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PLoS Pathogens Aug 2019Necrotrophic plant pathogens acquire nutrients from dead plant cells, which requires the disintegration of the plant cell wall and tissue structures by the pathogen....
Necrotrophic plant pathogens acquire nutrients from dead plant cells, which requires the disintegration of the plant cell wall and tissue structures by the pathogen. Infected plants lose tissue integrity and functional immunity as a result, exposing the nutrient rich, decayed tissues to the environment. One challenge for the necrotrophs to successfully cause secondary infection (infection spread from an initially infected plant to the nearby uninfected plants) is to effectively utilize nutrients released from hosts towards building up a large population before other saprophytes come. In this study, we observed that the necrotrophic pathogen Dickeya dadantii exhibited heterogeneity in bacterial cell length in an isogenic population during infection of potato tuber. While some cells were regular rod-shape (<10μm), the rest elongated into filamentous cells (>10μm). Short cells tended to occur at the interface of healthy and diseased tissues, during the early stage of infection when active attacking and killing is occurring, while filamentous cells tended to form at a later stage of infection. Short cells expressed all necessary virulence factors and motility, whereas filamentous cells did not engage in virulence, were non-mobile and more sensitive to environmental stress. However, compared to the short cells, the filamentous cells displayed upregulated metabolic genes and increased growth, which may benefit the pathogens to build up a large population necessary for the secondary infection. The segregation of the two subpopulations was dependent on differential production of the alarmone guanosine tetraphosphate (ppGpp). When exposed to fresh tuber tissues or freestanding water, filamentous cells quickly transformed to short virulent cells. The pathogen adaptation of cell length heterogeneity identified in this study presents a model for how some necrotrophs balance virulence and vegetative growth to maximize fitness during infection.
Topics: Bacterial Proteins; Cell Wall; Enterobacteriaceae; Gene Expression Regulation, Bacterial; Guanosine Tetraphosphate; Host-Pathogen Interactions; Plant Diseases; Solanum tuberosum; Virulence; Virulence Factors
PubMed: 31381590
DOI: 10.1371/journal.ppat.1007703 -
Nucleic Acids Research Sep 2019Small non-coding RNAs (sRNAs) regulate numerous cellular processes in all domains of life. Several approaches have been developed to identify them from RNA-seq data,...
Small non-coding RNAs (sRNAs) regulate numerous cellular processes in all domains of life. Several approaches have been developed to identify them from RNA-seq data, which are efficient for eukaryotic sRNAs but remain inaccurate for the longer and highly structured bacterial sRNAs. We present APERO, a new algorithm to detect small transcripts from paired-end bacterial RNA-seq data. In contrast to previous approaches that start from the read coverage distribution, APERO analyzes boundaries of individual sequenced fragments to infer the 5' and 3' ends of all transcripts. Since sRNAs are about the same size as individual fragments (50-350 nucleotides), this algorithm provides a significantly higher accuracy and robustness, e.g., with respect to spontaneous internal breaking sites. To demonstrate this improvement, we develop a comparative assessment on datasets from Escherichia coli and Salmonella enterica, based on experimentally validated sRNAs. We also identify the small transcript repertoire of Dickeya dadantii including putative intergenic RNAs, 5' UTR or 3' UTR-derived RNA products and antisense RNAs. Comparisons to annotations as well as RACE-PCR experimental data confirm the precision of the detected transcripts. Altogether, APERO outperforms all existing methods in terms of sRNA detection and boundary precision, which is crucial for comprehensive genome annotations. It is freely available as an open source R package on https://github.com/Simon-Leonard/APERO.
Topics: Algorithms; Datasets as Topic; Enterobacteriaceae; Escherichia coli; Genome, Bacterial; High-Throughput Nucleotide Sequencing; Internet; RNA, Antisense; RNA, Bacterial; RNA, Messenger; RNA, Small Untranslated; Salmonella enterica; Sequence Analysis, RNA; Software
PubMed: 31147705
DOI: 10.1093/nar/gkz485 -
Environmental Microbiology Aug 2019Dickeya dadantii is a plant pathogen that causes soft rot disease on vegetable and potato crops. To successfully cause infection, this pathogen needs to coordinately...
Dickeya dadantii is a plant pathogen that causes soft rot disease on vegetable and potato crops. To successfully cause infection, this pathogen needs to coordinately modulate the expression of genes encoding several virulence determinants, including plant cell wall degrading enzymes (PCWDEs), type III secretion system (T3SS) and flagellar motility. Here, we uncover a novel feed-forward signalling circuit for controlling virulence. Global RNA chaperone Hfq interacts with an Hfq-dependent sRNA ArcZ and represses the translation of pecT, encoding a LysR-type transcriptional regulator. We demonstrate that the ability of ArcZ to be processed to a 50 nt 3'- end fragment is essential for its regulation of pecT. PecT down-regulates PCWDE and the T3SS by repressing the expression of a global post-transcriptional regulator- (RsmA-) associated sRNA encoding gene rsmB. In addition, we show that the protein levels of two cyclic di-GMP (c-di-GMP) diguanylate cyclases (DGCs), GcpA and GcpL, are repressed by Hfq. Further studies show that both DGCs are essential for the Hfq-mediated post-transcriptional regulation on RsmB. Overall, our report provides new insights into the interplays between ubiquitous signalling transduction systems that were most studied independently and sheds light on multitiered regulatory mechanisms for a precise disease regulation in bacteria.
Topics: Bacterial Proteins; Cell Wall; Cyclic GMP; Enterobacteriaceae; Gene Expression Regulation, Bacterial; Plant Diseases; RNA, Bacterial; RNA, Small Untranslated; RNA-Binding Proteins; Signal Transduction; Type III Secretion Systems; Virulence; Virulence Factors
PubMed: 30895662
DOI: 10.1111/1462-2920.14603