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Dual transcriptomic analysis reveals metabolic changes associated with differential persistence of human pathogenic bacteria in leaves of Arabidopsis and lettuce
- Source :
- G3 (Bethesda, Md.), vol 11, iss 12, G3: Genes|Genomes|Genetics, G3: Genes, Genomes, Genetics, Vol 11, Iss 12 (2021)
- Publication Year :
- 2021
- Publisher :
- eScholarship, University of California, 2021.
-
Abstract
- Understanding the molecular determinants underlying the interaction between the leaf and human pathogenic bacteria is key to provide the foundation to develop science-based strategies to prevent or decrease the pathogen contamination of leafy greens. In this study, we conducted a dual RNA-sequencing analysis to simultaneously define changes in the transcriptomic profiles of the plant and the bacterium when they come in contact. We used an economically relevant vegetable crop, lettuce (Lactuca sativa L. cultivar Salinas), and a model plant, Arabidopsis thaliana Col-0, as well as two pathogenic bacterial strains that cause disease outbreaks associated with fresh produce, Escherichia coli O157:H7 and Salmonella enterica serovar Typhimurium 14028s (STm 14028s). We observed commonalities and specificities in the modulation of biological processes between Arabidopsis and lettuce and between O157:H7 and STm 14028s during early stages of the interaction. We detected a larger alteration of gene expression at the whole transcriptome level in lettuce and Arabidopsis at 24 h post inoculation with STm 14028s compared to that with O157:H7. In addition, bacterial transcriptomic adjustments were substantially larger in Arabidopsis than in lettuce. Bacterial transcriptome was affected at a larger extent in the first 4 h compared to the subsequent 20 h after inoculation. Overall, we gained valuable knowledge about the responses and counter-responses of both bacterial pathogen and plant host when these bacteria are residing in the leaf intercellular space. These findings and the public genomic resources generated in this study are valuable for additional data mining.
- Subjects :
- AcademicSubjects/SCI01140
H7 [Escherichia coli O157]
disease outbreak
AcademicSubjects/SCI00010
Colony Count
Colony Count, Microbial
Arabidopsis
Lactuca
QH426-470
Biology
Escherichia coli O157:H7
medicine.disease_cause
AcademicSubjects/SCI01180
Escherichia coli O157
Transcriptome
Microbial
dual transcriptomic profiling
medicine
Genetics
Arabidopsis thaliana
Humans
2.2 Factors relating to the physical environment
Aetiology
Molecular Biology
Leafy
Genetics (clinical)
Investigation
Prevention
food and beverages
Salmonella enterica
Pathogenic bacteria
Lettuce
biology.organism_classification
Foodborne Illness
Plant Leaves
food safety
Infectious Diseases
Emerging Infectious Diseases
AcademicSubjects/SCI00960
Infection
Bacteria
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- G3 (Bethesda, Md.), vol 11, iss 12, G3: Genes|Genomes|Genetics, G3: Genes, Genomes, Genetics, Vol 11, Iss 12 (2021)
- Accession number :
- edsair.doi.dedup.....a8e16d621ea9d5fe59e3139fdedefc16