Biology subjects

Fan, Y.

Publications and source records attributed to Fan, Y..

At least 271 records · Page 15Linked to original sources

bioRxiv2020

Targeted nanopore sequencing by real-time mapping of raw electrical signal with UNCALLED

ReadUntil sequencing allows nanopore devices to selectively eject individual reads from the pore in real-time. This could enable purely computational targeted sequencing, however most mapping methods require basecalling, which is computationally intensive. Here we present UNCALLED (github.com/skovaka/UNCALLED), an open-source mapper that rapidly matches streaming nanopore current signals to a reference sequence. UNCALLED probabilistically considers k-mers that the signal could represent, and then prunes the candidates based on the reference encoded within an FM-index. We used UNCALLED to deplete sequencing of known bacterial genomes within a metagenomics community, enriching the remaining species by 4.46 fold. UNCALLED also enriched 148 human genes associated with hereditary cancers to 29.6x coverage using one MinION flowcell, enabling accurate detection of SNPs, indels, structural variants (SVs), and methylation in these genes. Twice as many SVs were detected compared to 50x coverage Illumina sequencing, all verified by whole-genome nanopore and PacBio HiFi sequencing.

genomics↗

bioRxiv2020

IL4-driven microglia modulate stress resilience through BDNF-dependent neurogenesis

Adult neurogenesis in the dentate gyrus of the hippocampus is regulated by specific groups of microglia and is functionally implicated in behavioral responses to stress. However, the role of microglia in modulating hippocampal neurogenesis in stress responses remains poorly understood. Here we investigated the effects of IL4-driven Arg1+ microglia in the restoration of hippocampal neurogenesis and conferment of stress resilience. We found that low IL4 levels in the hippocampus of mice was associated with greater stress vulnerability and, conversely, overexpression of IL4 in the hippocampus induced a large number of Arg1+ microglia and ameliorated stress-induced depressive-like behaviors. Knockdown of microglial IL4 receptors in the hippocampus of mice exacerbated the stress-induced inflammatory response and abolished the antidepressant effects of IL4 overexpression. Enhancement or inhibition of IL4 signaling in hippocampal microglia modulated neurogenesis, and blockade of neurogenesis abolished the resilience to stress-induced depression. We further show that IL4-activated microglia is associated with upregulation of BDNF levels and neurogenesis. Taken together, our findings suggest that IL4-driven microglia in the hippocampus trigger BDNF-dependent neurogenesis in response to chronic stress, helping protect against depressive-like symptoms. These findings identify the modulation of a specific microglial phenotype as a treatment strategy for mood disorders. In BriefZhang et al. show that IL4-induced Arg1+ microglia restore hippocampal neurogenesis and promote resilience against stress in mice by increasing BDNF levels. Targeting microglia with immunomodulatory factors may be a strategy for treating mood disorders. HighlightsO_LIVulnerability to stress in mice is associated with reduced IL4 signaling in the hippocampus C_LIO_LIBrain-derived IL4 promotes adult hippocampal neurogenesis and stress resistance by driving Arg1+ microglia C_LIO_LIIL4-driven Arg1+ microglia enhance hippocampal neurogenesis via a BDNF-dependent pathway C_LI

neuroscience↗

bioRxiv2020

Opposing neural signals of CaV1-encoded peptides are tuned by C-terminus mediated inhibition

L-type calcium (CaV1) channels regulate gene expressions via the cascade of excitation-transcription coupling, or directly as standalone CCAT (Calcium Channel Associated Transcriptional-regulator) peptides encoding distal carboxyl-terminus (DCT) of CaV1, both evidenced in dendritogenesis signaling in neurons. We here discover that DCT peptides opposedly mediate these two sets of transcription signals, all tunable in accordance to C-terminus mediated inhibition (CMI) of Ca2+/CaV1 influx. By electrophysiology, neurite morphology, and FRET 2-hybrid binding analyses, we systematically examined native and derived DCT peptides across CaV1, unveiling that the overall balance between cytosolic inhibition versus nuclear facilitation is spatially and temporally tuned by CMI of each DCT variant. Our findings not only resolve several controversies existing to DCT variants, but also propose a de novo scheme of CaV1-centric gene regulation: two concurrent routes of transcription signals initiated from either membrane CaV1 channels or nuclear CaV1-encoded peptides are subject to autonomous feedback tuning by peptide/channel interactions.

neuroscience↗

bioRxiv2020

Alteration of fecal microbial compositions and bacterial taxa in female osteoporotic patients

BackgroundGut microbiota, mainly characterized by fecal bacterial compositions, affects human immune system and pathophysiological development. Our aim was to measure the quantitative differences of fecal bacterial compositions between osteoporotic patients and healthy subjects, and to identify novel bacterial taxa that speculate the incidence of osteoporosis in female. MethodWe recruited 104 female subjects, including 45 osteoporotic individuals and 59 healthy control. Fecal samples were collected for further analysis by 16S rRNA quantitative arrays and bioinformatics analysis. ResultsAnalyses of - and {beta}-diversity demonstrated that the diversity and composition of fecal bacterial compositions were both significant different in osteoporosis group, as compared with healthy group. Multiple bacterial genera were significantly increased (e.g., Roseburia and Bacteroides) or decreased (e.g., Streptococcus and Dorea) in the osteoporotic cases. Furthermore, the osteoporosiscould be efficiently determined by the random forest model based on differential taxa (area under ROC curve = 0.93). ConclusionThere were obvious different fecal microbial characteristics between female osteoporosis and healthy subjects. These findings provided evidence for understanding the host-gut microbiota interplay in female osteoporosis, and supported clinical applications of gut microbiota analysis for female osteoporosis diagnosis

microbiology↗

bioRxiv2020

Novel culture method to diagnose fungal infections with biopsy tissues

Biopsy tissue is a difficult sample to gain for the identification of potential pathogen in the clinical laboratory. At present, there are no effective culture methods for small-sized biopsy tissue. In this study, we propose a novel tissue biopsy culture method based on Myco/F lytic liquid culture system, namely, tissue was grinded before injected into culture bottles. More types and numbers of fungi are cultivated using this culture system than sputum or BALF culture. A few of mycobacteria were also detected with ground tissues. The method may be a promising alternative to or supplement for the traditional plate culture in clinical practice.

microbiology↗

bioRxiv2020

iterb-PPse: Identification of transcriptional terminators in bacterial by incorporating nucleotide properties into PseKNC

Terminator is a DNA sequence that give the RNA polymerase the transcriptional termination signal. Identifying terminators correctly can optimize the genome annotation, more importantly, it has considerable application value in disease diagnosis and therapies. However, accurate prediction methods are deficient and in urgent need. Therefore, we proposed a prediction method "iterb-PPse" for terminators by incorporating 47 nucleotide properties into PseKNC- I and PseKNC- II and utilizing Extreme Gradient Boosting to predict terminators based on Escherichia coli and Bacillus subtilis. Combing with the preceding methods, we employed three new feature extraction methods K-pwm, Base-content, Nucleotidepro to formulate raw samples. The two-step method was applied to select features. When identifying terminators based on optimized features, we compared five single models as well as 16 ensemble models. As a result, the accuracy of our method on benchmark dataset achieved 99.88%, higher than the existing state-of-the-art predictor iTerm-PseKNC in 100 times five-fold cross-validation test. Its prediction accuracy for two independent datasets reached 94.24% and 99.45% respectively. For the convenience of users, a software was developed with the same name on the basis of "iterb-PPse". The open software and source code of "iterb-PPse" are available at https://github.com/Sarahyouzi/iterb-PPse.

bioinformatics↗

bioRxiv2019

Slicing the genome of star-fruit (Averrhoa carambola L.)

The Averrhoa carambola is commonly known as star fruit because of its peculiar shape and its fruit is a rich source of minerals and vitamins. It is also used in traditional medicines in countries like India, China, the Philippines, and Brazil for treating various ailments such as fever, diarrhea, vomiting, and skin disease. Here we present the first draft genome of the Oxalidaceae family with an assembled genome size of 470.51 Mb. In total, 24,726 protein-coding genes were identified and 16,490 genes were annotated using various well-known databases. The phylogenomic analysis confirmed the evolutionary position of the Oxalidaceae family. Based on the gene functional annotations, we also discovered the enzymes possibly involved in the important nutritional pathways in star fruit genome. Overall, being the first sequenced genome in the Oxalidaceae family, the data provides an essential resource for the nutritional, medicinal, and cultivational studies for this economically important star-fruit plant.

genomics↗

bioRxiv2019

A literature mining method to judge whether there are uncertaintiesin empirical-dependent antineoplastic drug distribution in specificclinical scenarios.

Cancer clinical practice guidelines recommend different treatment options for different cancer types and are mainly developed by clinicians. In theory, those recommendation schemes that are supported by scientific research should provide better efficacy for patients. However, in actual clinical practice: "Is the choice of a specific antineoplastic drug for a specific cancer supported by the results of molecular biology mechanisms or based on the subjective experience of the clinician?" Answering this question is of significant importance for guiding clinical practice, but there is currently no operational method to provide objective judgment in specific cases. This paper describes a literature mining method that collates information from specific antineoplastic drug-related literature to establish an antineoplastic drug-gene association matrix for global or specific cancer scenarios, and further establishes a standard model and scenario models. Based on the parameters of these models, we constructed a linear regression analysis method to evaluate whether the models in different scenarios deviated from a random distribution. Finally, we determined the possible efficacy of an antineoplastic drug in different cancer types, which was validated by the Genomics of Drug Sensitivity in Cancer (GDSC) database. Using our mining method, we tested 18 antineoplastic drugs in 16 cancer types. We found that cisplatin used in ovarian cancer was more efficacious and may benefit patients more than when used in breast cancer, which provides a new paradigm for rational knowledge-driven drug distribution patterns in clinical practice.

bioinformatics↗

bioRxiv2019

Accurate MS-based Rab10 phosphorylation stoichiometry determination as readout for LRRK2 activity in Parkinson’s disease

Pathogenic mutations in the Leucine-rich repeat kinase 2 (LRRK2) are the predominant genetic cause of Parkinsons disease (PD). They increase its activity, resulting in augmented Rab10-Thr73 phosphorylation and conversely, LRRK2 inhibition decreases pRab10 levels. However, there is no assay to quantify pRab10 levels for drug target engagement or patient stratification. We developed an ultra-sensitive targeted mass spectrometry (MS)-based assay for determining Rab10-Thr73 phosphorylation stoichiometry in human samples. It uses synthetic stable isotope-labeled (SIL) analogues for both phosphorylated and non-phosphorylated tryptic peptides surrounding Rab10-Thr73 to directly derive the percentage of Rab10 phosphorylation from attomole amounts of the endogenous phosphopeptide. We test the reproducibility of our assay by determining Rab10-Thr73 phosphorylation stoichiometry in human neutrophils before and after LRRK2 inhibition. Compared to healthy controls, neutrophils of LRRK2 G2019S and VPS35 D620N carriers robustly display 1.4-fold and 3.7-fold increased pRab10 levels, respectively. Our generic MS-based assay further establishes the relevance of pRab10 as a prognostic PD marker and is a powerful tool for determining LRRK2 inhibitor efficacy and for stratifying PD patients for LRRK2 inhibitor treatment.

biochemistry↗

bioRxiv2019

Protein profiling reveals the characteristic changes of complement cascade pathway in the tissues of gastric signet ring cell carcinoma

Signet ring cell carcinoma (SRCC) is a histological subtype of gastric cancer that has distinct features in cellular morphology, epidemiology and clinicopathology compared with adenocarcinomas (ACs). Lacking of systematically molecular overview to this disease made a slow progress in diagnosis and therapy for SRCC. In the present proteomics study, the gastric tissues were collected from tumor and adjacent regions including 14 SRCC and 34 AC cases, and laser capture microdissection (LCM) was employed to eradicate cellular heterogeneity of the tissues. Over 6,000 proteins were quantified through data independent acquisition (DIA) mass spectrometry (MS). The quantitative profiles of proteomes in tumor tissues, either AC or SRCC, were dramatically different from that in the corresponding adjacencies, whereas the SRCC proteomes appeared not distinguishable to the AC proteomes via hierarchical clustering. However, focusing on univariate analysis and pathway enrichment unrevealed that some proteins and pathways bared the differences between SRCC and ACs. Importantly, the abundance changes for a bulk of proteins involved in complement cascade were highly associated with SRCC but not so sensitive to the AC status. A hypothesis, therefore, was proposed that the complement cascade was evoked in the SRCC microenvironment upon infiltration, while the SRCC cells survived from the complement cytotoxicity by secreting negative regulators. Moreover, an attempt was made to seek appropriate cell model for gastric SRCC, through proteomic comparison of the 15 gastric cell lines and the gastric tumors. The prediction upon supervised classifier suggested none of these gastric cell lines qualified in mimic to SRCC.

cell biology↗

bioRxiv2019

An evaluation model for aboveground biomass Based on Hyperspectral Data from field and TM8 in Khorchin grassland, China

Biomass is an important indicator for monitoring vegetation degradation and productivity. This study tests the applicability of Hyperspectral Remote-Sensing in situ measurements for high-precision estimation aboveground biomass (AGB) on regional scales of Khorchin grassland landscape in Inner Mongolia, China. Field experiments were carried out which collected hyperspectral data with a portable visible/NIR hyperspectral spectrometer (SOC 710), and collected aboveground net primary productivity (ANPP). Ground spectral models were then developed to estimate ANPP from the normalized difference vegetation index (NDVI), which was measured in the field following the same method as that of the Thematic Mapper(TM) from the Landsat 8 land imager (TM_NDVI). Regression analysis was used to assess the relationship between ANPP and NDVI based on coefficients of determination (R2) and error analysis. The estimation of ANPP had unique optimal regression models. By comparing the different spectral inversion models, we selected an exponential model associating ANPP with NDVI (ANPP = 12.523*e3.370*(0.462*TM_NDVI+0.413), standard error = 24.74 g m-2, R2 = 0.636, P < 0.001). This study suggests that the model can be used to monitor the condition and estimate the productivity of grassland at regional scales. The results still show a high potential to map grassland degradation proxies on the ground hyperspectral model. Thus, this study presents biomass hyperspectral inversion technology to remotely detect and monitor grassland degradation and productivity at high precision.

ecology↗

bioRxiv2019

Harmonization of large multi-site imaging datasets: Application to 10,232 MRIs for the analysis of imaging patterns of structural brain change throughout the lifespan

As medical imaging enters its information era and presents rapidly increasing needs for big data analytics, robust pooling and harmonization of imaging data across diverse cohorts with varying acquisition protocols have become critical. We describe a comprehensive effort that merges and harmonizes a large-scale dataset of 10,232 structural brain MRI scans from participants without known neuropsychiatric disorder from 18 different studies that represent geographic diversity. We use this dataset and multi-atlas-based image processing methods to obtain a hierarchical partition of the brain from larger anatomical regions to individual cortical and deep structures and derive normative age trends of brain structure through the lifespan (3 to 96 years old). Critically, we present and validate a methodology for harmonizing this pooled dataset in the presence of nonlinear age trends. We provide a web-based visualization interface to generate and present the resulting age trends, enabling future studies of brain structure to compare their data with this normative reference of brain development and aging, and to examine deviations from normative ranges, potentially related to disease.

bioinformatics↗

bioRxiv2019

Identification of gut microbiome markers for schizophrenia delineates a potential role of Streptococcus

Emerging evidence has linked the gut microbiota to schizophrenia. However, the functional changes in the gut microbiota and the biological role of individual bacterial species in schizophrenia have not been explored systematically. Here, we characterized the gut microbiota in schizophrenia using shotgun metagenomic sequencing of feces from a discovery cohort of 90 drug-free patients and 81 controls, as well as a validation cohort of 45 patients taking antipsychotics and 45 controls. We screened 83 schizophrenia-associated bacterial species and constructed a classifier comprising 26 microbial biomarkers that distinguished patients from controls with a 0.896 area under the receiver operating characteristics curve (AUC) in the discovery cohort and 0.765 AUC in the validation cohort. Our analysis of fecal metagenomes revealed that schizophrenia-associated gut-brain modules included short-chain fatty acids synthesis, tryptophan metabolism, and synthesis/degradation of neurotransmitters including glutamate, {gamma}-aminobutyric acid, and nitric oxide. The schizophrenia-enriched gut bacterial species include several oral cavity-resident microbes, such as Streptococcus vestibularis. We transplanted Streptococcus vestibularis into the gut of the mice with antibiotic-induced microbiota depletion to explore its functional role. We observed that this microbe transiently inhabited the mouse gut and this was followed by hyperactivity and deficit in social behaviors, accompanied with altered neurotransmitter levels in peripheral tissues. In conclusion, our study identified 26 schizophrenia-associated bacterial species representing potential microbial targets for future treatment, as well as gut-brain modules, some of which may give rise to new microbial metabolites involved in the development of schizophrenia.

microbiology↗

bioRxiv2019

Reconstruction and functional annotation of Ascosphaera apis full-length transcriptome via PacBio single-molecule long-read sequencing

Ascosphaera apis is a widespread fungal pathogen of honeybee larvae that results in chalkbrood disease, leading to heavy losses for the beekeeping industry in China and many other countries. This work was aimed at generating a full-length transcriptome of A. apis using PacBio single-molecule real-time (SMRT) sequencing. Here, more than 23.97 Gb of clean reads was generated from long-read sequencing of A. apis mecylia, including 464,043 circular consensus sequences (CCS) and 394,142 full-length non-chimeric (FLNC) reads. In total, we identified 174,095 high-confidence transcripts covering 5141 known genes with an average length of 2728 bp. We also discovered 2405 genic loci and 11,623 isoforms that have not been annotated yet within the current reference genome. Additionally, 16,049, 10,682, 4520 and 7253 of the discovered transcripts have annotations in the Non-redundant protein (Nr), Clusters of Eukaryotic Orthologous Groups (KOG), Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. Moreover, 1205 long non-coding RNAs (lncRNAs) were identified, which have less exons, shorter exon and intron lengths, shorter transcript lengths, lower GC percent, lower expression levels, and fewer alternative splicing (AS) evens, compared with protein-coding transcripts. A total of 253 members from 17 transcription factor (TF) families were identified from our transcript datasets. Finally, the expression of A. apis isoforms was validated using a molecular approach. Overall, this is the first report of a full-length transcriptome of entomogenous fungi including A. apis. Our data offer a comprehensive set of reference transcripts and hence contributes to improving the genome annotation and transcriptomic study of A. apis.

molecular biology↗

bioRxiv2019

Regularized-Ncut: Robust and homogeneous functional parcellation of neonate and adult brain networks

Brain network parcellation based on resting-state functional MRI (rs-fMRI) is affected by noise, resulting in spurious small patches and decreased functional homogeneity within each network. Robust and homogeneous parcellation of neonate brain is more difficult with neonate rs-fMRI associated with higher level of noise and no functional atlas as spatial constraints. To meet these challenges, we developed a novel data-driven Regularized Normalized-cut (RNcut) method. RNcut is formulated by adding two regularization terms, a smoothing term using Markov random fields and a small-patch removal term, to conventional normalized-cut (Ncut) method. The RNcut and competing methods were tested with simulated datasets with known ground truth and then applied to both adult and neonate rs-fMRI datasets. Based on the parcellated networks generated by RNcut, intra-network connectivity was quantified. The test results from simulated datasets demonstrated that the RNcut method is more robust (p<0.01) to noise and can delineate parcellated functional networks with significantly better (p<0.01) spatial contiguity and significantly higher (p<0.01) functional homogeneity than competing methods. Application of RNcut to neonate and adult rs-fMRI dataset revealed distinctive functional brain organization of neonate brains from that of adult brains. Collectively, we developed a novel data-driven RNcut method by integrating conventional Ncut with two regularization terms, generating robust and homogeneous functional parcellation without imposing spatial constraints. A broad range of brain network applications and analyses, especially exploratory investigations of parcellating neonate and infant brain with noisy dataset, can potentially benefit from this RNcut method.

neuroscience↗

bioRxiv2019

Post-EMT: Cadherin-11 mediates cancer hijacking fibroblasts

Current prevailing knowledge on EMT (epithelial mesenchymal transition) deems epithelial cells acquire the characters of mesenchymal cells to be capable of invading and metastasizing on their own. One of the signature events of EMT is called "cadherin switch", e.g. the epithelial E-cadherin switching to the mesenchymal Cadherin-11. Here, we report the critical events after EMT that cancer cells utilize cadherin-11 to hijack the endogenous cadherin-11 positive fibroblasts. Numerous 3-D cell invasion assays with high-content live cell imaging methods reveal that cadherin-11 positive cancer cells adhere to and migrate back and forth dynamically on the cell bodies of fibroblasts. By adhering to fibroblasts for co-invasion through 3-D matrices, cancer cells acquire higher invasion speed and velocity, as well as significantly elevated invasion persistence, which are exclusive characteristics of fibroblast invasion. Silencing cadherin-11 in cancer cells or in fibroblasts, or in both, significantly decouples such physical co-invasion. Additional bioinformatics studies and PDX (patient derived xenograft) studies link such cadherin-11 mediated cancer hijacking fibroblasts to the clinical cancer progression in human such as triple-negative breast cancer patients. Further animal studies confirm cadherin-11 mediates cancer hijacking fibroblasts in vivo and promotes significant solid tumor progression and distant metastasis. Moreover, overexpression of cadherin-11 strikingly protects 4T1-luc cells from implant rejection against firefly luciferase in immunocompetent mice. Overall, our findings report and characterize the critical post-EMT event of cancer hijacking fibroblasts in cancer progression and suggest cadherin-11 can be a therapeutic target for solid tumors with stroma. Our studies hence provide significant updates on the "EMT" theory that EMT cancer cells can hijack fibroblasts to achieve full mesenchymal behaviors in vivo for efficient homing, growth, metastasis and evasion of immune surveillance. Our studies also reveal that cadherin-11 is the key molecule that helps link cancer cells to stromal fibroblasts in the "Seed & Soil" theory. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=117 SRC="FIGDIR/small/729491v2_ufig1.gif" ALT="Figure 1"> View larger version (40K): org.highwire.dtl.DTLVardef@11317f1org.highwire.dtl.DTLVardef@88fffaorg.highwire.dtl.DTLVardef@5da692org.highwire.dtl.DTLVardef@62f6ed_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2019

ALS Motor Neurons Exhibit Hallmark Metabolic Defects That Are Rescued by Nicotinamide and SIRT3 Activation

Motor neurons (MNs) are highly energetic cells and recent studies suggest that altered energy metabolism precede MN loss in Amyotrophic Lateral Sclerosis (ALS), an age-onset neurodegenerative disease. However, clear mechanistic insights linking altered metabolism and MN death are still missing. In this study, induced pluripotent stem cells (iPSCs) from healthy controls, familial ALS and sporadic ALS patients were differentiated towards spinal MNs, cortical neurons and cardiomyocytes. Metabolic flux analyses reveal a MN-specific deficiency in mitochondrial respiration in ALS. Intriguingly, all forms of familial and sporadic ALS MNs tested in our study exhibited similar defective metabolic profiles, which were attributed to hyper-acetylation of mitochondrial proteins. In the mitochondria, SIRT3 functions as a mitochondrial deacetylase to maintain mitochondrial function and integrity. We found that activating SIRT3 using nicotinamide or a small molecule activator reversed the defective metabolic profiles in all our ALS MNs, as well as correct a constellation of ALS-associated phenotypes.

neuroscience↗

bioRxiv2019

Increased Mistranslation Protects E. coli from Protein Misfolding Stress due to Activation of a RpoS-dependent Heat Shock Response

The misincorporation of an incorrect amino acid into a polypeptide during protein synthesis is considered a detrimental phenomenon. Mistranslated protein is often misfolded and degraded or non-functional and results in an increased cost to quality control machinery. Despite these costs, errors during protein synthesis are common in bacteria. Here we report that increased rates of mistranslation in Escherichia coli provide protection from protein misfolding stress by increasing the level of the heat shock sigma factor, RpoH. Surprisingly, this increase in RpoH due to mistranslation is dependent on the presence of the general stress response sigma factor, RpoS. This report provides evidence for a protective function of mistranslation and suggests a novel regulatory role of RpoS on the RpoH-activated heat shock.

microbiology↗