Biology subjects

Zhao, Y.

Publications and source records attributed to Zhao, Y..

At least 865 records · Page 48Linked to original sources

bioRxiv2021

Alphaproteobacteria facilitate Trichodesmium community trimethylamine utilization

In the surface waters of the warm oligotrophic ocean, filaments and aggregated colonies of the nitrogen (N)-fixing cyanobacterium Trichodesmium create microscale nutrient-rich oases. These hotspots fuel primary productivity and harbor a diverse consortium of heterotrophs. Interactions with associated microbiota can affect the physiology of Trichodesmium, often in ways that have been predicted to support its growth. Recently, it was found that trimethylamine (TMA), a globally-abundant organic N compound, inhibits N2 fixation in cultures of Trichodesmium without impairing growth rate, suggesting that Trichodesmium receives nitrogen from TMA. In this study, 15N-TMA DNA stable isotope probing (SIP) of a Trichodesmium enrichment was employed to further investigate TMA metabolism and determine if TMA-N is incorporated directly or secondarily via cross-feeding facilitated by microbial associates. Herein we identify two members of the marine Roseobacter clade (MRC) of Alphaproteobacteria as the likely metabolizers of TMA and provide genomic evidence that they converted TMA into a more readily available form of N, e.g., NH4+, which was subsequently used by Trichodesmium and the rest of the community. The results implicate microbiome-mediated carbon (C) and N transformations in modulating N2 fixation, and thus highlight the involvement of host-associated heterotrophs in global biogeochemical cycling.

microbiology↗

bioRxiv2021

Novel inhibition mechanism of SARS-CoV-2 main protease by ebselen and its derivatives

The global emergence of SARS-CoV-2 has triggered numerous efforts to develop therapeutic options for COVID-19 pandemic. The main protease of SARS-CoV-2 (Mpro), which is a critical enzyme for transcription and replication of SARS-CoV-2, is a key target for therapeutic development against COVID-19. An organoselenium drug called ebselen has recently been demonstrated to have strong inhibition against Mpro and antiviral activity but its molecular mode of action is unknown preventing further development. We have examined the binding modes of ebselen and its derivative in Mpro via high resolution co-crystallography and investigated their chemical reactivity via mass spectrometry. Stronger Mpro inhibition than ebselen and potent ability to rescue infected cells were observed for a number of ebselen derivatives. A free selenium atom bound with cysteine 145 of Mpro catalytic dyad has been revealed by crystallographic studies of Mpro with ebselen and MR6-31-2 suggesting hydrolysis of the enzyme bound organoselenium covalent adduct, formation of a phenolic by-product is confirmed by mass spectrometry. The target engagement of these compounds with an unprecedented mechanism of SARS-CoV-2 Mpro inhibition suggests wider therapeutic applications of organo-selenium compounds in SARS-CoV-2 and other zoonotic beta-corona viruses.

biophysics↗

bioRxiv2021

Estimation of in-scanner head pose changes during structural MRI using a convolutional neural network trained on eye tracker video

IntroductionIn-scanner head motion is a common cause of reduced image quality in neuroimaging, and causes systematic brain-wide changes in cortical thickness and volumetric estimates derived from structural MRI scans. There are few widely available methods for measuring head motion during structural MRI. Here, we train a deep learning predictive model to estimate changes in head pose using video obtained from an in-scanner eye tracker during an EPI-BOLD acquisition with participants undertaking deliberate in-scanner head movements. The predictive model was used to estimate head pose changes during structural MRI scans, and correlated with cortical thickness and subcortical volume estimates. Methods21 healthy controls (age 32 {+/-} 13 years, 11 female) were studied. Participants carried out a series of stereotyped prompted in-scanner head motions during acquisition of an EPI-BOLD sequence with simultaneous recording of eye tracker video. Motion-affected and motion-free whole brain T1-weighted MRI were also obtained. Image coregistration was used to estimate changes in head pose over the duration of the EPI-BOLD scan, and used to train a predictive model to estimate head pose changes from the video data. Model performance was quantified by assessing the coefficient of determination (R2). We evaluated the utility of our technique by assessing the relationship between video-based head pose changes during structural MRI and (i) vertex-wise cortical thickness and (ii) subcortical volume estimates. ResultsVideo-based head pose estimates were significantly correlated with ground truth head pose changes estimated from EPI-BOLD imaging in a hold-out dataset. We observed a general brain-wide overall reduction in cortical thickness with increased head motion, with some isolated regions showing increased cortical thickness estimates with increased motion. Subcortical volumes were generally reduced in motion affected scans. ConclusionsWe trained a predictive model to estimate changes in head pose during structural MRI scans using in-scanner eye tracker video. The method is independent of individual image acquisition parameters and does not require markers to be to be fixed to the patient, suggesting it may be well suited to clinical imaging and research environments. Head pose changes estimated using our approach can be used as covariates for morphometric image analyses to improve the neurobiological validity of structural imaging studies of brain development and disease.

neuroscience↗

bioRxiv2021

The methylation of SDC2 and TFPI2 defined three methylator phenotypes of colorectal cancer

Methylation-based noninvasive molecular diagnostics are easy and feasible tools for the early detection of colorectal cancer (CRC). However, many of them have the limitation of low sensitivity with some CRCs detection failed in clinical practice. In this study, the clinical and pathological characteristics, as well as molecular features of three methylator-groups, defined by the promoter methylation status of SDC2 and TFPI2, were investigated in order to improve the performance of CRC detection. The Illumina Infinium 450k Human DNA methylation data and clinical information of CRCs were collected from The Cancer Genome Atlas (TCGA) project and Gene Expression Omnibus (GEO) database. CRC samples were divided into three groups, HH (dual-positive), HL (single positive) and LL (dual-negative) according to the methylation status of SDC2 and TFPI2 promoters. Differences in age, tumor location, microsatellite instable status and differentially expressed genes (DEGs) were evaluated among the three groups and these findings were then confirmed in our inner CRC dataset. The combination of methylated SDC2 and TFPI2 showed a superior performance of distinguishing CRCs from normal controls than each alone. Samples of HL group were more often originated from left-side CRCs whereas very few of them were from right-side (P < 0.05). HH grouped CRCs showed a higher level of microsatellite instability and mutation load than other two groups (mean nonsynonymous mutations for HH/HL/LL: 10.55/3.91/7.02, P = 0.0055). All mutations of BRAF, one of the five typical CpG island methylator phenotype (CIMP) related genes, were found in HH group (HH/HL/LL: 51/0/0, P = 0.018). Also there was a significantly older patient age at the diagnosis in HH group. Gene expression analysis identified 37, 84 and 22 group-specific DEGs for HH, HL and LL, respectively. Functional enrichment analysis suggested that HH specific DEGs were mainly related to the regulation of transcription and other processes, while LL specific DEGs were enriched in the biological processes of extracellular matrix interaction and cell migration. The three defined mathylator groups showed great difference in tumor location, patient age, MSI and ECM biological process, which could facilitate the development of more effective biomarkers for CRC detection.

cancer biology↗

bioRxiv2021

Self-organization of Tissue Growth by Interfacial Mechanical Interactions in Multi-layered Systems

Morphogenesis is a spatially and temporally regulated process involved in various physiological and pathological transformations. In addition to the associated biochemical factors, the physical regulation of morphogenesis has attracted increasing attention. However, the driving force of morphogenesis initiation remains elusive. Here, we show that during the growth of multi-layered tissues, morphogenetic process can be self-organized by the progression of compression gradient stemmed from the interfacial mechanical interactions between layers. In tissues with low fluidity, the compression gradient is progressively strengthened during growth and induces stratification by triggering symmetric-to-asymmetric cell division reorientation at the critical tissue size. In tissues with high fluidity, compression gradient is dynamic and induces cell junction remodelling regulated cell rearrangement leading to 2D in-plane morphogenesis instead of 3D deformation. Morphogenesis can be tuned by manipulating tissue fluidity, cell adhesion forces and mechanical properties to influence the progression of compression gradient during the development of cultured cell sheets and chicken embryos. Together, the dynamics of compression gradient arised from interfacial mechanical interaction provides a conserved mechanism underlying morphogenesis initiation and size control during tissue growth.

biophysics↗

bioRxiv2021

Development of a chemiluminescence immunoassay to accurately detect African swine fever virus antibodies in serum

The outbreak of African swine fever (ASF) has caused significant economic losses to animal husbandry worldwide. Currently, there is no effective vaccine or treatment available to control the disease, and therefore, efficient disease control is dependent on early detection and diagnosis of ASF virus (ASFV). In this study, a chemiluminescent immunoassay (CLIA) was developed using the ASFV protein p54 as a serum diagnostic antigen and an anti-p54 monoclonal antibody. After optimizing the working parameters of the CLIA, the sensitivity of the established CLIA was 1:128, ASFV-specific serum antibody was identified, and there was no cross-reaction with other swine virus antibodies. After testing 49 clinical serum samples, the consistency rate between the CLIA and the World Organization for Animal Health (OIE) recommended commercial kit was 100%. Thus, this CLIA had a high degree of specificity, sensitivity, and reliability, and could be used as a rapid detection method for epidemiological investigations of ASFV infection.

microbiology↗

bioRxiv2021

Whole Genome and Exome Sequencing Reference Datasets from A Multi-center and Cross-platform Benchmark Study

With the rapid advancement of sequencing technologies in the past decade, next generation sequencing (NGS) analysis has been widely applied in cancer genomics research. More recently, NGS has been adopted in clinical oncology to advance personalized medicine. Clinical applications of precision oncology require accurate tests that can distinguish tumor-specific mutations from errors or artifacts introduced during NGS processes or data analysis. Therefore, there is an urgent need to develop best practices in cancer mutation detection using NGS and the need for standard reference data sets for systematically benchmarking sequencing platforms, library protocols, bioinformatics pipelines and for measuring accuracy and reproducibility across platforms and methods. Within the SEQC2 consortium context, we established paired tumor-normal reference samples, a human triple-negative breast cancer cell line and a matched normal cell line derived from B lymphocytes. We generated whole-genome (WGS) and whole-exome sequencing (WES) data using 16 NGS library preparation protocols, seven sequencing platforms at six different centers. We systematically interrogated somatic mutations in the paired reference samples to identify factors affecting detection reproducibility and accuracy in cancer genomes. These large cross-platform/site WGS and WES datasets using well-characterized reference samples will represent a powerful resource for benchmarking NGS technologies, bioinformatics pipelines, and for the cancer genomics studies.

bioinformatics↗

bioRxiv2021

Pyroptosis of syncytia formed by fusion of SARS-CoV-2 Spike and ACE2 expressing cells

SARS-Cov-2 infected cells fused with the ACE2-positive neighboring cells forming syncytia. However, the effect of syncytia in disease development is largely unknown. We established an in vitro cell-cell fusion system and used it to mimic the fusion of SARS-CoV-2 infected cells with ACE2-expressing cells to form syncytia. We found that Caspase-9 was activated after syncytia formation, and Caspase-3/7 was activated downstream of Caspase-9, but it triggered GSDME-dependent pyroptosis rather than apoptosis. What is more, single cell RNA-sequencing data showed that both ACE2 and GSDME were expression in alveolar type 2 cells in human lung. We propose that pyroptosis is the fate of syncytia formed by SARS-CoV-2 infected host cells and ACE2-positive cells, which indicated that lytic death of syncytia may contribute to the excessive inflammatory responses in severe COVID-19 patients.

cell biology↗

bioRxiv2021

The proximal proteome of 17 SARS-CoV-2 proteins links to disrupted antiviral signaling and host translation

Viral proteins localize within subcellular compartments to subvert host machinery and promote pathogenesis. To study SARS-CoV-2 biology, we generated an atlas of 2422 human proteins vicinal to 17 SARS-CoV-2 viral proteins using proximity proteomics. This identified viral proteins at specific intracellular locations, such as association of accessary proteins with intracellular membranes, and projected SARS-CoV-2 impacts on innate immune signaling, ER-Golgi transport, and protein translation. It identified viral protein adjacency to specific host proteins whose regulatory variants are linked to COVID-19 severity, including the TRIM4 interferon signaling regulator which was found proximal to the SARS-CoV-2 M protein. Viral NSP1 protein adjacency to the EIF3 complex was associated with inhibited host protein translation whereas ORF6 localization with MAVS was associated with inhibited RIG-I 2CARD-mediated IFNB1 promoter activation. Quantitative proteomics identified candidate host targets for the NSP5 protease, with specific functional cleavage sequences in host proteins CWC22 and FANCD2. This data resource identifies host factors proximal to viral proteins in living human cells and nominates pathogenic mechanisms employed by SARS-CoV-2. Author SummarySARS-CoV-2 is the latest pathogenic coronavirus to emerge as a public health threat. We create a database of proximal host proteins to 17 SARS-CoV-2 viral proteins. We validate that NSP1 is proximal to the EIF3 translation initiation complex and is a potent inhibitor of translation. We also identify ORF6 antagonism of RNA-mediate innate immune signaling. We produce a database of potential host targets of the viral protease NSP5, and create a fluorescence-based assay to screen cleavage of peptide sequences. We believe that this data will be useful for identifying roles for many of the uncharacterized SARS-CoV-2 proteins and provide insights into the pathogenicity of new or emerging coronaviruses.

microbiology↗

bioRxiv2021

SARS-CoV-2 nucleocapsid protein dually regulates innate immune responses

The recently emerged severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of the ongoing global pandemic of COVID-19, may trigger immunosuppression in the early stage and a cytokine storm in the late stage of infection, however, the underlying mechanisms are not well understood. Here we demonstrated that the SARS-CoV-2 nucleocapsid (N) protein dually regulated innate immune responses, i.e., the low-dose N protein suppressed type I interferon (IFN-I) signaling and inflammatory cytokines, whereas high-dose N protein promoted IFN-I signaling and inflammatory cytokines. Mechanistically, the SARS-CoV-2 N protein interacted with the tripartite motif protein 25 (TRIM25), thereby dually regulating the phosphorylation and nuclear translocation of IRF3, STAT1 and STAT2. Additionally, low-dose N protein combined with TRIM25 could suppress retinoic acid-inducible gene I (RIG-I) ubiquitination and activation. Our findings revealed a regulatory mechanism of innate immune responses by the SARS-CoV-2 N protein, which would contribute to understanding the pathogenesis of SARS-CoV-2 and other SARS-like coronaviruses, and development of more effective strategies for controlling COVID-19.

microbiology↗

bioRxiv2021

Neurological mechanism of sensory deficits after developmental exposure to non-dioxin-like polychlorinated biphenyls (PCBs)

The most abundant polychlorinated biphenyl (PCB) congeners found in the environment and in humans are neurotoxic. This is of particular concern for early life stages because the exposure of the more vulnerable developing nervous system to chemicals can result in neurobehavioral disorders. To uncover currently unknown links between PCB target mechanisms and neurobehavioral deficits, we investigated the effects of the non-dioxin-like (NDL) congener PCB153 on neuronal morphology and synaptic transmission linked to the proper execution of a sensorimotor response using zebrafish as a vertebrate model. Zebrafish that were exposed during development to concentrations similar to those found in human cord blood and PCB contaminated sites showed a delay in startle response. A similar delay was observed for other NDL congeners but not for the potent dioxin-like congener PCB126. Morphological and biochemical data demonstrate that while exposure to PCB153 induced swelling of afferent sensory neurons, the disruption of dopaminergic and GABAergic signaling is the dominant mechanism associated with motor movement. The effects on important and broadly conserved signaling mechanisms in vertebrates suggest that NDL PCBs may contribute to neurodevelopmental abnormalities in humans and, with the startle response being critical for the survival of fish, to evolutionary adaptation in wildlife.

pharmacology and toxicology↗

bioRxiv2021

Beyond massive univariate tests: Covariance regression reveals complex patterns of functional connectivity related to attention-deficit/hyperactivity disorder, age, sex, and response control

We applied a novel Covariate Assisted Principal (CAP) whole-matrix regression approach to identify resting-state functional connectivity (FC) brain networks associated with attention-deficit/hyperactivity disorder (ADHD) and response control. Participants included 8-12 year-old children with ADHD (n=115, 29 girls) and typically developing controls (n=102, 35 girls) with a resting-state fMRI scan and go/no-go task behavioral data. We modeled three sets of covariates to identify resting-state networks associated with ADHD, age, sex, and response control. Four networks were identified across models revealing complex interactions between subregions of cognitive control, default mode, subcortical, visual, and somatomotor networks that relate to age, response control, and a diagnosis of ADHD among girls and boys. Unique networks were also identified in each of the three models suggesting some specificity to the covariates of interest. These findings demonstrate the utility of our novel covariance regression approach to studying functional brain networks relevant for development, behavior, and psychopathology.

neuroscience↗

bioRxiv2021

Identification and mechanistic analysis of an inhibitor of the CorC Mg2+ transporter

The CorC/CNNM family of Na+-dependent Mg2+ transporters is ubiquitously conserved from bacteria to humans. CorC, the bacterial member of the CorC/CNNM family of proteins, is involved in resistance to antibiotic exposure and in the survival of pathogenic microorganisms in their host environment. The CorC/CNNM family proteins possess a cytoplasmic region containing the regulatory ATP-binding site. While CorC and CNNM have attracted interest as therapeutic targets, inhibitors targeting the ir regulatory ATP-binding site have not yet been identified. Here, we performed a virtual screening of CorC by targeting its regulatory ATP-binding site, identified a chemical compound named IGN95a with inhibitory effects on both ATP binding and Mg2+ export, and determined the cytoplasmic domain structure in complex with IGN95a. Furthermore, a chemical cross-linking experiment indicated that with ATP bound to the cytoplasmic domain, the conformational equilibrium of CorC was shifted more towards the inward-facing state of the transmembrane domain. In contrast, IGN95a did not induce such a shift. Our results provide a structural basis for the further design and optimization of chemical compounds targeting the regulatory ATP-binding site of CorC as well as mechanistic insights into how ATP and chemical compounds modulate the transport activity of CorC.

biophysics↗

bioRxiv2021

Impact of the B.1.1.7 variant on neutralizing monoclonal antibodies recognizing diverse epitopes on SARS-CoV-2 Spike

The interaction of the SARS-CoV-2 Spike receptor binding domain (RBD) with the ACE2 receptor on host cells is essential for viral entry. RBD is the dominant target for neutralizing antibodies and several neutralizing epitopes on RBD have been molecularly characterized. Analysis of circulating SARS-CoV-2 variants has revealed mutations arising in the RBD, the N-terminal domain (NTD) and S2 subunits of Spike. To fully understand how these mutations affect the antigenicity of Spike, we have isolated and characterized neutralizing antibodies targeting epitopes beyond the already identified RBD epitopes. Using recombinant Spike as a sorting bait, we isolated >100 Spike-reactive monoclonal antibodies from SARS-CoV-2 infected individuals. ~45% showed neutralizing activity of which ~20% were NTD-specific. None of the S2-specific antibodies showed neutralizing activity. Competition ELISA revealed that NTD-specific mAbs formed two distinct groups: the first group was highly potent against infectious virus, whereas the second was less potent and displayed glycan-dependant neutralization activity. Importantly, mutations present in B.1.1.7 Spike frequently conferred resistance to neutralization by the NTD-specific neutralizing antibodies. This work demonstrates that neutralizing antibodies targeting subdominant epitopes need to be considered when investigating antigenic drift in emerging variants.

immunology↗

bioRxiv2021

Knowledge and Awareness of coronavirus disease 2019 (COVID-19) among Chinese dental students----a comparison study.

BackgroudThis study aimed to measure the knowledge and awareness of COVID-19 among Chinese dental students during the global outbreak recently. MethodA descriptive cross-sectional study was performed among dental students and nonmedical college students in China. All the participants were required to anonymously answer a reliable online questionnaire, which covered 3 different fields of COVID-19. Average scores of dental students (D group), including junior (JD group) and senior dental students (SD group), and nonmedical college students (N group) were compared respectively. Chi-square test and independent sample T test were taken for statistical analysis with SPSS.12. ResultsTotally 497 questionnaires were collected, including 224 from dental students and 273 from non-medical students. The overall average score was 57{+/-}19.2. The average scores of dental students were 64.5{+/-}18. The D group had significantly higher scores on the total score, section scores, and 20 questions respectively than with the N group. No significant differences were found on 5 questions. Compared with the N group, the SD group won on all three sections while JD group failed to win on the diagnose section. ConclusionAlthough the dental student showed good awareness regarding the clinical aspects of COVID-19 than non-medical students, there are still some weakness in the part of treatment and prevention, which need to be strengthened for better prepare during work. Besides, the low accuracy rate of lower grade dental students is also worth noting.

scientific communication and education↗

bioRxiv2021

Ketogenesis Impact on Liver Metabolism Revealed by Proteomics of Lysine β-hydroxybutyrylation

Ketone bodies are evolutionarily conserved metabolites that function as energy substrates, signaling molecules and epigenetic regulators. {beta}-hydroxybutyrate ({beta}-OHB) is utilized in lysine {beta}-hydroxybutyrylation (Kbhb) of histones, which associates with starvation-responsive genes, effectively coupling ketogenic metabolism with gene expression. The emerging diversity of the lysine acylation landscape prompted us to investigate the full proteomic impact of Kbhb. Global protein Kbhb is induced in a tissue-specific manner by a variety of interventions that evoke {beta}-OHB. Mass spectrometry analysis of the {beta}-hydroxybutyrylome in mouse liver revealed 891 sites of Kbhb within 267 proteins enriched for fatty acid, amino acid, detoxification and 1-carbon metabolic pathways. Kbhb of S-adenosyl-L-homocysteine hydrolase (AHCY), a rate-limiting enzyme of the methionine cycle, results in inhibition of enzymatic activity. Our results illuminate the role of Kbhb on hepatic metabolism under ketogenic conditions and demonstrate the functional consequence of this modification on a central metabolic enzyme.

molecular biology↗

bioRxiv2021

Mechanisms Driving Genome Reduction of a Novel Roseobacter Lineage Showing Vitamin B12 Auxotrophy

Members of the marine Roseobacter group are key players in the global carbon and sulfur cycles. While over 300 species have been described, only 2% possess reduced genomes (mostly 3-3.5 Mbp) compared to an average roseobacter (>4 Mbp). These taxonomic minorities are phylogenetically diverse but form a Pelagic Roseobacter Cluster (PRC) at the genome content level. Here, we cultivated eight isolates constituting a novel Roseobacter lineage which we named CHUG. Metagenomic and metatranscriptomic read recruitment analyses showed that CHUG members were globally distributed and active in marine environments. CHUG members possess some of the smallest genomes (~2.52 Mb) among all known roseobacters, but they do not exhibit canonical features of genome streamlining like higher coding density or fewer paralogues and pseudogenes compared to their sister lineages. While CHUG members are clustered with traditional PRC members at the genome content level, they show important differences. Unlike other PRC members, neither the relative abundances of CHUG members nor their gene expression levels are correlated with chlorophyll a concentration across the global samples. Moreover, CHUG members cannot synthesize vitamin B12, a key metabolite made by most roseobacters but not by many phytoplankton species and thus thought to mediate the roseobacter-phytoplankton interactions. This combination of features is evidence for the hypothesis that CHUG members may have evolved a free-living lifestyle decoupled from phytoplankton. This ecological transition was accompanied by the loss of signature genes involved in roseobacter-phytoplankton symbiosis, suggesting that relaxation of purifying selection is likely an important driver of genome reduction in CHUG.

microbiology↗

bioRxiv2021

Learning interpretable cellular and gene signature embeddings from single-cell transcriptomic data

The advent of single-cell RNA sequencing (scRNA-seq) technologies has revolutionized transcriptomic studies. However, large-scale integrative analysis of scRNA-seq data remains a challenge largely due to unwanted batch effects and the limited transferabilty, interpretability, and scalability of the existing computational methods. We present single-cell Embedded Topic Model (scETM). Our key contribution is the utilization of a transferable neural-network-based encoder while having an interpretable linear decoder via a matrix tri-factorization. In particular, scETM simultaneously learns an encoder network to infer cell type mixture and a set of highly interpretable gene embeddings, topic embeddings, and batch effect linear intercepts from multiple scRNA-seq datasets. scETM is scalable to over 106 cells and confers remarkable cross-tissue and cross-species zero-shot transfer-learning performance. Using gene set enrichment analysis, we find that scETM-learned topics are enriched in biologically meaningful and disease-related pathways. Lastly, scETM enables the incorporation of known gene sets into the gene embeddings, thereby directly learning the associations between pathways and topics via the topic embeddings.

bioinformatics↗