Emergence of apple bacterial quick decline caused by Dickeya dadantii in Japan

Fujikawa, Takashi; Ota, Nobuyoshi; Sasaki, Makoto; Nakamura, Taiki; Iwanami, Toru

doi:10.1007/s10327-019-00852-y

Cited by 9 publications

(10 citation statements)

References 11 publications

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“… Dickeya dadantii is a plant-pathogenic bacterium that causes soft-rot disease in various plants ( 1 ). In addition to being a soft-rot pathogen, it causes quick decline (QD) in fruit trees, such as apple, peach, and Japanese pear trees ( 2 , 3 ). The symptoms of QD include red-brown sap leakage from the trunk and/or branches, softening bark, defoliation, leaf and shoot necrosis, and dieback.…”

Section: Announcementmentioning

confidence: 99%

“…The symptoms of QD include red-brown sap leakage from the trunk and/or branches, softening bark, defoliation, leaf and shoot necrosis, and dieback. When QD pathogens have been identified by biochemical and molecular tests, to date only D. dadantii has been isolated ( 2 , 3 ). However, the life cycle of D. dadantii is not yet well understood.…”

Section: Announcementmentioning

confidence: 99%

“…The strains sequenced in this study were obtained from the Institute of Fruit Tree and Tea Science (National Agriculture and Food Research Organization) ( Table 1 ); they had been isolated from apple, peach, and Japanese pear trees and identified as D. dadantii according to our previous studies ( 2 , 3 ). The strains were cultivated in YP broth ( 2 ) at 27°C for 1 day with agitation at 140 rpm.…”

Section: Announcementmentioning

confidence: 99%

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Draft Genome Sequences of Seven Strains of Dickeya dadantii, a Quick Decline-Causing Pathogen in Fruit Trees, Isolated in Japan

Fujikawa

Hatomi

Ota

2020

Microbiol Resour Announc

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Section: Announcementmentioning

confidence: 99%

Section: Announcementmentioning

confidence: 99%

Section: Announcementmentioning

confidence: 99%

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Draft Genome Sequences of Seven Strains of Dickeya dadantii, a Quick Decline-Causing Pathogen in Fruit Trees, Isolated in Japan

Fujikawa

Hatomi

Ota

2020

Microbiol Resour Announc

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“…Escherichia coli (9), Salmonella enterica (10), Bacillus subtilis (2), Streptococcus pneumoniae (4), Campylobacter jejuni (11), Clostridium beijerinckii (12), Mycobacterium tuberculosis (13), Mycoplasma pneumoniae (14), and the phytopathogen Xanthomonas campestris (15,16), they are still lacking for Dickeya species. This study aims to provide the first comprehensive and annotated transcriptomic map of Dickeya dadantii, a Gram-negative phytopathogenic bacterium representative of the Dickeya genus that causes soft rot, a severe disease leading to tissue maceration and eventually plant death (17) in a wide range of plant hosts worldwide, including agriculturally important crops (18,19,20,21,22).…”

Section: While Transcriptomic Maps Have Been Established For Various Bacteria Includingmentioning

confidence: 99%

“…This severe disease leads to tissue maceration and eventually plant death (4). Dickeya species have received considerable attention in recent years due to their emergence in European and Asian countries where they cause major economic losses by infecting agriculturally important crops such as apple, potato, tomato and carrot (5)(6)(7)(8). Besides, the ability of Dickeya species to colonize various ecological niches such as soil, ground water, surfaces and interior of plant hosts and insects (2,9,10) makes them remarkably versatile models for the scientific community.…”

Section: Introductionmentioning

confidence: 99%

Mapping the complex transcriptional landscape of the phytopathogenic bacteriumDickeya dadantii

Forquet

Jiang

Nasser

et al. 2020

Preprint

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Dickeya dadantii is a phytopathogenic bacterium that causes soft rot in a wide range of plant hosts worldwide and a model organism for studying gene regulation during the pathogenic process. The present study provides a comprehensive and annotated transcriptomic map of D. dadantii obtained by a computational method combining three independent transcriptomic datasets covering a wide range of conditions which closely reproduce the variations of transcription occurring in the course of plant infection: (1) paired-end RNA-seq data for a precise reconstruction of the RNA landscape, (2) DNA microarray data reflecting gene response to sudden environmental shocks mimicking conditions encountered by bacteria in the plant, (3) dRNA-seq data for a specific high-resolution mapping of transcription start sites. We define transcription units throughout the genome, and map the associated transcription start and termination sites with a quantitative magnitude analysis. Our results show that transcription units sometimes coincide with predicted operons but are generally longer, most of them exhibiting internal promoters and terminators that generate alternative transcripts of variable gene composition. We characterize the occurrence of transcriptional read-through at terminators, which might play a basal regulation role and explain the extent of transcription beyond the scale of operons. We finally highlight the presence of noncontiguous operons and excludons in D. dadantii genome, novel genomic arrangements that might contribute to the basal coordination of transcription. The highlighted transcriptional organization may allow D. dadantii finely adjusting its gene expression program for a rapid adaptation to fast changing environment relevant to plant infection. Importance: this is the first transcriptomic map of a phytopathogen, characterized under physiological conditions encountered by the bacteria during the infection process. It might therefore significantly contribute to further progress in the field of phytopathogenicity. Our findings also provide insights into basal rules of coordination of transcription that might be valid for other bacteria, and may raise interest in the field of microbiology in general. In particular, we demonstrate that gene expression is coordinated at the scale of transcription units rather than operons, which are larger functional genomic units capable of generating transcripts with variable gene composition for a fine-tuning of gene expression in response to environmental changes. In line with recent studies, our findings indicate that the canonical operon model is insufficient to explain the complexity of bacterial transcriptomes.

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