Biology subjects

Peng, Y.

Publications and source records attributed to Peng, Y..

At least 235 records · Page 13Linked to original sources

bioRxiv2019

Epigenetic Effects of Assisted Reproductive Technology in Human Offspring

The births of more than 8 million infants have been enabled globally through assisted reproductive technologies (ARTs), including conventional in vitro fertilization (IVF) and intracytoplasmic sperm injection (ICSI) with either fresh embryo transfer (ET) or frozen embryo transfer (FET). However, the potential for elevated risks of ART-related disorders persists in adult life, and the underlying epigenetic mechanisms are largely uncharacterized. Here, we recruited 100 nuclear families and profiled the DNA methylomes, genome-wide histone modifications and transcriptomes to clarify the inherent extra risks attributable to specific ART procedures. We discovered that IVF-ET seemed to introduce less disturbance into the infant epigenome than IVF-FET or ICSI-ET did. Furthermore, we noted approximately half of the DNA methylomic changes in ART-conceived offspring could be explained by parental background biases. Through removal of the parental effect, we confirmed that ART per se would introduce minor DNA methylation changes locally. More importantly, we found that ART-induced epigenomic alterations were highly enriched in the processes which might contribute to increased incidence of preeclampsia during pregnancy and metabolic syndrome in offspring. Overall, our study provides an epigenetic basis for the potential long-term health risks in ART-conceived offspring that reinforces the need to review all methods of human ART.

genetics↗

bioRxiv2019

AKT2 deficiency causes sarcopenia and metabolic disorder of skeletal muscle

Skeletal muscle is responsible for the majority of glucose disposal in the body. Insulin resistance in the skeletal muscle accounts for 85-90% of the impairment of total body glucose disposal in patients with tye 2 diabetes (T2D). However, the mechanism remains controversial. AKT2 is a protein kinase performing important functions in the regulation of glucose metabolism. We observed that mice deficient for AKT2 (AKT2 KO) exhibited decreased body weight and lean mass and showed impaired glucose tolerance, compared to their age- and gender-matched wild type mice (WT). Therefore, to test whether AKT2 deficiency causes deficits in skeletal muscle development and metabolism, we analyzed the expression of molecules related to skeletal muscle development, glucose uptake and metabolism in young (3 months) and old (8 months) mice. We found that AMPK phosphorylation and MEF2A expression were downregulated in young AKT2 KO mice, and this downregulation was inverted by AMPK activation. We also observed reduced mtDNA abundance and reduced expression of genes involved in mitochondrial biogenesis in the skeletal muscle of adult AKT2 KO mice, which was prevented by AMPK activation. However, GLUT4 expression was regulated by AKT2 in an AMPK-independent manner in skeletal muscle. During high-fat-diet (HFD)-induced obesity, AKT2 KO mice exhibited increased insulin resistance compared to WT mice. Our study establishes a new and important function of AKT2 in regulating glucose uptake and AMPK-dependent development and mitochondrial biogenesis in skeletal muscle.

molecular biology↗

bioRxiv2019

A novel machine learning based approach for iPS progenitor cell identification

Identification of induced pluripotent stem (iPS) progenitor cells, the iPS forming cells in early stage of reprogramming, could provide valuable information for studying the origin and underlying mechanism of iPS cells. However, it is very difficult to identify experimentally since there are no biomarkers known for early progenitor cells, and only about 6 days after reprogramming initiation, iPS cells can be experimentally determined via fluorescent probes. What is more, the ratio of progenitor cells during early reprograming period is below 5%, which is too low to capture experimentally in the early stage.\n\nIn this paper, we propose a novel computational approach for the identification of iPS progenitor cells based on machine learning and microscopic image analysis. Firstly, we record the reprogramming process using a live cell imaging system after 48 hours of infection with retroviruses expressing Oct4, Sox2 and Klf4, later iPS progenitor cells and normal murine embryonic fibroblasts (MEFs) within 3 to 5 days after infection are labeled by retrospectively tracing the time-lapse microscopic image. We then calculate 11 types of cell morphological and motion features such as area, speed, etc., and select best time windows for modeling and perform feature selection. Finally, a prediction model using XGBoost is built based on the selected six types of features and best time windows. Our model allows several missing values/frames in the sample datasets, thus it is applicable to a wide range of scenarios.\n\nCross-validation, holdout validation and independent test experiments showed that the minimum precision is above 52%, that is, the ratio of predicted progenitor cells within 3 to 5 days after viral infection is above 52%. The results also confirmed that the morphology and motion pattern of iPS progenitor cells is different from that of normal MEFs, which helps with the machine learning methods for iPS progenitor cell identification.\n\nAuthor SummaryIdentification of induced pluripotent stem (iPS) progenitor cells could provide valuable information for studying the origin and underlying mechanism of iPS cells. However, it is very difficult to identify experimentally since there are no biomarkers known for early progenitor cells, and only after about 6 days of induction, iPS cells can be experimentally determined via fluorescent probes. What is more, the percentage of the progenitor cells during the early induction period is below 5%, too low to capture experimentally in early stage. In this work, we proposed an approach for the identification of iPS progenitor cells, the iPS forming cells, based on machine learning and microscopic image analysis. The aim is to help biologists to enrich iPS progenitor cells during the early stage of induction, which allows experimentalists to select iPS progenitor cells with much higher probability, and furthermore to study the biomarkers which trigger the reprogramming process.

bioinformatics↗

bioRxiv2019

From phages to mammalian viruses: viral receptors play a central role in protein-protein interaction network

MotivationReceptors on host cells play a critical role in viral infection. How phages select receptors is still unknown.\n\nResultsHere, we manually curated a high-quality database named phageReceptor, including 355 pairs of phage-host receptor interactions, 280 unique viral species or sub-species and 64 bacterial species. Sugars and proteins were most widely used by phages as receptors. The receptor usage of phages in Gram-positive bacteria was different from that in Gram-negative bacteria. Most protein receptors were located on the outer membrane. The protein receptors were highly diverse in their structures, and had little homology with mammalian virus receptors. Further functional characterization of phage protein receptors in Escherichia coli showed that they had larger node degrees and betweennesses in the protein-protein interaction (PPI) network, and higher expression levels, than other outer membrane proteins, plasma membrane proteins, or other intracellular proteins. These findings were consistent with what observed for mammalian virus receptors, suggesting that viral protein receptors play a central role in the hosts PPI network. The study deepens our understanding of virus-host interactions.\n\nAvailabilityThe database of phageReceptor is publicly accessible at http://www.computationalbiology.cn/viralRecepetor/index.html.

microbiology↗

bioRxiv2019

Experimental study of lumbar ligamentum flavum hypertrophy induced in bipedal mice

Lumbar spinal stenosis (LSS) is a common degenerative disease among the elderly. The role that mechanical stress-induced hypertrophic ligamentum flavum (HLF) plays in patients with LSS remains unclear. Here, we used a finite element analysis to investigate the stress characteristics on the ligamentum flavum (LF) and evaluate the feasibility of a mouse model of HLF. First, we induced a bipedal posture in mice by taking advantage of their hydrophobia. A micro-CT scan was performed to examine their spinal change during bipedal posture. A finite element analysis showed that the stress and strain on the upright posture were significantly increased compared with those on the sprawling posture. Tissue staining showed that the degeneration degree of the LF in bipedal standing group gradually increased over the modeling period. The amount of elastic fibers decreased under HLF, whereas the amount of collagen fibers, the number of the LF cells, and the expression of fibrosis-related factors increased. Compared with aged group, LF degeneration was more severe in the bipedal standing group. Our findings demonstrate that the increased stress caused by a posture change causes HLF and that a bipedal mouse model can be used to study HLF in vivo.

biophysics↗

bioRxiv2019

G protein-coupled potassium channels implicated in mouse and cellular models of GNB1 Encephalopathy

De novo mutations in GNB1, encoding the G{beta}1 subunit of G proteins, cause a neurodevelopmental disorder with global developmental delay and epilepsy. Mice carrying a pathogenic mutation, K78R, recapitulate aspects of the disorder, including developmental delay and frequent spike-wave discharges (SWD). Cultured mutant cortical neurons display aberrant bursting activity on multi-electrode arrays. Strikingly, the antiepileptic drug ethosuximide (ETX) restores normal neuronal network behavior in vitro and suppresses SWD in vivo. In contrast, while valproic acid suppresses SWD, it does not restore normal network behavior, suggesting that ETX has mechanistic specificity for the effects of aberrant G{beta}1 signaling. Consistent with this, we show that K78R is a gain-of-function of G protein-coupled potassium channel (GIRK) activation that is potently inhibited by ETX. This work suggests that altered G{beta}1 signaling causes disease in part through effects on GIRK channels, illustrates the utility of cultured neuronal networks in pharmacological screening, and establishes effective pre-clinical models for GNB1 Encephalopathy.

neuroscience↗

bioRxiv2019

High-throughput microcircuit analysis of individual human brains through next-generation multineuron patch-clamp

Comparing neuronal microcircuits across different brain regions, species and individuals can reveal common and divergent principles of network computation. Simultaneous patch-clamp recordings from multiple neurons offer the highest temporal and subthreshold resolution to analyse local synaptic connectivity. However, its establishment is technically complex and the experimental performance is limited by high failure rates, long experimental times and small sample sizes. We introduce an in-vitro multipatch setup with an automated pipette pressure and cleaning system facilitating recordings of up to 10 neurons simultaneously and sequential patching of additional neurons. We present hardware and software solutions that increase the usability, speed and data throughput of multipatch experiments which allowed probing of 150 synaptic connections between 17 neurons in one human cortical slice and screening of over 600 connections in tissue from a single patient. This method will facilitate the systematic analysis of microcircuits and allow unprecedented comparisons at the level of individuals.

neuroscience↗

bioRxiv2019

Comparative analysis of the Accelerated Aged seed transcriptome profiles of maize CSSLs (I178 and X178)

Seed longevity is one of the most essential characters of seed quality. Two Chromosome segment substitution lines (CSSL) I178 and X178 with significant difference on seed longevity were subjected to transcriptome sequencing before (0d-AA) and after five days of accelerated ageing (5d-AA) treatments. Compared to the non-accelerated ageing treatment (0d-AA), 286 and 220 differential expressed genes (DEGs) were identified in I178 and X178, respectively Among those, 98 DEGs were detected in both I178 and X178 after 5d-AA, Enriched GO terms included cellular components of cell part, intracellular part, organelle and membrane etc., including carbohydrate derivative catabolic process, carbohydrate synthesis, sugar isomerase (SIS) family protein etc. Transcriptome analysis of I178 and X178 showed that Alternative splicing (AS) occurs in 63.6% of the expressed genes in all samples. Only 381 genes specifically occurred AS in I178 and X178 after 5d-AA, mostly enriched in nucleotide and nucleoside binding. Combined with the reported QTL mapping result, the DEG and the AS information, 13 DEGs in the mapping intervals and 7 AS-DEGs were potential candidates may directly or indirectly associated to seed ageing.

plant biology↗

bioRxiv2019

Targeted mRNA demethylation using an engineered dCas13b-ALKBH5 fusion protein

Studies on biological functions of N6-methyladenosine (m6A) modification in mRNA have sprung up in recent years. Here we construct and characterize a CRISPR-Cas13b-based tool for the first time that targeted m6A methylation of mRNA by fusing the catalytically dead Type VI-B Cas13 enzyme from Prevotella sp.P5-125 (dPspCas13b) with the m6A demethylase ALKBH5, which is named as dm6ACRISPR. Subsequently, such system is shown to specific demethylase the m6A of target mRNA such as CYB5A to increase its mRNA stability. In addition, the dm6ACRISPR system appeared to afford efficient demethylation of the target genes with tenuous off-target effects. Together, we provide a programmable and in vivo manipulation tool to study mRNA modification and its potential biological functions of specific gene.

cell biology↗

bioRxiv2019

Identification of viruses with the potential to infect human

The virus has caused much mortality and morbidity to humans, and still posed a serious threat to the global public health. The virome with the human-infection potential is far from complete. Novel viruses have been discovered at an unprecedented pace as the rapid development of viral metagenomics. However, there is still a lack of a method for rapidly identifying the virus with the human-infection potential. This study built several machine learning models for discriminating the human-infecting viruses from other viruses based on the frequency of k-mers in the viral genomic sequences. The k-nearest neighbor (KNN) model could predict the human-infecting virus with an accuracy of over 90%. Even for the KNN models built on the contigs as short as 1kb, they performed comparably to those built on the viral genomes, suggesting that the models could be used to identify the human-infecting virus from the viral metagenomic sequences. This work could help for discovery of novel human-infecting virus in metagenomics studies.

bioinformatics↗

bioRxiv2019

Prediction of antiviral drugs against African Swine Fever Viruses based on protein-protein interaction analysis

The African swine fever virus (ASFV) has severely influenced the swine industry of the world. Unfortunately, there is no effective antiviral drug or vaccine against the virus until now. Identification of new anti-ASFV drugs is urgently needed. Here, an up-to-date set of protein-protein interactions (PPIs) between ASFV and swine were curated by integration of PPIs from multiple sources. Thirty-two swine proteins were observed to interact with ASFVs and were defined as AIPs. They were found to play a central role in the swine PPI network, with significant larger degree, betweenness and smaller shortest path length than other swine proteins. Some of AIPs also interacted with several other viruses and could be taken as potential targets of drugs for broad-spectrum effect, such as HSP90AB1. Finally, the antiviral drugs which targeted AIPs and ASFV proteins were predicted. Several drugs with either broad-spectrum effect or high specificity on AIPs were identified, such as Polaprezinc. This work could not only deepen our understanding towards the ASFV-swine interactions, but also help for the development of effective antiviral drugs against the ASFVs.

bioinformatics↗

bioRxiv2019

Composition and structure of synaptic ectosomes exporting antigen receptor linked to functional CD40 ligand from helper T-cells

Cell communication through extracellular vesicles is an emerging topic in biology, including communication between cells of the immune system. Planar supported lipid bilayers (PSLBs) presenting T cell receptor (TCR) ligands and intercellular adhesion molecule-1 (ICAM-1) induce budding of extracellular microvesicles enriched in functional TCR, defined here as synaptic ectosomes (SE), from helper T cells. SE bind peptide-MHC directly exporting TCR into the synaptic cleft, but their ability to incorporate other effectors is unknown. Here, we utilized bead supported lipid bilayers (BSLB) to capture SE from single immunological synapses (IS), determined SE composition by immunofluorescence flow cytometry and enriched SE for proteomic analysis by particle sorting. Our results demonstrate selective enrichment of CD40 ligand (CD40L) and inducible T-cell costimulator (ICOS) in SE in response to addition of CD40 and ICOS ligand (ICOSL), respectively, to SLB presenting TCR ligands and ICAM-1. TCR triggering mobilized intracellular CD40L to the T cells surface at the IS, where it engaged CD40 to enable sorting into SE. SEs were enriched in tetraspanins and bone marrow stromal cell antigen 2 (BST-2) by immunofluorescence and TCR signalling and endosomal sorting complexes required for transport by proteomics. Super-resolution microscopy demonstrated that CD40L is present in microclusters within CD81 defined SE that are spatially segregated from TCR/ICOS/BST-2 microclusters. CD40L in SE retains the capacity to induce dendritic cell (DC) maturation and cytokine production. SE enabled helper T cells to release effectors physically linked to TCR. One Sentence SummaryTCR and CD40L microclusters can be linked in synaptic ectosomes (extracellular vesicles) that are released in the immunological synapse by helper T cells and induce dendritic cell maturation and cytokine production.

immunology↗

bioRxiv2019

Neural and computational mechanisms of analogical reasoning

The ability to generate and process semantic relations is central to many aspects of human cognition. Theorists have long debated whether such relations are coded as atomistic links in a semantic network, or as distributed patterns over some core set of abstract relations. The form and content of the conceptual and neural representations of semantic relations remains to be empirically established. The present study combined computational modeling and neuroimaging to investigate the representation and comparison of abstract semantic relations in the brain. By using sequential presentation of verbal analogies, we decoupled the neural activity associated with encoding the representation of the first-order semantic relation between words in a pair from that associated with the second-order comparison of two relations. We tested alternative computational models of relational similarity in order to distinguish between rival accounts of how semantic relations are coded and compared in the brain. Analyses of neural similarity patterns supported the hypothesis that semantic relations are coded, in the parietal cortex, as distributed representations over a pool of abstract relations specified in a theory-based taxonomy. These representations, in turn, provide the immediate inputs to the process of analogical comparison, which draws on a broad frontoparietal network. This study sheds light not only on the form of relation representations but also on their specific content.\n\nSignificanceRelations provide basic building blocks for language and thought. For the past half century, cognitive scientists exploring human semantic memory have sought to identify the code for relations. In a neuroimaging paradigm, we tested alternative computational models of relation processing that predict patterns of neural similarity during distinct phases of analogical reasoning. The findings allowed us to draw inferences not only about the form of relation representations, but also about their specific content. The core of these distributed representations is based on a relatively small number of abstract relation types specified in a theory-based taxonomy. This study helps to resolve a longstanding debate concerning the nature of the conceptual and neural code for semantic relations in the mind and brain.

neuroscience↗

bioRxiv2019

Enhancer-promoter association determines Sox2 transcription regulation in mouse pluripotent cells

Distal enhancer-promoter associations are essential for transcription control and emerging as a common epigenetic way to determine gene expression in eukaryotes. However, it remains as an uncultivated land on how their diversity influences gene transcription during development. In this study, we select three defined Sox2 associated enhancers (E1, E2 and E3), representing different distal interaction categories, to further explore their biological effects. We construct three enhancer-knockout cells via CRISPR/Cas9 system in mouse embryonic stem cells. Results show that these associations carry out various biological features. Embryonic stem cell specific association (E1) speeds up cell cycle and involves in cardiac development, which has been validated in vivo. In contrast, the indirect one (E2) restrains nerve differentiation and has potential effect on lipid metabolism. The common one (E3) promotes nerve differentiation and inhibits oxidation-reduction process. Together, these different associations determine Sox2 transcription and function specificity in mouse embryonic stem cells. Our study will enable a way for exploring miscellaneous spatiotemporal gene transcription control and advancing quantitative knowledge by utilizing three-dimensional genomic information.\n\nSummary statementSox2 transcription is complicated in mouse embryonic stem cells. It involves in heavily enhancer-promoter associations, which might make it a suitable model for phase-separation study. To decompose this cooperative regulation, diverse interactions are investigated. The biological effects have been explored in multiple perspectives. This may represent a quantitative way to explore and a potential new strategy to transcription control study.

molecular biology↗

bioRxiv2019

Rapid Detection of Burkholderia pseudomallei with a Lateral Flow Recombinase Polymerase Amplification Assay

Melioidosis is a severe infectious disease caused by gram-negative, facultative intracellular pathogen Burkholderia pseudomallei (B. pseudomallei). Although cases are increasing reported from other parts of the world, it is an illness of tropical and subtropical climates primarily found in southeast Asia and northern Australia. Because of a 40% mortality rate, this life-threatening disease poses a public health risk in endemic area. Early detection of B. pseudomallei infection benefits greatly to implement effective treatment timely, which is vital for prognosis of a melioidosis patient. In this study, a novel isothermal recombinase polymerase amplification combined with lateral flow dipstick (LF-RPA) assay was established for rapid detection of B.pseudomallei. A set of probe and primers targeting orf2 gene of B. pseudomallei were generated and parameters for the LF-RPA assay were optimized. Result can be easy visualized in 30 minutes with the limit of detection (LoD) as low as 20 femtogram (ca. 25.6 copies) of B. pseudomallei genomic DNA. The assay is highly specific as no cross amplification was observed with 35 non-B. pseudomallei pathogens. Isolates (N=19) from patients of Hainan province of China were retrospectively confirmed by the newly developed method. LoD for B. pseudomallei spiked soil and blood samples were 2.1x103 CFU/g and 4.2x103 CFU/ml respectively. Sensitivity of the LF-RPA assay was comparable to TaqMan Real-Time PCR, however, the LF-RPA assay exhibited a better tolerant to inhibitors in blood than the later. Our results showed that the LF-RPA assay is an alternative to existing PCR-based methods for detection of B. pseudomallei with a potentiality of early accurate diagnosis of melioidosis at point of care or in-field use.

microbiology↗

bioRxiv2018

Homologous recombination shapes the genetic diversity and drives the evolution of African swine fever viruses

Recent outbreaks of African swine fever virus (ASFV) in China severely influenced the swine industry of the country. Currently, there is no effective vaccine or drugs against ASFVs. How to effectively control the virus is challenging. In this study, we have analyzed all the publicly available ASFV genomes and demonstrated that there was a large genetic diversity of ASFV genomes. Interestingly, the genetic diversity was mainly caused by extensive genomic insertions and/or deletions (indels) instead of the point mutations. The genomic diversity of the virus resulted in proteome diversity. Over 250 types of proteins were inferred from the ASFV genomes, among which only 144 were observed in all analyzed viruses. Further analyses showed that the homologous recombination may contribute much to the indels, as supported by significant associations between the occurrence of extensive recombination events and the indels in the ASFV genomes. Repeated elements of dozens of nucleotides in length were observed to widely distribute and cluster in the adjacent positions of ASFV genomes, which may facilitate the occurrence of homologous recombination. Moreover, two enzymes, which were possibly related to the homologous recombination, i.e., a Lambda-like exonuclease with a YqaJ-like viral recombinase domain, and a DNA topoisomerase II, were found to be conservative in all the analyzed ASFVs. This work highlighted the importance of the homologous recombination in the evolution of the ASFVs, and helped with the strategy development of the prevention and control of the virus.

microbiology↗

bioRxiv2018

Identification of genome-wide nucleotide sites associated with mammalian virulence in influenza A viruses

MotivationThe virulence of influenza viruses is a complex multigenic trait. Previous studies about the virulence determinants of influenza viruses mainly focused on amino acid sites, ignoring the influence of nucleotide mutations.\n\nResultsWe collected more than 200 viral strains from 21 subtypes of influenza A viruses with virulence in mammals and obtained over 100 mammalian virulence-related nucleotide sites across the genome by computational analysis. Interestingly, 50 of these nucleotide sites only experienced synonymous mutations. Further experiments showed that synonymous mutations in the top two of these nucleotide sites, i.e., PB1-2031 and PB1-633, enhanced the pathogenicity of the viruses in mice. Finally, machine-learning models with accepted accuracy for predicting mammalian virulence of influenza A viruses were built. Overall, this study highlighted the importance of nucleotide mutations, especially synonymous mutations in viral virulence, and provided rapid methods for evaluating the virulence of influenza A viruses. It could be helpful for early warning of newly emerging influenza A viruses.

microbiology↗

bioRxiv2018

Influenza incidence prediction for the United States: an update for the 2018-2019 season

IntroductionSeasonal influenza causes a high disease burden every year in the United States and worldwide. Anticipating epidemic size ahead of season can contribute to preparedness and more targetted control and prevention of seasonal influenza.\n\nMethodsA recently developed process-based epidemiological model that incorporates evolutionary change of the virus and generates incidence forecasts for the H3N2 subtype ahead of the season, was previously validated by several statistical criteria, including an accurate real-time prediction for the 2016-2017 influenza season. With this model, a new forecast is generated here for the upcoming 2018-2019 season. The accuracy of predictions published for the 2017-2018 season is also retrospectively evaluated.\n\nResultsFor 2017-2018, the model correctly predicted the dominance of the H3N2 subtype and its higher than average incidence. Based on surveillance and sequence data up to June 2018, the new forecast for the upcoming 2018-2019 season indicates low levels for H3N2, and suggests an H1N1 dominant season with low incidence of influenza B.\n\nDiscussionReal-time forecasts, those generated with a model that was parameterized based on data preceding the predicted season, allows valuable evaluation of the approach. Anticipating the dominant subtype and the size of the upcoming epidemic ahead of season informs disease control. Further studies are needed to promote more accurate ahead-of-season forecasts and extend the approach to multiple subtypes.

bioinformatics↗