xenomiRs along with our previously reported ones in human body were analyzed.\n\nConclusionsOur study, for the first time, presents the systematic plant-derived xenomiR sequences analysis and provides evidence for selective absorption of plant miRNA by human body, which could facilitate the future investigation about the mechanisms underlying the transference of plant-derived xenomiR.

bioinformatics↗