Biology subjects

Jiang, H.

Publications and source records attributed to Jiang, H..

At least 19 recordsLinked to original sources

bioRxiv2018

The mitochondrial DNA content can not predict the embryo viability

ObjectiveTo investigate whether the mitochondrial DNA content could predict the embryo viability\n\nDesignRetrospective analysis.\n\nSettingReproductive genetics laboratory\n\nPatient(s)A total of 421 biopsied samples obtained from 129 patients\n\nIntervention(s)Embryo biopsies samples underwent whole genome amplification (WGA) and were tested by next generation sequencing (NGS) and array Comparative Genomic Hybridization (aCGH), 30 samples were selected randomly to undergo quantitative real-time polymerase chain reaction (qPCR).\n\nMain Outcome Measure(s)Those embryos which obtained the consistent chromosome status determined both aCGH and NGS platform were further classified. We investigated the relationship of mtDNA content with several factors including female patient age, embryo morphology, chromosome status, and live birth rate of both blastocysts and blastomeres.\n\nResult(s)A total of 386 (110 blastomeres and 276 blastocysts) out of 399 embryos showed consistent chromosome status outcome. We found no statistically difference was observed in aneuploid and euploid blastocysts (p=0.14), the same phenomenon was observed in aneuploid and euploid blastomeres (p=0.89). Similarly, the mtDNA content was independent of female patient age, embryo morphology and live birth rate.\n\nConclusion(s)The mtDNA content did not provide a reliable prediction of the viability of blastocysts to initiate a pregnancy.

ecology↗

bioRxiv2018

The Dynamic Conformational Landscapes of the Protein Methyltransferase SETD8

Elucidating conformational heterogeneity of proteins is essential for understanding protein functions and developing exogenous ligands for chemical perturbation. While structural biology methods can provide atomic details of static protein structures, these approaches cannot in general resolve less populated, functionally relevant conformations and uncover conformational kinetics. Here we demonstrate a new paradigm for illuminating dynamic conformational landscapes of target proteins. SETD8 (Pr-SET7/SET8/KMT5A) is a biologically relevant protein lysine methyltransferase for in vivo monomethylation of histone H4 lysine 20 and nonhistone targets. Utilizing covalent chemical inhibitors and depleting native ligands to trap hidden high-energy conformational states, we obtained diverse novel X-ray structures of SETD8. These structures were used to seed massively distributed molecular simulations that generated six milliseconds of trajectory data of SETD8 in the presence or absence of its cofactor. We used an automated machine learning approach to reveal slow conformational motions and thus distinct conformational states of SETD8, and validated the resulting dynamic conformational landscapes with multiple biophysical methods. The resulting models provide unprecedented mechanistic insight into how protein dynamics plays a role in SAM binding and thus catalysis, and how this function can be modulated by diverse cancer-associated mutants. These findings set up the foundation for revealing enzymatic mechanisms and developing inhibitors in the context of conformational landscapes of target proteins.

biophysics↗

bioRxiv2018

Brg1 controls neurosensory cell fate commitment and differentiation in the mammalian inner ear

Otic ectoderm gives rise to almost all cell types of the inner ear; however, the mechanisms that link transcription factors, chromatin, lineage commitment and differentiation capacity are largely unknown. Here we show that Brg1 chromatin-remodeling factor is required for specifying neurosensory lineage in the otocyst and for inducing hair and supporting cell fates in the cochlear sensory epithelium. Brg1 interacts with the critical neurosensory-specific transcription factors Eya1/Six1, both of which simultaneously interact with BAF60a or BAF60c. Chromatin immunoprecipitation-sequencing (ChIP-seq) and ChIP assays demonstrate Brg1 association with discrete regulatory elements at the Eya1 and Six1 loci. Brg1-deficiency leads to markedly decreased Brg1 binding at these elements and loss of Eya1 and Six1 expression. Furthermore, ChIP-seq reveals Brg1-bound promoter-proximal and distal regions near genes essential for inner ear morphogenesis and cochlear sensory epithelium development. These findings uncover essential functions for chromatin-remodeling in the activation of neurosensory fates during inner ear development.

developmental biology↗

bioRxiv2018

The zebrafish orthologue of familial Alzheimer’s disease gene PRESENILIN 2 is required for normal adult melanotic skin pigmentation

Alzheimers disease is the most common form of age-related dementia. At least 15 mutations in the human gene PRESENILIN 2 (PSEN2) have been found to cause familial Alzheimers disease (fAD). Zebrafish possess an orthologous gene, psen2, and present opportunities for investigation of PRESENILIN function related to Alzheimers disease. The most prevalent and best characterized fAD mutation in PSEN2 is N141I. The equivalent codon in zebrafish psen2 is N140. We used genome editing technology in zebrafish to target generation of mutations to the N140 codon. We isolated two mutations: psen2N140fs, (hereafter \"N140fs\"), causing truncation of the coding sequence, and psen2T141_L142delinsMISLISV, (hereafter \"T141_L142delinsMISLISV\"), that deletes the two codons immediately downstream of N140 and replaces them with seven codons coding for amino acid residues MISLISV. Thus, like almost every fAD mutation in the PRESENILIN genes, this latter mutation does not truncate the genes open reading frame. Both mutations are homozygous viable although N140fs transcripts are subject to nonsense-mediated decay and lack any possibility of coding for an active {gamma}-secretase enzyme. N140fs homozygous larvae initially show grossly normal melanotic skin pigmentation but subsequently lose this as they grow while retaining pigmentation in the retinal pigmented epithelium. T141_L142delinsMISLISV homozygotes retain faint skin melanotic pigmentation as adults, most likely indicating that the protein encoded by this allele retains weak {gamma}-secretase activity. Null mutations in the human PRESENILIN genes do not cause Alzheimers disease so these two mutations may be useful for future investigation of the differential effects of null and fAD-like PRESENILIN mutations on brain aging.\n\nFinancial Disclosure StatementThis research was supported by grants from the National Health and Medical Research Council of Australia, GNT1061006 and GNT1126422, and by funds from the School of Biological Sciences of the University of Adelaide. HJ is supported by an Adelaide Scholarship International from the University of Adelaide.\n\nConflict of Interest StatementThe authors declare no conflict of interest.

genetics↗

bioRxiv2018

Sequencing of the MHC region defines HLA-DQA1 as the major independent risk for anti-citrullinated protein antibodies (ACPA)-positive rheumatoid arthritis in Han population

The strong genetic contribution of the major histocompatibility complex (MHC) to rheumatoid arthritis (RA) susceptibility has been generally attributed to HLA-DRB1. However, due to the high linkage disequilibrium in the MHC region, it is difficult to define the real or/and additional independent genetic risks using the conventional HLA genotyping or chip-based microarray technology. By the capture sequencing of entire MHC region for discovery and HLA-typing for validation in 2,773 subjects of Han ancestry, we identified HLA-DQ1:160D as the strongest independent genetic risk for anti-citrullinated protein antibodies (ACPA)-positive RA in Han population (P = 6.16 x 10-36, OR=2.29). Further stepwise conditional analysis revealed that DR{beta}1:37N has an independent protective effect on ACPA-positive RA (P = 5.81 x 10-16, OR=0.49). The DQ1:160 coding allele DQA1*0303 displayed high impact on joint radiographic severity, especially in patients with early disease and smoking (P = 3.02 x 10-5). Interaction analysis by comparative molecular modeling revealed that the negative charge of DQ1:160D stabilizes the dimer of dimers, leading to an increased T cell activation. The electrostatic potential surface analysis indicated that the negative charged DR{beta}1:37N encoding alleles could bind with epitope P9 arginine, thus may result in a decreased RA susceptibility.\n\nIn this study, we provide the first evidence that HLA-DQA1, instead of HLA-DRB1, is the strongest and independent genetic risk for ACPA-positive RA in Chinese Han population. Our study also illustrates the value of MHC deep sequencing for fine mapping disease risk variants in the MHC region.

genetics↗

bioRxiv2018

PARylation modulates stress granule assembly, phase separation, and neurotoxicity of ALS-related RNA-binding proteins

Mutations in RNA-binding proteins localized in ribonucleoprotein (RNP) granules, such as hnRNP A1 and TDP-43, promote aberrant protein aggregations, which are pathological hallmarks in neurodegenerative diseases including amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD). Protein posttranslational modifications (PTMs) are known to regulate RNP granules. In this study, we investigate the function of PARylation, an important PTM involved in DNA damage repair and cell death, in RNP-related neurodegeneration. We reveal that PARylation levels are a major regulator of the dynamic assembly-disassembly of RNP granules, and the disease-related RNPs such as hnRNP A1 and TDP-43 can both be PARylated and bind to PARylated proteins. We further identify the PARylation site of hnRNP A1 at K298, which controls the cytoplasmic translocation of hnRNP A1 in response to stress, as well as the PAR-binding motif (PBM) of hnRNP A1, which is required for the delivery and association of hnRNP A1 to stress granules. Moreover, we show that PAR not only dramatically enhances the liquid-liquid phase separation of hnRNP A1, but also promotes the co-phase separation of hnRNP A1 and TDP-43 in vitro and their interaction in vivo. Finally, we establish that both genetic and pharmacological inhibition of PARP mitigates hnRNP A1 and TDP-43-mediated neurotoxicity in cell and Drosophila models of ALS. Together, our findings indicate a novel and crucial role of PARylation in regulating the assembly and the dynamics of RNP granules, and dysregulation of PARylation may contribute to ALS disease pathogenesis.

neuroscience↗

bioRxiv2018

Suppression of p16 increases nucleotide synthesis via mTORC1

Reprogrammed metabolism and cell cycle dysregulation are two cancer hallmarks. p16 is a cell cycle inhibitor and tumor suppressor that is upregulated during oncogene-induced senescence (OIS). Loss of p16 allows for uninhibited cell cycle progression, bypass of OIS, and tumorigenesis. Whether p16 loss affects pro-tumorigenic metabolism is unclear. We report that suppression of p16 plays a central role in reprogramming metabolism by increasing nucleotide synthesis. This occurred via activation of mTORC1 signaling, which directly mediated increased translation of the mRNA encoding ribose-5-phosphate isomerase A (RPIA), a pentose phosphate pathway enzyme. p16 loss correlated with activation of the mTORC1-RPIA axis in multiple cancer types. Suppression of RPIA inhibited proliferation only in p16-low cells by inducing senescence both in vitro and in vivo. These data reveal the molecular basis whereby p16 loss modulates pro-tumorigenic metabolism through mTORC1-mediated upregulation of nucleotide synthesis and reveals a metabolic vulnerability of p16-null cancer cells.\n\nHighlightsO_LImTORC1 is activated by p16 knockdown to increase nucleotide synthesis and bypass senescence\nC_LIO_LImTORC1 directly increases translation RPIA to increase ribose-5-phosphate\nC_LIO_LIActivation of mTORC1 pathway downstream of p16 suppression is independent of RB\nC_LIO_LIRPIA suppression induces senescence only in cells and tumors with low p16\nC_LI

cancer biology↗

bioRxiv2018

Skin Lesion Classification Via Combining Deep Learning Features and Clinical Criteria Representations

Skin lesion is a severe disease globally. Early detection of melanoma in dermoscopy images significantly increases the survival rate. However, the accurate recognition of skin lesion is extremely challenging manually visualization. Hence, reliable automatic classification of skin lesions is meaningful to improve pathologists accuracy and efficiency. In this paper, we proposed a two-stage method to combine deep learning features and clinical criteria representations to address skin lesion automated diagnosis task. Stage 1 - feature encoding: Modified deep convolutional neural networks (CNNs, in this paper, we used Dense201 and Res50) were fine-tuned to extract rich image global features. To avoid hair noisy, we developed a lesion segmentation U-Net to mask out the decisive regions and used the masked image as CNNs inputs. In addition, color features, texture features and morphological features were exacted based on clinical criteria; Stage 2 - features fusion: LightGBM was used to select the salient features and model parameters, predicting diagnosis confidence for each category. The proposed deep learning frameworks were evaluated on the ISIC 2018 dataset. Experimental results show the promising accuracies of our frameworks were achieved.

bioinformatics↗

bioRxiv2018

Skin Lesion Segmentation with Improved C-UNet Networks

--This paper proposes an innovative method for Part1, skin lesion segmentation of the ISIC 2018 Challenge. Our network C-UNet is based on UNet network, we combined several methods on this basic network which made some improvements on Jaccard Index ultimately, our method yield an average Jaccard Index of 0.77 on the On-line validation dataset.

bioengineering↗

bioRxiv2018

Lesion Attributes Segmentation for Melanoma Detection with Deep Learning

Melanoma is the most deadly form of skin cancer worldwide. Many efforts have been made for early detection of melanoma. The International Skin Imaging Collaboration (ISIC) hosted the 2018 Challenges to help the diagnosis of melanoma based on dermoscopic images. In this paper, we describe our solutions for the task 2 of ISIC 2018 Challenges. We present two deep learning approaches to automatically detect lesion attributes of melanoma, one is a multi-task U-Net model and the other is a Mask R-CNN based model. Our multi-task U-Net model achieved a Jaccard index of 0.433 on official test data, which ranks the 5th place on the final leaderboard. The code for our solutions is publicly available.

bioinformatics↗

bioRxiv2018

A computational observer model of spatial contrast sensitivity: Effects of wavefront-based optics, cone mosaic structure, and inference engine

We present a computational observer model of the human spatial contrast sensitivity (CSF) function based on the Image Systems EngineeringTools for Biology (ISETBio) simulation framework. We demonstrate that ISETBio-derived CSFs agree well with CSFs derived using traditional ideal observer approaches, when the mosaic, optics, and inference engine are matched. Further simulations extend earlier work by considering more realistic cone mosaics, more recent measurements of human physiological optics, and the effect of varying the inference engine used to link visual representations to psy-chohysical performance. Relative to earlier calculations, our simulations show that the spatial structure of realistic cone mosaics reduces upper bounds on performance at low spatial frequencies, whereas realistic optics derived from modern wavefront measurements lead to increased upper bounds high spatial frequencies. Finally, we demonstrate that the type of inference engine used has a substantial effect on the absolute level of predicted performance. Indeed, the performance gap between an ideal observer with exact knowledge of the relevant signals and human observers is greatly reduced when the inference engine has to learn aspects of the visual task. ISETBio-derived estimates of stimulus representations at different stages along the visual pathway provide a powerful tool for computing the limits of human performance.

neuroscience↗

bioRxiv2018

Structural insight into the mechanism of neuraminidase inhibitor-resistant mutations in human-infecting H10N8 Influenza A virus

The emergence of drug resistance in avian influenza virus (AIV) is a serious concern for public health. Neuraminidase (NA) isolated from a fatal case of avian-origin H10N8 influenza virus infection was found to carry a drug-resistant mutation, NA-Arg292Lys (291 in N8 numbering). In order to understand the full potential of H10N8 drug resistance, the virus was first passaged in the presence of the most commonly used neuraminidase inhibitors (NAIs), oseltamivir and zanamivir. As expected, the Arg292Lys substitution was detected after oseltamivir treatment, however a novel Val116Asp substitution (114 in N8 numbering) was selected by zanamivir treatment. Next generation sequencing (NGS) confirmed that the mutations arose early (after passages 1-3) and became dominant in the presence of the NAI inhibitors. Extensive crystallographic studies revealed that N8-Arg292Lys resistance results mainly from loss of interactions with the inhibitor carboxylate, while rotation of Glu276 was not impaired as observed in the N9-Arg292Lys, a group 2 NA structure. In the case of Val116Asp, the binding mode between oseltamivir and zanamivir is different. Asp151 forms stabilized hydrogen bond to guanidine group of zanamivir, which may compensate the resistance caused by Val116Asp. By contrast, the amino group of oseltamivir is too short to maintain this hydrogen bond, which result in resistant. Moreover, the oseltamivir-zanamivir hybrid inhibitor MS-257 displays higher effectiveness to Val116Asp than oseltamivir, which support this notion.\n\nAuthor SummaryAside from vaccination, NAIs are currently the only alternative for the clinical treatment and prophylaxis of influenza. Understanding the mechanisms of resistance is critical to guide in drug development. In this study, two drug-resistant NA substitutions, Val116Asp and Arg292Lys, were discovered from oseltamivir and zanamivir treatment of H10N8 virus. Crystal structural analyses revealed two distinct mechanisms of these two resistant mutations and provide the explanation for the difference in susceptibility of different NAIs. Zanamivir and laninamivir were more effective against the resistant variants than oseltamivir, and Arg292Lys results in more serious oseltamivir resistance in N9 than N8 subtype. This study is well-correlated to influenza pandemic/epidemic pre-warning, as the discovery of inhibitor resistant viruses will help for new drug preparedness.

microbiology↗

bioRxiv2018

Protein Deacetylase CobB Interplays with c-di-GMP

As a ubiquitous bacterial secondary messenger, c-di-GMP plays key regulatory roles in processes such as bacterial motility and transcription regulation. CobB is the Sir2 family protein deacetylase that controls energy metabolism, chemotaxis and DNA supercoiling in many bacteria. Using an E.coli proteome microarray, we found that c-di-GMP strongly binds to CobB. Protein deacetylation assays showed that c-di-GMP inhibits CobB activity and thereby modulates the biogenesis of acetyl-CoA. Through mutagenesis studies, residues R8, R17 and E21 of CobB were shown to be required for c-di-GMP binding. Next, we found that CobB is an effective deacetylase of YdeH, a major diguanylate cyclase (DGC) of E.coli that is endogenously acetylated. Mass spectrometry analysis identified YdeH K4 as the major site of acetylation, and it could be deacetylated by CobB. Interestingly, deacetylation of YdeH enhances its stability and cyclase activity in c-di-GMP production. Thus, our work establishes a novel negative feedback loop linking c-di-GMP biogenesis and CobB-mediated protein deacetylation.

microbiology↗

bioRxiv2018

Reliable Multiplex Sequencing with Rare Index Mis-Assignment on DNB-Based NGS Platform

BackgroundMassively-parallel-sequencing, coupled with sample multiplexing, has made genetic tests broadly affordable. However, intractable index mis-assignments (commonly exceeds 1%) were repeatedly reported on some widely used sequencing platforms.\n\nResultsHere, we investigated this quality issue on BGI sequencers using three library preparation methods: whole genome sequencing (WGS) with PCR, PCR-free WGS, and two-step targeted PCR. BGIs sequencers utilize a unique DNB technology which uses rolling circle replication for DNA-nanoball preparation; this linear amplification is PCR free and can avoid error accumulation. We demonstrated that single index mis-assignment from free indexed oligos occurs at a rate of one in 36 million reads, suggesting virtually no index hopping during DNB creation and arraying. Furthermore, the DNB-based NGS libraries have achieved an unprecedentedly low sample-to-sample mis-assignment rate of 0.0001% to 0.0004% under recommended procedures.\n\nConclusionsSingle indexing with DNB technology provides a simple but effective method for sensitive genetic assays with large sample numbers.

genomics↗

bioRxiv2018

Overexpressed microRNA-141-3p enhance proliferation via targeting PLAG1 in non-diabetic macrosomia

Several studies have shown microRNAs (miRNAs) could regulate the placental development, yet the role and mechanism of miRNAs in the development of non-diabetic macrosomia (NDFMS) remains unclear. The key miRNA that abnormal expressed in NDFMS placentas was screened out by miRNA microarray and verified using qRT-PCR in 91 subjects. The effects of the key miRNA were verified by proliferation assay and invasion assay in HTR-8/SVneo cell, and also in pregnant C57BL/6J mice. miR-141-3p was determined as the key miRNA with the most significant difference, which could promote the proliferation and invasion by regulating the expression of target gene PLAG1. Overexpression of PLAG1 could reverse the effect of cell proliferation and invasion ability caused by miR-141-3p overexpression. Significant difference in fetal birth weight was observed between the control group and treated group with miR-141-3p agomir in late pregnancy, but not in early pregnancy. This study revealed miR-141-3p could increase the proliferation of placenta to participate in the occurrence and development of NDFMS through regulating PLAG1 expression.

developmental biology↗

bioRxiv2018

A genetically-encoded fluorescent acetylcholine indicator

Acetylcholine (ACh) regulates a diverse array of physiological processes throughout the body, yet cholinergic transmission in the majority of tissues/organs remains poorly understood due primarily to the limitations of available ACh-monitoring techniques. We developed a family of G-protein-coupled receptor activation-based ACh sensors (GACh) with sensitivity, specificity, signal-to-noise ratio, kinetics and photostability suitable for monitoring ACh signals in vitro and in vivo. GACh sensors were validated with transfection, viral and/or transgenic expression in a dozen types of neuronal and non-neuronal cells prepared from several animal species. In all preparations, GACh sensors selectively responded to exogenous and/or endogenous ACh with robust fluorescence signals that were captured by epifluorescent, confocal and/or two-photon microscopy. Moreover, analysis of endogenous ACh release revealed firing pattern-dependent release and restricted volume transmission, resolving two long-standing questions about central cholinergic transmission. Thus, GACh sensors provide a user-friendly, broadly applicable toolbox for monitoring cholinergic transmission underlying diverse biological processes.

neuroscience↗

bioRxiv2018

Identification and Quantification of Paclitaxel and its Metabolites in Human Meconium from Newborns with Gestational Chemotherapeutic Exposure

ObjectiveCancer diagnosis during pregnancy occurs in 1 out of 1000 pregnancies with common malignancies including breast and hematological cancers. Fetal exposure to currently utilized agents is poorly described. We directly assessed fetal exposure by screening meconium from 23 newborns whose mothers had undergone treatment for cancer during pregnancy.\n\nStudy DesignMeconium was collected from newborns whose mothers were diagnosed with cancer during pregnancy and underwent chemotherapy in the second or third trimester as part of the Cancer and Pregnancy Registry. We conducted screening of 23 meconium samples for chemotherapeutics and known metabolites of chemotherapeutics by liquid chromatography-high resolution mass spectrometry (LC-HRMS). Putative identification of paclitaxel and/or its metabolites was made in 8 screened samples. In positively screened samples, we quantified paclitaxel, 3-p-hydroxypaclitaxel, and 6-hydroxypaclitaxel by stable isotope dilution-LC-HRMS.\n\nResultsMean levels of paclitaxel were 399.9 pg/mg in meconium samples from newborn born to mothers that underwent chemotherapy during pregnancy. 3-p-hydroxypaclitaxel and 6-hydroxypaclitaxel mean levels were 105.2 and 113.4 pg/mg meconium, respectively.\n\nConclusionIntact paclitaxel, and at least two of its major metabolites were detected in meconium, providing unambiguous confirmation of human fetal exposure. Variability in meconium levels between individuals may indicate a potential for reducing fetal exposure based on timing, dosing, and individual characteristics. This preliminary study may provide an efficient approach for examining the effects of cancer diagnosis during pregnancy on other outcomes by providing a measure of direct fetal exposure.

pharmacology and toxicology↗

bioRxiv2018

Computational-Observer Analysis of Illumination Discrimination

The spectral properties of the ambient illumination provide useful information about time of day and weather. We study the perceptual representation of illumination by analyzing measurements of how well people discriminate between illuminations across scene configurations. More specifically, we compare human performance to a computational-observer analysis that evaluates the information available in the isomerizations of the cones in a model human photoreceptor mosaic. Some patterns of human performance are predicted by the computational observer, other aspects are not. The analysis clarifies which aspects of performance require additional explanation in terms of the action of visual mechanisms beyond the isomerization of light by the cones.

neuroscience↗