Biology subjects

Guo, Z.

Publications and source records attributed to Guo, Z..

At least 235 records · Page 13Linked to original sources

bioRxiv2020

Global profiling of the crotonylome in Small Cell Lung Cancer

Small cell lung cancer is a deadly neuroendocrine lung cancer subtype, which harbors the driver mutations of RB1 and TP53 as well as EP300/CREBBP. Since CREBBP/p300 are two prominent crotonyl-CoA transferases responsible for the global crotonylation in cells, here we investigated the crotonylome in SCLC tissues compared with normal lung tissues through TMT labeling coupled with LC-MS/MS and found unique patterns of protein crotonylation in SCLC related pathways.Competing Interest StatementThe authors have declared no competing interest.View Full Text

cancer biology↗

bioRxiv2020

Orderly assembly underpinning built-in asymmetry in the yeast centrosome duplication cycle requires cyclin-dependent kinase

Asymmetric astral microtubule organization drives the polarized orientation of the S. cerevisiae mitotic spindle and primes the invariant inheritance of the old spindle pole body (SPB, the yeast centrosome) by the bud. This model has anticipated analogous centrosome asymmetries featuring in self-renewing stem cell divisions. We previously implicated Spc72, the cytoplasmic receptor for the gamma-tubulin nucleation complex, as the most upstream determinant linking SPB age, functional asymmetry and fate. Here we used structured illumination microscopy and biochemical analysis to explore the asymmetric landscape of nucleation sites inherently built into the spindle pathway and under the control of cyclin-dependent kinase (CDK). We show that CDK enforces Spc72 asymmetric docking by phosphorylating Nud1/centriolin. Furthermore, CDK-imposed order in the construction of the new SPB promotes the correct balance of nucleation sites between the nuclear and cytoplasmic faces of the SPB. Together these contributions by CDK inherently link correct SPB morphogenesis, age and fate.

cell biology↗

bioRxiv2020

Ppd-1 Remodels Spike Architecture by Regulating Floral Development in wheat

The determination of spike architecture is critical to grain yield in wheat (Triticum aestivum), yet the underlying mechanisms remain largely unknown. Here, we measured 51 traits associated with spike architecture and floral development in 197 wheat accessions with photoperiod sensitive and insensitive alleles. We included five distinct allele combinations at the Photoperiod-1 (Ppd-1) loci. A systematic dissection of all recorded phenotypes revealed connections between floral development, spike architecture and grain yield. Modifying the durations of spikelet primordia initiation did not necessarily affect spikelet number. In addition, Ppd-1 loci clearly influenced rachis dry weight, pointing to the rachis vascular system as a potential target for higher yield. Ppd-1 displayed opposite effects on the durations of pre and post-anthesis phases. Ppd-1 controlled carpel size, but not anther size. Finally, the photoperiod-insensitive alleles of Ppd-1 triggered floral degeneration. In parallel, we profiled the spike transcriptome at six stages and four positions in three Ppd-1 genotypes which consists of 234 samples. Integrating phenotypic and expression data suggested that loss of function in Ppd-1 loci delayed floral degeneration by regulating autophagy and extended floret development by regulating genes in different families. Therefore, we concluded that Ppd-1 remodels spike architecture by regulating floral development in wheat.

plant biology↗

bioRxiv2020

Endophilin A1 promotes Actin Polymerization in response to Ca2+/calmodulin to Initiate Structural Plasticity of Dendritic Spines

Dendritic spines of excitatory neurons undergo activity-dependent structural and functional plasticity, which are cellular correlates of learning and memory. However, mechanisms underlying the rapid morphological changes immediately after NMDAR-mediated Ca2+ influx into spines remain poorly understood. Here we report that endophilin A1, a neuronal N-BAR protein, orchestrates membrane dynamics with actin polymerization to initiate spine enlargement in the induction phase of long-term potentiation (LTP). Upon LTP induction, Ca2+/calmodulin enhances its binding to both membrane and p140Cap, a cytoskeleton regulator. As a result, endophilin A1 rapidly associates with the relaxed plasma membrane and promotes actin polymerization, leading to acute expansion of spine head. Moreover, not only the p140Cap-binding, but also calmodulin- and membrane-binding capacities of endophilin A1 are required for LTP and long-term memory. Thus, endophilin A1 functions as calmodulin effector to drive spine enlargement in response to Ca2+ influx in the initial phase of structural plasticity.

cell biology↗

bioRxiv2020

Cytotoxicity evaluation of chloroquine and hydroxychloroquine in multiple cell lines and tissues by dynamic imaging system and PBPK model

Chloroquine (CQ) and hydroxychloroquine (HCQ) have been used in treating COVID-19 patients recently. However, both drugs have some contradictions and rare but severe side effects, such as hypoglycemia, retina and cardiac toxicity. To further uncover the toxicity profile of CQ and HCQ in different tissues, we evaluated the cytotoxicity of them in 8 cell lines, and further adopted the physiologically-based pharmacokinetic models (PBPK) to predict the tissue risk respectively. Retina, myocardium, lung, liver, kidney, vascular endothelium and intestinal epithelium originated cells were included in the toxicity evaluation of CQ and HCQ respectively. The proliferation pattern was monitored in 0-72 hours by IncuCyte S3, which could perform long-term continuous image and video of cells upon CQ or HCQ treatment. CC50 and the ratio of tissue trough concentrations to CC50 (RTTCC) were brought into predicted toxicity profiles. The CC50 at 24 h, 48 h, 72 h of CQ and HCQ decreased in the time-dependent manner, which indicates the accumulative cytotoxic effect. HCQ was found to be less toxic in 7 cell types except cardiomyocytes H9C2 cells (CC50-48 h=29.55 M; CC50-72 h=15.26 M). In addition, RTTCC is significant higher in CQ treatment group compared to HCQ group, which indicates that relative safety of HCQ. Both CQ and HCQ have certain cytotoxicity in time dependent manner which indicates the necessity of short period administration clinically. HCQ has the less impact in 7 cell lines proliferation and less toxicity compared to CQ in heart, liver, kidney and lung.

pharmacology and toxicology↗

bioRxiv2020

Comparative proteomics analysis identifies L-FABP as a putative biomarker of graft injury during liver transplantation

BackgroundTo a large extent the success of liver transplantation depends on quality of allografts. The molecular basis of the susceptibility of different liver allografts to transplant injury remains undefined. MethodsTransplanted liver samples were collected and divided into three groups: the optimal graft (OG) group, early allograft dysfunction (EAD) group, and primary nonfunction (PNF) group. iTRAQ comparative quantitative proteomic analysis and multiple reaction monitoring (MRM) verification was performed. ResultsMore than 160 differentially expressed proteins were detected in the PNF group, compared to 54 and 36 proteins in the EAD and OG groups respectively. Liver-type fatty acid-binding protein (L-FABP) was found as differentially expressed in both cold preserved and reperfused liver. Serum L-FABP level in donors was higher in the PNF and EAD groups than in the OG group. A lower tissue expression of L-FABP was observed in the PNF groups than other groups after reperfusion, indicating incompetent liver donor quality. In mouse ischemia reperfusion injury (IRI) model, the serum levels and tissue expression of L-FABP corresponded to the ALT variation curve. ConclusionsSuboptimal donor livers are more sensitive to ischemia reperfusion injury. L-FABP might be an effective biomarker for evaluating donor quality in liver transplantation.

molecular biology↗

bioRxiv2020

Single-cell analysis of upper airway cells reveals host-viral dynamics in influenza infected adults

Influenza virus infections are major causes of morbidity and mortality. Research using cultured cells, bulk tissue, and animal models cannot fully capture human disease dynamics. Many aspects of virus-host interactions in a natural setting remain unclear, including the specific cell types that are infected and how they and neighboring bystander cells contribute to the overall antiviral response. To address these questions, we performed single-cell RNA sequencing (scRNA-Seq) on cells from freshly collected nasal washes from healthy human donors and donors diagnosed with acute influenza during the 2017-18 season. We describe a previously uncharacterized goblet cell population, specific to infected individuals, with high expression of MHC class II genes. Furthermore, leveraging scRNA-Seq reads, we obtained deep viral genome coverage and developed a model to rigorously identify infected cells that detected influenza infection in all epithelial cell types and even some immune cells. Our data revealed that each donor was infected by a unique influenza variant and that each variant was separated by at least one unique non-synonymous difference. Our results demonstrate the power of massively-parallel scRNA-Seq to study viral variation, as well as host and viral transcriptional activity during human infection.

genomics↗

bioRxiv2020

NOGEA: Network-Oriented Gene Entropy Approach for Dissecting Disease Comorbidity and Drug Repositioning

Rapid development of high-throughput technologies has permitted the identification of an increasing number of disease-associated genes (DAGs), which are important for understanding disease initiation and developing precision therapeutics. However, DAGs often contain large amounts of redundant or false positive information, leading to difficulties in quantifying and prioritizing potential relationships between these DAGs and human diseases. In this study, a network-oriented gene entropy approach (NOGEA) is proposed for accurately inferring master genes that contribute to specific diseases by quantitatively calculating their perturbation abilities on directed disease-specific gene networks. In addition, we confirmed that the master genes identified by NOGEA have a high reliability for predicting disease-specific initiation events and progression risk. Master genes may also be used to extract the underlying information of different diseases, thus revealing mechanisms of disease comorbidity. More importantly, approved therapeutic targets are topologically localized in a small neighborhood of master genes on the interactome network, which provides a new way for predicting new drug-disease associations. Through this method, 11 old drugs were newly identified and predicted to be effective for treating pancreatic cancer and then validated by in vitro experiments. Collectively, the NOGEA was useful for identifying master genes that control disease initiation and co-occurrence, thus providing a valuable strategy for drug efficacy screening and repositioning. NOGEA codes are publicly available at https://github.com/guozihuaa/NOGEA.

systems biology↗

bioRxiv2020

Single-cell transcriptome profiling an adult human cell atlas of 15 major organs

BackgroundAs core units of organ tissues, cells of various types play their harmonious rhythms to maintain the homeostasis of the human body. It is essential to identify the characteristics of cells in human organs and their regulatory networks for understanding the biological mechanisms related to health and disease. However, a systematic and comprehensive single-cell transcriptional profile across multiple organs of a normal human adult is missing. ResultsWe perform single-cell transcriptomes of 84,363 cells derived from 15 tissue organs of one adult donor and generate an adult human cell atlas. The adult human cell atlas depicts 252 subtypes of cells, including major cell types such as T, B, myeloid, epithelial, and stromal cells, as well as novel COCH+ fibroblasts and FibSmo cells, each of which is distinguished by multiple marker genes and transcriptional profiles. These collectively contribute to the heterogeneity of major human organs. Moreover, T cell and B cell receptor repertoire comparisons and trajectory analyses reveal direct clonal sharing of T and B cells with various developmental states among different tissues. Furthermore, novel cell markers, transcription factors and ligand-receptor pairs are identified with potential functional regulations in maintaining the homeostasis of human cells among tissues. ConclusionsThe adult human cell atlas reveals the inter- and intra-organ heterogeneity of cell characteristics and provides a useful resource in uncovering key events during the development of human diseases in the context of the heterogeneity of cells and organs.

cell biology↗

bioRxiv2020

DeepDist: real-value inter-residue distance prediction with deep residual network

MotivationDriven by deep learning techniques, inter-residue contact/distance prediction has been significantly improved and substantially enhanced ab initio protein structure prediction. Currently all the distance prediction methods classify inter-residue distances into multiple distance intervals (i.e. a multi-classification problem) instead of directly predicting real-value distances (i.e. a regression problem). The output of the former has to be converted into real-value distances in order to be used in tertiary structure prediction. ResultsTo explore the potentials of predicting real-value inter-residue distances, we develop a multi-task deep learning distance predictor (DeepDist) based on new residual convolutional network architectures to simultaneously predict real-value inter-residue distances and classify them into multiple distance intervals. We demonstrate that predicting the real-value distance map and multi-class distance map at the same time performs better than predicting real-value distances alone, indicating their complementarity. On 43 CASP13 hard domains, the average mean square error (MSE) of DeepDists real-value distance predictions is 0.896 [A] when filtering out the predicted distance >=16 [A], which is lower than 1.003 [A] of DeepDists multi-class distance predictions. When the predicted real-value distances are converted to binary contact predictions at 8[A] threshold, the precisions of top L/5 and L/2 contact predictions are 78.6% and 64.5%, respectively, higher than the best results reported in the CASP13 experiment. These results demonstrate that the real-value distance prediction can predict inter-residue distances well and improve binary contact prediction over the existing state-of-the-art methods. Moreover, the predicted real-value distances can be directly used to reconstruct protein tertiary structures better than multi-class distance predictions due to the lower MSE.

bioinformatics↗

bioRxiv2020

Genome-wide Identification and Analysis of Enhancer Regulated microRNAs Across 31 Human Tissues

Enhancers are cis-regulatory DNA elements that positively regulate the transcription of target genes in a tissue-specific manner and dysregulation in various diseases such as cancer. Recent studies showed that enhancers can regulate miRNAs and participate in the biological synthesis of miRNAs. However, the network of enhancer-regulated miRNAs across multiple cancers is still unclear. Here, a total of 2,418 proximal enhancer-miRNA interactions and 1,280 distal enhancer-miRNA interactions were identified through the integration of genomic distance, co-expression, and 3D genome data in 31 cancers. The results showed that both proximal and distal interactions exhibited significant tissue-specific feature and there was a noteworthy positive correlation between the expression of miRNA and the number of regulated enhancers in most tissues. Furthermore, it was found that there was a high correlation between the formation of enhancer-miRNA pairs and the expression of eRNAs whether in distal or proximal regulation. The characteristics analysis showed that miRes (enhancers that regulated miRNAs) and non-miRes presented significant differences in sequence conservation, GC content and histone modification signatures. Notably, GC content, H3K4me1, H3K36me3 were present differently between distal regulation and proximal regulation, suggesting they might participate in chromosome looping of enhancer-miRNA interactions. Finally, we introduced a case study, enhancer: chr1:1186391-1186507[~]miR-200a was highly relevant to the survival of thyroid cancer patients and a cis-eQTL SNP on enhancer affected the expression TNFRSF18 gene as a tumor suppressor.

bioinformatics↗

bioRxiv2020

A Generalized Discrete Dynamic Model for Human Epidemics

A discrete dynamic model for human epidemics was developed in present study. The model included major parameters as transmission strength and its decline parameters, mean incubation period, hospitalization time, non-hospitalization daily mortality, non-hospitalization daily recovery rate, and hospitalization proportion, etc. Sensitivity analysis of the model indicated the total cumulative cases significantly increased with initial transmission strength, hospitalization time. The total cumulative cases significantly decreased with transmission strengths decline and hospitalization proportion, and linearly decreased with non-hospitalization daily mortality and non-hospitalization daily recovery rate. In a certain range, the total cumulative cases significantly increased with mean incubation period. Sensitivity analysis demonstrated that dynamic change of transmission strength is one of the most important and controllable factors. In addition, reducing the delay for hospitalization is much effective in weakening disease epidemic. Non-hospitalization recovery rate is of importance for enhancing immunity to recover from the disease.

microbiology↗

bioRxiv2020

From SARS-CoV to Wuhan 2019-nCoV: Will History Repeat Itself?

This manuscript has been withdrawn as it was submitted without the full consent of all the authors. Therefore, the authors do not wish this work to be cited as reference for the project. If you have any questions, please contact the corresponding author.

microbiology↗

bioRxiv2019

Soil Water Carrying Capacity for Vegetation

Non-native plantation can effectively conserve soil and water and improve ecological environment,but soil desiccation occurs and then changes to severe desiccation in most forest and grass lands of water-limited regions, which causes soil degradation, vegetation decline and crop failure, so it is necessary to regulate the changed relationship between plant growth and soil water. However, there is a lack of a universally accepted theory to provide guidance of sustainable use of soil water resources and sustainable management of forest and sustainable produce of crop in such regions. The theory of regulating the relationship between plant growth and soil water in water-limited regions includes the Soil Water Resources Use Limit by Plant (SWRULP) and Soil Water Carrying Capacity for Vegetation (SWCCV). The SWCCV is the population in a plant population or density of indicator plants in a plant community when the soil water supply is equal to soil water consumption in the root zone and a given time, and changes with plant community type, location and time. The degree of coverage, productivity and benefits of a plant community when population quantity of an indicator plant equals SWCCV should be the theoretical basis for ensuring sustainable use of soil water resources and sustainable development of forest.

ecology↗

bioRxiv2019

Systems-level analysis identifies key regulators driving epileptogenesis in temporal lobe epilepsy

Temporal lobe epilepsy (TLE) is the most prevalent and often devastating form of epilepsy. The molecular mechanism underlying the development of TLE remains largely unknown, which hinders the discovery of effective anti-epileptogenic drugs. In this study, we built a systems-level analytic framework which integrates gene meta-signatures, gene coexpression network and cellular regulatory network to unveil the evolution landscape of epileptogenic process and to identify key regulators that govern the transition between different epileptogenesis stages. The time-specific hippocampal transcriptomic profiles from five independent rodent TLE models were grouped into acute, latent and chronic stages of epileptogenesis, and were utilized for generating stage-specific gene expression signatures. 13 cell-type specific functional modules were identified from the epilepsy-context coexpression network, and five of them were significantly associated with the entire epileptogenic process. By inferring the differential protein activity of gene regulators in each stage, 265 key regulators underlying epileptogenesis were obtained. Among them, 122 regulators were demonstrated being associated with high seizure frequency and/or hippocampal sclerosis in human TLE patients. Importantly, we discovered four new gene regulators (ANXA5, FAM107A, SEPT2 and SPARC) whose upregulation may drive the process of epileptogenesis and further lead to chronic recurrent seizures or hippocampal sclerosis. Our findings provide a landscape of the gene network dynamics underlying epileptogenesis and uncovered candidate regulators that may serve as potential targets for future anti-epileptogenic therapy development.

bioinformatics↗

bioRxiv2019

TRESK K+ Channel Activity Regulates Trigeminal Nociception and Headache

Although dominant-negative mutations of TRESK background K+ channel have been reported in migraine patients, whether TRESK activity controls the generation of trigeminal pain, especially headache, is not established. We found that loss of TRESK in all trigeminal ganglia (TG) neurons preferentially increased the intrinsic excitability of small-diameter TG nociceptors that express neuropeptide CGRP or TRPM8 channels. Surprisingly, loss of TRESK increased the number of TG neurons expressing TRPV1 channels. In dorsal root ganglia neurons, neither the persistent outward current nor the intrinsic excitability was affected by the loss of TRESK. Compared with wild-type controls, TRESK knockout mice exhibited more robust trigeminal pain, especially headache-like behaviors; but displayed normal body and visceral pain responses. Our findings indicate that endogenous TRESK activity is required for trigeminal pain regulation. A substantial reduction of TRESK activity may selectively affect the functions of TG nociceptors, thereby increasing the susceptibility to migraine headache in humans.

neuroscience↗

bioRxiv2019

DNSS2: improved ab initio protein secondary structure prediction using advanced deep learning architectures

MotivationAccurate prediction of protein secondary structure (alpha-helix, beta-strand and coil) is a crucial step for protein inter-residue contact prediction and ab initio tertiary structure prediction. In a previous study, we developed a deep belief network-based protein secondary structure method (DNSS1) and successfully advanced the prediction accuracy beyond 80%. In this work, we developed multiple advanced deep learning architectures (DNSS2) to further improve secondary structure prediction.\n\nResultsThe major improvements over the DNSS1 method include (i) designing and integrating six advanced one-dimensional deep convolutional/recurrent/residual/memory/fractal/inception networks to predict secondary structure, and (ii) using more sensitive profile features inferred from Hidden Markov model (HMM) and multiple sequence alignment (MSA). Most of the deep learning architectures are novel for protein secondary structure prediction. DNSS2 was systematically benchmarked on two independent test datasets with eight state-of-art tools and consistently ranked as one of the best methods. Particularly, DNSS2 was tested on the 82 protein targets of 2018 CASP13 experiment and achieved the best Q3 score of 83.74% and SOV score of 72.46%. DNSS2 is freely available at: https://github.com/multicom-toolbox/DNSS2.

bioinformatics↗

bioRxiv2019

The mineralization characteristics of organic carbon and particle composition analysis in reconstructed soil with different proportions of soft rock and sand

The organic carbon mineralization process can reflect the release intensity of soil CO2. Therefore, the study of organic carbon mineralization and particle composition analysis of soft rock and sand compound soil can provide technical support and theoretical basis for the theory of soil organic reconstruction. Based on the previous research, this paper mainly selected four typical treatments of 0:1 (CK), 1:5 (C1), 1:2 (C2) and 1:1 (C3), respectively, and analyzed the soil organic carbon mineralization process and particle composition by lye absorption method, laser particle size meter and scanning electron microscope. The results showed that there was no significant difference in organic carbon content between C1, C2 and C3 treatments, but they were significantly higher than CK treatment (P < 0.05). The organic carbon mineralization rate of each treatment accords with a logarithmic function throughout the culture period (P < 0.01), which can be divided into a rapid decline phase of 1-11 days and a steady decline phase of 11-30 days. The cumulative mineralization amount on the 11th day reached 54.96%-74.44% of the total mineralization amount. At the end of the culture, the cumulative mineralization and potential mineralizable organic carbon content of C1 and C2 treatments were significantly higher than those of CK treatment, and the cumulative mineralization rate was also the lowest with C1 and C2 treatment. The turnover rate constant of soil organic carbon in each treatment was significantly lower than that of CK treatment, and the residence time increased. With the increase of volume fraction of soft rock, the content of silt and clay particles increases gradually, the texture of soil changes from sandy soil to sandy loam, loam and silty loam, and because of the increase of small particles, the structure of soil appears to collapse when the volume ratio of soft rock was 50%. In summary, the ratio of soft rock to sand volume was 1:5-1: 2, which can effectively increased the accumulation of soil organic carbon. At this time, the distribution of soil particles was more uniform, the soil structure was stable, and the mineralization level of unit organic carbon was lower. The research results have practical significance for the large area popularization of soft rock and sand compound technology.

ecology↗