Biology subjects

Tao, S.

Publications and source records attributed to Tao, S..

63 records · Page 4Linked to original sources

bioRxiv2019

VGLUT2/ Cdk5/p25 Signaling Pathway Contributed to Inflammatory Pain By CFA

Vesicular glutamate transporter type 2 (VGLUT2) is known to play an important role in mediating the heat hyperalgesia induced by inflammation. However, the underlying mechanism for this activity is poorly understood. Cyclin-dependent kinase 5 (Cdk5), serving as a key regulator in mediating release of glutamate, contributed to the inflammatory heat. It remains unknown whether there is a bridge between Cdk5 and VGLUT2 for mediating inflammatory pain. Therefore, we designed the experiment to determine whether VGLUT2 signaling pathway is involved in Inflammatory pain mediated by Cdk5 and the heat hyperalgesia induced by complete Freunds adjuvant (CFA) can be reversed by roscovitine, a selective inhibitor for Cdk5 through inhibition of VGLUT2 expression. Immunohistochemistry results suggest that when compared with rats in a control group, rats in an experimental group showed significant coexpression of Cdk5/VGLUT2 in small and medium-sized neuronal cells of the dorsal root ganglion (DRG) and spinal cord between days 1 and 3 following subcutaneous injection of CFA. Moreover, our study revealed that the expression of VGLUT2 protein in DRG and spinal cord was remarkably increased between days 1 and 3 following CFA injection. Additionally, p25 but not p35, a activator of Cdk5, protein was significantly increased and reduced by roscovitine. The increased expressions of VGLUT2 protein was significantly reduced by roscovitine as well. Our study showed that VGLUT2/Cdk5 signaling pathway contributed to the inflammatory pain medicated by Cdk5/p25.

neuroscience↗

bioRxiv2019

Translational control of Bcl-2 promotes apoptosis of gastric carcinoma cells

Aberrantly expressed microRNAs (miRNAs) are essential for the tumorigenesis of gastric carcinoma (GC). Nevertheless, an effect of miR-383 on GC cells apoptosis has not been acknowledged previously. Here, we investigated the miR-383 level and anti-apoptotic protein Bcl-2 level in specimens of GC. Bioinformatics analyses was performed, and assay of luciferase-reporter was used for analyzing the relationship between Bcl-2 and miR-383. We analyzed survival of GC cells upon Fluorouracil treatment in an assay of CCK, and measured apoptosis of cells using flow cytometric FITC Annexin V apoptosis detection assay. The level of miR-383 was found extremely lower while the level of Bcl-2 levels was found extremely higher in GC specimens, in comparison with tissue from the adjacent non-tumor region. Additionally, the miR-383 level and Bcl-2 level inversely correlated in specimens of GC. In comparison with miR-383-high subjects, MiR-383-low subjects showed overall lower survival. Bioinformatics analyses revealed that miR-383 targeted the 3-UTR of Bcl-2 mRNA to restrain its translation, demonstrated in a luciferase reporter assay. MiR-383 overexpression inhibited the Bcl-2-mediated survival of cell against apoptosis induced by Fluorouracil, while miR-383 depletion enhanced the cell survival. Together, these data indicate that suppression of miR-383 in GC improves the Bcl-2-mediated cell survival of GC against the chemotherapy-induced cell death. MiR-383 re-expression in cells of GC might augment apoptosis of GC cells during chemotherapy.

cancer biology↗

bioRxiv2019

An Array of 60,000 Antibodies for Proteome-Scale Antibody Generation and Target Discovery

Antibodies are essential for elucidating the roles of genes decoded by genome sequencing. However, affordable technology for proteome-scale antibody generation does not exist. To address this, we developed the Proteome Epitope Tag Antibody Library (PETAL) and its array. PETAL consists of 62,208 mAbs against 15,199 peptides from diverse proteomes. PETAL harbors binders for a great multitude of proteins in nature due to antibody multispecificity, an intrinsic feature of an antibody. Distinctive combinations of 10,000-20,000 mAbs were found to target specific proteomes by array screening. Phenotype-specific mAb-target pairs were discovered for maize and zebrafish samples. Immunofluorescence and flow cytometry mAbs for human membrane proteins and ChIP-seq mAbs for transcription factors were identified from respective proteome-binding PETAL mAbs. Differential screening of cell surface proteomes of tumor and normal tissues discovered internalizing tumor antigens for antibody-drug conjugates. By discovering high affinity mAbs at a fraction of current time and cost, PETAL enables proteome-scale antibody generation and target discovery.

systems biology↗

bioRxiv2019

Pleiotropic effects for Parkin and LRRK2 in leprosy type-1 reactions and Parkinson’s disease

Type-1 reactions (T1Rs) are pathological inflammatory episodes and main contributors to nerve damage in leprosy. Here, we evaluate the gene-wise enrichment of rare protein altering variants in seven genes where common variants were previously associated with T1R. We selected 474 Vietnamese leprosy-patients of which 237 were T1R-affected and 237 were T1R-free matched controls. Gene-wise enrichment of nonsynonymous variants was tested with both kernel based (SKAT) and burden methods. Of the seven genes tested two showed statistical evidence of association with T1R. For the LRRK2 gene an enrichment of nonsynonymous variants was observed in T1R-free controls (p O_SCPCAPSKAT-OC_SCPCAP= 1.6x10-4). This gene-wise association was driven almost entirely by the gain of function variant R1628P (p = 0.004; OR = 0.29). The second gene-wise association was found for the Parkin coding gene PRKN (formerly PARK2) where seven rare variants were enriched in T1R-affected cases (p O_SCPCAPSKAT-OC_SCPCAP = 7.4x10-5). Mutations in both PRKN and LRRK2 are known causes of Parkinsons Disease (PD). Hence, we evaluated to what extent such rare amino acid changes observed in T1R are shared with PD. We observed that nonsynonymous T1R-risk mutations in Parkin were enriched for amino acid mutations implicated in PD (p = 1.5x10-4). Hence, neuro-inflammation in PD and peripheral nerve damage due to inflammation in T1R share overlapping mechanisms of pathogenicity.

genetics↗

bioRxiv2018

Ischemic Preconditioning and Left Ventricular Dysfunction: A Novel Mechanism & Model for Pulseless Electrical Activity

BackgroundPulseless electrical activity (PEA) is a very common rhythm in cardiac arrest and survival is {approx} 5%. Population data suggest coronary ischemia significantly contributes to PEA, but the mechanism is unknown.\n\nObjectivesWe hypothesize ischemic preconditioning (IPC) in the setting of left ventricular (LV) dysfunction can convert ischemia-induced ventricular fibrillation (VF) into ischemia-induced PEA.\n\nMethodsUsing percutaneous coronary interventions in anesthetized swine, we studied the effect of IPC prior to ischemia on arrhythmic burden in normal animals and in animals with LV dysfunction. IPC protocol: four cycles of three minutes of coronary occlusion followed by seven minutes of reperfusion. Chronic LV dysfunction protocol: two serial infarcts in two coronary territories, separated by one week of recovery.\n\nResultsIn normal animals, IPC prior to ischemia significantly reduced VF incidence (2/8 IPC vs. 7/8 control). In IPC animals with VF, the time to VF was significantly delayed (37.2 {+/-} 7.3 min vs. 20.7 {+/-} 4.9 min, p<0.005). In chronic LV dysfunction animals (EF 15% {+/-} 5%), ischemia caused PEA in all animals (18/18). In non-preconditioned animals, VF followed PEA in all cases (12/12). In preconditioned animals, PEA sustained without VF in 2/6 animals. In 4/6 animals, PEA was prolonged and time to VF was significantly delayed compared to non-preconditioned animals (33.7 {+/-} 7.8 min vs. 12.2 {+/-} 5.0 min, p<0.0001).\n\nConclusionIPC delays/prevents VF. IPC with LV dysfunction prior to ischemia produces prolonged PEA. IPC with LV dysfunction prior to ischemia is likely an important mechanism for human PEA arrest. This is the first animal model of ischemic pulseless electrical activity.

physiology↗

bioRxiv2018

Unbiased Age-Appropriate Structural Brain Atlases for Chinese Pediatrics

In magnetic resonance imaging (MRI) studies of children brain development, structural brain atlases usually serve as important references of pediatric population in which individual images are spatially normalized into a common or standard stereotactic space. However, the existing popular children brain atlases (e.g., National Institutes of Health pediatric atlases, NIH-PD atlases) are made mostly based on MR images from Western populations, and are thus insufficient to characterize the brains of Chinese children due to the neuroanatomical differences that are relevant to genetic and environmental factors. By collecting high-quality T1- and T2- weighted MR images from 328 typically developing Chinese children aged from 6 to 12 years old, we created a set of age-appropriate Chinese pediatric (CHN-PD) atlases using an unbiased template construction algorithm. The CHN-PD atlases included the head/brain templates, the symmetric brain template, the gender-specific brain templates and the corresponding tissue probability atlases. Moreover, the atlases contained multiple age-specific templates with a one-year interval. A direct comparison of the CHN-PD and the NIH-PD atlases revealed remarkable anatomical differences bilaterally in the lateral frontal and parietal regions and somatosensory cortex. While applying the CHN-PD atlases to two independent Chinese pediatric datasets (N = 114 and N = 71, respectively), machine-learning regression approaches revealed higher prediction accuracy on brain ages than the usage of NIH-PD atlases. These results suggest that the CHN-PD brain atlases are necessary and important for future typical and atypical developmental studies in Chinese pediatric population. Currently, the CHN-PD atlases have been released on the NITRC website (https://www.nitrc.org/projects/chn-pd).

neuroscience↗

bioRxiv2018

Template-assisted synthesis of adenine-mutagenized cDNA by a retroelement protein complex

Diversity-generating retroelements (DGRs) create unparalleled levels of protein sequence variation through mutagenic retrohoming. Sequence information is transferred from an invariant template region (TR), through an RNA intermediate, to a protein-coding variable region. Selective infidelity at adenines during transfer is a hallmark of DGRs from disparate bacteria, archaea, and microbial viruses. We recapitulated selective infidelity in vitro for the prototypical Bordetella bacteriophage DGR. A complex of the DGR reverse transcriptase bRT and pentameric accessory variability determinant (Avd) protein along with DGR RNA were necessary and sufficient for synthesis of template-primed, covalently linked RNA-cDNA molecules, as observed in vivo. We identified RNAcDNA molecules to be branched and most plausibly linked through 2'-5' phosphodiester bonds. Adenine-mutagenesis was intrinsic to the bRT-Avd complex, which displayed unprecedented promiscuity while reverse transcribing adenines of either DGR or non-DGR RNA templates. In contrast, bRT-Avd processivity was strictly dependent on the template, occurring only for the DGR RNA. This restriction was mainly due to a noncoding segment downstream of TR, which specifically bound Avd and created a privileged site for processive polymerization. Restriction to DGR RNA may protect the host genome from damage. These results define the early steps in a novel pathway for massive sequence diversification.

biochemistry↗

bioRxiv2018

Deciphering the rules which mRNA structures differs from vivo and vitro in Saccharomyces cerevisiae by deep neural networks

The structure of mRNA in vivo is influenced by various factors involved in the translation process, resulting in significant differentiation of mRNA structure from that in vitro. Because multiple factors cause the differentiation of in vivo and in vitro mRNA structures, it was difficult to perform a more accurate analysis of mRNA structures in previous studies. In this study, we have proposed a novel application of a deep neural network (DNN) model to predict the structural stability of mRNA in vivo by fitting six quantifiable features that may affect mRNA folding: ribosome density, minimum folding free energy, GC content, mRNA abundance, ribosomal initial density and position of mRNA structure. Simulated mutations of the mRNA structure were designed and then fed into the trained DNN model to compute their structural stability. We found unique effects of these six features on mRNA structural stability in vivo. Strikingly, the ribosome density of the structural region is the most important factor affecting the structural stability of mRNA in vivo, and the strength of the mRNA structure in vitro should have a relatively small effect on its structural stability in vivo. The recruitment of DNNs provides a new paradigm to decipher the differentiation of mRNA structure in vivo and in vitro. This improved knowledge on the mechanisms of factors influencing mRNA structural stability will facilitate the design and functional analysis of mRNA structure in vivo.

bioinformatics↗

bioRxiv2018

Identification of key genes related to dexamethasone-resistance in acute lymphoblastic leukemia

Drug resistance is the main cause of poor chemotherapy response in acute leukemia. Despite the extensive use of dexamethasone(DEX) in the treatment of acute lymphoblastic leukemia for many years, the mechanisms of dexamethasone - resistance has not been fully understood. We choose GSE94302 from GEO database aiming to identify key genes that contribute to the DEX resistance in acute lymphoblastic leukemia. Differentially expressed gene(DEGs) are selected by using GEO2R tools. A total of 837 DEGs were picked out, including 472 up-regulated and 365 down-regulated DEGs. All the DEGs were underwent gene ontology(GO) analysis and Kyoto Encyclopedia of Gene and Genome(KEGG) pathway analysis. In addition, the DEGs-encoded protein-protein interaction (PPI) was screened by using Cytoscape and Search Tool for the Retrieval of Interacting Genes(STRING). Total 20 genes were found as key genes related to DEX resistance with high degree of connectivity, including CDK1, PCNA, CCNB1, MYC, KPNA2, AURKA, NDC80, HSPA4, KIF11, UBE2C, PIK3CG, CD44, CD19, STAT1, DDX41, LYN, BCR, CD48, JAK1 and ITGB1. They could be used as biomarkers to identify the DEX-resistant acute lymphoblastic leukemia.

bioinformatics↗