Biology subjects

Xu, Z.

Publications and source records attributed to Xu, Z..

At least 505 records · Page 28Linked to original sources

bioRxiv2019

Gene-methylation interactions: Discovering region-wise DNA methylation levels that modify SNP-associated disease risk

The genetic code is tightly linked to epigenetic instructions as to what genes to express, and when and where to express them. The most studied epigenetic mark is DNA methylation at CpG dinucleotides. Todays technology enables a rapid assessment of DNA sequence and methylation levels at a single-site resolution for hundreds of thousands of sites in the human genome, in thousands of individuals at a time. Recent years have seen a rapid increase in epigenome-wide association studies (EWAS) searching for the causes of risk for genetic diseases that previous genome-wide association studies (GWAS) could not pinpoint. However, those single-omics data analyses led to even more questions and it has become clear that only by integrating data one can get closer to answers. Here, we propose two new methods within genetic association analyses that treat the level of DNA methylation at a given CpG site as environmental exposure. Our analyses search for statistical interactions between a given allele and DNA methylation (GxMe), and between a parent-of-origin effect and DNA methylation (PoOx Me). The new methods were implemented in the R package Haplin and were tested on a dataset comprising genotype data from mother-father-child triadsm with DNA methylation data from the children only. The phenotype here was orofacial clefts (OFC), a relatively common birth defect in humans, which is known to have a genetic origin and an environmental component possibly mediated by DNA methylation. We found no significant PoOxMe interactions and a few significant GxMe interactions. Our results show that the significance of these interaction effects depends on the genomic region in which the CpGs reside and on the number of strata of methylation level. We demonstrate that, by including the methylation level around the SNP in the analyses, the estimated relative risk of OFC can change significantly. We also discuss the importance of including control data in such analyses. The new methods will be of value for all the researchers who want to explore genome- and epigenome-wide datasets in an integrative manner. Moreover, thanks to the implementation in a popular R package, the methods are easily accessible and enable fast scans of the genome- and epigenome-wide datasets.

epidemiology↗

bioRxiv2019

Translational control of breast cancer plasticity

Plasticity of neoplasia, whereby cancer cells attain stem-cell-like properties, is required for disease progression and represents a major therapeutic challenge. We report that in breast cancer cells NANOG, SNAIL and NODAL transcripts manifest multiple isoforms characterized by different 5 Untranslated Regions (5UTRs), whereby translation of a subset of these isoforms is stimulated under hypoxia. This leads to accumulation of corresponding proteins which induce plasticity and \"fate-switching\" toward stem-cell like phenotypes. Surprisingly, we observed that mTOR inhibitors and chemotherapeutics induce translational activation of a subset of NANOG, SNAIL and NODAL mRNA isoforms akin to hypoxia, engendering stem cell-like phenotypes. Strikingly, these effects can be overcome with drugs that antagonize translational reprogramming caused by eIF2 phosphorylation (e.g. ISRIB). Collectively, our findings unravel a hitherto unappreciated mechanism of induction of plasticity of breast cancer cells, and provide a molecular basis for therapeutic strategies aimed at overcoming drug resistance and abrogating metastasis.

cancer biology↗

bioRxiv2019

Volumetric two-photon imaging in live cells and embryos via axially gradient excitation

Two-photon microscopy(TPM) that features subcellular resolution, intrinsic optical sectioning ability, and deep penetration in sample is a powerful tool of bioimaging. However, the process of layer-by-layer scanning to form a 3D image inherently limits the volumetric imaging speed and significantly increases the phototoxicity. Here we develop a gradient TPM technique that enables rapid volumetric imaging by only acquiring two 2D images. By sequentially exciting the specimen with two axially elongated two-photon beams with complementary gradient intensities, the axial positions of fluorophores can be decoded from the intensity ratio of the paired images. We achieve an axial localization accuracy of 0.728 {+/-} 0.657 m, which is sufficient for rapid 3D subcellular imaging. We demonstrate the flexibility of the gradient TPM on a variety of sparsely labelled samples, including bead phantoms, mouse brain tissues, live macrophages and live nematode embryos. The results show that, compared with conventional TPM, the 3D imaging speed increases 6 folds while the photobleaching and photodamage are extremely reduced.

bioengineering↗

bioRxiv2019

Characterizing neuronal synaptic transmission using stochastic hybrid systems

Action potential-triggered release of neurotransmitters at chemical synapses forms the key basis of communication between two neurons. To quantify the stochastic dynamics of the number of neurotransmitters released, we investigate a model where neurotransmitter-filled vesicles attach to a finite number of docking sites in the axon terminal, and are subsequently released when the action potential arrives. We formulate the model as a Stochastic Hybrid System (SHS) that combines three key noise mechanisms: random arrival of action potentials, stochastic refilling of docking sites, and probabilistic release of docked vesicles. This SHS representation is used to derive exact analytical formulas for the mean and noise (as quantified by Fano factor) in the number of vesicles released per action potential. Interestingly, results show that in relevant parameter regimes, noise in the number of vesicles released is sub-Poissonian at low frequencies, super-Poissonian at intermediate frequencies, and approaches a Poisson limit at high frequencies. In contrast, noise in the number of neurotransmitters in the synaptic cleft is always super-Poissonian, but is lowest at intermediate frequencies. We further investigate changes in these noise properties for non-Poissonian arrival of action potentials, and when the probability of release is frequency dependent. In summary, these results provide the first glimpse into synaptic parameters not only determining the mean synaptic strength, but also shaping its stochastic dynamics that is critical for information transfer between neurons.

neuroscience↗

bioRxiv2019

FabriEVEs: A dedicated platform for endogenous viral elements in fishes, amphibians, birds, reptiles and invertebrates

Endogenous viral elements (EVEs) are heritable viral deriving elements present in the genomes of other species. As DNA fossils left by ancient viruses, EVEs were used to infer the characteristics of extinct viruses. EVEs in mammals have been well classified by several databases, however, EVEs in non-mammalian organisms are poorly documented. Here, we report FabriEVEs (http://tfbsbank.co.uk/FabriEVEs), the first dedicated and comprehensive online platform for the collection, classification and annotation of EVEs in fishes, amphibians, birds, reptiles and invertebrates. In total, nearly 1.5 million EVEs from 82 species deriving from class I (dsDNA), II (ssDNA), III (dsRNA), IV (positive ssRNA), V (negative ssRNA), VI (ssRNA-RT) and VII (dsDNA-RT) viruses were recorded in FabriEVEs, accompanying with comprehensive annotation including the species name, location, genomic features, virus family and associated literature. Flexible and powerful query options were provided to pinpoint desired EVEs. Furthermore, FabriEVEs provides free access to all EVEs data in case users need to download them for further analysis. Taken together, our database provided systematic classification and annotation of EVEs in non-mammal species, which paves the way for comparative analysis of EVEs and throws light upon the co-evolution of EVEs and their hosts.

evolutionary biology↗

bioRxiv2019

Molecular characterization of Chlamydomonas reinhardtii telomeres and telomerase mutants

Telomeres are repeated sequences found at the end of the linear chromosomes of most eukaryotes and are required for chromosome integrity. They shorten with each cell division because of the end-replication problem. Expression of the reverse transcriptase telomerase allows for extension of telomeric repeats to counteract telomere shortening. Although Chlamydomonas reinhardtii, a photosynthetic unicellular green alga, is widely used as a model organism in photosynthesis and flagella research, and for biotechnological applications, the biology of its telomeres has not been investigated in depth. Here, we show that the C. reinhardtii (TTTTAGGG)n telomeric repeats are mostly non-degenerate and that the telomeres form a protective structure, ending with a 3' overhang. While telomere size and length distributions are stable under various standard growth conditions, they vary substantially between 12 genetically close reference strains. Finally, we identify CrTERT, the gene encoding the catalytic subunit of telomerase and show that mutants of this gene display an \"ever shortening telomere\" phenotype and eventually enter replicative senescence, demonstrating that telomerase is required for long-term maintenance of telomeres in C. reinhardtii.

plant biology↗

bioRxiv2019

egKnock: identifying direct gene knockout strategies for microbial strain optimization based on metabolic network with gene-protein-reaction relationships

BackgroundGene knockout method has been used to improve the conversion ratio of industrial strains for many chemical products. There are a series of published algorithms to predict the targets for deletion. Based on metabolic networks, many of these algorithms are designed to predict the target of reaction or enzyme deletion. But as for the many-to-many relationship between genes and reactions, reaction or enzyme deletion is not the ideal strategy for metabolic engineering. GDLS algorithm aims to find direct gene deletion target by using local search, but it actually ignores the logic relationship of gene-protein-reaction.\n\nResultsIn this study, we aim to find direct gene deletion targets for metabolic network, but the logic relationship of gene-protein-reaction (GPR) is considered. Our algorithm is call egKnock. At the same time, egKnock will provide the solution with multiple strategies and can maximize the minimum target flux of industrial objective in flux variability analysis. We compare egKnock with the algorithm of GDLS and OptORF by predicting the targets of gene deletion for several chemical products with their flux balance analysis testification, flux variability analysis testification and the main flux distribution.\n\nConclusionsBy comparison with the algorithm of GDLS and OptORF, we can conclude that egKnock is a nice algorithm for identifying direct gene knockout strategies for microbial strain optimization.

synthetic biology↗

bioRxiv2019

Budding yeast centromeric DNA and A+T rich bacterial DNA can function as centromeres in the fission yeast Schizosaccharomyces pombe.

Eukaryotic centromeric DNA is famously variable in evolution but currently, this cannot be reconciled with the conservation of eukaryotic centromere function. It seems likely that centromeric DNA from different organisms contains conserved functionally important features but the identity of these features is unknown. The point centromeres of the budding yeast Saccharomyces cerevisiae and the regional centromeres of the fission yeast Schizosaccharomyces pombe are separated by 350 million years of evolution and are canonical examples of the paradoxical relationship1 between centromeric DNA sequence and function. We have established a centromere-replacement strategy in Schizosaccharomyces pombe in order to resolve this paradox experimentally. Centromere-replacement shows that an A+T rich bacterial DNA sequence has weak centromere function and that elements of the Saccharomyces cerevisiae centromere embedded in short sequences from the non-centromeric S. pombe wee1 gene function almost as well as native S. pombe centromeric DNA. These observations demonstrate that determinants of centromere function are held in common by the budding and fission yeasts and that A+T rich DNA is both necessary and sufficient for function in S. pombe. Given the evolutionary distance between these yeasts, it is likely that A+T rich DNA has centromere function in a wide variety of eukaryotes. Centromere-replacement uses unidirectional serine recombinases that work well in many organisms2 3 and our experimental strategy should allow this idea to be tested in other eukaryotes.

genetics↗

bioRxiv2018

Native CRISPR-Cas mediated in situ genome editing reveals extensive resistance synergy in the clinical multidrug resistant Pseudomonas aeruginosa

Antimicrobial resistance (AMR) is imposing a global public health threat. Despite its importance, resistance characterization in the native background of clinically isolated resistant pathogens is frequently hindered by the lack of genome editing tools in these \"non-model\" strains. Pseudomonas aeruginosa is both a prototypical multidrug resistant (MDR) pathogen and a model species for understanding CRISPR-Cas functions. In this study, we report the successful development of the first native type I-F CRISPR-Cas mediated, one-step genome editing technique in a paradigmatic MDR strain PA154197. The technique is readily applicable in additional type I-F CRISPR-containing, clinical/environmental P. aeruginosa isolates. A two-step In-Del strategy is further developed to edit genomic locus lacking an effective PAM (protospacer adjacent motif) or within an essential gene, which together principally allows any type of non-lethal genomic manipulations in these strains. Exploiting these powerful techniques, a series of reverse mutations are constructed and the key resistant determinants of the MDR PA154197 are elucidated which include over-production of two multidrug efflux pumps MexAB-OprM and MexEF-OprN, and a typical fluoroquinolone (FQ) resistance mutation T83I in the drug target gene gyrA. Characterizing antimicrobial susceptibilities in isogenic strains containing various combinations of single, double, or all three key resistance determinants reveal that i) extensive synergy exists between the target mutation and over-production of efflux pumps, and between the two over-produced tripartite efflux pumps to confer clinically significant FQ resistance; ii) while basal level MexAB-OprM confers resistance only to penicillins, its over-production leads to substantial resistance to all antipseudonmonal {beta}-lactams and additional resistance to FQs; iii) despite the acquisition and over-production of multiple resistant mutations, no obvious evolutionary trade-off of collateral sensitivity is developed in PA154197. Together, these results provide new insights into resistance development in clinical MDR P. aeruginosa strains and demonstrate the great potentials of native CRISPR systems in AMR research.

microbiology↗

bioRxiv2018

An Empirical Bayes Approach for the Identification of Long-range Chromosomal Interaction from Hi-C Data

Hi-C experiments have become very popular for studying the 3D genome structure in recent years. Identification of long-range chromosomal interaction, i.e., peak detection, is crucial for Hi-C data analysis. But it remains a challenging task due to the inherent high dimensionality, sparsity and the over-dispersion of the Hi-C count data matrix. We propose EBHiC, an empirical Bayes approach for peak detection from Hi-C data. The proposed framework provides flexible over-dispersion modeling by explicitly including the 'true' interaction intensities as latent variables. To implement the proposed peak identification method (via the empirical Bayes test), we estimate the overall distributions of the observed counts semiparametrically using a smoothed EM algorithm, and the empirical null by discrete curve fitting. We conducted extensive simulations to validate and evaluate the performance of our proposed approach and applied it to real datasets. Our results suggest that EBHiC can better identify peaks than Fit-Hi-C in terms of accuracy, biological interpretability, and the consistency across biological replicates.

bioinformatics↗

bioRxiv2018

Integrated analysis of sex-biased mRNA and miRNA expression profiles in the gonad of the discus fish (Symphysodon aequifasciatus)

The discus fish (Symphysodon aequifasciatus) is an ornamental fish that is well-known around the world. Phenotype investigation indicated that there are no significant differences in appearance between males and females of the discus fish. To better understand the sexual development mechanisms and obtain a high efficiency sex identification method in the artificial reproduction process of the discus fish, we constructed six cDNA libraries from three adult testes and three adult ovaries, and perform RNA-sequencing for identifying sex-biased candidate genes, microRNA (miRNA), and metabolic pathway using the Illumina Hiseq 4000. A total of 50,082 non-redundant genes (unigenes) were identified, of which 18,570 unigenes were significantly overexpressed in testes, and 11,182 unigenes were significantly overexpressed in ovaries, and 8 differentially expressed unigenes were validated by quantitative Real-Time PCR (qPCR). A total of 551 miRNAs were identified, of which 47 miRNAs were differentially expressed between testes and ovaries, and 7 differentially expressed miRNAs and one non-differential miRNA were validated by qPCR. Twenty-four of these differentially expressed miRNAs and their 15 predicted target genes constituted 41 important miRNA-mRNA interaction pairs, which may be important candidates for sex-related miRNAs and sex-related genes in the discus fish. Some of vital sex-related metabolic pathways were also identified that may play key roles in regulating gonad development of the discus fish. These results can provide important insights to better understand molecular mechanisms for sexual dimorphism in gonads development.

genetics↗

bioRxiv2018

Comparative genetic architectures of schizophrenia in East Asian and European populations

Author summarySchizophrenia is a severe psychiatric disorder with a lifetime risk of about 1% world-wide. Most large schizophrenia genetic studies have studied people of primarily European ancestry, potentially missing important biological insights. Here we present a study of East Asian participants (22,778 schizophrenia cases and 35,362 controls), identifying 21 genome-wide significant schizophrenia associations in 19 genetic loci. Over the genome, the common genetic variants that confer risk for schizophrenia have highly similar effects in those of East Asian and European ancestry (rg=0.98), indicating for the first time that the genetic basis of schizophrenia and its biology are broadly shared across these world populations. A fixed-effect meta-analysis including individuals from East Asian and European ancestries revealed 208 genome-wide significant schizophrenia associations in 176 genetic loci (53 novel). Trans-ancestry fine-mapping more precisely isolated schizophrenia causal alleles in 70% of these loci. Despite consistent genetic effects across populations, polygenic risk models trained in one population have reduced performance in the other, highlighting the importance of including all major ancestral groups with sufficient sample size to ensure the findings have maximum relevance for all populations.

genetics↗

bioRxiv2018

RegKnock: identifying gene knockout strategies for microbial strain optimization based on regulatory and metabolic integrated network

BackgroundGene knockout has been used to improve the conversion ratio of strains for some chemical products. Based on mixed integer bi-level linear programming (MIBLP) and cell network models, there have been several algorithms to predict the target for deletion to improve the productivity of chemicals. At present, the cell models on which these algorithms based have changed from metabolic network to metabolic-regulatory integrated network, for integrated network is more comprehensive in describing the behavior of cells. Metabolic-regulatory integrated network is better than metabolic network in flux prediction, but will introduce integer variables in the inner of MIBLP. How to solve the intractable MIBLP, however, is not explicated clearly as in mathematical literatures, especially for MIBLP with integer variables in the inner problem (named as MIBLP-2) where integer variables are introduced by the flux balance analysis (FBA) for integrated network. Dual theory was still be used to transform MIBLP-2 to a single level with ignoring integer variables in the inner problem. Intelligent computation is another choice for solving MIBLP, but it usually was used to solve the single level nonlinear programming (NLP) which was the transformation from MIBLP by using joint objective of upper/lower level, while the equivalence between this MIBLP and this NLP was not be proved in mathematics.\n\nMethodsIn this study, we develop a new target predicting algorithm for gene knockouts, named RegKnock. The cell model on which we base is metabolic-regulatory integrated network as well. When solving the MIBLP-2, RegKnock uses Parallel Genetic Algorithm (PGA), but not use joint objective. GA was used to generate control variables of the upper, indicating which genes should be deleted, while the fitness function is to maximize the objective product calculated from the inner FBA of the integrated network. FBA of the inner problem, a mixed integer programming, could be solved by existing optimization softwares. Parallel computation aims to accelerate finding the optimal solution and thus decreases the time of computation.\n\nResults and ConclusionsWith comparing with OptORF and OptFlux, two published target predicting algorithm for gene knockouts which also aiming at integrated network, two merits have been shown for RegKnock, i.e. absolutely accuracy and not a long time of computation. So RegKnock is a nice algorithm for predicting algorithm for gene deletions as for integrated network.

synthetic biology↗

bioRxiv2018

A draft reference genome sequence for Scutellaria baicalensis Georgi

Scutellaria baicalensis Georgi is an important medicinal plant used worldwide. Information about the genome of this species is important for scientists studying the metabolic pathways that synthesise the bioactive compounds in this plant. Here, we report a draft reference genome sequence for S. baicalensis obtained by a combination of Illumina and PacBio sequencing, which was assembled using 10 X Genomics and Hi-C technologies. We assembled 386.63 Mb of the 408.14 Mb genome, amounting to about 94.73% of the total genome size, and the sequences were anchored onto 9 pseudochromosomes with a super-N50 of 33.2 Mb. The reference genome sequence of S. baicalensis offers an important foundation for understanding the biosynthetic pathways for bioactive compounds in this medicinal plant and for its improvement through molecular breeding.

plant biology↗

bioRxiv2018

The Enzymes that beyond Non-Oxidative Glycolysis

High yield is an important objective of cell factory. One or several genes cloned into the bacterial may make the synthetic pathway much more optimal, so can increase the yield. But the global benefit enzymes are rare, which can increase the yields of many chemical products for a cell factory such as E.coli. Two of these kinds of global benefit enzymes are the famous enzymes, D-fructose-6-phosphate D-erythrose-4-phosphate-lyase and D-Xylulose 5-phosphate D-glyceraldehyde-3-phosphate-lyase, of non-oxidative glycolysis (NOG) published in Nature, which can improve the utilization ratio of carbon. We expect to find other global benefit enzymes. We use an integrated model, which integrated in silico model of E.coli and KEGG. By computation, we analyze the effect of adding each reaction from KEGG on the theoretical yields of several products with E.coli and find 83 enzymes that may be potentially global benefit enzymes. By comparison, we find about 30 of the 83 enzymes are better in improving the theoretical yields than the two enzymes of NOG.\n\nIn order to compare the global benefit enzymes with NOG, as an example, we select \"Glycerol:NADP+ oxidoreductase\" (GNO) which can increase the supply of NADPH in E.coli. But To increase the supply of reducing power, such as NADPH will probably increase the yield of chemicals in a cell factory. We use flux balance analysis method to testify our assumption. By comparing the maximum yields of 80 products produced by E.coli with respectively using GNO and NOG, we find GNO has better performance in the product production of E.coli. So GNO is a global benefit enzyme which can increase the yields of many chemical products in E.coli.

synthetic biology↗

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

Histone deacetylase HDA19 affects cortical cell fate by interacting with SCARECROW in the Arabidopsis root

Abstract/SummaryThe Arabidopsis root epidermis is a simple model for investigating cell fate specification and pattern formation. In addition to regulatory networks consisting of transcription factors, histone deacetylases are also involved in the cellular patterning process. Here we report HDA19 affects the root epidermal cellular pattern through regulation of cortical cell fate by interacting with SCARECROW. This work reveals two new components in cortical cell specification and uncovers a new facet of SCR function.

plant biology↗

bioRxiv2018

Noise Analysis in Biochemical Complex Formation

Several biological functions are carried out via complexes that are formed via multimerization of either a single species (homomers) or multiple species (heteromers). Given functional relevance of these complexes, it is arguably desired to maintain their level at a set point and minimize fluctuations around it. Here we consider two simple models of complex formation - one for homomer and another for heteromer of two species - and analyze how important model parameters affect the noise in complex level. In particular, we study effects of (i) sensitivity of the complex formation rate with respect to constituting species abundance, and (ii) relative stability of the complex as compared with that of the constituents. By employing an approximate moment analysis, we find that for a given steady state level, there is an optimal sensitivity that minimizes noise (quantified by fano-factor; variance/mean) in the complex level. Furthermore, the noise becomes smaller if the complex is less stable than its constituents. Finally, for the heteromer case, our findings show that noise is enhanced if the complex is comparatively more sensitive to one constituent. We briefly discuss implications of our result for general complex formation processes.

systems biology↗