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Yang, Z.

Publications and source records attributed to Yang, Z..

At least 577 records · Page 32Linked to original sources

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↗

Cross-disorder GWAS meta-analysis for Attention Deficit/Hyperactivity Disorder, Autism Spectrum Disorder, Obsessive Compulsive Disorder, and Tourette Syndrome

Attention Deficit/Hyperactivity Disorder (ADHD), Autism Spectrum Disorder (ASD), Obsessive-Compulsive Disorder (OCD), and Tourette Syndrome (TS) are among the most prevalent neurodevelopmental psychiatric disorders of childhood and adolescence. High comorbidity rates across these four disorders point toward a common etiological thread that could be connecting them across the repetitive behaviors-impulsivity-compulsivity continuum. Aiming to uncover the shared genetic basis across ADHD, ASD, OCD, and TS, we undertake a systematic cross-disorder meta-analysis, integrating summary statistics from all currently available genome-wide association studies (GWAS) for these disorders, as made available by the Psychiatric Genomics Consortium (PGC) and the Lundbeck Foundation Initiative for Integrative Psychiatric Research (iPSYCH). We present analysis of a combined dataset of 93,294 individuals, across 6,788,510 markers and investigate associations on the single-nucleotide polymorphism (SNP), gene and pathway levels across all four disorders but also pairwise. In the ADHD-ASD-OCD-TS cross disorder GWAS meta-analysis, we uncover in total 297 genomewide significant variants from six LD (linkage disequilibrium) -independent genomic risk regions. Out of these genomewide significant association results, 199 SNPs, that map onto four genomic regions, show high posterior probability for association with at least three of the studied disorders (m-value>0.9). Gene-based GWAS meta-analysis across ADHD, ASD, OCD, and TS identified 21 genes significantly associated under Bonferroni correction. Out of those, 15 could not be identified as significantly associated based on the individual disorder GWAS dataset, indicating increased power in the cross-disorder comparisons. Cross-disorder tissue-specificity analysis implicates the Hypothalamus-Pituitary-Adrenal axis (stress response) as possibly underlying shared pathophysiology across ADHD, ASD, OCD, and TS. Our work highlights genetic variants and genes that may contribute to overlapping neurobiology across the four studied disorders and highlights the value of re-defining the framework for the study across this spectrum of highly comorbid disorders, by using transdiagnostic approaches.

genetics↗

A Bayesian implementation of the multispecies coalescent model with introgression for comparative genomic analysis

Recent analyses suggest that cross-species gene flow or introgression is common in nature, especially during species divergences. Genomic sequence data can be used to infer introgression events and to estimate the timing and intensity of introgression, providing an important means to advance our understanding of the role of gene flow in speciation. Here we implement the multispecies-coalescent-with-introgression (MSci) model, an extension of the multispecies-coalescent (MSC) model to incorporate introgression, in our Bayesian Markov chain Monte Carlo (MCMC) program BPP. The MSci model accommodates deep coalescence (or incomplete lineage sorting) and introgression and provides a natural framework for inference using genomic sequence data. Computer simulation confirms the good statistical properties of the method, although hundreds or thousands of loci are typically needed to estimate introgression probabilities reliably. Re-analysis of datasets from the purple cone spruce confirms the hypothesis of homoploid hybrid speciation. We estimated the introgression probability using the genomic sequence data from six mosquito species in the Anopheles gambiae species complex, which varies considerably across the genome, likely driven by differential selection against introgressed alleles.

evolutionary biology↗

Genome sequencing and neurotoxin diversity of a wandering spider Pardosa pseudoannulata (pond wolf spider)

Spiders constitute an extensive and diverse branch of the phylum Arthropoda. Whereas the genomes of four web-weaver spider species and a single cave-living spider have been determined, similar studies have not been reported previously for a wandering spider. The pond wolf spider, Pardosa pseudoannulata, is a wandering hunter that immobilizes prey using venom rather than a web. It is also an important predator against a range of agriculturally important insect pests. The increasing interest in its wandering lifestyle and in the potential of spider venom as a tool for pest control have prompted a detailed study on this wandering spider species. We have generated a high-quality genome sequence of P. pseudoannulata and analysed genes associated with the production of silk and venom toxins. Sequencing reveals that P. pseudoannulata has a large genome of 4.26 Gb. The presence of only 16 spidroin genes and four types of silk glands is consistent with the moderate use of silk and the lack of a prey-catching web. A large number of genes encode neurotoxins and there is evidence that the majority are highly selective for invertebrates. Comparison between spider species reveals a correlation between spider neurotoxin selectivity for target organisms and spider prosoma size, suggesting a possible coevolution of these two features. The genome data provides valuable insights into the biology of P. pseudoannulata and its potential role as a natural enemy in pest control.

genomics↗

Spatiotemporal Feature Selection Improves Prediction Accuracy of Multi-Voxel Pattern Classification

The importance of spatiotemporal feature selection in fMRI decoding studies has not been studied exhaustively. Temporal embedding of features allows the incorporation of brain activity dynamics into multivariate pattern classification, and may provide enriched information about stimulus-specific response patterns and potentially improve prediction accuracy. This study investigates the possibility of enhancing the classification performance by exploring spatial and temporal (spatiotemporal) domain, to identify the optimum combination of the spatiotemporal features based on the classification performance. We investigated the importance of spatiotemporal feature selection using a slow event-related design adapted from the classic Haxby et al. (2001) study. Data were collected using a multiband fMRI sequence with temporal resolution of 0.568 seconds. A wide range of spatiotemporal observations was created as various combinations of spatiotemporal features. Using both random forest, and support vector machine, classifiers, prediction accuracies for these combinations were then compared with the single time-point spatial multivariate pattern approach that uses only a single temporal observation. The results showed that on average spatiotemporal feature selection improved prediction accuracy. Moreover, the random forest algorithm outperformed the support vector machine and benefitted from temporal information to a greater extent. As expected, the most influential temporal durations were found to be around the peak of the hemodynamic response function, a few seconds after the stimuli onset until [~]4 seconds after the peak of the hemodynamic response function. The superiority of spatiotemporal feature selection over single time-point spatial approaches invites future work to design systematic and optimal approaches to the incorporation of spatiotemporal dependencies into feature selection for decoding.\n\nHighlightsO_LISpatiotemporal feature selection effect on MVPC was assessed in slow event-related fMRI\nC_LIO_LISpatiotemporal feature selection improved brain decoding accuracy\nC_LIO_LIFrom [~]2-11 seconds after stimuli onset were the most informative part of each trial\nC_LIO_LIRandom forest outperformed support vector machines\nC_LIO_LIRandom forest benefited more from temporal changes compared with support vector machine\nC_LI

neuroscience↗

RNA-Binding Proteins MSI-1 (Musashi) and EXC-7 (HuR) Regulate Serotonin-Mediated Behaviors in C. elegans

The evolutionarily conserved RNA-binding proteins HuR and MSI are essential for multiple developmental processes and are upregulated in many cancer tissues. The C. elegans homologues EXC-7 (HuR) and MSI-1 (MSI1 and MSI2) have been implicated in tubulogenesis, neural development, and specific behaviors that include male tail-curling to maintain contact with the hermaphrodite during mating. This behavior is mediated by serotonin signaling. Here, drug studies plus biochemical and genetic results indicate that MSI-1 affects serotonergic signaling through stabilization of mRNA of the G protein GOA-1/GNAO1 in neurons, which in turn affects activity of the serotonin synthase TPH-1/tryptophan hydroxylase via the response element CRH-1/CREB. EXC-7 (HuR) is also involved in this regulatory pathway. These results indicate a novel pathway and role for these RNA-binding proteins in regulating neurotransmitter levels that could be conserved in other tissues where these RNA-binding proteins are present.\n\nImpact Statement\n\nRNA-binding proteins Musashi and HuR upregulate serotonin levels for male-specific movement during mating via a novel pathway involving a neural G protein, response element, and serotonin synthase.

cell biology↗

A robust deep neural network for denoising task-based fMRI data: An application to working memory and episodic memory

In this study, a deep neural network (DNN) is proposed to reduce the noise in task-based fMRI data without explicitly modeling noise. The DNN artificial neural network consists of one temporal convolutional layer, one long short-term memory (LSTM) layer, one time-distributed fully-connected layer, and one unconventional selection layer in sequential order. The LSTM layer takes not only the current time point but also what was perceived in a previous time point as its input to characterize the temporal autocorrelation of fMRI data. The fully-connected layer weights the output of the LSTM layer, and the output denoised fMRI time series is selected by the selection layer. Assuming that task-related neural response is limited to gray matter, the model parameters in the DNN network are optimized by maximizing the correlation difference between gray matter voxels and white matter or ventricular cerebrospinal fluid voxels. Instead of targeting a particular noise source, the proposed neural network takes advantage of the task design matrix to better extract task-related signal in fMRI data. The DNN network, along with other traditional denoising techniques, has been applied on simulated data, working memory task fMRI data acquired from a cohort of healthy subjects and episodic memory task fMRI data acquired from a small set of healthy elderly subjects. Qualitative and quantitative measurements were used to evaluate the performance of different denoising techniques. In the simulation, DNN improves fMRI activation detection and also adapts to varying hemodynamic response functions across different brain regions. DNN efficiently reduces physiological noise and generates more homogeneous task-response correlation maps in real data.

neuroscience↗

Proteomic Profiling and Biological Characterization of Extracellular Vesicles Isolated from Human Alzheimer’s Disease Brain Tissues

IntroductionExtracellular vesicles (EVs) from human Alzheimers disease (AD) biospecimens contain amyloid-{beta} peptide (A{beta}) and tau. While AD EVs are known to affect brain disease pathobiology, their biochemical and molecular characterizations remain ill defined.\n\nMethodsEVs were isolated from the cortical grey matter of 20 AD and 18 control brains. Tau and A{beta} levels were measured by immunoassay. Differentially expressed EV proteins were assessed by quantitative proteomics and machine learning.\n\nResultsLevels of pS396 tau and A{beta} were significantly elevated in AD EVs. High levels of neuron- and glia- specific factors are detected in control and AD EVs, respectively. Machine learning identified ANXA5, VGF, GPM6A and ACTZ in AD EV compared to controls. They distinguished AD EVs from controls in the test sets with 88% accuracy.\n\nDiscussionIn addition to A{beta} and tau, ANXA5, VGF, GPM6A and ACTZ are new signature proteins in AD EVs.

biochemistry↗

Auxin-induced nanoclustering of membrane signaling complexes underlies cell polarity establishment in Arabidopsis

Cell polarity is fundamental to the development of both eukaryotic and prokaryotic organisms, yet the mechanism of its establishment remains poorly understood. Here we show that signal-activated nanoclustering of membrane proteins and a cytoskeleton-based feedback loop provide an important mechanism for the establishment of cell polarity. The phytohormone auxin promoted sterol-dependent nanoclustering of cell surface transmembrane receptor-like kinase 1 (TMK1) to initiate cell polarity during the morphogenesis of Arabidopsis puzzle piece-shaped leaf pavement cells (PC). Auxin-triggered nanoclustering of TMK1 stabilized flotillin-associated ordered nanodomains, which were essential for auxin-mediated formation of ROP6 GTPase nanoclusters that act downstream TMK1 to promote cortical microtubule ordering. Mathematical modeling further demonstrated the essential role of this auxin-mediated stabilization of TMK1 and ROP6 nanoclusters, and predicted the additional requirement of ROP6-dependent cortical microtubules for further stabilization of TMK1-sterol nanodomains and the polarization of PC. This prediction was experimentally validated by genetic and biochemical data. Our studies reveal a new paradigm for polarity establishment: A diffusive signal triggers cell polarization by activating cell surface receptor-mediated lateral segregation of signaling components and a cytoskeleton-mediated positive feedback loop of nanodomain stabilization.\n\nHighlightsO_LISterols are required for cell polarity in Arabidopsis leaf epidermal cells\nC_LIO_LIAuxin promotes lipid ordering and polar distribution of ordered lipid nanodomains at the plasma membrane (PM)\nC_LIO_LIAuxin stabilizes sterol-dependent nanoclustering of transmembrane kinase (TMK1), a PM auxin signal transducer\nC_LIO_LIAuxin-induced TMK1 nanoclustering is required but insufficient for cell polarization\nC_LIO_LIMicrotubule-based feedback stabilization of the auxin-induced TMK1 nanodomains can generate cell polarity\nC_LI

cell biology↗

Map3k2-Regulated Intestinal Stromal Cells (MRISC) Define a Distinct Sub-cryptic Stem Cell Niche for Damage Induced Wnt Agonist R-spondin1 Production

Intestinal stem cell propagation and differentiation are essential for rapid repair of tissue damage in the gut. While intestinal stromal cells were recently identified as key mediators of this process, the cellular and molecular mechanisms by which this diverse population induces tissue repair remains poorly understood. Here we show that Map3k2 has a colon stromal cell specific function critically required for maintenance of Lgr5+ intestinal stem cells and protection against acute intestinal damage. This Map3k2-specific function is mediated by enhancing Wnt agonist R-spondin1 production. We further reveal a unique novel cell population, named Map3k2-regulated intestinal stromal cells (MRISC), as the primary cellular source of R-spondin1 following intestinal injury. Together, our data identify a novel intestinal stem cell niche organized by MRISC, which specifically dependent on the Map3k2-signaling pathway to augment the production of Wnt agonist R-spondin1 and promote regeneration of the acutely damaged intestine.\n\nHighlightsO_LIMap3k2 protects mice from DSS-induced colitis by promoting intestinal stem cell regeneration.\nC_LIO_LIMap3k2-MAPK pathway cross-talks with Wnt signaling pathway via upregulation of R-spondin1.\nC_LIO_LIMap3k2-Regulated Intestinal Stromal Cells (MRISC) marked by co-expression of CD90, CD34 and CD81 defines a novel colonic stem cell niche.\nC_LI

cell biology↗

Arabidopsis ECERIFERUM3 (CER3) Plays a Critical Role in Maintaining Hydration for Pollen-Stigma Recognition during Fertilization

ABSTRACTPlants distinguish the pollen grains that land on their stigmas, only allowing compatible pollen to fertilize female gametes. To analyze the underlying mechanism, conditional male-sterile mutations with affected pollen coat and disrupted pollen-stigma recognition were isolated and described. The mutant pollen failed to germinate, but germinated in vitro, suggesting that they are viable. In mutants, stigma cells that contacted their own pollen generated callose, a carbohydrate produced in response to foreign pollen. High humidity restored pollen hydration and successful fertilization, indicating defective dehydration in pollen-stigma interaction. Further analysis results from mixed pollination experiments demonstrated that the mutant pollen specifically lacked a functional pollen-stigma recognition system. The sterile plants lacked stem waxes and displayed postgenital fusion between aerial floral organs. In addition, the mutant pollen was deficient in long-chain lipids and had excess tryphine. Transmission electron microscopy observation showed that mutant pollen had almost the same surface structure as the wild type at bicellular pollen stage. However, abnormal plastoglobuli were observed in the plastids of the mutant tapetum, which was indicative of altered lipid accumulation. CER3 transcript was found in anther tapetum and microspores at development stage 9 while CER3-GFP fusion protein was localized to the cell plasma membrane. Our data reveal that CER3 is required for biosynthesis of tryphine lipids which play a critical role in maintaining hydration for pollen-stigma recognition during fertilization.

developmental biology↗

Regenerative neurogenesis is induced from glia by Ia-2 driven neuron glia communication

Some animals can regenerate their central nervous system (CNS) after injury by inducing de novo neurogenesis: discovering the underlying mechanisms would help promote regeneration in the damaged human CNS. Glial cells could be the source of regenerative neurogenesis, but this is debated. The glia transmembrane protein Neuron-Glia antigen-2 (NG2) may have a key role in sensing injury-induced neuronal signals, however these have not been identified. Here, we used Drosophila genetics to search for functional neuronal partners of the NG2 homologue kon-tiki (kon), and identified Islet Antigen-2 (Ia-2), required in neurons for insulin secretion. Alterations in Ia-2 function induced neural stem cell fate, injury increased ia-2 expression and induced ectopic neural stem cells. Using genetic epistasis analysis and lineage tracing, we demonstrate that Ia-2 functions with Kon to regulate Drosophila insulin-like peptide 6 (Dilp-6) which in turn generates both more glial cells and neural stem cells from glia. Ectopic neural stem cells can divide, and limited de novo neurogenesis could be traced back to glial cells. Altogether, Ia-2 and Dilp-6 drive a neuron-glia relay that restores glia, and reprograms glia into neural stem cells for CNS regeneration.

neuroscience↗

Single-cell in vivo imaging reveals light-initiated circadian oscillators in zebrafish

Circadian clock is a cell-autonomous time-keeping mechanism established gradually during embryonic development. Here we generated a transgenic zebrafish line carrying a destabilized fluorescent protein driven by the promoter of a core clock gene, nr1d1, to report in vivo circadian rhythm at the single-cell level. By time-lapse imaging of this fish line, we observed the sequential initiation of the reporter expression starting at photoreceptors in pineal gland then spreading to cells in other brain regions. Even within pineal gland, we found heterogeneous onset of nr1d1 expression in which each cell undergoes circadian oscillation superimposed over cell-type specific developmental trajectory. Furthermore, we found that single-cell expression of nr1d1 showed synchronous circadian oscillation under light-dark cycle. Remarkably, single-cell oscillations were lost in animals raised under constant darkness while developmental trend still persists. It suggests that light exposure in early clock development initializes cellular clocks rather than synchronizes existing individual oscillators as previously believed.

neuroscience↗

Drought Resistance of 10 Ground Cover Seedling Species during Roof Greening

10 species drought resistance cases have been studied, including Paeonia lactiflora, Hemerocallis dumortieri, Physostegia virginiana, Iris lacteal, Hylotelephium erythrostictum, Sedum lineare, Iris germanica, Cosmos bipinnata, Hosta plantaginea and Dianthus barbatus. By researching these drought resistance cases, a suggestion can be given for roof greening. This research sets 3 drought stress scenarios by controlling the soil relative water content (RWC), including moderately drought stress (40%{+/-}2% < RWC < 45%{+/-}2%), strong drought stress (RWC < 30%{+/-}2%) and control group (RWC > 75%{+/-}2%). After the seedlings survived the drought stress, the damaging rate of permeability (DRP), total chlorophylls concentrations (Chl), superoxide dismutase (SOD), peroxidase (POD) and ascorbate peroxidase (AsAPOD) of seedlings will be measured. Finally, a subordinate function method was applied to assess these species drought resistance. Cosmos bipinnata and Physostegia virginiana was dead after having suffered with moderately drought stress and strong drought stress, respectively. Although other species survived, the individual variation was huge especially for physiological and biochemical index. Hemerocallis dumortieri, Iris lactea and Hosta plantagineas DRP had little change when they lived in the normal water condition and suffered with drought stress. Most of the species (except Paeonia lactiflora and Sedum lineare) showed a lower SOD activity during moderately drought stress compared with the sufficient soil water condition and strong drought stress condition. The changes of plants POD activity and AsAPOD activity are very similar: when drought stress enhanced, the activity of protect enzyme reduced. According to the subordinate function method, the order of plants resistance to the drought is as follow: Hosta plantaginea > Sedum lineare > Iris germanica > Hemerocallis dumortieri > Iris lactea >Hylotelephium erythrostictum > Dianthus barbatus > Paeonia lactiflora > Physostegia virginiana > Cosmos bipinnata.

ecology↗

The influence of visual cortex on perception is modulated by behavioural state

Our understanding of the link between neural activity and perception remains incomplete. Microstimulation and optogenetic experiments have shown that manipulating cortical activity can influence sensory-guided behaviour or elicit artificial percepts. And yet, some perceptual tasks can still be solved when sensory cortex is silenced or removed, suggesting that cortical activity may not always be essential. Reconciling these findings, and providing a quantitative framework linking cortical activity and behaviour, requires knowledge of the identity of the cells being activated during the behaviour, the engagement of the local and downstream networks, and the cortical and behavioural state. Here, we performed two-photon population calcium imaging in L2/3 primary visual cortex (V1) of headfixed mice performing a visual detection task while simultaneously activating specific groups of neurons using targeted two-photon optogenetics during low contrast visual stimulation. Only activation of groups of cells with similar tuning to the relevant visual stimulus led to a measurable bias of detection behaviour. Targeted photostimulation revealed signatures of centre-surround, predominantly inhibitory and like-to-like connectivity motifs in the local network which shaped the visual stimulus representation and partially explained the change in stimulus detectability. Moreover, the behavioural effects depended on overall performance: when the task was challenging for the mouse, V1 activity was more closely linked to performance, and cortical stimulation boosted perception. In contrast, when the task was easy, V1 activity was less informative about performance and cortical stimulation suppressed stimulus detection. Altogether, we find that both the selective routing of information through functionally specific circuits, and the prevailing cortical state, make similarly large contributions to explaining the behavioural response to photostimulation. Our results thus help to reconcile contradictory findings about the involvement of primary sensory cortex in behavioural tasks, suggesting that the influence of cortical activity on behaviour is dynamically reassigned depending on the demands of the task.

neuroscience↗

MicroRNA-378 suppressed osteogenesis of mesenchymal stem cells and impaired bone formation via inactivating Wnt/β-catenin signaling

MicroRNAs (miRNAs) have been reported to serve as silencers to repress gene expression at post-transcriptional level. Multiple miRNAs have been demonstrated to play important roles in osteogenesis. MiR-378, a conserved miRNA, was reported to mediate bone metabolism and influence bone development, but the detailed function and underlying mechanism remain obscure. In this study, the miR-378 transgenic (TG) mouse was developed to study the role of miR-378 in osteogenic differentiation as well as bone formation. The abnormal bone tissues and impaired bone quality were displayed in the miR-378 TG mice, and a delayed healing effect was observed during bone fracture of the miR-378 TG mice. The osteogenic differentiation of MSCs derived from this TG mouse was also inhibited. We also found that miR-378 mimics suppressed while anti-miR-378 promoted osteogenesis of human MSCs. Two Wnt family members Wnt6 and Wnt10a were identified as bona fide targets of miR-378, and their expression were decreased by this miRNA, which eventually induced the inactivation of Wnt/{beta}-catenin signaling. Finally, the sh-miR-378 modified MSCs were locally injected into the fracture sites in an established mouse fracture model. The results indicated that miR-378 inhibitor therapy could promote bone formation and stimulate healing process in vivo. In conclude, miR-378 suppressed osteogenesis and bone formation via inactivating Wnt/{beta}-catenin signaling, suggesting miR-378 may be a potential therapeutic target for bone diseases.

cell biology↗

New genotype invasion of dengue virus serotype 1 drove massive outbreak in Guangzhou, China

BackgroundDengue fever is a mosquito-borne infectious disease that has caused major health problems. Variations in dengue virus (DENV) genes are important features of epidemic outbreaks. However, the associations of DENV genes with epidemic scale have not been extensively examined. Here, we assessed new genotype invasion of DENV-1 isolated from Guangzhou in China to evaluate associations with epidemic outbreaks.\n\nMethodology/Principal FindingsWe used DENV-1 strains isolated from sera of dengue cases from 2002 to 2016 in Guangzhou for complete genome sequencing. A neighbor-joining phylogenetic tree was constructed to elucidate the genotype characteristics and determine if new genotype invasion correlated with major outbreaks. In our study, a new genotype invasion event was observed during each significant outbreak period in 2002-2003, 2006-2007 and 2013-2014. Genotype II was the main epidemic genotype in 2003 and before. Invasion of genotype I in 2006 caused an unusual outbreak with 765 cases (relative risk (RR)=16.24, 95% confidence interval (CI) =12.41-21.25). At the middle and late stages of the 2013 outbreak, genotype III was introduced to Guangzhou as a new genotype invasion responsible for 37340 cases with RR 541.73 (95%CI=417.78-702.45), after which genotypes I and III began co-circulating. Base mutations occurred after new genotype invasion, and the gene sequence of NS3 protein had the lowest average similarity ratio (99.82%), followed by the gene sequence of E protein (99.86%), as compared to the 2013 strain.\n\nConclusions/SignificanceGenotype replacement and co-circulation of multiple DENV-1 genotypes were observed. New genotype invasion was highly correlated with local unusual outbreaks. In addition to DENV-1 genotype I in the unprecedented outbreak in 2014, new genotype invasion by DENV-1 genotype III occurred in Guangzhou.\n\nAuthor SummaryNew genotype invasion of dengue virus highly correlates with the massive outbreaks. In this study, we examined the association of the genotype of dengue virus serorype 1 (DENV-1) from human cases through complete genome sequencing with outbreak scale during 2002 and 2016 in Guangzhou, China. It was observed that genotype replacement and co-circulation of multiple genotypes occurred. Most importantly, it indicated that new genotype invasion was highly related with local unusual outbreaks in major outbreak periods in 2002-2003, 2006-2007 and 2013-2014. DENV-1 genotype II was the main epidemic genotype in 2003 and before. Invasion of genotype I in 2006 caused an unusual outbreak with 765 cases reported. In addition to genotype I circulation, new genotype invasion by genotype III was the key determinant for the 2014 massive outbreak reaching the highest number of cases with 37340. Furthermore, base mutations appeared after genotype III invasion, and the gene sequence of NS3 protein had the lowest average similarity ratio, followed by the gene sequence of E protein, as compared to the 2013 strain.

epidemiology↗

Decoding WW Domain Tandem-mediated Target Recognitions in Tissue Growth and Cell Polarity

WW domain tandem-containing proteins such as KIBRA, YAP, and MAGI play critical roles in cell growth and polarity via binding to and positioning target proteins in specific subcellular regions. An immense disparity exists between promiscuity of WW domain-mediated target bindings and specific roles of WW domain scaffold proteins in cell growth regulation. Here, we discovered that WW domain tandems of KIBRA and MAGI, but not YAP, bind to specific target proteins with extremely high affinity and exquisite specificity. Via systematic structural biology and biochemistry approaches, we decoded the target binding rules of WW domain tandems from cell growth regulatory proteins and uncovered a list of previously unknown WW tandem binding proteins such as {beta}-Dystroglycan, JCAD, and PTPN21. The WW tandem-mediated target recognition mechanisms elucidated here can guide functional studies of WW domain proteins in cell growth and polarity as well as in other cellular processes including neuronal synaptic signaling.

biophysics↗