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Biology subjects

Zhu, Z.

Publications and source records attributed to Zhu, Z..

At least 325 records · Page 18Linked to original sources

Molecular profiles and mutation burden analysis in Chinese patients with gastric carcinoma

The goal of this work was to investigate the molecular profiles and mutation burden in Chinese patients with gastric carcinoma (GC). In total, we performed whole exome sequencing (WES) on 74 GC patients with tumor and adjacent normal formalin-fixed, paraffin-embedded (FFPE) tissue samples. The mutation spectrum of these samples showed a high concordance with TCGA and other studies on GC. We found the alterations of 17 DNA repair genes (including BRCA2, POLE and MSH3, etc.) were strongly correlated with the tumor mutation burden (TMB) and tumor neoantigen burden (TNB) of GC patients. Patients with mutations of these genes tend to have high TMB (median of TMB = 12.77, p=2.3e-6) and TNB (median of TNB = 5.97, p= 2.8e-3). In addition, younger GC patients (age < 60) have lower TMB (p = 0.0021) and TNB (p = 0.034) than older patients (age >= 60). Furthermore, we found a list of 18 genes and two genomic regions (1p36.21 and Xq26.3) were associated with peritoneal metastasis (PM) of GC, and patients with amplification of 1p36.21 and Xq26.3 have a worse prognosis (p=0.002, 0.01, respectively). Our analysis provides GC patients with potential markers for single and combination therapies.

cancer biology↗

OSCA: a tool for omic-data-based complex trait analysis

The rapid increase of omic data in the past decades has greatly facilitated the investigation of associations between omic profiles such as DNA methylation (DNAm) and complex traits in large cohorts. Here, we proposed a mixed-linear-model-based method (called MOMENT) that tests for association between a DNAm probe and trait with all other distal probes fitted in multiple random-effect components to account for the effects of unobserved confounders as well as the correlations between distal probes induced by the confounders. We demonstrated by simulations that MOMENT showed a lower false positive rate and more robustness than existing methods. MOMENT has been implemented in a versatile software package (called OSCA) together with a number of other implementations for omic-data-based analysis including the estimation of variance in a trait captured by all measures of multiple omic profiles, omic-data-based quantitative trait locus (xQTL) analysis, and meta-analysis of xQTL data.

bioinformatics↗

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↗

The landscape of intrinsic and evolved fluoroquinolone resistance in Acinetobacter baumannii includes suppression of drug-induced prophage replication

The emergence of fluoroquinolone resistance in nosocomial pathogens has restricted the clinical efficacy of this antibiotic class. In Acinetobacter baumannii, the majority of clinical isolates now show high-level resistance due to mutations in gyrA (DNA gyrase) and parC (Topo IV). To investigate the molecular basis for fluoroquinolone resistance, an exhaustive mutation analysis was performed in both drug sensitive and resistant strains to identify loci that alter the sensitivity of the organism to ciprofloxacin. To this end, parallel fitness tests of over 60,000 unique insertion mutations were performed in strains with various alleles in genes encoding the drug targets. The spectrum of mutations that altered drug sensitivity was found to be similar in the drug sensitive and double mutant gyrAparC background having resistance alleles in both genes. In contrast, introduction of a single gyrA resistance allele, resulting in preferential poisoning of Topo IV by ciprofloxacin, led to extreme alterations in the insertion mutation fitness landscape. The distinguishing feature of preferential Topo IV poisoning was induction of DNA synthesis in the region of two endogenous prophages, which appeared to occur in situ. Induction of the selective DNA synthesis in the gyrA background was also linked to enhanced activation of SOS response and heightened transcription of prophage genes relative to that observed in either the WT or gyrAparC double mutants. Therefore, the accumulation of mutations that result in the stepwise evolution of high ciprofloxacin resistance is tightly connected to suppression of hyperactivation of the SOS response and endogenous prophage DNA synthesis.\n\nImportanceFluoroquinolones have been extremely successful antibiotics. Their clinical efficacy derives from the ability to target multiple bacterial enzymes critical to DNA replication, the topoisomerases DNA gyrase and Topo IV. Unfortunately, mutations lowering drug affinity for both enzymes are now widespread, rendering these drugs ineffective for many pathogens. To undermine this form of resistance, we sought to understand how bacteria with target alterations differentially cope with fluoroquinolone exposures. We studied this problem in the nosocomial pathogen A. baumannii, which causes resistant, life-threating infections. Employing genome-wide approaches, we uncovered numerous pathways that could be exploited to lower fluoroquinolone resistance independently of target alteration. Remarkably, fluoroquinolone targeting of Topo IV in specific mutants caused dramatic prophage hyperinduction, a response that was muted in strains with DNA gyrase as the primary target. This work demonstrates that resistance evolution via target modification can profoundly modulate the antibiotic stress response, revealing potential resistance-associated liabilities.

microbiology↗

Identification of genome-wide nucleotide sites associated with mammalian virulence in influenza A viruses

MotivationThe virulence of influenza viruses is a complex multigenic trait. Previous studies about the virulence determinants of influenza viruses mainly focused on amino acid sites, ignoring the influence of nucleotide mutations.\n\nResultsWe collected more than 200 viral strains from 21 subtypes of influenza A viruses with virulence in mammals and obtained over 100 mammalian virulence-related nucleotide sites across the genome by computational analysis. Interestingly, 50 of these nucleotide sites only experienced synonymous mutations. Further experiments showed that synonymous mutations in the top two of these nucleotide sites, i.e., PB1-2031 and PB1-633, enhanced the pathogenicity of the viruses in mice. Finally, machine-learning models with accepted accuracy for predicting mammalian virulence of influenza A viruses were built. Overall, this study highlighted the importance of nucleotide mutations, especially synonymous mutations in viral virulence, and provided rapid methods for evaluating the virulence of influenza A viruses. It could be helpful for early warning of newly emerging influenza A viruses.

microbiology↗

Wheat avenin-like protein and its significant Fusarium Head Blight resistant functions

Wheat Avenin-like proteins (TaALP) are atypical storage proteins belonging to the Prolamin superfamily. Previous studies on ALPs have focused on the proteins positive effects on dough strength, whilst no correlation has been made between TaALPs and the plant immune system. Here, we performed genome-wide characterization of ALP encoding genes in bread wheat. In silico analyses indicated the presence of critical peptides in TaALPs that are active in the plant immune system. Pathogenesis-related nucleotide motifs were also identified in the putative promoter regions of TaALP encoding genes. RT-PCR was performed on TaALP and previously characterised pathogenesis resistance genes in developing wheat caryopses under control and Fusarium graminearum infection conditions. The results showed that TaALP and NMT genes were upregulated upon F. graminearum inoculation. mRNA insitu hybridization showed that TaALP genes were expressed in the embryo, aleurone and sub-aleurone layer cells. Seven TaALP genes were cloned for the expression of recombinant proteins in Escherichia coli, which displayed significant inhibitory function on F. graminearum under anti-fungal tests. In addition, FHB index association analyses showed that allelic variations of two ALP genes on chromosome 7A were significantly correlated with FHB symptoms. Over-expression of an ALP gene on chromosome 7A showed an enhanced resistance to FHB. Yeast two Hybridization results revealed that ALPs have potential proteases inhibiting effect on metacaspases and beta-glucosidases. A vital infection process related pathogen protein, F. graminearum Beta-glucosidase was found to interact with ALPs. Our study is the first to report a class of wheat storage protein or gluten protein with biochemical functions. Due to its abundance in the grain and the important multi-functions, the results obtained in the current study are expected to have a significant impact on wheat research and industry.

molecular biology↗

Changes in Microorganisms in the Rhizosphere of Mulberry Genotypes with Differing Resistance to Bacterial Wilt

A close relationship between soil-borne diseases, soil microbial community structure, and functional diversity has been described in the mulberry plant. In the present study, microbial abundance, community structure, and functional diversity in the soil rhizosphere were compared in resistant (Kangqing10) and susceptible (Guisang12) mulberry genotypes using the dilution plate method, micro-ecology technology, and polymerase chain reaction-denaturing gradient gel electrophoresis (PCR-DGGE). The goal of this study was to develop better management methods for mulberry cultivation and preventing and controlling bacterial wilt. Rhizosphere soil microorganisms were more abundant in the resistant normal mulberry genotype than in the susceptible normal mulberry genotype. Carbon source utilization was better in the susceptible normal mulberry genotype. These properties were lower in the resistant sickly mulberry genotype than in the susceptible sickly mulberry genotype. PCR-DGGE indicated that the bacterial and fungal community structures of the resistant genotypes were more stable than those of the susceptible genotypes. Correlation regression analysis implicated mulberry bacterial wilt in the loss of soil nutrients, particularly organic matter and nitrogen, which can disrupt the balance of the soil microbial community. Loss of soil organic matter and nitrogen had a lower impact on resistant genotype plants than on susceptible genotype plants. Therefore, resistant genotype plants displayed some resistance to bacterial wilt. Further insights into the soil rhizosphere microbial diversities of resistant and susceptible genotypes will help in the control and prevention of mulberry bacterial wilt.

microbiology↗

Forecasting bacterial survival-success and adaptive evolution through multi-omics stress response-mapping, network analyses and machine learning

Whether a bacterial pathogen establishes an infection and/or evolves antibiotic resistance depends on successful survival while experiencing stress from for instance the host immune system and/or antibiotics. Predictions on bacterial survival and adaptive outcomes could thus have great prognostic value. However, it is unknown what information is required to enable such predictions. By developing a novel network-based analysis method, a bacterium's phenotypic and transcriptional response can be objectively quantified in temporal 3D-feature space. The resulting trajectories can be interpreted as a degree of coordination, where a focused and coordinated response predicts bacterial survival-success, and a random uncoordinated response predicts survival-failure. These predictions extend to both antibiotic resistance and in vivo infection conditions and are applicable to both Gram-positive and Gram-negative bacteria. Moreover, through experimental evolution we show that the degree of coordination is an adaptive outcome - an uncoordinated response evolves into a coordinated response when a bacterium adapts to its environment. Most surprisingly, it turns out that phenotypic and transcriptional response data, network features and genome plasticity data can be used to train a machine learning model that is able to predict which genes in the genome will adapt under nutrient or antibiotic selection. Importantly, this suggests that deterministic factors help drive adaptation and that evolution is, at least partially, predictable. This work demonstrates that with the right information predictions on bacterial short-term survival and long-term adaptive outcomes are feasible, which underscores that personalized infectious disease diagnostics and treatments are possible, and should be developed.

microbiology↗

Palbociclib and fulvestrant act in synergy to modulate central carbon metabolism in breast cancer cells

Palbociclib, is a selective inhibitor of cyclin-dependent kinases 4 and 6 and used as a first-line treatment for patients with estrogen receptor positive breast cancer. It has been shown that patients have improved progression-free survival when treated in combination with fulvestrant, an estrogen receptor antagonist. However, the mechanisms for this survival advantage are not known. We sought to analyze metabolic and transcriptomic changes in MCF-7 adenocarcinoma breast cancer cells following single and combined treatments to determine if selective metabolic pathways are targeted during combination therapy. Our results showed that individually, the drugs caused metabolic disruption to the same metabolic pathways, however fulvestrant additionally attenuated the pentose phosphate pathway and the production of important coenzymes. A comprehensive effect was observed when the drugs were applied together, confirming the combinatory therapy's synergism in the cell model. This study highlights the power of merging high-dimensional datasets to unravel mechanisms involved in cancer metabolism and therapy.\n\nHighlights{circ} First study employing multi-omics to investigate combined therapy on breast cancer cells\n{circ}Fulvestrant attenuates the pentose phosphate pathway and coenzyme production\n{circ}Synergism of palbociclib and fulvestrant was confirmed in vitro\n{circ}Altered key pathways have been identified\n\n\neTOC BlurbJohnson et al. applied an innovative multi-omics approach to decipher metabolic pathways affected by single versus combination dosing of palbociclib and fulvestrant in estrogen receptor positive breast cancer. Key metabolites and genes were correlated within metabolic pathways and shown to be involved in the drugs' synergism.

biochemistry↗

Genome-Wide Identification of HES1 Target Genes Uncover Novel Roles for HES1 in Pancreatic Development

Notch signalling and the downstream effector HES1 is required for multiple pancreatic cell fate choices during development, but the direct target genes remain poorly characterised. Here we identify direct HES1 target genes on a genome-wide scale using ChIP-seq and RNA-seq analyses combined with human embryonic stem cell (hESC) directed differentiation of CRISPR/Cas9-generated HES1-/- mutant hESC lines. We found that HES1 binds to a distinct set of endocrine-specific genes, a set of genes encoding basic Helix-Loop-Helix (bHLH) proteins not normally expressed in the pancreas, genes in the Notch pathway, and the known HES1 target NEUROG3. RNA-seq analysis of wild type, HES1-/-, NEUROG3-/-, and HES1-/-NEUROG3-/- mutant hESC lines allowed us to uncover NEUROG3-independent, direct HES1 target genes. Among the HES1 bound genes that were derepressed in HES1-/-NEUROG3-/- cells compared to NEUROG3-/- cells, we found members of the endocrine-specific gene set, the Notch pathway genes DLL1, DLL4, and HEY1, as well as the non-pancreatic bHLH genes ASCL1 and ATOH1. We also found a large number of transcripts specific to the intestinal secretory lineage to be increased in HES1-/-NEUROG3-/- cells. Together, our data reveal that HES1 employs a multi-layered control of endocrine differentiation, controls Notch ligand expression independent of NEUROG3, and prevents initiation of ectopic intestinal transcriptional programmes in pancreas progenitors.

developmental biology↗

Post-reactivation new learning impairs and updates human episodic memory through dissociable processes

Learning of competing information after reactivation has the potential to disrupt memory reconsolidation and thus impair a consolidated memory. Yet this effect has rarely been detected in episodic memory. By introducing an additional retrieving cue to the target memory, the current study detected significant impairment on the reactivated episodic memory, in addition to an integration of new information to the old memory. However, while the integration effect followed the time window of reconsolidation disruption, the impairment effect did not. MEG measurements further revealed alpha power change during reactivation and post-reactivation learning which showed different correlation patterns with the integration and impairment effects, confirming that the two effects relied on different processes. Therefore, post-reactivation new learning disrupts episodic memory but not through reconsolidation disruption. Further findings that the impairment effect was correlated with participants voluntary inhibition ability suggest an inhibition-based memory updating process underlying post-reactivation new learning.

neuroscience↗

Development and validation of a phenotypic high-content imaging assay for assessing the antiviral activity of small-molecule inhibitors targeting the Zika virus

Zika virus (ZIKV) has been linked to the development of microcephaly in newborns, as well as Guillain-Barre syndrome. There are currently no drugs available to treat infection, and accordingly there is an unmet medical need for discovery of new therapies. High-throughput drug screening efforts focusing on indirect readouts of cell viability are prone to a higher frequency of false positives in cases where the virus is viable in the cell but the cytopathic effect is reduced or delayed. Here, we describe a fast and label-free phenotypic high-content imaging assay used to detect cells affected by the viral-induced cytopathic effect (CPE) using automated imaging and analysis. Protection from CPE correlates with a decrease in viral antigen production as observed by immunofluorescence. We trained our assay using a collection of nucleoside analogues against ZIKV; the previously reported antiviral activities of 2-C-methylribonucleosides and ribavirin against the Zika virus in Vero cells were confirmed using our developed method. Profiling of a novel library of 24 natural product derivatives using our assay revealed compound 1 as an inhibitor of ZIKV-induced cytopathic effect; activity of the compound was confirmed in human fetal neural stem cells (NSCs). The described technique can be easily leveraged as a primary screening assay for profiling large compound libraries against ZIKV, and can be expanded to other ZIKV strains and other cell lines displaying morphological changes upon ZIKV infection.

microbiology↗

Large-scale neuroimaging and genetic study reveals genetic architecture of brain white matter microstructure

Microstructural changes of white matter (WM) tracts are known to be associated with various neuropsychiatric disorders/diseases. Heritability of structural changes of WM tracts has been examined using diffusion tensor imaging (DTI) in family-based studies for different age groups. The availability of genetic and DTI data from recent large population-based studies offers opportunity to further improve our understanding of genetic contributions. Here, we analyzed the genetic architecture of WM tracts using DTI and single-nucleotide polymorphism (SNP) data of unrelated individuals in the UK Biobank (n [~] 8000). The DTI parameters were generated using the ENIGMA-DTI pipeline. We found that DTI parameters are substantially heritable on most WM tracts. We observed a highly polygenic or omnigenic architecture of genetic influence across the genome as well as the enrichment of SNPs in active chromatin regions. Our bivariate analyses showed strong genetic correlations for several pairs of WM tracts as well as pairs of DTI parameters. We performed voxel-based analysis to illustrate the pattern of genetic effects on selected parts of the tract-based spatial statistics skeleton. Comparing the estimates from the UK Biobank to those from small population-based studies, we illustrated that sufficiently large sample size is essential for genetic architecture discovery in imaging genetics. We confirmed this finding with a simulation study.

genetics↗

The Transcriptional landscape of Streptococcus pneumoniae reveals a complex operon architecture and abundant riboregulation critical for growth and virulence

Efficient and highly organized transcription initiation and termination is fundamental to an organisms ability to survive, proliferate, and quickly respond to its environment. Over the last decade, our simplistic outlook of bacterial transcriptional regulation and architecture has evolved to include stimulus-responsive regulation by untranslated RNA and the formation of alternate transcriptional units. In this study, we map the transcriptional landscape of the bacterial pathogen Streptococcus pneumoniae by applying a combination of high-throughput RNA-sequencing techniques. Our study reveals a complex transcriptome wherein environment-respondent alternate transcriptional units are observed within operons stemming from internal transcription start sites (TSS) and transcription terminators (TTS) suggesting that more fine-tuning of regulation occurs than previously thought. Additionally, we identify many putative cis-regulatory RNA elements and riboswitches within 5-untranslated regions (5-UTR) of genes. By integrating TSSs and TTSs with independently collected RNA-Seq datasets from a variety of conditions, we establish the response of these regulators to changes in growth conditions and validate several of them. Furthermore, to determine the importance of ribo-regulation by 5-UTR elements for in vivo virulence, we show that the pyrR regulatory element is essential for survival, successful colonization and infection in mice suggesting that such RNA elements are potential drug targets. Importantly, we show that our approach of combining high-throughput sequencing with in vivo experiments can reconstruct a global understanding of regulation, but also pave the way for discovery of compounds that target (ribo-) regulators to mitigate virulence and antibiotic resistance.

microbiology↗

Novel susceptibility loci and genetic regulation mechanisms for type 2 diabetes

We conducted a meta-analysis of genome-wide association studies (GWAS) with [~]16 million genotyped/imputed genetic variants in 62,892 type 2 diabetes (T2D) cases and 596,424 controls of European ancestry. We identified 139 common and 4 rare (minor allele frequency < 0.01) variants associated with T2D, 42 of which (39 common and 3 rare variants) were independent of the known variants. Integration of the gene expression data from blood (n = 14,115 and 2,765) and other T2D-relevant tissues (n = up to 385) with the GWAS results identified 33 putative functional genes for T2D, three of which were targeted by approved drugs. A further integration of DNA methylation (n = 1,980) and epigenomic annotations data highlighted three putative T2D genes (CAMK1D, TP53INP1 and ATP5G1) with plausible regulatory mechanisms whereby a genetic variant exerts an effect on T2D through epigenetic regulation of gene expression. We further found evidence that the T2D-associated loci have been under purifying selection.

genetics↗

Identifying gene targets for brain-related traits using transcriptomic and methylomic data from blood

Understanding the difference in genetic regulation of gene expression between brain and blood is important for discovering genes associated with brain-related traits and disorders. Here, we estimate the correlation of genetic effects at the top associated cis-expression (cis-eQTLs or cis-mQTLs) between brain and blood for genes expressed (or CpG sites methylated) in both tissues, while accounting for errors in their estimated effects (rb). Using publicly available data (n = 72 to l,366), we find that the genetic effects of cis-eQTLs (PeQTL < 5x10-8) or mQTLs (PmQTL < 1x10-10) are highly correlated between independent brain and blood samples ([Formula] with SE = 0.015 for cis-eQTL and [Formula] with SE = 0.006 for cis-mQTLs). Using meta-analyzed brain eQTL/mQTL data (n = 526 to 1,194), we identify 61 genes and 167 DNA methylation (DNAm) sites associated with 4 brain-related traits and disorders. Most of these associations are a subset of the discoveries (97 genes and 295 DNAm sites) using data from blood with larger sample sizes (n = l,980 to 14,115). We further find that cis-eQTLs with tissue-specific effects are approximately uniformly distributed across all the functional annotation categories, and that mean difference in gene expression level between brain and blood is almost independent of the difference in the corresponding cis-eQTL effect. Our results demonstrate the gain of power in gene discovery for brain-related phenotypes using blood cis-eQTL or cis-mQTL data with large sample sizes.

genetics↗

Membrane proteins with high N-glycosylation, high expression, and multiple interaction partners were preferred by mammalian viruses as receptors

Receptor mediated entry is the first step for viral infection. However, the relationship between viruses and receptors is still obscure. Here, by manually curating a high-quality database of 268 pairs of mammalian virus-host receptor interaction, which included 128 unique viral species or sub-species and 119 virus receptors, we found the viral receptors were structurally and functionally diverse, yet they had several common features when compared to other cell membrane proteins: more protein domains, higher level of N-glycosylation, higher ratio of self-interaction and more interaction partners, and higher expression in most tissues of the host. Additionally, the receptors used by the same virus tended to co-evolve. Further correlation analysis between viral receptors and the tissue and host specificity of the virus shows that the virus receptor similarity was a significant predictor for mammalian virus cross-species. This work could deepen our understanding towards the viral receptor selection and help evaluate the risk of viral zoonotic diseases.

microbiology↗

Local Delivery of Stromal Cell-Derived Factor-1α Improves the Pregnancy Rate of Injured Uterus through the Promotion of Endometrial and Vascular Regeneration

Severe infection and mechanical injury of the uterus may lead to infertility and miscarriage. Currently, there is a lack of effective treatment modality for functional repair of uterine injury. To address this clinical challenge, this study aimed to develop a chemotactic composite scaffold by incorporating recombinant human stromal cell-derived factor-1 (rhSDF-1) into a silk fibroin-bacterial cellulose (SF-BC) membrane carrier. A rat model of uterine injury was utilized for this study, which was composed of three groups: blank control, implantation with SF-BC only or SF-BC loaded with rhSDF-1. The tissue regeneration efficacy of the three groups were analyzed and compared. The results showed that SF-BC loaded with rhSDF-1 significantly enhanced endometrial regeneration and arteriogenesis of the injured rat uterus, which led to improved pregnancy outcomes, thus indicating much promise for functional uterine repair and regeneration.

bioengineering↗