DNA methylation dynamics in response to abiotic and pathogen stress in plants

Plant Cell Reports, Journal Year: 2022, Volume and Issue: 41(10), P. 1931 - 1944

Published: July 14, 2022

Language: Английский

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Composition identification and functional verification of bacterial community in disease‐suppressive soils by machine learning

Environmental Microbiology, Journal Year: 2022, Volume and Issue: 24(8), P. 3405 - 3419

Published: Jan. 20, 2022

It has been widely reported that probiotic consortia in the rhizosphere can enhance plant resistance to pathogens. However, general composition and functional profiles of bacterial community soils which suppress multiple diseases for various plants remain largely unknown. Here, we combined metadata analysis with machine learning identify patterns bacterial-community disease-suppressive soils. Disease-suppressive significantly enriched Firmicutes Actinobacteria but showed a decrease Proteobacteria Bacteroidetes. Our machine-learning models accurately identified disease-conducive -suppressive 54 biomarker genera, 28 were potentially beneficial. We further carried out successive passaging experiment susceptible rps2 mutant Arabidopsis thaliana invaded by Pseudomonas syringae pv. tomato DC3000 (avrRpt2) verification potential beneficial bacteria. The ability Kribbella, Nocardioides Bacillus was confirmed, they positively activated pathogen-associated molecular patterns-triggered immunity pathway. Results also chemical control pesticides agricultural production decreased soil. This study provides method predicting occurrence soil bacteria guide wide range multiple-strain biological strategies management.

Language: Английский

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Machine Learning for Plant Stress Modeling: A Perspective towards Hormesis Management

Plants, Journal Year: 2022, Volume and Issue: 11(7), P. 970 - 970

Published: April 2, 2022

Plant stress is one of the most significant factors affecting plant fitness and, consequently, food production. However, may also be profitable since it behaves hormetically; at low doses, stimulates positive traits in crops, such as synthesis specialized metabolites and additional tolerance. The controlled exposure crops to doses stressors therefore called hormesis management, a promising method increase crop productivity quality. Nevertheless, management has severe limitations derived from complexity physiological responses stress. Many technological advances assist science overcoming limitations, which results extensive datasets originating multiple layers defensive response. For that reason, artificial intelligence tools, particularly Machine Learning (ML) Deep (DL), have become crucial for processing interpreting data accurately model genomic variation, gene protein expression, metabolite biosynthesis. In this review, we discuss recent ML DL applications science, focusing on their potential improving development protocols.

Language: Английский

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Cloning southern corn rust resistant gene RppK and its cognate gene AvrRppK from Puccinia polysora

Nature Communications, Journal Year: 2022, Volume and Issue: 13(1)

Published: July 29, 2022

Broad-spectrum resistance has great values for crop breeding. However, its mechanisms are largely unknown. Here, we report the cloning of a maize NLR gene, RppK, against southern corn rust (SCR) and cognate Avr AvrRppK, from Puccinia polysora (the causal pathogen SCR). The AvrRppK gene no sequence variation in all examined isolates. It high expression level during infection can suppress pattern-triggered immunity (PTI). Further, introgression RppK into inbred lines hybrids enhances multiple isolates P. polysora, thereby increasing yield presence SCR. Together, show that is involved it recognize which broadly distributed conserved

Language: Английский

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Direct recognition of pathogen effectors by plant NLR immune receptors and downstream signalling

Essays in Biochemistry, Journal Year: 2022, Volume and Issue: 66(5), P. 471 - 483

Published: June 22, 2022

Plants deploy extracellular and intracellular immune receptors to sense restrict pathogen attacks. Rapidly evolving effectors play crucial roles in suppressing plant immunity but are also monitored by nucleotide-binding, leucine-rich repeat (NLRs), leading effector-triggered (ETI). Here, we review how NLRs recognize with a focus on direct interactions summarize recent research findings the signalling functions of NLRs. Coiled-coil (CC)-type NLR proteins execute responses oligomerizing form membrane-penetrating ion channels after effector recognition. Some CC-NLRs function sensor-helper networks sensor triggering oligomerization helper NLR. Toll/interleukin-1 receptor (TIR)-type possess catalytic activities that activated upon recognition-induced oligomerization. Small molecules produced TIR activity detected additional partners EDS1 lipase-like family (enhanced disease susceptibility 1), activation trigger defense response.

Language: Английский

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