Biology subjects

Yang, J.

Publications and source records attributed to Yang, J..

At least 1,009 records · Page 56Linked to original sources

bioRxiv2019

Recombinant Expression of Aldehyde Dehydrogenase 2 (ALDH2) in Escherichia coli Nissle 1917 for Oral Delivery in ALDH2-Deficient Individuals

Turning red after consuming alcohol may seem like a mere social inconvenience. Yet, this flushing response is caused by an accumulation of acetaldehyde, a carcinogenic intermediate of alcohol metabolism. Aldehyde dehydrogenase 2 (ALDH2) deficiency, the result of a point mutation, produces a less efficient ALDH2. The resulting accumulation of acetaldehyde greatly increases the risk of developing esophageal and head and neck cancers. In this study, we produced recombinant ALDH2 in the probiotic E. coli Nissle 1917, which successfully reduces acetaldehyde levels in simulated oral conditions. Packaged in a hard candy, the ALDH2-probiotic would remain in the mouth to specifically target salivary acetaldehyde. Using mathematical modeling, we also determined how much recombinant ALDH2 is needed to reduce elevated acetaldehyde levels.\n\nFinancial DisclosureThis work was funded by Taipei American School. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.\n\nCompeting InterestsThe authors have declared that no competing interests exist.\n\nEthics StatementN/A\n\nData AvailabilityYes - all data are fully available without restriction. Sequences for the plasmids used in this study are available through the Registry of Standard Biological Parts. Links to raw data are included in Supplementary Information.

synthetic biology↗

bioRxiv2019

The succession pattern of bacterial diversity in compost using pig manure mixed with wood chips analyzed by 16S rRNA gene analysis

The pig manure mixed with wood chips and formed compost by means of fermentation. We found that the protease activity, organic matter content and ammonium nitrogen concentration were higher in the early stage of composting. Meanwhile, the urease activity was highest in the high temperature period. The carbon to nitrogen ratio of the compost decreased continuously with fermentation. The dynamic change in the composition of bacterial overtime in the compost of a 180 kg piles were explored using microbial diversity analysis. The results showed that the microbial species increased with the compost fermentation. At the early stage of composting, the phyla of Firmicutes and Actinomycetes were dominant. The microbes in the high temperature period were mainly composed of Firmicutes and Proteobacteria while the proportion of Bacteroides was increased during the cooling period. In the compost of maturity stage, the proportion of Chloroflexi increased, becoming dominant species with other microorganisms including Firmicutes, Proteobacteria, Bacteroides, Chloroflexi but not Actinomycetes. Bacteria involved in lignocellulose degradation, such as those of the Thermobifida, Cellvibrio, Mycobacterium, Streptomyces and Rhodococcus, were concentrated in the maturity stages of composting. Through correlation analysis, the environmental factors including organic matter, ammonium nitrogen and temperature were consistent with the succession of microbial including Rhodocyclaceae, Anaerolineaceae, Thiopseudomonas, Sinibacillus and Tepidimicrobium. The change of urease activity and carbon to nitrogen ratio corresponded to microbial communities, mainly containing Anaerolineaceae, Rhodocyclaceae, Luteimoas, Bacillaceae, Corynebacterium, Bacillus, Anaerococcus, Lactobacillus, Ignatzschineria, and Bacillaceae.

microbiology↗

bioRxiv2019

Biased Signaling: Distinct Ligand-directed Plasma Membrane Signalsomes Using a Common RGS/G Protein Core

Biased signaling occurs when different ligands that are directed at the same receptor launch different cellular outcomes. Because of their pharmacological importance, we know the most about biased ligands and little is known about other mechanisms to achieve signaling bias. In the canonical animal G protein system, endocytosis of a 7-transmembrane GPCR is mediated by arrestins to propagate or arrest cytoplasmic signaling depending on the bias. In Arabidopsis, GPCRs are not required for G protein coupled signaling because the heterotrimeric G protein complex spontaneously exchanges nucleotide. Instead, the prototype 7-transmembrane Regulator of G Signaling 1 protein AtRGS1 modulates G signaling and through ligand-dependent endocytosis, de-repression of signaling is initiated but canonical arrestins are not involved. Endocytosis initiates from two separate pools of plasma membrane: sterol-dependent domains, possibly lipid rafts, and a clathrin-accessible neighborhood, each with a select set of discriminators, activators, and newly-discovered arrestin-like adaptors. Different trafficking origins and trajectories lead to different cellular outcomes. Thus, compartmentation with its attendant signalosome architecture is a previously unknown mechanism to drive biased signaling.

plant biology↗

bioRxiv2019

A key interfacial residue identified with in-cell structure characterization of a Class-A GPCR dimer

G protein coupled receptors (GPCRs) have been shown homo-dimeric. Despite extensive studies, no single residue has been found essential for dimerization. Lacking an efficient method to shift the monomer-dimer equilibrium also makes functional relevance of GPCR dimer elusive. Here, using fluorescence lifetime-based imaging for distance measurements, we characterize the dimeric structure of GPR17, a class A GPCR, in cells. The structure reveals transmembrane helices 5 and 6 the dimer interface, and pinpoints F229 a key residue, mutations of which can render GPR17 monomeric or dimeric. Using the resulting mutants, we show that GPR17 dimer is coupled to both Gi and Gq signaling and is internalized, whereas GPR17 monomer is coupled to Gi signaling only and is not internalized. We further show that residues equivalent to F229 of GPR17 in several other class A GPCRs are also important for dimerization. Our findings thus provide fresh insights into GPCR structure and function.

biochemistry↗

bioRxiv2019

Serum Alpha-2-Macroglobulin as an intrinsic radioprotective factor in patients undergoing thoracic radiation therapy

ObjectiveTo investigate the impact of alpha-2-macroglobulin (A2M), a suspected intrinsic radioprotectant, on radiation pneumonitis and esophagitis. Additionally, we establish multifactorial predictive models for pneumonitis and esophagitis.\n\nMaterials/MethodsBaseline A2M levels were obtained for 258 patients prior to thoracic radiotherapy (RT). Dose-volume characteristics were extracted from treatment plans. Spearmans correlation (Rs) test was used to correlate A2M levels, smoking status and dosimetric variables with toxicities. Esophagitis and pneumonitis prediction models were built using least absolute shrinkage and selection operator (LASSO) logistic regression on 1000 bootstrapped datasets. Models were built using 2/3 of the data for training and 1/3 for validation.\n\nResultsThere were 36 (14.0%) patients with grade [≥]2 pneumonitis and 61 (23.6%) with grade [≥]2 esophagitis. The median A2M level was 191 mg/dL (range: 94-511). Never/former/current smoker status was 47 (18.2%)/179 (69.4%)/32 (12.4%). We found a significant correlation between baseline A2M levels and esophagitis (Rs=-0.18/p=0.003) and between A2M and smoking status (former or current) (Rs=0.13/p=0.04) but not between A2M and pneumonitis. On univariate analysis, significant parameters for grade [≥]2 esophagitis included number of fractions (Rs=0.47/p<0.0001), treatment days (Rs=0.44/p<0.0001), chemotherapy use (Rs=0.40/p<0.0001), dose per fraction (Rs=-0.34/p<0.0001), total dose (Rs=0.29/p<0.0001), age (Rs=-0.22/p=0.0003), and several dosimetric variables in esophagus with Rs>0.5 (p<0.0001). For pneumonitis, significant clinical parameters were treatment days (Rs=0.24/p=0.0001), chemotherapy use (Rs=0.22/p=0.0004), number of fractions (Rs=0.21/p=0.0007), dose per fraction (Rs=-0.18/p=0.0035), and total dose (Rs=0.15/p=0.013). The most significant dosimetric variable in lung and heart was D70 (Rs=0.28/p<0.0001) and max dose (Rs=0.27/p<0.0001), respectively. LASSO bootstrap logistic regression models on the validation data resulted in the area under the receiver operating characteristic curve of 0.84 and 0.75 for esophagitis and pneumonitis, respectively.\n\nConclusionOur findings show an association of higher A2M values with lower risk of radiation esophagitis and smoking status. Multivariate predictive models also confirmed a role of heart dose in the risk of pneumonitis.

cancer biology↗

bioRxiv2019

Dynamic Changes of G-CSF etc. Nine Cytokines in Mouse Bloodstream Infection Models of Staphylococcus aureus and Klebsiella pneumoniae and their Clinical Performances

Blood culture has been considered as the gold standard to diagnose the bacterial bloodstream infection, but its long turnaround time gravely obstructed the clinical medication by physicians. Cytokines play an important role in bacterial infection. The purpose of this study was to monitor the kinetic changes of nine cytokines in mouse infection models and to infer their diagnostic value in early infection.\n\nMethodsThe mouse bloodstream infection model of Staphylococcus aureus and the other model of Staphylococcus aureus and Klebsiella pneumoniae were constructed respectively, and the dynamic changes of nine cytokines were monitored within 48 hours after infected with 1/2 LD50 bacterial concentration. Cytokines with significant differences between the two groups and PBS control group from 0 to 6 hours after infection were selected for theoretical proof in patient sera that were clearly diagnosed as bloodstream infection. Receiver operating characteristic (ROC) curve analysis was conducted to determine the clinical differentiation of different cytokines.\n\nResultsTwo models of S.aureus and K. pneumoniae bloodstream infection in mice were constructed successfully. In the two mouse models, six of the nine cytokines monitored were different (P<0.05) in each experimental group. In the 121 patient sera samples, three cytokines, IL-6, IL-12p70 and G-CSF in the infection groups and control group had showed differences. In particular, AUC of G-CSF was 0.9051, the accuracy is better than IL-6 for diagnosing the infection. In addition, only G-CSF was significantly different between the two infection groups and in the analysis of ROC curve, AUC is equal to 0.735.\n\nConclusionsG-CSF can not only judge the bacterial infection and non-infection, but also distinguish the infection of S.aureus from K. pneumoniae.

microbiology↗

bioRxiv2019

Efficient RNA-mediated reprogramming of human somatic cells to naive pluripotency facilitated by tankyrase inhibition

In contrast to conventional human pluripotent stem cells (hPSC) that are related to post-implantation embryo stages, naive hPSC exhibit features of pre-implantation epiblast. Naive hPSC are established by resetting conventional hPSC, or are derived from dissociated embryo inner cell masses. Here we investigate conditions for transgene-free reprogramming of human somatic cells to naive pluripotency. We find that tankyrase inhibition promotes RNA-mediated induction of naive pluripotency. We demonstrate application to independent human fibroblast cultures and endothelial progenitor cells. We show that induced naive hPSC can be clonally expanded with a diploid karyotype and undergo somatic lineage differentiation following formative transition. Induced naive hPSC lines exhibit distinctive surface marker, transcriptome, and methylome properties of naive epiblast identity. This system for efficient, facile, and reliable induction of transgene free naive hPSC offers a robust platform, both for delineation of human reprogramming trajectories and for evaluating the attributes of isogenic naive versus conventional hPSC.

developmental biology↗

bioRxiv2019

Brain microRNAs associated with late-life depressive symptoms are also associated with cognitive trajectory and dementia

ObjectiveLate-life depression is associated with an increased risk for dementia, but our knowledge of the molecular mechanisms underlying this association is limited. Hence, the authors investigated whether microRNAs, important post-transcriptional regulators of gene expression, contribute to this association.\n\nMethodLate-life depressive symptoms were assessed annually in 300 non-demented participants of the Religious Orders Study and Rush Memory and Aging Project for a mean of seven years using the Center for Epidemiological Studies Depression scale. Participants underwent annual cognitive testing, clinical assessment of cognitive status, and uniform neuropathologic examination after death. microRNAs were profiled from the prefrontal cortex using Nanostring platform. A global microRNA association study of late-life depressive symptoms was performed using linear mixed model adjusting for sex, age, Alzheimers dementia pathological burden, proportions of brain cell types, post-mortem interval, and RNA integrity.\n\nResultsFour brain microRNAs were associated with late-life depressive symptoms at adjusted p<0.05 (miR-484, miR-26b, miR-30d, and miR-197). Lower expressions of these miRNAs were associated with greater depressive symptoms. Furthermore, lower expressions of miR-484 and miR-197 were associated with faster decline of cognitive performance over time. Additionally, lower miR-484 level was associated with higher probability of having Alzheimers dementia. Lastly, the predicted targets of miR-484 were enriched in a brain protein co-expression module involving synaptic transmission and regulation of long-term neuronal synaptic plasticity.\n\nConclusionsThis is the first study to identify brain microRNAs associated with late-life depressive symptoms assessed longitudinally. Additionally, the authors found a link between late-life depressive symptoms and dementia through miR-484 and miR-197.

genomics↗

bioRxiv2019

A resource-efficient tool for mixed model association analysis of large-scale data

The genome-wide association study (GWAS) has been widely used as an experimental design to detect associations between genetic variants and a phenotype. Two major confounding factors, population stratification and relatedness, could potentially lead to inflated GWAS test-statistics and thereby spurious associations. Mixed linear model (MLM)-based approaches can be used to account for sample structure. However, genome-wide association (GWA) analyses in biobank samples such as the UK Biobank (UKB) often exceed the capability of most existing MLM-based tools especially if the number of traits is large. Here, we developed an MLM-based tool (called fastGWA) that controls for population stratification by principal components and relatedness by a sparse genetic relationship matrix for GWA analyses of biobank-scale data. We demonstrated by extensive simulations that fastGWA is reliable, robust and highly resource-efficient. We then applied fastGWA to 2,173 traits on 456,422 array-genotyped and imputed individuals and 2,048 traits on 46,191 whole-exome-sequenced individuals in the UKB.

genetics↗

bioRxiv2019

The Parkinsons Disease Mendelian Randomization Research Portal

BackgroundMendelian randomization (MR) is a method for exploring observational associations to find evidence of causality.\n\nObjectiveTo apply MR between multiple risk factors/phenotypic traits (exposures) and Parkinsons disease (PD) in a large, unbiased manner, and to create a public resource for research.\n\nMethodsWe used two-sample MR in which the summary statistics relating to SNPs from genome wide association studies (GWASes) of 5,839 exposures curated on MR Base were used to assess causal relationships with PD. We selected the highest quality exposure GWASes for this report (n=401). For the disease outcome, summary statistics from the largest published PD GWAS were used. For each exposure, the causal effect on PD was assessed using the inverse variance weighted (IVW) method, followed by a range of sensitivity analyses. We used a false discovery rate (FDR) corrected p-value of <0.05 from the IVW analysis to prioritize traits of interest.\n\nResultsWe observed evidence for causal associations between twelve exposures and risk of PD. Of these, nine were causal effects related to increasing adiposity and decreasing risk of PD. The remaining top exposures that affected PD risk were tea drinking, time spent watching television and forced vital capacity, but the latter two appeared to be biased by violations of underlying MR assumptions.\n\nDiscussionWe present a new platform which offers MR analyses for a total of 5,839 GWASes versus the largest PD GWASes available (https://pdgenetics.shinyapps.io/pdgenetics/). Alongside, we report further evidence to support a causal role for adiposity on lowering the risk of PD.

neuroscience↗

bioRxiv2019

Pharmacological inhibition of soluble epoxide hydrolase as a new therapy for Alzheimer’s Disease

The inhibition of the enzyme soluble epoxide hydrolase (sEH) has demonstrated clinical therapeutic effects in several peripheral inflammatory-related diseases, with two compounds that have entered clinical trials. However, the role of this enzyme in the neuroinflammation process has been largely neglected. Herein, we disclose the pharmacological validation of sEH as a novel target for the treatment of Alzheimers Disease (AD). Of interest, we have found that sEH is upregulated in brains from AD patients. We have evaluated the cognitive impairment and the pathological hallmarks in two models of age-related cognitive decline and AD using three structurally different and potent sEH inhibitors as chemical probes. Our findings supported our expectations on the beneficial effects of central sEH inhibition, regarding of reducing cognitive impairment, tau hyperphosphorylation pathology and the number of amyloid plaques. Interestingly, our results suggest that reduction of inflammation in the brain is a relevant therapeutic strategy for all stages of AD.

pharmacology and toxicology↗

bioRxiv2019

Conditional GWAS analysis identifies putative disorder-specific SNPs for psychiatric disorders

Substantial genetic liability is shared across psychiatric disorders but less is known about risk variants that are specific to a given disorder. We used multi-trait conditional and joint analysis (mtCOJO) to adjust GWAS summary statistics of one disorder for the effects of genetically correlated traits to identify putative disorder-specific SNP associations. We applied mtCOJO to summary statistics for five psychiatric disorders from the Psychiatric Genomics Consortium - schizophrenia (SCZ), bipolar disorder (BIP), major depression (MD), attention-deficit hyperactivity disorder (ADHD) and autism (AUT). Most genom-wide significant variants for these disorders had evidence of pleiotropy (i.e., impact on multiple psychiatric disorders) and hence have reduced mtCOJO conditional effect sizes. However, subsets of genome-wide significant variants had larger conditional effect sizes consistent with disorder-specific effects: 15 of 130 genome-wide significant variants for schizophrenia, 5 of 40 for major depression, 3 of 11 for ADHD and 1 of 2 for autism. In addition, we identified a number of variants that approached genome-wide significance in the original GWAS and have larger conditional effect sizes after conditioning on the other disorders. We show that decreased expression of VPS29 in the brain may increase risk to SCZ only and increased expression of CSE1L is associated with SCZ and MD, but not with BIP. Likewise, decreased expression of PCDHA7 in the brain is linked to increased risk of MD but decreased risk of SCZ and BIP.

genetics↗

bioRxiv2019

Parasites Acquired Beta Satellite DNAs from Hominid Hosts via Horizontal Gene Transfer

Beta satellite DNA (satDNA) sequences are repeated DNA elements located in primate centromeres and telomeres, and might play roles in genome stability and chromosome segregation. Beta satDNAs mainly exist in great apes. Previous studies suggested that beta satDNAs may originate in old world monkeys. In this study, we searched both GenBank and SRA database, and identified beta satDNA sequences from the genomic sequences of 22 species. The beta satDNA sequences found in Prosimian, Dermoptera and Scandentia indicated that the origin of beta satDNAs might be as early as 80 MYA. Strikingly, beta satDNA sequences were also found in a number of some species evolutionarily far from primates, including several endoparasites of human and other great apes, which could be the results of multiple horizontal gene transfer (HGT) events. The similar phylogenic profiles between beta satDNAs in the parasite genomes and the human genome indicates that the parasite beta satDNAs have undergone similar concerted evolution and play similar roles as the beta satDNAs in primates.\n\nHighlightsO_LIThe ever largest scale analysis on beta satDNAs.\nC_LIO_LIThe origin of beta satDNAs was traced back to [~]80 MYA.\nC_LIO_LIMass existence of beta satDNAs in non-primate species was contributed by multiple HGT events.\nC_LI

evolutionary biology↗

bioRxiv2019

Evaluation of PicoGreen variants for use in microscopy and flow cytometry

PicoGreen is a fluorescent probe that binds dsDNA and forms a highly luminescent complex when compared to the free dye in solution. This unique probe is widely used in DNA quantitation assays but has limited application in flow cytometry and microscopy. Here we have investigated various PicoGreen variants for the ability to stain low amounts of cytosolic DNA present in many tumor cells. Analysis of stained cells by flow cytometry and fluorescent microscopy showed that certain variants improved the ability to stain low levels of cytosolic DNA when compared to the commercially available PicoGreen molecule.

cancer biology↗

bioRxiv2019

Promoter-anchored chromatin interactions predicted from genetic analysis of epigenomic data

Promoter-anchored chromatin interactions (PAIs) play a pivotal role in transcriptional regulation. Current high-throughput technologies for detecting PAIs, such as promoter capture Hi-C, are not scalable to large cohorts. Here, we present an analytical approach that uses summary-level data from cohort-based DNA methylation (DNAm) quantitative trait locus (mQTL) studies to predict PAIs. Using mQTL data from human peripheral blood (n=1,980), we predicted 34,797 PAIs which showed strong overlap with the chromatin contacts identified by previous experimental assays. The promoter-interacting DNAm sites were enriched in enhancers or near expression QTLs. Genes whose promoters were involved in PAIs were more actively expressed, and gene pairs with promoter-promoter interactions were enriched for co-expression. Integration of the predicted PAIs with GWAS data highlighted interactions among 601 DNAm sites associated with 15 complex traits. This study demonstrates the use of mQTL data to predict PAIs and provides insights into the role of PAIs in complex trait variation.

genetics↗

bioRxiv2019

siRNA containing a unique 5-nucleotide motif acts as a quencher of IFI16-mediated innate immune response

We previously reported that small interfering RNA (siRNA) enhances DNA or DNA virus mediated-interferon (IFN)-{lambda}1 induction through retinoic acid-inducible gene I (RIG-I) and interferon gamma-inducible protein 16 (IFI16) crosstalk-signalling pathway. Here we provide further evidence of a new role for siRNA. siRNA containing a 5-nucleotide (nt) motif sequence suppresses DNA-mediated IFNs and inflammatory cytokines. We determined that motif siRNA inhibits the induction when the motif is located at the 3 or 5-terminus of siRNA. Using THP1-Lucia ISG cells with various DNA stimulants, it is demonstrated that motif siRNA inhibits DNA or DNA virus but not RNA virus-mediated signaling. Motif siRNA specifically interrupts IFI16 binding to DNA and has 2.5-fold higher affinity to IFI16 than that of siRNA without the motif. Collectively, these findings may shed lights on a novel function of siRNA with the 5-nt motif as a quencher of innate immunity and facilitate the development of potential therapeutics to treat diseases in which this pathway is dysregulated.

immunology↗

bioRxiv2019

Comparison of different orders of Legendre polynomials in random regression model for estimation of genetic parameters and breeding values of milk yield in the Chinese Holstein population

Random regression test-day model has become the most commonly adopted model for routine genetic evaluations for different dairy populations, which allows accurately accounting for genetic and environmental effects at different periods during lactation. The objective of this study was to explore appropriate random regression test-day model for genetic evaluation of milk yield in Chinese Holstein population. Data included 419,567 test-day records from 54,417 cows in the first lactation. Variance components and breeding values were estimated using random regression test-day model with different order (first order to fifth order) of Legendre polynomials, and accounted for homogeneous or heterogeneous residual variance across the lactation. The goodness of fit of the models was evaluated by total residual variance (TRV) and - 2logL. Further, the predictive ability of the models was assessed by Spearmans rank correlation between estimated breeding values for 305d milk yield (EBV305) from the full data set and reduced data set in which the records from the last calving year were masked. The results showed that random regression models using third order Legendre polynomials (LP3) with heterogeneous residual variance achieved the lower TRV and - 2logL value and the highest correlation for EBV305 between full data and reduced data. Heritability estimated by this model was 0.250 for 305d milk yield and ranged from 0.163 to 0.304 for test-day milk yield. We suggest random regression model with Legendre polynomial of order 3 and accounting for heterogeneous residual variances could be an appropriate model to be used for genetic evaluation of milk yield for Chinese Holstein population.

genetics↗

bioRxiv2019

Systematic Analysis of Metabolic Pathway Distributions of Bacterial Energy Reserves

Metabolism of energy reserves are essential for bacterial functions such as pathogenicity, metabolic adaptation, and environmental persistence, etc. Previous bioinformatics studies have linked gain or loss of energy reserves such as glycogen and polyphosphate (polyP) with host-pathogen interactions and bacterial virulence based on a comparatively small number of bacterial genomes or proteomes. Thus, understanding the distribution patterns of energy reserves metabolism across bacterial species provides a shortcut route to look into bacterial lifestyle and physiology theoretically. So far, five major energy reserves have been identified in bacteria due to their effective capacity to support bacterial persistence under nutrient deprivation conditions, which include wax ester (WE), triacylglycerol (TAG), polyhydroxyalkanoates (PHA), polyphosphate, and glycogen. Although unknown pathways directly involved in energy reserves keep being discovered with the continuous endeavour of molecular microbiologists and it is currently rather clear about the enzymes related with the metabolism of energy reserves, there is a lack of systematic study of the pathway or key enzyme distributions of the five energy reserves in bacteria from an evolutionary point of view. With the fast development of sequencing technology, abundant bacterial proteomes are available in public database now. In this study, we sourced 8214 manually reviewed bacterial reference proteomes from UniProt database and used statistical models to search homologous sequences of key enzymes related with energy reserves. The distribution patterns of the pathways for energy reserves metabolism are visualized in taxonomy-based phylogenetic trees. According to the study, it was revealed that specific pathways and enzymes are associated with certain types of bacterial groups, which provides evolutionary insights into the understanding of their origins and functions. In addition, the study also confirmed that loss of energy reserves is correlated with bacterial genome reduction. Through this analysis, a much clearer picture about energy reserves metabolism in bacteria is present, which could serve a guide for further theoretical and experimental analyses of energy reserves metabolism in bacteria.

microbiology↗