Literature DB >> 33128615

Comparative genomic analysis reveals metabolic diversity of different Paenibacillus groups.

Wen-Cong Huang1, Yilun Hu2,3, Gengxin Zhang4,5, Meng Li6.   

Abstract

The genus Paenibacillus was originally recognized based on the 16S rRNA gene phylogeny. Recently, a standardized bacterial taxonomy approach based on a genome phylogeny has substantially revised the classification of Paenibacillus, dividing it into 23 genera. However, the metabolic differences among these groups remain undescribed. Here, genomes of 41 Paenibacillus strains comprising 25 species were sequenced, and a comparative genomic analysis was performed considering these and 187 publicly available Paenibacillus genomes to understand their phylogeny and metabolic differences. Phylogenetic analysis indicated that Paenibacillus clustered into 10 subgroups. Core genome and pan-genome analyses revealed similar functional categories among the different Paenibacillus subgroups; however, each group tended to harbor specific gene families. A large proportion of genes in the subgroups A, E, and G are related to carbohydrate metabolism. Among them, genes related to the glycoside hydrolase family were most abundant. Metabolic reconstruction of the newly sequenced genomes showed that the Embden-Meyerhof-Parnas pathway, pentose phosphate pathway, and citric acid cycle are central pathways of carbohydrate metabolism in Paenibacillus. Further, the genomes of the subgroups A and G lack genes involved in glyoxylate cycle and D-galacturonate degradation, respectively. The current study revealed the metabolic diversity of Paenibacillus subgroups assigned based on a genomic phylogeny and could inform the taxonomy of Paenibacillus. KEY POINTS: • Paenibacillus clustered into 10 subgroups. • Genomic content variation and metabolic diversity in the subgroup A, E, and G were described. • Carbohydrate transport and metabolism is important for Paenibacillus survival.

Entities:  

Keywords:  CAZymes; Metabolism; Paenibacillus; Pan-genome; Phylogeny

Mesh:

Substances:

Year:  2020        PMID: 33128615     DOI: 10.1007/s00253-020-10984-3

Source DB:  PubMed          Journal:  Appl Microbiol Biotechnol        ISSN: 0175-7598            Impact factor:   4.813


  40 in total

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Journal:  Science       Date:  2006-03-03       Impact factor: 47.728

4.  Perisynaptic satellite cells in human external intercostal muscle: a quantitative and qualitative study.

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5.  Urinary MHPG: improved tricyclic antidepressant drug selection in clinical practice.

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Journal:  Med J Aust       Date:  1979-09-08       Impact factor: 7.738

6.  Role of Glyoxylate Shunt in Oxidative Stress Response.

Authors:  Sungeun Ahn; Jaejoon Jung; In-Ae Jang; Eugene L Madsen; Woojun Park
Journal:  J Biol Chem       Date:  2016-04-01       Impact factor: 5.157

7.  An emerging phylogenetic core of Archaea: phylogenies of transcription and translation machineries converge following addition of new genome sequences.

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Journal:  BMC Evol Biol       Date:  2005-06-02       Impact factor: 3.260

8.  OrthoFinder: phylogenetic orthology inference for comparative genomics.

Authors:  David M Emms; Steven Kelly
Journal:  Genome Biol       Date:  2019-11-14       Impact factor: 13.583

9.  Comparative and genetic analysis of the four sequenced Paenibacillus polymyxa genomes reveals a diverse metabolism and conservation of genes relevant to plant-growth promotion and competitiveness.

Authors:  Alexander W Eastman; David E Heinrichs; Ze-Chun Yuan
Journal:  BMC Genomics       Date:  2014-10-03       Impact factor: 3.969

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  2 in total

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Authors:  Ke Ma; Wei Chen; Shi-Qing Yan; Xiao-Qi Lin; Zhen-Zhen Liu; Jia-Bao Zhang; Yu Gao; Yong-Jun Yang
Journal:  BMC Genomics       Date:  2022-05-19       Impact factor: 4.547

2.  Occurrence of phenotypic variation in Paenibacillus polymyxa E681 associated with sporulation and carbohydrate metabolism.

Authors:  Younmi Lee; Kotnala Balaraju; Soon-Young Kim; Yongho Jeon
Journal:  Biotechnol Rep (Amst)       Date:  2022-03-14
  2 in total

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