Biodiversity of epiphytic Pseudomonas strains isolated from leaves of pepper and lettuce

Rice leaf endophytic Microbacterium testaceum: Antifungal actinobacterium confers immunocompetence against rice blast disease

Genetic and functional characteristics of rice leaf endophytic actinobacterial member, Microbacterium are described. Morphotyping, multilocus sequence analysis and transmission electron microscopy indicated the species identity of the endophytic bacterium, OsEnb-ALM-D18, as Microbacterium testaceum. The endophytic Microbacterium showed probiotic solubilization of plant nutrients/minerals, produced hydrolytic enzyme/phytohormones, and showed endophytism in rice seedlings. Further, the endophytic colonization by M. testaceum OsEnb-ALM-D18 was confirmed using reporter gene coding for green fluorescence protein. Microbacterium OsEnb-ALM-D18 showed volatilome-mediated antibiosis (95.5% mycelial inhibition) on Magnaporthe oryzae. Chemical profiling of M. testaceum OsEnb-ALM-D18 volatilome revealed the abundance of 9-Octadecenoic acid, Hexadecanoic acid, 4-Methyl-2-pentanol, and 2,5-Dihydro-thiophene. Upon endobacterization of rice seedlings, M. testaceum altered shoot and root phenotype suggestive of activated defense. Over 80.0% blast disease severity reduction was observed on the susceptible rice cultivar Pusa Basmati-1 upon foliar spray with M. testaceum. qPCR-based gene expression analysis showed induction of OsCERK1, OsPAD4, OsNPR1.3, and OsFMO1 suggestive of endophytic immunocompetence against blast disease. Moreover, M. testaceum OsEnb-ALM-D18 conferred immunocompetence, and antifungal antibiosis can be the future integrated blast management strategy.

Integrated Metabarcoding and Culturomic-Based Microbiome Profiling of Rice Phyllosphere Reveal Diverse and Functional Bacterial Communities for Blast Disease Suppression

Phyllosphere-the harsh foliar plant part exposed to vagaries of environmental and climatic variables is a unique habitat for microbial communities. In the present work, we profiled the phyllosphere microbiome of the rice plants using 16S rRNA gene amplicon sequencing (hereafter termed metabarcoding) and the conventional microbiological methods (culturomics) to decipher the microbiome assemblage, composition, and their functions such as antibiosis and defense induction against rice blast disease. The blast susceptible rice genotype (PRR78) harbored far more diverse bacterial species (294 species) than the resistant genotype (Pusa1602) that showed 193 species. Our metabarcoding of bacterial communities in phyllomicrobiome revealed the predominance of the phylum, Proteobacteria, and its members Pantoea, Enterobacter, Pseudomonas, and Erwinia on the phyllosphere of both rice genotypes. The microbiological culturomic validation of metabarcoding-taxonomic annotation further confirmed the prevalence of 31 bacterial isolates representing 11 genera and 16 species with the maximum abundance of Pantoea. The phyllomicrobiome-associated bacterial members displayed antifungal activity on rice blast fungus, Magnaporthe oryzae, by volatile and non-volatile metabolites. Upon phyllobacterization of rice cultivar PB1, the bacterial species such as Enterobacter sacchari, Microbacterium testaceum, Pantoea ananatis, Pantoea dispersa, Pantoea vagans, Pseudomonas oryzihabitans, Rhizobium sp., and Sphingomonas sp. elicited a defense response and contributed to the suppression of blast disease. qRT-PCR-based gene expression analysis indicated over expression of defense-associated genes such as OsCEBiP, OsCERK1, and phytohormone-associated genes such as OsPAD4, OsEDS1, OsPR1.1, OsNPR1, OsPDF2.2, and OsFMO in phyllobacterized rice seedlings. The phyllosphere bacterial species showing blast suppressive activity on rice were found non-plant pathogenic in tobacco infiltration assay. Our comparative microbiome interrogation of the rice phyllosphere culminated in the isolation and identification of agriculturally significant bacterial communities for blast disease management in rice farming through phyllomicrobiome engineering in the future.

Transmission Routes of the Microbiome and Resistome from Manure to Soil and Lettuce

The land application of animal manure can introduce manure microbiome and resistome to croplands where food crops are grown. The objective of this study was to characterize the microbiome and resistome on and in the leaves of lettuce grown in manured soil and identify the main transmission routes of microbes and antibiotic resistance genes (ARGs) from soil to the episphere and endosphere of lettuce. Shotgun metagenomic results show that manure application significantly altered the composition of the microbiome and resistome of surface soil. SourceTracker analyses indicate that manure and original soil were the main source of the microbiome and resistome of the surface soil and rhizosphere soil, respectively. Manure application altered the microbiome and resistome in the episphere of lettuce (ADONIS p < 0.05), and surface soil accounted for ∼81% of the microbes and ∼62% of the ARGs in episphere. Manure application had limited impacts on the microbiome and resistome in the endosphere (ADONIS p > 0.05). Our results show that manure-borne microbes and ARGs reached the episphere primarily through surface soil and some epiphytic microbes and ARGs further entered the endosphere. Our findings can inform the development of pre- and postharvest practices to minimize the transmission of manure-borne resistome from food crops to consumers.

Raman Spectroscopy and Machine-Learning for Early Detection of Bacterial Canker of Tomato: The Asymptomatic Disease Condition

Bacterial canker of tomato is caused by Clavibacter michiganensis subsp. michiganensis (Cmm). The disease is highly destructive, because it produces latent asymptomatic infections that favor contagion rates. The present research aims consisted on the implementation of Raman spectroscopy (RS) and machine-learning spectral analysis as a method for the early disease detection. Raman spectra were obtained from infected asymptomatic tomato plants (BCTo) and healthy controls (HTo) with 785 nm excitation laser micro-Raman spectrometer. Spectral data were normalized and processed by principal component analysis (PCA), then the classifiers algorithms multilayer perceptron (PCA + MLP) and linear discriminant analysis (PCA + LDA) were implemented. Bacterial isolation and identification (16S rRNA gene sequencing) were realized of each plant studied. The Raman spectra obtained from tomato leaf samples of HTo and BCTo exhibited peaks associated to cellular components, and the most prominent vibrational bands were assigned to carbohydrates, carotenoids, chlorophyll, and phenolic compounds. Biochemical changes were also detectable in the Raman spectral patterns. Raman bands associated with triterpenoids and flavonoids compounds can be considered as indicators of Cmm infection during the asymptomatic stage. RS is an efficient, fast and reliable technology to differentiate the tomato health condition (BCTo or HTo). The analytical method showed high performance values of sensitivity, specificity and accuracy, among others.