Biology subjects

Zhao, D.

Publications and source records attributed to Zhao, D..

125 records · Page 7Linked to original sources

bioRxiv2020

A preliminary study on the reproductive toxicity of GS-5734 on male mice

BackgroundGS-5734 as a novel and promising medicine for COVID-2019, its biological impact on the mammalian reproductive system has not been systematically studied. The aim of this study was to evaluate the effects of GS-5734 on sperm parameters and spermatogenesis in mice. Materials and MethodsIn this study, GS-5734 was synthesized according to the report. 28 adult male mice were randomly segregated into four groups (n=7 for each group). The group 1 was set as the control group, the group 1, 2, 3 and 4 were administered with GS-5734 at a daily dose of 0, 10, 50, 150 g/mouse respectively, by intraperitoneal injection for 10 days. On the 7th day after the last injection, the testes and cauda epididymides were collected for HE staining and sperm concentration, motility, morphology analysis. ResultsThe results indicated that after treated with GS-5734, the total sperm count and motile sperm rate showed downward trends, the abnormal sperm rate showed an increasing trend. As compared with the control group, GS-5734 at a daily dose of 150 g/mouse caused a significant decrease in sperm concentration and motility, and a significant increased of abnormal sperm rate; the 50 g/mouse drug treatment lead to a significant decrease in sperm motility and an increase in abnormal sperm rate. The HE staining of testicular and epididymal tissues showed that the spermatogenesis of mice was significantly deteriorated with the increasing dosage of GS-5734, especially in the 150 g/mouse group. ConclusionOur findings suggest that a high dosage of GS-5734 may induce testicular toxicity and result in deterioration of sperm parameters in mice. More investigation on the reproductive toxicity of GS-5734 is required.

developmental biology↗

bioRxiv2020

A data-driven drug repositioning framework discovered a potential therapeutic agent targeting COVID-19

The global spread of SARS-CoV-2 requires an urgent need to find effective therapeutics for the treatment of COVID-19. We developed a data-driven drug repositioning framework, which applies both machine learning and statistical analysis approaches to systematically integrate and mine large-scale knowledge graph, literature and transcriptome data to discover the potential drug candidates against SARS-CoV-2. The retrospective study using the past SARS-CoV and MERS-CoV data demonstrated that our machine learning based method can successfully predict effective drug candidates against a specific coronavirus. Our in silico screening followed by wet-lab validation indicated that a poly-ADP-ribose polymerase 1 (PARP1) inhibitor, CVL218, currently in Phase I clinical trial, may be repurposed to treat COVID-19. Our in vitro assays revealed that CVL218 can exhibit effective inhibitory activity against SARS-CoV-2 replication without obvious cytopathic effect. In addition, we showed that CVL218 is able to suppress the CpG-induced IL-6 production in peripheral blood mononuclear cells, suggesting that it may also have anti-inflammatory effect that is highly relevant to the prevention immunopathology induced by SARS-CoV-2 infection. Further pharmacokinetic and toxicokinetic evaluation in rats and monkeys showed a high concentration of CVL218 in lung and observed no apparent signs of toxicity, indicating the appealing potential of this drug for the treatment of the pneumonia caused by SARS-CoV-2 infection. Moreover, molecular docking simulation suggested that CVL218 may bind to the N-terminal domain of nucleocapsid (N) protein of SARS-CoV-2, providing a possible model to explain its antiviral action. We also proposed several possible mechanisms to explain the antiviral activities of PARP1 inhibitors against SARS-CoV-2, based on the data present in this study and previous evidences reported in the literature. In summary, the PARP1 inhibitor CVL218 discovered by our data-driven drug repositioning framework can serve as a potential therapeutic agent for the treatment of COVID-19.

systems biology↗

bioRxiv2020

An In Vitro Vascularized Micro-Tumor Model of Human Colorectal Cancer Recapitulates In Vivo Drug Responses

Around 95% of anti-cancer drugs that show promise during preclinical study fail to gain FDA-approval for clinical use. This failure of the preclinical pipeline highlights the need for improved, physiologically-relevant in vitro models that can better serve as reliable drug-screening tools. The vascularized micro-tumor (VMT) is a novel three-dimensional model system that recapitulates the complex human tumor microenvironment, including perfused vasculature, within a transparent microfluidic device, allowing real-time study of drug responses and tumor-stromal interactions. Here we have validated the VMT platform for the study of colorectal cancer (CRC), the second leading cause of cancer-related deaths, by showing that gene expression, tumor heterogeneity, and treatment response in the VMT more closely model CRC tumor clinicopathology than current standard drug screening modalities, including 2-dimensional (2D) monolayer culture and 3-dimensional (3D) spheroids.

cancer biology↗

bioRxiv2020

Mycobacterium tuberculosis Rv3194c efficiently facilitates mycobacterial-lung epithelial interaction through its HA-binding site

Mycobacterium tuberculosis adhesins are surface-exposed molecules that mediate pathogen-host interaction, a fundamental step towards host infection. Here we show that serine protease (Rv3194c) promotes mycobacterial infection to lung epithelial through its hyaluronic acid (HA)-binding site. Both enzyme-linked immunosorbent assay and surface plasmon resonance analysis revealed that Rv3194c bound to HA. Utilizing synthetic peptides, we next defined HA-binding site of 20 amino acids from 91 to 110 of Rv3194c (P91-110). Immunofluorescence assay and an FACScan showed that Rv3194c was interacted with A549 cells (human lung epithelial cells), and its interaction was abolished by the addition of hyaluronidase or P91-110. Experimental infection in Vitro revealed that Rv3194c participates in attachment of recombinant Mycobacterium smegmatis (Rv3194c/MS) to A549 cells, and P91-110 treatment of A549 cells almost inhibited Rv3194c/MS-A549 cells interaction. To provide in vivo evidence, we constructed a reporter strain of M. smegmatis expressed a derivative of the firefly luciferase that is shifted to red (FFlucRT) in combination with Rv3194c (Rv3194c+FFlucRT/MS) to infect the rodents and monitor the progression of the disease. Using bioluminescence imaging and bacterial counts in lung tissue confirmed that Rv3194c dramatically enhanced the persistence of M. smegmatis. In addition, treatment of intratracheal Rv3194c+FFlucRT/MS-infected mice with P91-110 significantly suppressed the growth of Rv3194c+FFlucRT/MS in vivo. Taken together, these results demonstrate that Rv3194c was identified as a HA-binding adhesin, and P91-110 as anti-adhesion agents has potential for therapeutic and prophylactic interventions in mycobacterial infection.

microbiology↗

bioRxiv2019

MONN: a Multi-Objective Neural Network for Predicting Pairwise Non-Covalent Interactions and Binding Affinities between Compounds and Proteins

Computational approaches for inferring the mechanisms of compound-protein interactions (CPIs) can greatly facilitate drug development. Recently, although a number of deep learning based methods have been proposed to predict binding affinities and attempt to capture local interaction sites in compounds and proteins through neural attentions, they still lack a systematic evaluation on the interpretability of the identified local features. In addition, in these previous approaches, the exact matchings between interaction sites from compounds and proteins, which are generally important for understanding drug mechanisms of action, still remain unknown. Here, we compiled the first benchmark dataset containing the inter-molecular non-covalent interactions for more than 10,000 compound-protein pairs, and used it to systematically evaluate the interpretability of neural attentions in existing prediction models. We developed a multi-objective neural network, called MONN, to predict both non-covalent interactions and binding affinity for a given compound-protein pair. MONN uses convolution neural networks on molecular graphs of compounds and primary sequences of proteins to effectively capture the intrinsic features from both inputs, and also takes advantage of the predicted non-covalent interactions to further boost the accuracy of binding affinity prediction. Comprehensive evaluation demonstrated that while the previous neural attention based approaches fail to exhibit satisfactory interpretability results without extra supervision, MONN can successfully predict non-covalent interactions on our benchmark dataset as well as another independent dataset derived from the Protein Data Bank (PDB). Moreover, MONN can outperform other state-of-the-art methods in predicting compound-protein binding affinities. In addition, the pairwise interactions predicted by MONN displayed compatible and accordant patterns in chemical properties, which provided another evidence to support the strong predictive power of MONN. These results suggested that MONN can offer a powerful tool in predicting binding affinities of compound-protein pairs and also provide useful insights into understanding the molecular mechanisms of compound-protein interactions, which thus can greatly advance the drug discovery process. The source code of the MONN model and the dataset creation process can be downloaded from https://github.com/lishuya17/MONN.

bioinformatics↗

bioRxiv2019

Mitochondrial DNA Copy Number and Incident Atrial Fibrillation

BackgroundMechanistic studies suggests that mitochondria DNA (mtDNA) dysfunction may be associated with increased risk of atrial fibrillation (AF). The association between mtDNA copy number (mtDNA-CN) and incident AF in the general population, however, remains unknown. MethodsWe conducted prospective analyses of 19,709 participants from the Atherosclerosis Risk in Communities Study (ARIC), the Multi-Ethnic Study of Atherosclerosis (MESA) and the Cardiovascular Health Study (CHS). mtDNA-CN from peripheral blood was calculated from probe intensities on the Affymetrix Genome-Wide Human single nucleotide polymorphisms (SNP) Array 6.0 in ARIC and MESA, and from multiplexed real time quantitative polymerase chain reaction (qPCR) in CHS. Incident AF cases were identified through electrocardiograms, review of hospital discharge codes, Medicare claims, and death certificates. ResultsThe median follow-up time was 21.4 years in ARIC, 12.9 years in MESA and 11.0 years in CHS, during which 4,021 participants developed incident atrial fibrillation (1,761 in ARIC, 790 in MESA, and 1,470 in CHS). The fully-adjusted pooled hazard ratio for incident atrial fibrillation comparing the 1st to the 5th quintile of mitochondria DNA copy number was 1.13 (1.01, 1.27). The fully-adjusted pooled hazard ratio comparing the 10th vs the 90th percentile of mitochondria DNA copy number was 1.13 (1.04, 1.24). Dose-response spline analysis also showed an inverse association between mitochondria DNA copy number and hazard for atrial fibrillation for all three cohorts. These associations were consistent across subgroups. ConclusionsMitochondria DNA copy number was inversely associated with the risk of AF independent of traditional cardiovascular risk factors. These findings implicate mitochondria DNA copy number as a novel risk factor for atrial fibrillation. Further research is warranted to understand the underlying mechanisms and to evaluate the role of mitochondria DNA copy number in the management of atrial fibrillation risk.

genetics↗

bioRxiv2019

Temporal-Spatial Visualization of Endogenous Chromosome Rearrangements in Living Cells

Visualizing the real-time dynamics of genome rearrangement in single living cells is core to studying genomics and diagnostics. Here, we report a robust, versatile approach named CRISPR Live-cell fluorescent in situ hybridization (LiveFISH) for multi-locus genome tracking and cytogenetic detection in a broad variety of cell types including primary cells. LiveFISH utilizes an intrinsic stability switch of CRISPR guide RNAs, which enables efficient and accurate detection of chromosomal disorders such as Patau Syndrome in prenatal amniotic fluid cells and allows multi-locus tracking in human T lymphocytes. Using LiveFISH, we are able to detect and track real-time spatiotemporal dynamics of non-homologous endogenous chromosome translocations induced by gene editing. This new approach enables FISH imaging in living primary cells, which can provide useful insights into the spatiotemporal changes of genome organization and rearrangements in normal and diseased primary cells and will enable fast cytogenetic visualization of various gene-editing associated chromosomal translocations.

bioengineering↗

bioRxiv2019

Bivalent and Broad Chromatin Domains Regulate Pro-metastatic Drivers in Melanoma

Chromatin deregulation is an emerging hallmark of cancer. However, the extent of epigenetic aberrations during tumorigenesis and their relationship with genetic aberrations are poorly understood. Using ChIP-sequencing for enhancers (H3K27ac and H3K4me1), promoters (H3K4me3), active transcription (H3K79me2) and polycomb (H3K27me3) or heterochromatin (H3K9me3) repression we generated chromatin state profiles in metastatic melanoma using 46 tumor samples and cell lines. We identified a strong association of NRAS, but not BRAF mutations, with bivalent states harboring H3K4me3 and H3K27me3 marks. Importantly, the loss and gain of bivalent states occurred on important pro-metastasis regulators including master transcription factor drivers of mesenchymal phenotype including ZEB1, TWIST1, SNAI1 and CDH1. Unexpectedly, a subset of these and additional pro-metastatic drivers (e.g. POU3F2, SOX9 and PDGFRA) as well as melanocyte-specific master regulators (e.g. MITF, ZEB2, and TFAP2A) were regulated by exceptionally wide H3K4me3 domains that can span tens of thousands of kilobases suggesting roles of this new epigenetic element in melanoma metastasis. Overall, we find that BRAF, NRAS and WT melanomas may use bivalent states and broad H3K4me3 domains in a specific manner to regulate pro-metastatic drivers. We propose that specific epigenetic traits - such as bivalent and broad domains - get assimilated in the epigenome of pro-metastatic clones to drive evolution of cancer cells to metastasis.

cancer biology↗

bioRxiv2019

In the chick embryo, estrogen can induce chromosomally male ZZ left gonad epithelial cells to form an ovarian cortex which supports oogenesis

In chickens, as in most amniotes, the first morphogenetic event in ovary differentiation is the formation of two distinct domains: a steroidogenic core, the medulla, overlain by the germ cell niche, the cortex. This process normally starts immediately after sex determination in the ZW embryos, substantially before the progression of germ cells into meiosis. In order to address the extent to which the cortical domain depends on intrinsic or extrinsic factors, we generated models of gonadal intersex by mixing ZW (female) and ZZ (male) cells in gonadal chimeras, or by altering estrogen levels of ZZ and ZW embryos in ovo. We found that both chomosomally female and male cells can be induced to form the cortical domain and that this can form relatively independently of the phenotypic sex of the medulla as long as estrogen is provided. We also show that the cortex promoting activity of estrogen signalling is mediated via Estrogen Receptor alpha within the left gonad epithelium. Therefore, either a ZW or ZZ cortical domain can provide an adequate niche to allow the germ cells to progress into meiosis. However, the presence of a medulla with an \"intersex\" or male phenotype may compromise this progression, causing cortical germ cells to remain in an immature state in the embryo.

developmental biology↗

bioRxiv2019

Molecular basis of P major human rotavirus VP8* domain interactions with histo-blood group antigens

Initial cell attachment of rotavirus (RV) to specific cell surface glycans, which is the essential first step in RV infection, is mediated by the VP8* domain of the spike protein VP4. Recently, human histo-blood group antigens (HBGAs) have been identified as ligands or receptors for human RV strains. RV strains in the P[4] and P[8] genotypes of the P[II] genogroup share common recognition of the Lewis b and H type 1 antigens, while P[6], which is one of the other genotypes in P[II], only recognizes the H type 1 antigen. The molecular basis of receptor recognition by the major human P[8] RVs remains unknown due to lack of experimental structural information. Here, we used nuclear magnetic resonance (NMR) titration experiments and NMR-derived high ambiguity driven docking (HADDOCK) methods to elucidate the molecular basis for P[8] VP8* recognition of the Leb and type 1 HBGAs and for P[6] recognition of H type 1 HBGAs. Unlike P[6] VP8* that recognizes H type 1 HGBAs in a binding surface composed of an -helix and a {beta}-sheet, referred as \"{beta} binding domain\", the P[8] VP8* binds the type 1 HBGAs requiring the presence of the Lewis epitope in a previously undescribed pocket formed by two {beta}-sheets, referred as \"{beta}{beta} binding domain\". The observation that P[6] and P[8] VP8* domains recognize different glycan structures at distinct binding sites supports the hypothesis that RV evolution is driven, at least in part, by selective pressure driven adaptation to HBGA structural diversity of their natural hosts living in the world. Recognition of the role that HBGAs play in driving RV evolution is essential to understanding RV diversity, host ranges, disease burden and zoonosis and to developing strategies to improve vaccines against RV infections.\n\nAuthor summaryRotaviruses (RV)s are the main cause of severe diarrhea in humans and animals. Significant advances in understanding RV diversity, evolution and epidemiology have been made after discovering that RVs recognize histo-blood group antigens (HBGAs) as host cell receptors. While different RV strains are known to have distinct binding preferences for HBGA receptors, the molecular basis in controlling strain-specific host ranges remains unclear. In this study, we used solution nuclear magnetic resonance to determine the molecular level details for interactions of the human P[8] and P[6] RV VP8* domains with their HBGA receptors. The distinct binding patterns observed between these major human RVs and their respective receptor ligands provides insight into the evolutionary relationships between different P[II] genotypes that ultimately determine host ranges, disease burden, zoonosis and epidemiology, which may impact future strategies for vaccine development against RVs.

biochemistry↗

bioRxiv2018

ACME: Pan-specific peptide-MHC class I binding prediction through attention-based deep neural networks

Prediction of peptide binding to MHC molecules plays a vital role in the development of therapeutic vaccines for the treatment of cancer. Although numerous computational methods have been developed to this end, several challenges still remain in predicting peptide-MHC interactions. Many previous methods are allele-specific, training separate models for individual alleles and are thus unable to yield accurate predictions for those alleles with limited training data. Despite that there exist several pan-specific algorithms that train a common model for different alleles, they only adopt simple model structures that generally have limited performance in capturing the complex underlying patterns of peptide-MHC interactions. Here we present ACME (Attention-based Convolutional neural networks for MHC Epitope binding prediction), a new pan-specific algorithm to accurately predict the binding affinities between peptides and MHC class I molecules, even for those new alleles that are not seen in the training data. Extensive tests have demonstrated that ACME can significantly outperform other state-of-the-art prediction methods with an increase of the Pearson Correlation Coefficient by up to 23 percent. In addition, its ability to identify strong-binding peptides has been experimentally validated. Moreover, by integrating the convolutional neural network with attention mechanism, ACME is able to extract interpretable patterns that can provide useful and detailed insights into the binding preferences between peptides and their MHC partners. All these results have demonstrated that ACME can provide a powerful and practically useful tool for the studies of peptide-MHC class I interactions.

bioinformatics↗

bioRxiv2018

Microbial and Metabolic Succession on Common Building Materials Under High Humidity Conditions

Despite considerable efforts to characterize the ecology of bacteria and fungi in the built environment (BE), the metabolic mechanisms underpinning their colonization and successional dynamics remain unclear. Here, we applied bacterial/viral particle counting, qPCR, 16S and ITS rRNA amplicon sequencing, and metabolomics to longitudinally characterize the ecological dynamics of four commonly used building materials maintained at high humidity conditions (~94% RH). We varied the natural inoculum provided to each material by placing them in different occupied spaces, and we wet the surface of half of the samples of each material to simulate a flooding event. As expected, different materials showed different bacterial and viral particle abundance, with wet materials having higher growth rates and lower alpha diversity compared to non-wetted materials. Wetting described the majority of the variance in bacterial, fungal and metabolite structure, and material type only influenced bacterial and metabolic diversity, while location of inoculation was only weakly associated with bacterial and fungal beta diversity. Metabolites indicative of microbial activity were identified, as were those that were native to the surface material. Glucose-phosphate was abundant on all materials (except mold-free gypsum) and was correlated with Enterobacteriaceae, which could indicate a potential bacterial nutrient source. A compound consistent with scopoletin, a plant metabolite with antimicrobial activity, was significantly negatively correlated with Bacillus and positively correlated with Pseudomonas and enriched in medium density fiberboard (MDF) materials. In wet samples, the alkaloids nigragillin and fumigaclavine C, both with antimicrobial properties, were significantly positively correlated with the fungal phylum Ascomycota. Nigragillin, was also negatively correlated with Bacillus and Pseudomonas abundance. Thiabendazole and azoxystrobin (anti-fungal compounds) were highly abundant on mold-resistant gypsum wallboard and likely directly influenced the decreased fungal growth observed on this material. The mold-resistant gypsum material also showed a significant increase in bacterial alpha diversity, and bacterial and viral particle abundance, as well as a decrease in metabolite diversity, likely a result of reduced fungal growth. Penicillium taxa were positively correlated with thiabendazole, which suggested the persistence of resistant strains. Also, specific to the wet samples, Bacillus abundance was positively correlated with the azoxystrobin, suggesting bi-directional competitive adaptation, and positively correlated with metabolites known to interfere with Pseudomonas biofilm formation, which could explain the anti-correlation between these taxa. As expected, high moisture conditions enabled faster growth of inoculating microorganisms, whose composition, chemistry, and competition was shaped by surface material, suggesting that both fungal and bacterial growth need to be considered when determining the impact of dampness in built environments.

microbiology↗

bioRxiv2018

PKD2 influence uric acid levels and gout risk by interacting with ABCG2

BackgroundUric acid is the final product of purine metabolism and elevated serum urate levels can cause gout. Conflicting results were reported for the effect of PKD2 on serum urate levels and gout risk. Therefore, our study attempted to state the important role of PKD2 in influencing the pathogenesis of gout.\n\nMethodSNPs in PKD2 (rs2725215 and rs2728121) and ABCG2 (rs2231137 and rs1481012) were tested in approximately 5,000 Chinese individuals.\n\nResultsTwo epistatic interactions between loci in PKD2 (rs2728121) and ABCG2 (rs1481012 and rs2231137) showed distinct contributions to uric acid levels with P int values of 0.018 and 0.004, respectively, and the associations varies by gender and BMI. The SNP pair of rs2728121 and rs1481012 justly played roles in uric acid in females (P int = 0.006), while the other pair did in males (P int = 0.017). Regarding BMI, the former SNP pair merely contributed in overweigh subjects (P int = 0.022) and the latter one did in both normal and overweigh individuals (P int = 0.013 and 0.047, respectively). Furthermore, the latter SNP pair was also associated with gout pathology (P int = 0.001), especially in males (P int = 0.001). Finally, functional analysis showed potential epistatic interactions in those genes region and PKD2 mRNA expression had a positive correlation with ABCG2s (r = 0.743, P = 5.83e-06).\n\nConclusionOur study for the first time identified that epistatic interactions between PKD2 and ABCG2 influenced serum urate concentrations and gout risk, and PKD2 might affect the pathogenesis from elevated serum urate to hyperuricemia to gout by modifying ABCG2.

genetics↗

bioRxiv2018

SMARTcleaner: identify and clean off-target signals in SMART ChIP-seq analysis

BackgroundNoises and artifacts may arise in several steps of the next-generation sequencing (NGS) process. Recently, a NGS library preparation method called SMART, or Switching Mechanism At the 5 end of the RNA Transcript, is introduced to prepare ChIP-seq (chromatin immunoprecipitation and deep sequencing) libraries from small amount of DNA material. The protocol adds Ts to the 3 end of DNA templates, which is subsequently recognized and used by SMART poly(dA) primers for reverse transcription and then addition of PCR primers and sequencing adapters. The poly(dA) primers, however, can anneal to poly(T) sequences in a genome and amplify DNA fragments that are not enriched in the immunoprecipitated DNA templates. This off-target amplification results in false signals in the ChIP-seq data.\n\nResultsHere, we show that the off-target ChIP-seq reads derived from false amplification of poly(T/A) genomic sequences have unique and strand-specific features. Accordingly, we develop a tool (called \"SMARTcleaner\") that can exploit the features to remove SMART ChIP-seq artifacts. Application of SMARTcleaner to several SMART ChIP-seq datasets demonstrates that it can remove reads from off-target amplification effectively, leading to improved ChIP-seq peaks and results.\n\nConclusionsSMARTcleaner could identify and clean the false signals in SMART-based ChIP-seq libraries, leading to improvement in peak calling, and downstream data analysis and interpretation.

bioinformatics↗

bioRxiv2017

High-throughput fitness profiling of Zika virus E protein reveals different roles for N-linked glycosylation during infection of mammalian and mosquito cells

Zika virus (ZIKV) infection causes Guillain-Barre syndrome and severe birth defects. ZIKV envelope (E) protein is the major viral protein involved in cell receptor binding and entry and therefore considered one of the major determinants in ZIKV pathogenesis. Here, we report a gene-wide mapping of functional residues of ZIKV E protein using a mutant library with changes covering every nucleotide position. By comparing the replication fitness of every viral mutant between mosquito and human cells, we identified that mutations affecting N-linked glycosylation at N154 position display the most divergence. Through characterizing individual mutants, we show that, while ablation of N-linked glycosylation selectively benefits ZIKV infection of mosquito cells by enhancing cell entry, it either had little impact on ZIKV infection on certain human cells or decreased infection through entry factor DC-SIGN. In conclusion, we define the roles of individual residues of ZIKV envelope protein, which contribute to ZIKV replication fitness in human and mosquito cells.\n\nHighlightsO_LIGene-wide mapping of functional residues of E protein in human and mosquito cells.\nC_LIO_LIMutations affecting N-linked glycosylation display the most dramatic difference.\nC_LIO_LIN-linked glycosylation decreases ZIKV entry into mosquito cells.\nC_LIO_LIN-linked glycosylation is important for DC-SIGN mediated infection of human cells.\nC_LI

microbiology↗

bioRxiv2017

Identification of Iridoid Synthases from Nepeta species: Iridoid cyclization does not determine nepetalactone stereochemistry

Graphical Abstract\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=105 SRC=\"FIGDIR/small/179572_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (91K):\norg.highwire.dtl.DTLVardef@cc600dorg.highwire.dtl.DTLVardef@1b6240dorg.highwire.dtl.DTLVardef@f8e1beorg.highwire.dtl.DTLVardef@1acb9dd_HPS_FORMAT_FIGEXP M_FIG Iridoid synthase from Nepeta cateria (catnip) and Nepeta mussinii, have been cloned and characterized.\n\nC_FIG AbstractNepetalactones are iridoid monoterpenes with a broad range of biological activities produced by plants in the Nepeta genus. However, none of the genes for nepetalactone biosynthesis have been discovered. Here we report the transcriptomes of two Nepeta species, each with distinctive profiles of nepetalactone stereoisomers. As a starting point for investigation of nepetalactone biosynthesis in Nepeta, these transcriptomes were used to identify candidate genes for iridoid synthase homologs, an enzyme that has been shown to form the core iridoid skeleton in several iridoid producing plant species. Iridoid synthase homologs identified from the transcriptomes were cloned, heterologously expressed, and then assayed with the 8-oxogeranial substrate. These experiments revealed that catalytically active iridoid synthase enzymes are present in Nepeta, though there are unusual mutations in key active site residues. Nevertheless, these enzymes exhibit similar catalytic activity and product profile compared to previously reported iridoid synthases from other plants. Notably, four nepetalactone stereoisomers with differing stereochemistry at the 4 and 7 positions - which are generated during the iridoid synthase reaction - are observed at different ratios in various Nepeta species. This work strongly suggests that the variable stereochemistry at these 4 and 7 positions of nepetalactone diastereomers is established further downstream in the iridoid pathway in Nepeta. Overall, this work provides a gateway into the biosynthesis of nepetalactones in Nepeta.\n\nHighlightsO_LISpecies within the Nepeta genus (such as catnip) produce nepetalactone iridoids\nC_LIO_LIThe enzymes that produce the iridoid scaffold of nepetalactone were identified from two species of Nepeta\nC_LIO_LIThe iridoid synthase enzymes are not responsible for the stereochemical variation in these iridoids\nC_LI

biochemistry↗

bioRxiv2017

Enriched expression of genes associated with autism spectrum disorders in human inhibitory neurons

Autism spectrum disorder (ASD) is highly heritable but genetically heterogeneous. The affected neural circuits and cell types remain unclear and may vary at different developmental stages. By analyzing multiple sets of human single cell transcriptome profiles, we found that ASD candidates showed enriched gene expression in neurons, especially in inhibitory neurons. ASD candidates were also more likely to be the hubs of the co-expressed module that is highly expressed in inhibitory neurons, a feature not detected for excitatory neurons. In addition, we found that upregulated genes in multiple ASD cortex samples were also enriched with genes highly expressed in inhibitory neurons, suggesting a potential increase of inhibitory neurons and an imbalance in the ratio between excitatory and inhibitory neurons. Furthermore, the downstream targets of several ASD candidates, such as CHD8, EHMT1 and SATB2, also displayed enriched expression in inhibitory neurons. Taken together, our analysis of single cell transcriptomic data suggest that inhibitory neurons may be the major neuron subtype affected by the disruption of ASD gene networks, providing single cell functional evidence to support the excitatory/inhibitory (E/I) imbalance hypothesis.

genetics↗