Genomic Characterization of  Lactobacillus delbrueckii  TUA4408L and Evaluation of the Antiviral Activities of its Extracellular Polysaccharides in Porcine Intestinal Epithelial Cells

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Abstract

In lactic acid bacteria, the synthesis of exopolysaccharides (EPS) has been associated with some favorable technological properties as well as health-promoting benefits. Research works have shown the potential of EPS produced by lactobacilli to differentially modulate immune responses. However, most studies were performed in immune cells and few works have concentrated in the immunomodulatory activities of EPS in non-immune cells such as intestinal epithelial cells. In addition, the cellular and molecular mechanisms involved in the immunoregulatory effects of EPS have not been studied in detail. In this work, we have performed a genomic characterization of Lactobacillus delbrueckii subsp. delbrueckii TUA4408L and evaluated the immunomodulatory and antiviral properties of its acidic (APS) and neutral (NPS) EPS in porcine intestinal epithelial (PIE) cells. Whole genome sequencing allowed the analysis of the general features of L. delbrueckii TUA4408L genome as well as the characterization of its EPS genes. A typical EPS gene cluster was found in the TUA4408L genome consisting in five highly conserved genes epsA- E, and a variable region, which includes the genes for the polymerase wzy, the flippase wzx, and seven glycosyltransferases. In addition, we demonstrated here for the first time that L. delbrueckii TUA4408L and its EPS are able to improve the resistance of PIE cells against rotavirus infection by reducing viral replication and regulating inflammatory response. Moreover, studies in PIE cells demonstrated that the TUA4408L strain and its EPS differentially modulate the antiviral innate immune response triggered by the activation of Toll-like receptor 3 (TLR3). L. delbrueckii TUA4408L and its EPS are capable of increasing the activation of interferon regulatory factor (IRF)-3 and nuclear factor κB (NF-κB) signaling pathways leading to an improved expression of the antiviral factors interferon (IFN)-β, Myxovirus resistance gene A (MxA) and RNaseL.

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Most cited references 31

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IslandViewer 4: expanded prediction of genomic islands for larger-scale datasets

Claire Bertelli, Matthew Laird, Kelly P. Williams … (2017)

Abstract IslandViewer (http://www.pathogenomics.sfu.ca/islandviewer/) is a widely-used webserver for the prediction and interactive visualization of genomic islands (GIs, regions of probable horizontal origin) in bacterial and archaeal genomes. GIs disproportionately encode factors that enhance the adaptability and competitiveness of the microbe within a niche, including virulence factors and other medically or environmentally important adaptations. We report here the release of IslandViewer 4, with novel features to accommodate the needs of larger-scale microbial genomics analysis, while expanding GI predictions and improving its flexible visualization interface. A user management web interface as well as an HTTP API for batch analyses are now provided with a secured authentication to facilitate the submission of larger numbers of genomes and the retrieval of results. In addition, IslandViewer's integrated GI predictions from multiple methods have been improved and expanded by integrating the precise Islander method for pre-computed genomes, as well as an updated IslandPath-DIMOB for both pre-computed and user-supplied custom genome analysis. Finally, pre-computed predictions including virulence factors and antimicrobial resistance are now available for 6193 complete bacterial and archaeal strains publicly available in RefSeq. IslandViewer 4 provides key enhancements to facilitate the analysis of GIs and better understand their role in the evolution of successful environmental microbes and pathogens.

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ARDB—Antibiotic Resistance Genes Database

Bo Liu, Mihai Pop (2009)

The treatment of infections is increasingly compromised by the ability of bacteria to develop resistance to antibiotics through mutations or through the acquisition of resistance genes. Antibiotic resistance genes also have the potential to be used for bio-terror purposes through genetically modified organisms. In order to facilitate the identification and characterization of these genes, we have created a manually curated database—the Antibiotic Resistance Genes Database (ARDB)—unifying most of the publicly available information on antibiotic resistance. Each gene and resistance type is annotated with rich information, including resistance profile, mechanism of action, ontology, COG and CDD annotations, as well as external links to sequence and protein databases. Our database also supports sequence similarity searches and implements an initial version of a tool for characterizing common mutations that confer antibiotic resistance. The information we provide can be used as compendium of antibiotic resistance factors as well as to identify the resistance genes of newly sequenced genes, genomes, or metagenomes. Currently, ARDB contains resistance information for 13 293 genes, 377 types, 257 antibiotics, 632 genomes, 933 species and 124 genera. ARDB is available at http://ardb.cbcb.umd.edu/.

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Selection of reference genes for gene expression studies in pig tissues using SYBR green qPCR

Ann-Britt Nygard, Claus Jørgensen, Susanna Cirera … (2007)

Background Real-time quantitative PCR (qPCR) is a method for rapid and reliable quantification of mRNA transcription. Internal standards such as reference genes are used to normalise mRNA levels between different samples for an exact comparison of mRNA transcription level. Selection of high quality reference genes is of crucial importance for the interpretation of data generated by real-time qPCR. Results In this study nine commonly used reference genes were investigated in 17 different pig tissues using real-time qPCR with SYBR green. The genes included beta-actin (ACTB), beta-2-microglobulin (B2M), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), hydroxymethylbilane synthase (HMBS), hypoxanthine phosphoribosyltransferase 1 (HPRT1), ribosomal protein L4 (RPL4), succinate dehydrogenase complex subunit A (SDHA), TATA box binding protein (TPB)and tyrosine 3-monooxygenase/tryptophan 5-monooxygenase activation protein zeta polypeptide (YWHAZ). The stability of these reference genes in different pig tissues was investigated using the geNorm application. The range of expression stability in the genes analysed was (from the most stable to the least stable): ACTB/RPL4, TBP, HPRT, HMBS, YWHAZ, SDHA, B2M and GAPDH. Conclusion Expression stability varies greatly between genes. ACTB, RPL4, TPB and HPRT1 were found to have the highest stability across tissues. Based on both expression stability and expression level, our data suggest that ACTB and RPL4 are good reference genes for high abundant transcripts while TPB and HPRT1 are good reference genes for low abundant transcripts in expression studies across different pig tissues.

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Author and article information

Contributors

Paulraj Kanmani: URI : http://loop.frontiersin.org/people/383917/overview

Leonardo Albarracin: URI : http://loop.frontiersin.org/people/376689/overview

Elvira Maria Hebert: URI : http://loop.frontiersin.org/people/337335/overview

Hisashi Aso: URI : http://loop.frontiersin.org/people/180257/overview

Hideki Takahashi: URI : http://loop.frontiersin.org/people/49188/overview

Julio Villena: URI : http://loop.frontiersin.org/people/121873/overview

Haruki Kitazawa: URI : http://loop.frontiersin.org/people/101625/overview

Journal

Journal ID (nlm-ta): Front Immunol

Journal ID (iso-abbrev): Front Immunol

Journal ID (publisher-id): Front. Immunol.

Title: Frontiers in Immunology

Publisher: Frontiers Media S.A.

ISSN (Electronic): 1664-3224

Publication date (Electronic): 24 September 2018

Publication date Collection: 2018

Volume: 9

Electronic Location Identifier: 2178

Affiliations

[1] ¹Food and Feed Immunology Group, Laboratory of Animal Products Chemistry, Graduate School of Agricultural Science, Tohoku University , Sendai, Japan

[2] ²Livestock Immunology Unit, International Education and Research Center for Food Agricultural Immunology (CFAI), Graduate School of Agricultural Science, Tohoku University , Sendai, Japan

[3] ³Reference Centre for Lactobacilli (CERELA-CONICET) , Tucuman, Argentina

[4] ⁴Scientific Computing Laboratory, Computer Science Department, Faculty of Exact Sciences and Technology, National University of Tucuman , Tucuman, Argentina

[5] ⁵Department of Pharmacology, University of Concepcion , Concepcion, Chile

[6] ⁶Viral Diseases and Epidemiology Research Division, National Institute of Animal Health, NARO , Tsukuba, Japan

[7] ⁷Department of Food, Agriculture, and Environment, Miyagi University , Sendai, Japan

[8] ⁸Cell Biology Laboratory, Graduate School of Agricultural Science, Tohoku University , Sendai, Japan

[9] ⁹Research & Development Division, Marusan-Ai Co., Ltd. , Okazaki, Japan

[10] ¹⁰Graduate School of Regional Innovation Studies, Mie University , Tsu, Japan

[11] ¹¹Laboratory of Plant Pathology, Graduate School of Agricultural Science, Tohoku University , Sendai, Japan

[12] ¹²Plant Immunology Unit, International Education and Research Center for Food Agricultural Immunology (CFAI), Graduate School of Agricultural Science, Tohoku University , Sendai, Japan

Author notes

Edited by: Willem Van Eden, Utrecht University, Netherlands

Reviewed by: Christine Jansen, Utrecht University, Netherlands; Huub Savelkoul, Wageningen University & Research, Netherlands

*Correspondence: Haruki Kitazawa haruki.kitazawa.c7@ 123456tohoku.ac.jp

Julio Villena jcvillena@ 123456cerela.org.ar

This article was submitted to Nutritional Immunology, a section of the journal Frontiers in Immunology

†These authors have contributed equally to this work

Article

DOI: 10.3389/fimmu.2018.02178

PMC ID: 6165883

PubMed ID: 30319634

SO-VID: 02d7ae4e-5a03-49c6-a1f3-8f1db31b7fb6

License:

This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

History

Date received : 11 April 2018

Date accepted : 03 September 2018

Page count

Figures: 8, Tables: 1, Equations: 0, References: 47, Pages: 16, Words: 10770

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Genomic Characterization of Lactobacillus delbrueckii TUA4408L and Evaluation of the Antiviral Activities of its Extracellular Polysaccharides in Porcine Intestinal Epithelial Cells

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Most cited references 31

IslandViewer 4: expanded prediction of genomic islands for larger-scale datasets

ARDB—Antibiotic Resistance Genes Database

Selection of reference genes for gene expression studies in pig tissues using SYBR green qPCR

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