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323 results on '"Du, Wenhao"'

10. Nucleolus localization of SpyCas9 affects its stability and interferes with host protein translation in mammalian cells

Author

Tan, Renke, Du, Wenhao, Liu, Yiyang, Cong, Xiaoji, Bai, Meirong, Jiang, Chenxiao, Li, Zengxia, Tan, Minjia, K., Dengke, Huang, Qiang, Jiang, Wei, and Dang, Yongjun

Subjects
Emerging Infectious Diseases, Biotechnology, Genetics, Aetiology, 1.1 Normal biological development and functioning, 2.1 Biological and endogenous factors, Underpinning research, Generic health relevance, CRISPR/Cas9, Gene editing, Global transcription, Nucleolus detention signal, Translation
Abstract

The CRISPR/Cas9 system, originally derived from the prokaryotic adaptive immune system, has been developed as efficient genome editing tools. It enables precise gene manipulation on chromosomal DNA through the specific binding of programmable sgRNA to target DNA, and the Cas9 protein, which has endonuclease activity, will cut a double strand break at specific locus. However, Cas9 is a foreign protein in mammalian cells, and the potential risks associated with its introduction into mammalian cells are not fully understood. In this study, we performed pull-down and mass spectrometry (MS) analysis of Streptococcus pyogenes Cas9 (SpyCas9) interacting proteins in HEK293T cells and showed that the majority of Cas9-associated proteins identified by MS were localized in the nucleolus. Interestingly, we further discovered that the Cas9 protein contains a sequence encoding a nucleolus detention signal (NoDS). Compared with wild-type (WT) Cas9, NoDS-mutated variants of Cas9 (mCas9) are less stable, although their gene editing activity is minimally affected. Overexpression of WT Cas9, but not mCas9, causes general effects on transcription and protein translation in the host cell. Overall, identification of NoDS in Cas9 will improve the understanding of Cas9's biological function in vivo, and the removal of NoDS in Cas9 may enhance its safety for future clinical use.

Published
2022

15. Surrogate-assisted cooperative signal optimization for large-scale traffic networks

Author

Liang, Yongsheng, Ren, Zhigang, Wang, Lin, Liu, Hanqing, and Du, Wenhao

Subjects
Computer Science - Neural and Evolutionary Computing
Abstract

Reasonable setting of traffic signals can be very helpful in alleviating congestion in urban traffic networks. Meta-heuristic optimization algorithms have proved themselves to be able to find high-quality signal timing plans. However, they generally suffer from performance deterioration when solving large-scale traffic signal optimization problems due to the huge search space and limited computational budget. Directing against this issue, this study proposes a surrogate-assisted cooperative signal optimization (SCSO) method. Different from existing methods that directly deal with the entire traffic network, SCSO first decomposes it into a set of tractable sub-networks, and then achieves signal setting by cooperatively optimizing these sub-networks with a surrogate-assisted optimizer. The decomposition operation significantly narrows the search space of the whole traffic network, and the surrogate-assisted optimizer greatly lowers the computational burden by reducing the number of expensive traffic simulations. By taking Newman fast algorithm, radial basis function and a modified estimation of distribution algorithm as decomposer, surrogate model and optimizer, respectively, this study develops a concrete SCSO algorithm. To evaluate its effectiveness and efficiency, a large-scale traffic network involving crossroads and T-junctions is generated based on a real traffic network. Comparison with several existing meta-heuristic algorithms specially designed for traffic signal optimization demonstrates the superiority of SCSO in reducing the average delay time of vehicles.

Published
2021

16. A Surrogate-Assisted Variable Grouping Algorithm for General Large Scale Global Optimization Problems

Author

Chen, An, Ren, Zhigang, Wang, Muyi, Liang, Yongsheng, Liu, Hanqing, and Du, Wenhao

Subjects
Computer Science - Neural and Evolutionary Computing
Abstract

Problem decomposition plays a vital role when applying cooperative coevolution (CC) to large scale global optimization problems. However, most learning-based decomposition algorithms either only apply to additively separable problems or face the issue of false separability detections. Directing against these limitations, this study proposes a novel decomposition algorithm called surrogate-assisted variable grouping (SVG). SVG first designs a general-separability-oriented detection criterion according to whether the optimum of a variable changes with other variables. This criterion is consistent with the separability definition and thus endows SVG with broad applicability and high accuracy. To reduce the fitness evaluation requirement, SVG seeks the optimum of a variable with the help of a surrogate model rather than the original expensive high-dimensional model. Moreover, it converts the variable grouping process into a dynamic-binary-tree search one, which facilitates reutilizing historical separability detection information and thus reducing detection times. To evaluate the performance of SVG, a suite of benchmark functions with up to 2000 dimensions, including additively and non-additively separable ones, were designed. Experimental results on these functions indicate that, compared with six state-of-the-art decomposition algorithms, SVG possesses broader applicability and competitive efficiency. Furthermore, it can significantly enhance the optimization performance of CC.

Published
2021

44. Effect of Scoparia dulcis Extract on Lipid Oxidation in Fish Feed, Growth Performance, and Hypoxia Tolerance in Juvenile Jian Carp (Cyprinus carpio var. Jian).

Author

Chen, Gangfu, Xu, Jing, Li, Fengyi, He, Mingquan, Yu, Xiaolu, Du, Wenhao, Ye, Yuxue, Liao, Ling, Wu, Min, and Li, Huatao

Subjects
DIGESTIVE enzymes, CARP, FISH feeds, HYPOXEMIA, GLUTATHIONE reductase, WEIGHT gain, LINOLENIC acids
Abstract

Lipid oxidation and hypoxia can lead to oxidative damage in aquatic animals. This study explored the effects of Scoparia dulcis extracts (SDE) on lipid oxidation, fish growth performance, digestive ability, antioxidant capacity, and hypoxia tolerance ability. The results showed that SDE decreased malonaldehyde (MDA), conjugated diene (CD), and peroxide value (PO) in the linoleic acid and linolenic acid as well as in fish feed. Broken-line analysis revealed that the optimal acetone extract of S. dulcis (AE) supplements was 4.02, 4.01, and 4.01 g kg−1 determined from PO, CD, and MDA, respectively. Dietary AE supplementation increased feed intake and specific growth rate and activities of amylase, trypsin, and lipase as well as alkaline phosphatase in fish hepatopancreas and gut. Polynomial regression analysis showed that optimal dietary AE supplement was 3.61 g kg−1 diet determined from weight gain. Furthermore, dietary AE supplementation decreased MDA content and increased glutathione content and the activities of glutathione peroxidase, catalase, superoxide dismutase, and glutathione reductase in fish digestive organs, gills, erythrocytes, and muscle. Dietary AE supplementation increased durative time (DT) and oxygen consumption rate (OCR) under hypoxia condition. Based on polynomial regression analysis, optimal dietary AE supplements were 4.73 and 4.60 g kg−1 diet determined from DT and OCR for hypoxia tolerance in fish, respectively. According to our current research, SDE's antioxidant capacity may be attribute to their phenolic chemicals. [ABSTRACT FROM AUTHOR]

Published
2024
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46. Discovery of a PROTAC degrader for METTL3-METTL14 complex

Author

Du, Wenhao, primary, Huang, Yuting, additional, Chen, Xiaoai, additional, Deng, Yue, additional, Sun, Yaoliang, additional, Yang, Hong, additional, Shi, Qiongyu, additional, Wu, Feifei, additional, Liu, Guobin, additional, Huang, He, additional, Ding, Jian, additional, Huang, Xun, additional, and Xu, Shilin, additional

Published
2024
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