Literature DB >> 33436670

Comparative genomics and metabolomics analysis of Riemerella anatipestifer strain CH-1 and CH-2.

Jibin Liu1,2,3, Anchun Cheng4,5,6, Mingshu Wang7,8,9, Mafeng Liu1,2,3, Dekang Zhu2,3, Qiao Yang1,2,3, Ying Wu1,2,3, Renyong Jia1,2,3, Shun Chen1,2,3, Xinxin Zhao1,2,3, Shaqiu Zhang1,2,3, Juan Huang1,2,3, Xumin Ou1,2,3, Sai Mao1,2,3, Qun Gao1,2,3, Xingjian Wen1,2,3, Ling Zhang1,2,3, Yunya Liu1,2,3, Yanling Yu1,2,3, Bin Tian1,3, Leichang Pan1,3, Mujeeb Ur Rehman1,3, Xiaoyue Chen2,3.   

Abstract

Riemerella anatipestifer is a major pathogenic microorganism in poultry causing serositis with significant mortality. Serotype 1 and 2 were most pathogenic, prevalent, and liable over the world. In this study, the intracellular metabolites in R. anatipestifer strains RA-CH-1 (serotype 1) and RA-CH-2 (serotype 2) were identified by gas chromatography-mass spectrometer (GC-MS). The metabolic profiles were performed using hierarchical clustering and partial least squares discriminant analysis (PLS-DA). The results of hierarchical cluster analysis showed that the amounts of the detected metabolites were more abundant in RA-CH-2. RA-CH-1 and RA-CH-2 were separated by the PLS-DA model. 24 potential biomarkers participated in nine metabolisms were contributed predominantly to the separation. Based on the complete genome sequence database and metabolite data, the first large-scale metabolic models of iJL463 (RA-CH-1) and iDZ470 (RA-CH-2) were reconstructed. In addition, we explained the change of purine metabolism combined with the transcriptome and metabolomics data. The study showed that it is possible to detect and differentiate between these two organisms based on their intracellular metabolites using GC-MS. The present research fills a gap in the metabolomics characteristics of R. anatipestifer.

Entities:  

Year:  2021        PMID: 33436670      PMCID: PMC7804117          DOI: 10.1038/s41598-020-79733-w

Source DB:  PubMed          Journal:  Sci Rep        ISSN: 2045-2322            Impact factor:   4.379


  75 in total

1.  Pathway Activity Profiling (PAPi): from the metabolite profile to the metabolic pathway activity.

Authors:  Raphael B M Aggio; Katya Ruggiero; Silas Granato Villas-Bôas
Journal:  Bioinformatics       Date:  2010-10-06       Impact factor: 6.937

2.  Double-check: validation of diagnostic statistics for PLS-DA models in metabolomics studies.

Authors:  Ewa Szymańska; Edoardo Saccenti; Age K Smilde; Johan A Westerhuis
Journal:  Metabolomics       Date:  2011-07-08       Impact factor: 4.290

3.  Cold glycerol-saline: the promising quenching solution for accurate intracellular metabolite analysis of microbial cells.

Authors:  Silas G Villas-Bôas; Per Bruheim
Journal:  Anal Biochem       Date:  2007-06-22       Impact factor: 3.365

4.  Dynamic modeling of Escherichia coli metabolic and regulatory systems for amino-acid production.

Authors:  Yoshihiro Usuda; Yosuke Nishio; Shintaro Iwatani; Stephen J Van Dien; Akira Imaizumi; Kazutaka Shimbo; Naoko Kageyama; Daigo Iwahata; Hiroshi Miyano; Kazuhiko Matsui
Journal:  J Biotechnol       Date:  2010-02-26       Impact factor: 3.307

5.  Identification of a wza-like gene involved in capsule biosynthesis, pathogenicity and biofilm formation in Riemerella anatipestifer.

Authors:  Haibo Yi; Biao Yuan; Jibin Liu; Dekang Zhu; Ying Wu; Mingshu Wang; Renyong Jia; Kunfeng Sun; Qiao Yang; Shun Chen; Mafeng Liu; Xiaoyue Chen; Anchun Cheng
Journal:  Microb Pathog       Date:  2017-04-22       Impact factor: 3.738

6.  Development and application of specific polymerase chain reaction assay targeting the gyrB gene for rapid detection of Riemerella anatipestifer.

Authors:  X P Wang; D K Zhu; M S Wang; A C Cheng; R Y Jia; S Chen; X Y Chen; T Tang
Journal:  Poult Sci       Date:  2012-10       Impact factor: 3.352

7.  Identification of ribosomal RNA methyltransferase gene ermF in Riemerella anatipestifer.

Authors:  Hongyan Luo; Mafeng Liu; Lanying Wang; Wangshu Zhou; Mingshu Wang; Anchun Cheng; Renyong Jia; Shun Chen; Kunfeng Sun; Qiao Yang; Xiaoyue Chen; Dekang Zhu
Journal:  Avian Pathol       Date:  2015-04-02       Impact factor: 3.378

Review 8.  Bacterial Metabolism Shapes the Host-Pathogen Interface.

Authors:  Karla D Passalacqua; Marie-Eve Charbonneau; Mary X D O'Riordan
Journal:  Microbiol Spectr       Date:  2016-06

9.  Cas1 and Cas2 From the Type II-C CRISPR-Cas System of Riemerella anatipestifer Are Required for Spacer Acquisition.

Authors:  Yang He; Mingshu Wang; Mafeng Liu; Li Huang; Chaoyue Liu; Xin Zhang; Haibo Yi; Anchun Cheng; Dekang Zhu; Qiao Yang; Ying Wu; Xinxin Zhao; Shun Chen; Renyong Jia; Shaqiu Zhang; Yunya Liu; Yanling Yu; Ling Zhang
Journal:  Front Cell Infect Microbiol       Date:  2018-06-12       Impact factor: 5.293

10.  The SEED and the Rapid Annotation of microbial genomes using Subsystems Technology (RAST).

Authors:  Ross Overbeek; Robert Olson; Gordon D Pusch; Gary J Olsen; James J Davis; Terry Disz; Robert A Edwards; Svetlana Gerdes; Bruce Parrello; Maulik Shukla; Veronika Vonstein; Alice R Wattam; Fangfang Xia; Rick Stevens
Journal:  Nucleic Acids Res       Date:  2013-11-29       Impact factor: 16.971

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