Biology subjects

Wei, R.

Publications and source records attributed to Wei, R..

44 records · Page 3Linked to original sources

bioRxiv2019

Peripheral Serum Metabolomic Profiles InformAntecedent Central Cognitive Impairment in Older Adults

The incidence of Alzheimers disease (AD) increases with age and is a significant cause of worldwide morbidity and mortality. However, the metabolic perturbations behind the onset of AD remains unclear. In this study, we performed metabolite profiling in both brain (n = 109) and matching serum samples (n = 566) to identify differentially expressed metabolites and metabolic pathways associated with neuropathology and cognitive performance and to identify individuals at high risk of developing cognitive impairment. The abundances of six metabolites, GLCA, petroselinic acid, linoleic acid, myristic acid, palmitic acid, and palmitoleic acid as well as the DCA/CA ratio, along with the dysregulation scores of three metabolic pathways, primary bile acid biosynthesis, fatty acid biosynthesis, and biosynthesis of unsaturated fatty acids showed significant differences in diagnostic groups across both brain and serum (P-value < 0.05).Significant associations were observed between the levels of differential metabolites/pathways and cognitive performance, neurofibrillary tangles, and neuritic plaque burden. Metabolites abundances and personalized metabolic pathways scores were used to derive machine learning models that could be used to differentiate cognitively impaired persons from those without cognitive impairment (median of AUC = 0.772 for the metabolite level model; median of AUC = 0.731 for the pathway level model). Utilizing these two models on the entire baseline control group, we identified those who experienced cognitive decline (AUC = 0.804, sensitivity = 0.722, specificity = 0.749 for the metabolite level model; AUC = 0.778, sensitivity = 0.633, specificity = 0.825 for the pathway level model) and demonstrated their pre-AD onset prediction potentials. Our study provides a proof-of-concept that it is possible to discriminate antecedent cognitive impairment in older adults before the onset of overt clinical symptoms using metabolomics. Our findings, if validated in future studies, could enable the earlier detection and intervention of cognitive impairment that may halt its progression.

neuroscience↗

bioRxiv2019

Phylogenomics of Selaginellaceae with special reference to the enigmatic sanguinolenta group

Selaginellaceae has been repeatedly proved as monophyly by previous studies with only one genus being recognized. However, the subgeneric classification has been debated during the recent decades. Furthermore, phylogenetic position of the newly identified sanguinolenta group has not been resolved, varying depending on the datasets and analysis methods. We carried out the phylogenomic analyses of twenty-six species from Selaginellaceae with ten species being newly sequenced and three species representing the sanguinolenta group. Four of the ten newly sequenced plastomes are assembled into the complete molecules, whereas the other six species are only assembled into five to sixteen contigs owing to high numbers of repeats. The phylogenetic framework from our study is basically congruent with the subgeneric classification of Weststrand and Korall (2016b). The position of sanguinolenta group was resolved as the basal clade in subg. Stachygynandrum, which support the position {beta} proposed by Weststrand and Korall (2016a), also supported by the morphological characters of dimorphic vegetative leaves, monomorphic sporophylls and intermixed sporangial arrangements. Both values of dS, dN and GC content in Selaginellaceae plastomes were significantly higher than those of other lycophytes (Isoetaceae and Lycopodiaceae). The correlation analysis showed that the elevated synonymous substitution rate was significantly correlated with the high GC content in Selaginellaceae. Besides, the values of dS and dN differs significantly between branches in the phylogenetic tree of Selaginellaceae. We propose that both high GC content and the extensive RNA editing sites contributed to the elevated substitution rate in Selaginellaceae, and all of these three factors could influence the stability of phylogenetic topology of Selaginellaceae.

evolutionary biology↗

bioRxiv2018

Polyploidy and elevation contribute to opposing latitudinal gradients in diversification and species richness in lady ferns (Athyriaceae)

O_LIIn ferns, the temperate-tropical sister clades Athyrium and Diplazium present an opportunity to study a latitudinal contrast in diversification dynamics.\nC_LIO_LIWe generated a taxonomically expanded molecular chronogram and used macroevolutionary models to analyze how diversification rates have changed through time, across lineages, and in concert with changes in elevation and ploidy. We tested a novel model of cladogenetic state-change in which polyploidy can arise as an infraspecific polymorphism, with diversification parameters distinct from those of pure diploids and polyploids.\nC_LIO_LIBoth Athyrium and Diplazium accelerated their diversification near the Oligocene-Miocene transition. In Diplazium, the rate shift is older, with subsequent net diversification somewhat slower and suggestive of diversity-dependence. In Athyrium, diversification is faster and associated with higher elevations. In both clades, polyploids have the highest rate of net accumulation but lowest (negative) net diversification, while the converse is true for polymorphic species; diploids have low rates of both net accumulation and diversification.\nC_LIO_LIDiversification in Athyrium may have responded to ecological opportunities in expanding temperate habitats during the Neogene, especially in mountains, while the pattern in Diplazium suggests saturation in the tropics. Neopolyploids are generated rapidly, primarily through accelerated cladogenesis in polymorphic species, but are evolutionary dead ends.\nC_LI

plant biology↗

bioRxiv2018

The reduced prevalence of macrolide resistance in Mycoplasma pneumoniae clinical isolates from pediatric patients in Beijing in 2016

Older children especially from seven to thirteen years old are more prone to develop Mycoplasma pneumoniae (MP) infection; in winter children are more susceptible to infect with MP. In Beijing, China in 2016 the rates of macrolide resistance of MP were 69.48% (in total children), 61.59% (in outpatients) and 79.28% (in hospitalized patients), respectively. All the macrolide resistant isolates harbored A2063G or A2064G mutation in the 23S rRNA gene. Seven isolates showed a mixed infection. Susceptibility results showed that 73 isolates with the A2063G mutation demonstrated different levels resistance to erythromycin (MIC=8 to>256g/ml), azithromycin (MIC=8 to>64g/ml) and josamycin (MIC=2 to 8g/ml). No cross-resistance was observed in the in the antibiotics of levofloxacin and tetracycline against MP.

microbiology↗

bioRxiv2018

PorSignDB: a database of in vivo perturbation signatures for dissecting clinical outcome of PCV2 infection

Porcine Circovirus Type 2 (PCV2) is a pathogen that has the ability to cause often devastating disease manifestations in pig populations with major economic implications. How PCV2 establishes subclinical persistence and why certain individuals progress to lethal lymphoid depletion remain to be elucidated. Here we present PorSignDB, a gene signature database describing in vivo porcine tissue physiology that we generated from a large compendium of in vivo transcriptional profiles and that we subsequently leveraged for deciphering the distinct physiological states underlying PCV2-affected lymph nodes. This systems biology approach indicated that subclinical PCV2 infections shut down the immune system. A robust signature of PCV2 disease emphasized that immune activation is dysfunctional in subclinical infections, however, in contrast it is promoted in PCV2 patients with clinical manifestations. Functional genomics further uncovered IL-2 as a driver of PCV2-mediated disease and we identified STAT3 as a druggable PCV2 host factor candidate. Our systematic dissection of the mechanistic basis of PCV2 reveals that subclinical and clinical PCV2 display two diametrically opposed immunotranscriptomic recalibrations that represent distinct physiological states in vivo, which suggests a paradigm shift in this field. Finally, our PorSignDB signature database is publicly available as a community resource (http://www.vetvirology.ugent.be/PorSignDB/, included in Gene Sets from Community Contributors http://software.broadinstitute.org/gsea/msigdb/contributed_genesets.jsp) and provides systems biologists with a valuable tool for catalyzing studies of human and veterinary disease.\n\nAuthor SummaryPorcine Circovirus Type 2 (PCV2) is a small but economically important pathogen circulating endemically in pig populations. Although PCV2 causes mostly chronic subclinical infections, many individuals develop a lethal form of circoviral disease consisting of a collapse of lymphoid tissue. In order to provide a fresh look at how PCV2 reprograms host tissue, we created PorSignDB, a compendium of hundreds of transcriptomic gene-expression signatures derived from primary porcine tissue specimens of well over 1500 patients or lab animals. By leveraging PorSignDB on transcriptomic data of PCV2 patients, we uncover that subclinical PCV2 reprograms the host into a striking state of non-infection, which explains its failure to respond to an initial phase of circoviral presence. A PCV2 disease signature further demonstrates that the silenced immune system associated with subclinical PCV2 becomes fully activate in PCV2 patients, triggering severe circoviral disease. Further genomic and functional analysis demonstrate STAT3 as a druggable host factor and IL-2 as a disease driver. Together, this study demonstrates the mechanistic underpinnings of clinical outcome of PCV2 infections: subclinical and clinical PCV2 display two entirely opposing transcriptomic recalibrations of lymphoid tissue.

microbiology↗

bioRxiv2017

GSimp: A Gibbs sampler based left-censored missing value imputation approach for metabolomics studies

MotivationLeft-censored missing values commonly exist in targeted metabolomics datasets and can be considered as missing not at random (MNAR). Improper data processing procedures for missing values will cause adverse impacts on subsequent statistical analyses. However, few imputation methods have been developed and applied to the situation of MNAR in the field of metabolomics. Thus, a practical left-censored missing value imputation method is urgently needed.\n\nResultsWe have developed an iterative Gibbs sampler based left-censored missing value imputation approach (GSimp). We compared GSimp with other three imputation methods on two real-world targeted metabolomics datasets and one simulation dataset using our imputation evaluation pipeline. The results show that GSimp outperforms other imputation methods in terms of imputation accuracy, observation distribution, univariate and multivariate analyses, and statistical sensitivity.\n\nAvailability and implementationThe R code for GSimp, evaluation pipeline, vignette, real-world and simulated targeted metabolomics dataset are available on: https://github.com/WandeRum/GSimp.

bioinformatics↗

bioRxiv2017

Missing Value Imputation Approach for Mass Spectrometry-based Metabolomics Data

IntroductionMissing values exist widely in mass-spectrometry (MS) based metabolomics data. Various methods have been applied for handling missing values, but the selection of methods can significantly affect following data analyses and interpretations. According to the definition, there are three types of missing values, missing completely at random (MCAR), missing at random (MAR), and missing not at random (MNAR).\n\nObjectivesThe aim of this study was to comprehensively compare common imputation methods for different types of missing values using two separate metabolomics data sets (977 and 198 serum samples respectively) to propose a strategy to deal with missing values in metabolomics studies.\n\nMethodsImputation methods included zero, half minimum (HM), mean, median, random forest (RF), singular value decomposition (SVD), k-nearest neighbors (kNN), and quantile regression imputation of left-censored data (QRILC). Normalized root mean squared error (NRMSE) and NRMSE-based sum of ranks (SOR) were applied to evaluate the imputation accuracy for MCAR/MAR and MNAR correspondingly. Principal component analysis (PCA)/partial least squares (PLS)-Procrustes sum of squared error were used to evaluate the overall sample distribution. Students t-test followed by Pearson correlation analysis was conducted to evaluate the effect of imputation on univariate statistical analysis.\n\nResultsOur findings demonstrated that RF imputation performed the best for MCAR/MAR and QRILC was the favored one for MNAR.\n\nConclusionCombining with \"modified 80% rule\", we proposed a comprehensive strategy and developed a public-accessible web-tool for missing value imputation in metabolomics data.

bioinformatics↗

bioRxiv2017

PGC-1α coordinates with Bcl-2 to control cell cycle in U251 cells through reducing ROS

B-cell lymphoma 2 (Bcl-2) has a dual function, acting both as an oncogene and an anti-tumor gene. It is well known that Bcl-2 exerts its tumor promoting function through the mitochondrial pathway. However, the mechanism by which Bcl-2 suppresses tumor formation is not well understood. We have previously shown that Bcl-2 inhibits cell cycle progression from the G0/G1 to the S phase after serum starvation, and that quiescent Bcl-2 expressing cells maintained a significant lower level of mitochondrial reactive oxygen species (ROS) than the control cells. Based on the fact that ROS mediate cell cycle progression, and are controlled by peroxisome proliferator-activated receptor-{gamma} co-activator 1 (PGC-1), a key molecule induced by prolonged starvation and involved in mitochondrial metabolism, we hypothesized that PGC-1 might be related with the cell cycle function of Bcl-2. Here, we showed that PGC-1 was upregulated upon Bcl-2 overexpression and downregulated following Bcl-2 knockdown during serum starvation. Knockdown of PGC-1 activated Bcl-2 expression. Taken together, our results suggest that after serum depletion, PGC-la might coordinate with Bcl-2 to reduce ROS, which in turn delay cell cycle progression.\n\nSummary statementPGC-1 coordinate with Bcl-2 delay cell cycle progression to reduce ROS after serum depletion in human glioma U251 cells.

biochemistry↗