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

Xiaoyue Chen,Qun Gao,Xumin Ou,Shaqiu Zhang,Qiao Yang,Ling Zhang,Mujeeb Ur Rehman,Mingshu Wang,Bin Tian,Xinxin Zhao,Mafeng Liu,Renyong Jia,Ji‐Bin Liu ,Dekang Zhu,Sai Mao,Anchun Cheng,Xingjian Wen,Ying Wu,Leichang Pan,Shun Chen,Yunya Liu,Juan Huang,Yanling Yu

doi:10.1038/s41598-020-79733-w

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.

Highlights

Riemerella anatipestifer (RA) is a Gram-negative pathogen with a capsule and belongs to the family of Flavobacteriaceae
To find more intracellular metabolites in RA, a non-target metabolomics approach was used for RA metabolic profiling
Metabolomics is a group of indicators for high-throughput detection and data processing, dynamic metabolic changes in the overall, especially for intercellular metabolism, genetic variation and environmental changes

Summary

Introduction

Riemerella anatipestifer (RA) is a Gram-negative pathogen with a capsule and belongs to the family of Flavobacteriaceae. As biological scientific technology advances, high-throughput data has reshaped many approaches to studying the biology of an organism For model organisms such as E. coli, the combination of genomics, proteomics and metabolomics are a critical supplement to biology and p hysiology[34]. This study is the first to report a reconstructed genome-scale metabolic model for RA based on the available genomics and metabolomics data. We believe these data sets of RA further illustrate the use of metabolic profiling as an additional tool and offer some important insights into metabolism

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Conclusion