Publications by authors named "Yanjie Wei"

46 Publications

MiRNA-20b/SUFU/Wnt axis accelerates gastric cancer cell proliferation, migration and EMT.

Heliyon 2021 Apr 12;7(4):e06695. Epub 2021 Apr 12.

Guangdong Key Laboratory for Genome Stability & Disease Prevention, Department of Pathology, Shenzhen University School of Medicine, Shenzhen, Guangdong 518060, China.

Previous research has found that miRNA-20b is highly expressed in gastric cancer (GC), however, its function and underlying mechanism are not clear. Wnt signaling pathway, implicated in tumorigeneisis, is activated in more than 30% of GC. We would like to characterize the biological behavior of miRNA-20b in terms of modulating Wnt/β-catenin signaling and EMT. We showed that miRNA-20b inhibitors suppressed Topflash/Fopflash dependent luciferase activity and the β-catenin nuclear translocation, resulting in inhibition of Wnt pathway activity and EMT. SUFU, negatively regulating Wnt and Hedgehog signaling pathway, was proved to be targeted by miRNA-20b. Moreover, additional knockdown of SUFU alleviated the inhibitory effect on Wnt pathway activity, EMT, cell proliferation/migration and colony formation caused by miRNA-20b inhibition. In summary, miRNA-20b is an oncogenic miRNA and promoted cell proliferation, migration and EMT in GC partially by activating Wnt pathway via targeting SUFU.
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http://dx.doi.org/10.1016/j.heliyon.2021.e06695DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8065298PMC
April 2021

Dual activation of Hedgehog and Wnt/β-catenin signaling pathway caused by downregulation of SUFU targeted by miRNA-150 in human gastric cancer.

Aging (Albany NY) 2021 Apr 12;13(7):10749-10769. Epub 2021 Apr 12.

Guangdong Key Laboratory for Genome Stability and Disease Prevention, Department of Pathology, Shenzhen University School of Medicine, Shenzhen 518060, Guangdong, P.R. China.

Mounting evidence has shown that miRNA-150 expression is upregulated in gastric cancer (GC) and is associated with gastric carcinogenesis, but the underlying oncogenic mechanism remains elusive. Here, we discovered that miRNA-150 targets the tumor suppressor SUFU to promote cell proliferation, migration, and the epithelial-mesenchymal transition (EMT) via the dual activation of Hedgehog (Hh) and Wnt signaling. MiRNA-150 was highly expressed in GC tissues and cell lines, and the level of this miRNA was negatively related to that of SUFU. In addition, both the miRNA-150 and SUFU levels were associated with tumor differentiation. Furthermore, miRNA-150 activated GC cell proliferation and migration . We found that miRNA-150 inhibitors repressed not only Wnt signaling by promoting cytoplasmic β-catenin localization, but also repressed Hh signaling and EMT. MiRNA-150 inhibition also resulted in significant tumor volume reductions , suggesting the potential application of miRNA-150 inhibitors in GC therapy. The expression of genes downstream of Hh and Wnt signaling was also reduced in tumors treated with miRNA-150 inhibitors. Notably, anti-SUFU siRNAs rescued the inhibitory effects of miRNA-150 inhibitors on Wnt signaling, Hh activation, EMT, cell proliferation, cell migration, and colony formation. Taken together, these findings indicate that miRNA-150 is oncogenic and promotes GC cell proliferation, migration, and EMT by activating Wnt and Hh signaling via the suppression of SUFU expression.
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http://dx.doi.org/10.18632/aging.202895DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8064165PMC
April 2021

Microbial analysis for the ammonium removal from landfill leachate in an aerobic granular sludge sequencing batch reactor.

Bioresour Technol 2021 Mar 5;324:124639. Epub 2021 Jan 5.

Centre for Technology in Water and Wastewater, School of Civil and Environmental Engineering, University of Technology Sydney, Sydney, NSW 2007, Australia. Electronic address:

In this study, a laboratory-scale sequencing batch reactor (SBR) equipped with aerobic granular sludge (AGS) technology was continuously operated for 220 days to remove ammonium from an existing landfill leachate. The ammonium removal was characterized by polymerase chain reaction (PCR)-denaturing gradient gel electrophoresis (DGGE) technology. This method helped to analyze the long-term community structural stability of ammonia-oxidizing bacteria (AOB), nitrite-oxidizing bacteria (NOB) and denitrifying bacteria (DB) throughout the experiment. Simultaneously, 16S rRNA gene cloning and sequencing analysis identified the dominant species of different microbial species. Experimental results confirmed that ammonium removal was inhibited at the high nitrogen loading rate (NLR) stage while the low NLR stage achieved satisfactory ammonium removal. Moreover, the findings demonstrated that functionally stable wastewater treatment bioreactors facilitated the occurrence of stable microbial community structures.
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http://dx.doi.org/10.1016/j.biortech.2020.124639DOI Listing
March 2021

Editorial: Computational Learning Models and Methods Driven by Omics for Precision Medicine.

Front Genet 2020 23;11:620976. Epub 2020 Dec 23.

Faculty of Computing, Engineering and the Built Environment, School of Computing, Engineering and Intelligent Systems, Ulster University, Coleraine, United Kingdom.

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http://dx.doi.org/10.3389/fgene.2020.620976DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7785880PMC
December 2020

A novel virtual screening procedure identifies Pralatrexate as inhibitor of SARS-CoV-2 RdRp and it reduces viral replication in vitro.

PLoS Comput Biol 2020 12 31;16(12):e1008489. Epub 2020 Dec 31.

Center for High Performance Computing, Joint Engineering Research Center for Health Big Data Intelligent Analysis Technology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong, China.

The spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus poses serious threats to the global public health and leads to worldwide crisis. No effective drug or vaccine is readily available. The viral RNA-dependent RNA polymerase (RdRp) is a promising therapeutic target. A hybrid drug screening procedure was proposed and applied to identify potential drug candidates targeting RdRp from 1906 approved drugs. Among the four selected market available drug candidates, Pralatrexate and Azithromycin were confirmed to effectively inhibit SARS-CoV-2 replication in vitro with EC50 values of 0.008μM and 9.453 μM, respectively. For the first time, our study discovered that Pralatrexate is able to potently inhibit SARS-CoV-2 replication with a stronger inhibitory activity than Remdesivir within the same experimental conditions. The paper demonstrates the feasibility of fast and accurate anti-viral drug screening for inhibitors of SARS-CoV-2 and provides potential therapeutic agents against COVID-19.
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http://dx.doi.org/10.1371/journal.pcbi.1008489DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7774833PMC
December 2020

Histone methyltransferase SET8 is regulated by miR-192/215 and induces oncogene-induced senescence via p53-dependent DNA damage in human gastric carcinoma cells.

Cell Death Dis 2020 10 30;11(10):937. Epub 2020 Oct 30.

Guangdong Key Laboratory for Genome Stability & Disease Prevention and Regional Immunity and Diseases, Department of Pathology, Shenzhen University School of Medicine, Shenzhen, Guangdong, 518060, People's Republic of China.

Gastric cancer (GC) is the most common cancer throughout the world. Despite advances of the treatments, detailed oncogenic mechanisms are largely unknown. In our previous study, we investigated microRNA (miR) expression profiles in human GC using miR microarrays. We found miR-192/215 were upregulated in GC tissues. Then gene microarray was implemented to discover the targets of miR-192/215. We compared the expression profile of BGC823 cells transfected with miR-192/215 inhibitors, and HFE145 cells transfected with miR-192/-215 mimics, respectively. SET8 was identified as a proposed target based on the expression change of more than twofold. SET8 belongs to the SET domain-containing methyltransferase family and specifically catalyzes monomethylation of H4K20me. It is involved in diverse functions in tumorigenesis and metastasis. Therefore, we focused on the contributions of miR-192/215/SET8 axis to the development of GC. In this study, we observe that functionally, SET8 regulated by miR-192/215 is involved in GC-related biological activities. SET8 is also found to trigger oncogene-induced senescence (OIS) in GC in vivo and in vitro, which is dependent on the DDR (DNA damage response) and p53. Our findings reveal that SET8 functions as a negative regulator of metastasis via the OIS-signaling pathway. Taken together, we investigated the functional significance, molecular mechanisms, and clinical impact of miR-192/215/SET8/p53 in GC.
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http://dx.doi.org/10.1038/s41419-020-03130-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7599338PMC
October 2020

Structural basis for the inhibition of SARS-CoV2 main protease by Indian medicinal plant-derived antiviral compounds.

J Biomol Struct Dyn 2020 Oct 19:1-9. Epub 2020 Oct 19.

Department of Molecular Microbiology, School of Biotechnology, Madurai Kamaraj University, Madurai, Tamilnadu, India.

A novel coronavirus (SARS-CoV2) has caused a major outbreak in humans around the globe, and it became a severe threat to human healthcare than all other infectious diseases. Researchers were urged to discover and test various approaches to control and prevent such a deadly disease. Considering the emergency and necessity, we screened reported antiviral compounds present in the traditional Indian medicinal plants for the inhibition of SARS-CoV2 main protease. In this study, we used molecular docking to screen 41 reported antiviral compounds that exist in Indian medicinal plants and shown amentoflavone from the plant with a higher docking score. Furthermore, we performed a 40 ns atomic molecular dynamics simulation and free binding energy calculations to explore the stability of the top five protein-ligand complexes. Through the article, we insist that the amentoflavone, hypericin and Torvoside H from the traditional Indian medicinal plants may be used as a potential inhibitor of SARS-CoV2 main protease and further biochemical experiments could shed light on understanding the mechanism of inhibition by these plant-derived antiviral compounds. Communicated by Ramaswamy H. Sarma.
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http://dx.doi.org/10.1080/07391102.2020.1834457DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7594188PMC
October 2020

SUFU mediates EMT and Wnt/β-catenin signaling pathway activation promoted by miRNA-324-5p in human gastric cancer.

Cell Cycle 2020 10 5;19(20):2720-2733. Epub 2020 Oct 5.

Guangdong Key Laboratory for Genome Stability & Disease Prevention, Guangdong Provincial Key Laboratory of Regional Immunity and Diseases, Department of Pathology, Shenzhen University School of Medicine , Shenzhen, Guangdong, China.

The poor prognosis of late gastric carcinomas (GC) underscores the necessity to identify novel biomarkers for earlier diagnosis and effective therapeutic targets. MiRNA-324-5p has been shown to be over-expressed in GC, however the biological function of miRNA-324-5p implicated in gastric cancer and its downstream targets were not well understood. Wnt/β-catenin signaling pathway is aberrantly regulated in GC. We sought to explore if miRNA-324-5p promotes oncogenesis through modulating Wnt signaling and EMT. MiRNA-324-5p is highly expressed in GC based on qRT-PCR and TCGA data. In addition, in vitro cell proliferation, cell migration assays and in vivo animal exenograft were executed to show that miRNA-324-5p is an oncogenic miRNA in GC. MiRNA-324-5p activates Wnt signaling and induces EMT in GC. Further, SUFU was identified as a target of miRNA-324-5p confirmed by western blotting and luciferase assays. Spearson analysis and TCGA data indicate that the expression of SUFU is negatively associated with the expression of miRNA-324-5p. Rescue experiments were performed to determine if SUFU mediates the Wnt activation, EMT and oncogenic function of miRNA-324-5p. MiRNA-324-5p inhibitors plus SUFU siRNAs rescue partially the inhibitory effect on Wnt signaling and EMT caused by miRNA-324-5p inhibitors. Finally, the suppression of cell proliferation, migration, and colony formation ability induced by miRNA-324-5p inhibitors is alleviated by addition of SUFU siRNAs. In summary, miRNA-324-5p is overexpressed and exerts cell growth and migration-promoting effects through activating Wnt signaling and EMT by targeting SUFU in GC. It represents a potential miRNA with an oncogenic role in human gastric cancer.
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http://dx.doi.org/10.1080/15384101.2020.1826632DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7644164PMC
October 2020

RabbitMash: accelerating hash-based genome analysis on modern multi-core architectures.

Bioinformatics 2021 May;37(6):873-875

School of Software, Shandong University, Jinan 250101, China.

Motivation: Mash is a popular hash-based genome analysis toolkit with applications to important downstream analyses tasks such as clustering and assembly. However, Mash is currently not able to fully exploit the capabilities of modern multi-core architectures, which in turn leads to high runtimes for large-scale genomic datasets.

Results: We present RabbitMash, an efficient highly optimized implementation of Mash which can take full advantage of modern hardware including multi-threading, vectorization and fast I/O. We show that our approach achieves speedups of at least 1.3, 9.8, 8.5 and 4.4 compared to Mash for the operations sketch, dist, triangle and screen, respectively. Furthermore, RabbitMash is able to compute the all-versus-all distances of 100 321 genomes in <5 min on a 40-core workstation while Mash requires over 40 min.

Availability And Implementation: RabbitMash is available at https://github.com/ZekunYin/RabbitMash.

Supplementary Information: Supplementary data are available at Bioinformatics online.
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http://dx.doi.org/10.1093/bioinformatics/btaa754DOI Listing
May 2021

RabbitQC: high-speed scalable quality control for sequencing data.

Bioinformatics 2021 May;37(4):573-574

School of Software, Shandong University, Jinan, China.

Motivation: Modern sequencing technologies continue to revolutionize many areas of biology and medicine. Since the generated datasets are error-prone, downstream applications usually require quality control methods to pre-process FASTQ files. However, existing tools for this task are currently not able to fully exploit the capabilities of computing platforms leading to slow runtimes.

Results: We present RabbitQC, an extremely fast integrated quality control tool for FASTQ files, which can take full advantage of modern hardware. It includes a variety of operations and supports different sequencing technologies (Illumina, Oxford Nanopore and PacBio). RabbitQC achieves speedups between one and two orders-of-magnitude compared to other state-of-the-art tools.

Availability And Implementation: C++ sources and binaries are available at https://github.com/ZekunYin/RabbitQC.

Supplementary Information: Supplementary data are available at Bioinformatics online.
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http://dx.doi.org/10.1093/bioinformatics/btaa719DOI Listing
May 2021

On the Conformational Dynamics of β-Amyloid Forming Peptides: A Computational Perspective.

Front Bioeng Biotechnol 2020 3;8:532. Epub 2020 Jun 3.

Center for High Performance Computing, Joint Engineering Research Center for Health Big Data Intelligent Analysis Technology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.

Understanding the conformational dynamics of proteins and peptides involved in important functions is still a difficult task in computational structural biology. Because such conformational transitions in β-amyloid (Aβ) forming peptides play a crucial role in many neurological disorders, researchers from different scientific fields have been trying to address issues related to the folding of Aβ forming peptides together. Many theoretical models have been proposed in the recent years for studying Aβ peptides using mathematical, physicochemical, and molecular dynamics simulation, and machine learning approaches. In this article, we have comprehensively reviewed the developmental advances in the theoretical models for Aβ peptide folding and interactions, particularly in the context of neurological disorders. Furthermore, we have extensively reviewed the advances in molecular dynamics simulation as a tool used for studying the conversions between polymorphic amyloid forms and applications of using machine learning approaches in predicting Aβ peptides and aggregation-prone regions in proteins. We have also provided details on the theoretical advances in the study of Aβ peptides, which would enhance our understanding of these peptides at the molecular level and eventually lead to the development of targeted therapies for certain acute neurological disorders such as Alzheimer's disease in the future.
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http://dx.doi.org/10.3389/fbioe.2020.00532DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7325929PMC
June 2020

An Infrared Defect Sizing Method Based on Enhanced Phase Images.

Sensors (Basel) 2020 Jun 28;20(13). Epub 2020 Jun 28.

Shanghai Institute of Applied Mathematics and Mechanics, School of Mechanics and Engineering Science, Shanghai University, Shanghai 200444, China.

Infrared thermography (IRT) is a full-field, contactless technique that has been widely used for nondestructive evaluation of structural materials due to many advantages. One of the major limitations of IRT is the fuzzy edge and low contrast in the inspected images-as well as the cost of the system. An efficient image post-processing with an affordable and portable device is of great interest to the engineering society. In this study, a convenient and economical inspection system using common halogen lamps was constructed. The corresponding image-processing scheme, which includes Fourier phase analysis and specific image enhancement was developed to identify defects with sharp and clear edges and good contrast. This system was applied to localized of defects in glass-fiber-reinforced composite panels. The results showed that defects with an effective diameter as small as 5 mm can be detected with excellent image quality. As a conclusion, the developed system provides an economic alternative to traditional infrared thermography which is able to identify defects with good qualities.
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http://dx.doi.org/10.3390/s20133626DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7374367PMC
June 2020

FcircSEC: An R Package for Full Length circRNA Sequence Extraction and Classification.

Int J Genomics 2020 28;2020:9084901. Epub 2020 May 28.

Joint Engineering Research Center for Health Big Data Intelligent Analysis Technology, Center for High Performance Computing, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong Province, China 518055.

Circular RNAs (circRNAs) are formed by joining the 3' and 5' ends of RNA molecules. Identification of circRNAs is an important part of circRNA research. The circRNA prediction methods can predict the circRNAs with start and end positions in the chromosome but cannot identify the full-length circRNA sequences. We present an R package FcircSEC (Full Length circRNA Sequence Extraction and Classification) to extract the full-length circRNA sequences based on gene annotation and the output of any circRNA prediction tools whose output has a chromosome, start and end positions, and a strand for each circRNA. To validate FcircSEC, we have used three databases, circbase, circRNAdb, and plantcircbase. With information such as the chromosome and strand of each circRNA as the input, the identified sequences by FcircSEC are consistent with the databases. The novelty of FcircSEC is that it can take the output of state-of-the-art circRNA prediction tools as input and is applicable for human and other species. We also classify the circRNAs as exonic, intronic, and others. The R package FcircSEC is freely available.
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http://dx.doi.org/10.1155/2020/9084901DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7285417PMC
May 2020

Deep Learning Based Drug Screening for Novel Coronavirus 2019-nCov.

Interdiscip Sci 2020 Sep 1;12(3):368-376. Epub 2020 Jun 1.

Center for High Performance Computing, Joint Engineering Research Center for Health Big Data Intelligent Analysis Technology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong, 518055, People's Republic of China.

A novel coronavirus, called 2019-nCoV, was recently found in Wuhan, Hubei Province of China, and now is spreading across China and other parts of the world. Although there are some drugs to treat 2019-nCoV, there is no proper scientific evidence about its activity on the virus. It is of high significance to develop a drug that can combat the virus effectively to save valuable human lives. It usually takes a much longer time to develop a drug using traditional methods. For 2019-nCoV, it is now better to rely on some alternative methods such as deep learning to develop drugs that can combat such a disease effectively since 2019-nCoV is highly homologous to SARS-CoV. In the present work, we first collected virus RNA sequences of 18 patients reported to have 2019-nCoV from the public domain database, translated the RNA into protein sequences, and performed multiple sequence alignment. After a careful literature survey and sequence analysis, 3C-like protease is considered to be a major therapeutic target and we built a protein 3D model of 3C-like protease using homology modeling. Relying on the structural model, we used a pipeline to perform large scale virtual screening by using a deep learning based method to accurately rank/identify protein-ligand interacting pairs developed recently in our group. Our model identified potential drugs for 2019-nCoV 3C-like protease by performing drug screening against four chemical compound databases (Chimdiv, Targetmol-Approved_Drug_Library, Targetmol-Natural_Compound_Library, and Targetmol-Bioactive_Compound_Library) and a database of tripeptides. Through this paper, we provided the list of possible chemical ligands (Meglumine, Vidarabine, Adenosine, D-Sorbitol, D-Mannitol, Sodium_gluconate, Ganciclovir and Chlorobutanol) and peptide drugs (combination of isoleucine, lysine and proline) from the databases to guide the experimental scientists and validate the molecules which can combat the virus in a shorter time.
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http://dx.doi.org/10.1007/s12539-020-00376-6DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7266118PMC
September 2020

DeepBindPoc: a deep learning method to rank ligand binding pockets using molecular vector representation.

PeerJ 2020 6;8:e8864. Epub 2020 Apr 6.

Center for High Performance Computing, Joint Engineering Research Center for Health Big Data Intelligent Analysis Technology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong Province, China.

Accurate identification of ligand-binding pockets in a protein is important for structure-based drug design. In recent years, several deep learning models were developed to learn important physical-chemical and spatial information to predict ligand-binding pockets in a protein. However, ranking the native ligand binding pockets from a pool of predicted pockets is still a hard task for computational molecular biologists using a single web-based tool. Hence, we believe, by using closer to real application data set as training and by providing ligand information, an enhanced model to identify accurate pockets can be obtained. In this article, we propose a new deep learning method called DeepBindPoc for identifying and ranking ligand-binding pockets in proteins. The model is built by using information about the binding pocket and associated ligand. We take advantage of the mol2vec tool to represent both the given ligand and pocket as vectors to construct a densely fully connected layer model. During the training, important features for pocket-ligand binding are automatically extracted and high-level information is preserved appropriately. DeepBindPoc demonstrated a strong complementary advantage for the detection of native-like pockets when combined with traditional popular methods, such as fpocket and P2Rank. The proposed method is extensively tested and validated with standard procedures on multiple datasets, including a dataset with G-protein Coupled receptors. The systematic testing and validation of our method suggest that DeepBindPoc is a valuable tool to rank near-native pockets for theoretically modeled protein with unknown experimental active site but have known ligand. The DeepBindPoc model described in this article is available at GitHub (https://github.com/haiping1010/DeepBindPoc) and the webserver is available at (http://cbblab.siat.ac.cn/DeepBindPoc/index.php).
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http://dx.doi.org/10.7717/peerj.8864DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7144620PMC
April 2020

miRNA-192 and -215 activate Wnt/β-catenin signaling pathway in gastric cancer via APC.

J Cell Physiol 2020 09 24;235(9):6218-6229. Epub 2020 Feb 24.

Department of Pathology, Guangdong Key Laboratory for Genome Stability & Disease Prevention, The Shenzhen University School of Medicine, Shenzhen, Guangdong, China.

Although great progress has been made in surgical techniques, traditional radiotherapy, and chemotherapy, gastric cancer (GC) is still the most common malignant tumor and has a high mortality, which highlights the importance of novel diagnostic markers. Emerging studies suggest that different microRNAs (miRNAs) are involved in tumorigenesis of GC. In this study, we found that miRNA-192 and -215 are significantly upregulated in GC and promote cell proliferation and migration. Adenomatous polyposis coli (APC), a well-known negative regulator in Wnt signaling, has been proved to be a target of miRNA-192 and -215. Inhibition of miRNA-192 or -215 reduced the Topflash activities and repressed the expression of Wnt signaling pathway proteins, while APC small interfering RNAs reversed the inhibitory effects, suggesting that miRNA-192 and -215 activate Wnt signaling via APC. In addition, APC mediates the cell proliferation and migration regulated by miRNA-192 and -215. Furthermore, APC is downregulated in GC tissues and negatively correlated with the expression of miRNA-192 and -215. In summary, miRNA-192 and -215 target APC and function as oncogenic miRNAs by activating Wnt signaling in GC, revealing to be potential therapeutic targets.
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http://dx.doi.org/10.1002/jcp.29550DOI Listing
September 2020

A novel machine learning based approach for iPS progenitor cell identification.

PLoS Comput Biol 2019 12 26;15(12):e1007351. Epub 2019 Dec 26.

Joint Engineering Research Center for Health Big Data Intelligent Analysis Technology, Center for High Performance Computing, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong, China.

Identification of induced pluripotent stem (iPS) progenitor cells, the iPS forming cells in early stage of reprogramming, could provide valuable information for studying the origin and underlying mechanism of iPS cells. However, it is very difficult to identify experimentally since there are no biomarkers known for early progenitor cells, and only about 6 days after reprogramming initiation, iPS cells can be experimentally determined via fluorescent probes. What is more, the ratio of progenitor cells during early reprograming period is below 5%, which is too low to capture experimentally in the early stage. In this paper, we propose a novel computational approach for the identification of iPS progenitor cells based on machine learning and microscopic image analysis. Firstly, we record the reprogramming process using a live cell imaging system after 48 hours of infection with retroviruses expressing Oct4, Sox2 and Klf4, later iPS progenitor cells and normal murine embryonic fibroblasts (MEFs) within 3 to 5 days after infection are labeled by retrospectively tracing the time-lapse microscopic image. We then calculate 11 types of cell morphological and motion features such as area, speed, etc., and select best time windows for modeling and perform feature selection. Finally, a prediction model using XGBoost is built based on the selected six types of features and best time windows. Our model allows several missing values/frames in the sample datasets, thus it is applicable to a wide range of scenarios. Cross-validation, holdout validation and independent test experiments show that the minimum precision is above 52%, that is, the ratio of predicted progenitor cells within 3 to 5 days after viral infection is above 52%. The results also confirm that the morphology and motion pattern of iPS progenitor cells is different from that of normal MEFs, which helps with the machine learning methods for iPS progenitor cell identification.
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http://dx.doi.org/10.1371/journal.pcbi.1007351DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6932749PMC
December 2019

Atomistic and dynamic structural characterizations in low-dimensional materials: recent applications of in situ transmission electron microscopy.

Microscopy (Oxf) 2019 Dec;68(6):423-433

School of Physics and Technology, Center for Electron Microscopy, MOE Key Laboratory of Artificial Micro- and Nano-structures, and Institute for Advanced Studies, Wuhan University, Wuhan 430072, China.

In situ transmission electron microscopy has achieved remarkable advances for atomic-scale dynamic analysis in low-dimensional materials and become an indispensable tool in view of linking a material's microstructure to its properties and performance. Here, accompanied with some cutting-edge researches worldwide, we briefly review our recent progress in dynamic atomistic characterization of low-dimensional materials under external mechanical stress, thermal excitations and electrical field. The electron beam irradiation effects in metals and metal oxides are also discussed. We conclude by discussing the likely future developments in this area.
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http://dx.doi.org/10.1093/jmicro/dfz038DOI Listing
December 2019

Counting Kmers for Biological Sequences at Large Scale.

Interdiscip Sci 2020 Mar 16;12(1):99-108. Epub 2019 Nov 16.

Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Beijing, 518055, China.

Counting the abundance of all the distinct kmers in biological sequence data is a fundamental step in bioinformatics. These applications include de novo genome assembly, error correction, etc. With the development of sequencing technology, the sequence data in a single project can reach Petabyte-scale or Terabyte-scale nucleotides. Counting demand for the abundance of these sequencing data is beyond the memory and computing capacity of single computing node, and how to process it efficiently is a challenge on a high-performance computing cluster. As such, we propose SWAPCounter, a highly scalable distributed approach for kmer counting. This approach is embedded with an MPI streaming I/O module for loading huge data set at high speed, and a counting bloom filter module for both memory and communication efficiency. By overlapping all the counting steps, SWAPCounter achieves high scalability with high parallel efficiency. The experimental results indicate that SWAPCounter has competitive performance with two other tools on shared memory environment, KMC2, and MSPKmerCounter. Moreover, SWAPCounter also shows the highest scalability under strong scaling experiments. In our experiment on Cetus supercomputer, SWAPCounter scales to 32,768 cores with 79% parallel efficiency (using 2048 cores as baseline) when processing 4 TB sequence data of 1000 Genomes. The source code of SWAPCounter is publicly available at https://github.com/mengjintao/SWAPCounter.
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http://dx.doi.org/10.1007/s12539-019-00348-5DOI Listing
March 2020

Large-Scale Target Identification of Herbal Medicine Using a Reverse Docking Approach.

ACS Omega 2019 Jun 4;4(6):9710-9719. Epub 2019 Jun 4.

State Key Laboratory of Stress Cell Biology, School of Life Sciences, Xiamen University, Xiamen, Fujian 361102, PR China.

Herbal medicine has been used to countermine various diseases for centuries. However, most of the therapeutic targets underlying herbal therapy remain unclear, which largely slow down the novel drug discovery process from natural products. In this study, we developed a novel computational pipeline for assisting de novo identification of protein targets for herbal ingredients. The pipeline involves pharmacophore comparison and reverse ligand-protein docking simulation in a high throughput manner. We evaluated the pipeline using three traditional Chinese medicine ingredients such as acteoside, quercetin, and epigallocatechin gallate as examples. A majority of current known targets of these ingredients were successfully identified by the pipeline. Structural comparative analyses confirmed that the predicted ligand-target interactions used the same binding pockets and binding modes as those of known ligand-target interactions. Furthermore, we illustrated the mechanism of actions of the ingredients by constructing the pharmacological networks on the basis of the predicted target profiles. In summary, we proposed an efficient and economic option for large-scale target exploration in the herb study. This pipeline will be particularly valuable in aiding precise drug discovery and drug repurposing from natural products.
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http://dx.doi.org/10.1021/acsomega.9b00020DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6648299PMC
June 2019

DeepBindRG: a deep learning based method for estimating effective protein-ligand affinity.

PeerJ 2019 25;7:e7362. Epub 2019 Jul 25.

Joint Engineering Research Center for Health Big Data Intelligent Analysis Technology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong, China.

Proteins interact with small molecules to modulate several important cellular functions. Many acute diseases were cured by small molecule binding in the active site of protein either by inhibition or activation. Currently, there are several docking programs to estimate the binding position and the binding orientation of protein-ligand complex. Many scoring functions were developed to estimate the binding strength and predict the effective protein-ligand binding. While the accuracy of current scoring function is limited by several aspects, the solvent effect, entropy effect, and multibody effect are largely ignored in traditional machine learning methods. In this paper, we proposed a new deep neural network-based model named DeepBindRG to predict the binding affinity of protein-ligand complex, which learns all the effects, binding mode, and specificity implicitly by learning protein-ligand interface contact information from a large protein-ligand dataset. During the initial data processing step, the critical interface information was preserved to make sure the input is suitable for the proposed deep learning model. While validating our model on three independent datasets, DeepBindRG achieves root mean squared error (RMSE) value of pKa (-logK or -logK) about 1.6-1.8 and value around 0.5-0.6, which is better than the autodock vina whose RMSE value is about 2.2-2.4 and value is 0.42-0.57. We also explored the detailed reasons for the performance of DeepBindRG, especially for several failed cases by vina. Furthermore, DeepBindRG performed better for four challenging datasets from DUD.E database with no experimental protein-ligand complexes. The better performance of DeepBindRG than autodock vina in predicting protein-ligand binding affinity indicates that deep learning approach can greatly help with the drug discovery process. We also compare the performance of DeepBindRG with a 4D based deep learning method "pafnucy", the advantage and limitation of both methods have provided clues for improving the deep learning based protein-ligand prediction model in the future.
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http://dx.doi.org/10.7717/peerj.7362DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6661145PMC
July 2019

SQSTM1/p62 loss reverses the inhibitory effect of sunitinib on autophagy independent of AMPK signaling.

Sci Rep 2019 07 31;9(1):11087. Epub 2019 Jul 31.

Department of Urology, Peking University First Hospital, Beijing, 100034, China.

Sunitinib (ST), a multitargeted receptor tyrosine kinase inhibitor, has been demonstrated to be effective for the treatment of renal carcinoma. It has been reported that ST is involved in the mediation of autophagy; however, its regulatory role in the autophagic process remains controversial. Furthermore, the mechanism by which activated AMP-activated protein kinase (AMPK) negatively regulates autophagy remains nearly unexplored. In the present study, we revealed that ST inhibited AMPK activity and regulated autophagy in a cell type- and dose-dependent manner. In a number of cell lines, ST was demonstrated to inhibit HO-induced autophagy and the phosphorylation of acetyl-CoA carboxylase (ACC), whereas alone it could block the autophagic flux concurrent with increased expression of p62. An immunoprecipitation assay revealed that LC3 directly interacted with p62, whereas ST increased punctate LC3 staining, which was well colocalized with p62. Taken together, we reveal a previously unnoticed pathway for ST to regulate the autophagic process, and p62, although often utilized as a substrate in autophagy, plays a critical role in regulating the inhibition of ST in both basal and induced autophagy.
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http://dx.doi.org/10.1038/s41598-019-47597-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6668422PMC
July 2019

The TwistDock workflow for evaluation of bivalent Smac mimetics targeting XIAP.

Drug Des Devel Ther 2019 26;13:1373-1388. Epub 2019 Apr 26.

Joint Engineering Research Center for Health Big Data Intelligent Analysis Technology and Center for High Performance Computing, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong, People's Republic of China.

Mimetics based on Smac, the native inhibitor of XIAP, are promising drug-candidates for the treatment of cancer. Bivalent Smac mimetics inhibit XIAP with even higher potency than monovalent mimetics, but how to optimize the linker that tethers the two monovalent binding motifs remains controversial. To construct an ensemble of bivalent complex structures for evaluating various linkers, we propose herein a workflow, named TwistDock, consisting of steps of monovalent docking and linker twisting, in which the degrees of freedom are sampled focusing on the rotation of single bonds of the linker. The obtained conformations of bivalent complex distribute randomly in the conformational space with respect to two reaction coordinates introduced by the linker, which are the distance of the two binding motifs and the dihedral angle of the two planes through the linker and each of the binding motifs. Molecular dynamics starting from 10 conformations with the lowest enthalpy of every complex shows that the conformational tendency of the complex participated by compound 9, one of the compounds with the largest binding affinity, is distinct from others. By umbrella sampling of the complex, we find its global minimum of the free energy landscape. The structure shows that the linker favors a compact conformation, and the two BIR domains of XIAP encompass the ligand on the opposite sides. TwistDock can be used in fine-tuning of bivalent ligands targeting XIAP and similar receptors dimerized or oligomerized.
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http://dx.doi.org/10.2147/DDDT.S194276DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6499140PMC
February 2020

Systematic analysis of NO Regular Secondary structural regions (NORS) in membrane and non-membrane proteins.

J Biomol Struct Dyn 2020 01 5;38(1):268-274. Epub 2019 Feb 5.

Center for High Performance Computing, Joint Engineering Research Center for Health Big Data Intelligent Analysis Technology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, PR China.

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http://dx.doi.org/10.1080/07391102.2019.1566092DOI Listing
January 2020

Inhibition of miR‑194 suppresses the Wnt/β‑catenin signalling pathway in gastric cancer.

Oncol Rep 2018 Dec 8;40(6):3323-3334. Epub 2018 Oct 8.

Guangdong Key Laboratory for Genome Stability & Disease Prevention, Department of Pathology, The Shenzhen University School of Medicine, Shenzhen, Guangdong 518060, P.R. China.

A mounting body of evidence has revealed that microRNAs (miRs) serve pivotal roles in various developmental processes, and in tumourigenesis, by binding to target genes and subsequently regulating gene expression. Continued activation of the Wnt/β‑catenin signalling is positively associated with human malignancy. In addition, miR‑194 dysregulation has been implicated in gastric cancer (GC); however, the molecular mechanisms underlying the effects of miR‑194 on GC carcinogenesis remain to be elucidated. The present study demonstrated that miR‑194 was upregulated in GC tissues and SUFU negative regulator of Ηedgehog signaling (SUFU) was downregulated in GC cell lines. Subsequently, inhibition of miR‑194 attenuated nuclear accumulation of β‑catenin, which consequently blocked Wnt/β‑catenin signalling. In addition, the cytoplasmic translocation of β‑catenin induced by miR‑194 inhibition was mediated by SUFU. Furthermore, genes associated with the Wnt/β‑catenin signalling pathway were revealed to be downregulated following inhibition of the Wnt signalling pathway by miR‑194 suppression. Finally, the results indicated that cell apoptosis was markedly increased in response to miR‑194 inhibition, strongly suggesting the carcinogenic effects of miR‑194 in GC. Taken together, these findings demonstrated that miR‑194 may promote gastric carcinogenesis through activation of the Wnt/β‑catenin signalling pathway, making it a potential therapeutic target for GC.
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http://dx.doi.org/10.3892/or.2018.6773DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6196585PMC
December 2018

Atomistic Interface Dynamics in Sn-Catalyzed Growth of Wurtzite and Zinc-Blende ZnO Nanowires.

Nano Lett 2018 07 11;18(7):4095-4099. Epub 2018 Jun 11.

School of Physics and Technology, Center for Electron Microscopy, MOE Key Laboratory of Artificial Micro- and Nano-structures, and Institute for Advanced Studies , Wuhan University , Wuhan 430072 , China.

Unraveling the phase selection mechanisms of semiconductor nanowires (NWs) is critical for the applications in future advanced nanodevices. In this study, the atomistic vapor-solid-liquid growth processes of Sn-catalyzed wurtzite (WZ) and zinc blende (ZB) ZnO are directly revealed based on the in situ transmission electron microscopy. The growth kinetics of WZ and ZB crystal phases in ZnO appear markedly different in terms of the NW-droplet interface, whereas the nucleation site as determined by the contact angle ϕ between the seed particle and the NW is found to be crucial for tuning the NW structure through combined experimental and theoretical investigations. These results offer an atomic-scale view into the dynamic growth process of ZnO NW, which has implications for the phase-controllable synthesis of II-VI compounds and heterostructures with tunable band structures.
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http://dx.doi.org/10.1021/acs.nanolett.8b00420DOI Listing
July 2018

Hydroxycamptothecin mediates antiproliferative effects through apoptosis and autophagy in A549 cells.

Oncol Lett 2018 May 22;15(5):6322-6328. Epub 2018 Feb 22.

Medical Research Center, North China University of Science and Technology, Tangshan, Hebei 063000, P.R. China.

Hydroxycamptothecin (HCPT) represents a new generation of anticancer drugs, with almost no side effects when used for the treatment of a number of types of cancer. Autophagy is becoming recognized as an important biological mechanism in human cancer, including lung cancer. However, the involvement of autophagy in the antiproliferative effects of HCPT on lung cancer remains unclear. In the present study, A549 cells, an accepted model of non-small cell lung cancer (NSCLC) cells, were employed. It was demonstrated that HCPT was able to suppress proliferation and induce apoptosis and autophagy in A549 cells. The molecular mechanism underlying HCPT-induced cell death was attributed to apoptosis and autophagy. Furthermore, it was demonstrated that an autophagy inhibitor, 3-methyladenine, accelerated HCPT-induced cell death in A549 cells. The results of the present study may lead to a deeper understanding of the molecular mechanism by which HCPT regulates NSCLC A549 cells. These results highlight the potential use of autophagy inhibitors in combination with traditional chemotherapy drugs for the treatment of lung cancer.
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http://dx.doi.org/10.3892/ol.2018.8107DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5876437PMC
May 2018

Ensemble Methods with Voting Protocols Exhibit Superior Performance for Predicting Cancer Clinical Endpoints and Providing More Complete Coverage of Disease-Related Genes.

Int J Genomics 2018 10;2018:8124950. Epub 2018 Jan 10.

Biogas Appliance Quality Supervision and Inspection Center, Biogas Institute of Ministry of Agriculture, Chengdu, Sichuan, China.

In genetic data modeling, the use of a limited number of samples for modeling and predicting, especially well below the attribute number, is difficult due to the enormous number of genes detected by a sequencing platform. In addition, many studies commonly use machine learning methods to evaluate genetic datasets to identify potential disease-related genes and drug targets, but to the best of our knowledge, the information associated with the selected gene set was not thoroughly elucidated in previous studies. To identify a relatively stable scheme for modeling limited samples in the gene datasets and reveal the information that they contain, the present study first evaluated the performance of a series of modeling approaches for predicting clinical endpoints of cancer and later integrated the results using various voting protocols. As a result, we proposed a relatively stable scheme that used a set of methods with an ensemble algorithm. Our findings indicated that the ensemble methodologies are more reliable for predicting cancer prognoses than single machine learning algorithms as well as for gene function evaluating. The ensemble methodologies provide a more complete coverage of relevant genes, which can facilitate the exploration of cancer mechanisms and the identification of potential drug targets.
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http://dx.doi.org/10.1155/2018/8124950DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5818887PMC
January 2018

SMG-1 inhibition by miR-192/-215 causes epithelial-mesenchymal transition in gastric carcinogenesis via activation of Wnt signaling.

Cancer Med 2018 01 13;7(1):146-156. Epub 2017 Dec 13.

Department of Pathology, The Shenzhen University School of Medicine, Shenzhen, Guangdong, 518060, China.

SMG-1,a member of the phosphoinositide kinase-like kinase family, functioned as a tumor suppressor gene. However, the role of SMG-1 in GC remain uncharacterized. In this study, regulation of SMG-1 by miR-192 and-215, along with the biological effects of this modulation, were studied in GC. We used gene microarrays to screening and luciferase reporter assays were to verify the potential targets of miR-192 and-215. Tissue microarrays analyses were applied to measure the levels of SMG-1 in GC tissues. Western blot assays were used to assess the signaling pathway of SMG-1 regulated by miR-192 and-215 in GC. SMG-1 was significantly downregulated in GC tissues.The proliferative and invasive properties of GC cells were decreased by inhibition of miR-192 and-215, whereas an SMG-1siRNA rescued the inhibitory effects. Finally, SMG-1 inhibition by miR-192 and-215 primed Wnt signaling and induced EMT. Wnt signaling pathway proteins were decreased markedly by inhibitors of miR-192 and-215, while SMG-1 siRNA reversed the inhibition apparently. Meanwhile, miR-192 and-215 inhitibtors increased E-cadherin expression and decreased N-cadherin and cotransfection of SMG-1 siRNA reversed these effects. In summary, these findings illustrate that SMG-1 is suppressed by miR-192 and-215 and functions as a tumor suppressor in GC by inactivating Wnt signaling and suppressing EMT.
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http://dx.doi.org/10.1002/cam4.1237DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5773975PMC
January 2018

Fibril-Barrel Transitions in Cylindrin Amyloids.

J Chem Theory Comput 2017 Aug 17;13(8):3936-3944. Epub 2017 Jul 17.

Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences , Shenzhen 518055, China.

We introduce Replica-Exchange-with-Tunneling (RET) simulations as a tool for studies of the conversion between polymorphic amyloids. For the 11-residue amyloid-forming cylindrin peptide we show that this technique allows for a more efficient sampling of the formation and interconversion between fibril-like and barrel-like assemblies. We describe a protocol for optimized analysis of RET simulations that allows us to propose a mechanism for formation and interconversion between various cylindrin assemblies. Especially, we show that an interchain salt bridge between residues K3 and D7 is crucial for formation of the barrel structure.
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http://dx.doi.org/10.1021/acs.jctc.7b00383DOI Listing
August 2017