Gga-miR-30d regulates infectious bronchitis virus infection by targeting USP47 in HD11 cells

Li, Hao; Li, Jianan; Zhai, Yan; Zhang, Lan; Cui, Pengfei; Feng, Lan; Yan, Wenjun; Xue, Fu Shan; Tian, Yiming; Wang, Hongning; Yang, Xin

doi:10.1016/j.micpath.2020.103998

Cited by 17 publications

(22 citation statements)

References 31 publications

(36 reference statements)

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“…MicroRNAs (miRNAs), as 19-22 nucleotide non-coding RNAs, involve in multiple important biological processes by binding partially complementary sequences of its target gene mRNA 3'-untanslated region (3'-UTR) and repressing target gene functions. Many studies have demonstrated that miRNAs play important roles in resisting kinds of disease in birds, like Marek's disease virus, avian in uenza virus, bursal disease virus and others virus infection [6][7][8]. Our previous studies have also highlighted the critical role of miRNAs during MG-HS (Mycoplasma gallisepticum-Huangshi) infection in lung tissue of chicken embryo, including miR-19a, miR-130b-3p, miR-451 ect [9][10][11][12][13].…”

Section: Introductionmentioning

confidence: 88%

Exosomal miR-181a-5p Protects against MG Infection by Targeting PPM1B and Activating the TLR2-Mediated MyD88/NF-κB Pathway

Sun¹,

Zhao²,

Pang³

et al. 2020

Preprint

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BackgroundMycoplasma gallisepticum (MG) is one of the most important pathogens that causes chronic respiratory disease (CRD) in chickens. Exosomes secreted from cells have been well documented to deliver miRNAs to recipient cells to modulate cellular function. The purpose of this current study was to explore the functions of exosomal miR-181a-5p in MG infection and the underlying mechanisms. ResultsHere, we found that miR-181a-5p expression in vivo and in vitro was significantly upregulated after MG infection. Exosomes enriched in MG-infected chicken type-II pneumocytes (CP-II) could selectively load miR-181a-5p and transfer it into recipient DF-1 cells. PPM1B was further identified as the target gene of miR-181a-5p. Overexpression of miR-181a-5p and/or knockdown of PPM1B activated the TLR2-mediated MyD88/NF-κB signaling pathways, whereas inhibition of miR-181a-5p and the overexpression of PPM1B led to the opposite results. In addition, depressing miR-181a-5p significantly reduced the expression of tumor necrosis factors alpha (TNF-α) and interleukin-1β (IL-1β) by MG-induced. Upregulated miR-181a-5p promoted cell proliferation and cell cycle progression and inhibited apoptosis to resist MG infection. Moreover, overexpression of miR-181a-5p significantly depressed pMAG1.2 expression by directly inhibiting PPM1B.ConclusionsTaken together, we conclude that the newly identified primary CP-II cells exosomal miR-181a-5p activates the TLR2-mediated MyD88/NF-κB pathway by directly targeting PPM1B to promote pro-inflammatory cytokines expression for defending against MG infection in recipient DF-1 cells.

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Section: Introductionmentioning

confidence: 88%

Exosomal miR-181a-5p Protects against MG Infection by Targeting PPM1B and Activating the TLR2-Mediated MyD88/NF-κB Pathway

Sun¹,

Zhao²,

Pang³

et al. 2020

Preprint

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“…As a predicted DEmiRNA by sequence analysis, miR-146a-5p was also found to promote IBV replication of by targeting tumor necrosis factor receptor superfamily member 18 (TNFRSF18) and IL-1 receptor associated kinase-2 (IRAK2) [120]. As another DEmiRNA, miR-30d was showed to inhibit IBV replication through suppressing ubiquitin-specific protease 47 (USP47) in HD11 (avian macrophage-like cells) cells [121].…”

Section: Ncrnas Involved In Infectious Bronchitis Virus (Ibv) Infectionmentioning

confidence: 98%

“…miRNAs can regulate various aspects of immune response process. In avian, some specific miRNAs were identified to be differentially expressed in many different types of chicken diseases from virus, parasite, and bacteria, such as miR-155 [68,110,141,142], miR-221/222 [60,83,119,138], miR-130 [59,90,109], miR-30 [121,152,155], miR-34 [59,63,132,154,163], let-7 [57,81,155], miR-181 [77,134,155], miR-16 [80,115], miR-455 [125,134,155], etc. It indicated their extensive roles in regulating avian immunity.…”

Section: Ncrnas and Salmonella Typhimuriummentioning

confidence: 99%

Epigenetic Regulation by Non-Coding RNAs in the Avian Immune System

Chen

Abdalla

et al. 2020

Life

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The identified non-coding RNAs (ncRNAs) include circular RNAs, long non-coding RNAs, microRNAs, ribosomal RNAs, small interfering RNAs, small nuclear RNAs, piwi-interacting RNAs, and transfer RNAs, etc. Among them, long non-coding RNAs, circular RNAs, and microRNAs are regulatory RNAs that have different functional mechanisms and were extensively participated in various biological processes. Numerous research studies have found that circular RNAs, long non-coding RNAs, and microRNAs played their important roles in avian immune system during the infection of parasites, virus, or bacterium. Here, we specifically review and expand this knowledge with current advances of circular RNAs, long non-coding RNAs, and microRNAs in the regulation of different avian diseases and discuss their functional mechanisms in response to avian diseases.

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“…VP35 is a virus protein of the other highly infectious disease Ebola [31]. HD11, also known as Homeobox protein, is known for regulating infectious diseases such as Avian infectious bronchitis virus (IBV) [32] that is in the coronavirus family. Pulmonary coronavirus infection was grouped in cluster #1 and has the closest associations with gene PTP (protein tyrosine phosphatase), which has been mentioned in SARS-CoV replication inhibition studies [33].…”

Section: Qualitative Evaluationmentioning

confidence: 99%

Constructing co-occurrence network embeddings to assist association extraction for COVID-19 and other coronavirus infectious diseases

Oniani

Jiang

Liu

et al. 2020

Journal of the American Medical Informatics Association

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Objective As COVID-19 started its rapid emergence and gradually transformed into an unprecedented pandemic, the need for having a knowledge repository for the disease became crucial. To address this issue, a new COVID-19 machine readable dataset known as COVID-19 Open Research Dataset (CORD-19) has been released. Based on this, our objective was to build a computable co-occurrence network embeddings to assist association detection amongst COVID-19 related biomedical entities. Materials and Methods Leveraging a Linked Data version of CORD-19 (i.e., CORD-19-on-FHIR), we first utilized SPARQL to extract co-occurrences among chemicals, diseases, genes, and mutations and build a co-occurrence network. We then trained the representation of the derived co-occurrence network using node2vec with four edge embeddings operations (L1, L2, Average, and Hadamard). Six algorithms (Decision Tree, Linear Regression, Support Vector Machine, Random Forest, Naive Bayes, and Multi-layer Perceptron) were applied to evaluate performance on link prediction. An unsupervised learning strategy was also developed incorporating the t-SNE and DBSCAN algorithms for case studies. Results Random Forest classifier showed the best performance on link prediction across different network embeddings. For edge embeddings generated using the Average operation, Random Forest achieved the optimal average precision of 0.97 and F1 score of 0.90. For unsupervised learning, 63 clusters were formed with silhouette score of 0.128. Significant associations were detected for five coronavirus infectious diseases in their corresponding subgroups. Conclusion In this study, we constructed COVID-19-centered co-occurrence network embeddings. Results indicated that the generated embeddings were able to extract significant associations for COVID-19 and coronavirus infectious diseases.

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Gga-miR-30d regulates infectious bronchitis virus infection by targeting USP47 in HD11 cells

Cited by 17 publications

References 31 publications

Exosomal miR-181a-5p Protects against MG Infection by Targeting PPM1B and Activating the TLR2-Mediated MyD88/NF-κB Pathway

Exosomal miR-181a-5p Protects against MG Infection by Targeting PPM1B and Activating the TLR2-Mediated MyD88/NF-κB Pathway

Epigenetic Regulation by Non-Coding RNAs in the Avian Immune System

Constructing co-occurrence network embeddings to assist association extraction for COVID-19 and other coronavirus infectious diseases

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