Molecular mechanisms of resistance to Myzus persicae conferred by the peach Rm2 gene: A multi-omics view

The transcriptomic and metabolomic responses of peach to Myzus persicae infestation were studied in Rubira, an accession carrying the major resistance gene Rm2 causing antixenosis, and GF305, a susceptible accession. Transcriptome and metabolome showed both a massive reconfiguration in Rubira 48 hours after infestation while GF305 displayed very limited changes. The Rubira immune system was massively stimulated, with simultaneous activation of genes encoding cell surface receptors involved in pattern-triggered immunity and cytoplasmic NLRs (nucleotide-binding domain, leucine-rich repeat containing proteins) involved in effector-triggered immunity. Hypersensitive reaction featured by necrotic lesions surrounding stylet punctures was supported by the induction of cell death stimulating NLRs/helpers couples, as well as the activation of H₂O₂-generating metabolic pathways: photorespiratory glyoxylate synthesis and activation of the futile P5C/proline cycle. The triggering of systemic acquired resistance was suggested by the activation of pipecolate pathway and accumulation of this defense hormone together with salicylate. Important reduction in carbon, nitrogen and sulphur metabolic pools and the repression of many genes related to cell division and growth, consistent with reduced apices elongation, suggested a decline in the nutritional value of apices. Finally, the accumulation of caffeic acid conjugates pointed toward their contribution as deterrent and/or toxic compounds in the mechanisms of resistance.

Auto-deconvolution and molecular networking of gas chromatography-mass spectrometry data

We engineered a machine learning approach, MSHub, to enable auto-deconvolution of gas chromatography-mass spectrometry (GC-MS) data. We then designed workflows to enable the community to store, process, share, annotate, compare and perform molecular networking of GC-MS data within the Global Natural Product Social (GNPS) Molecular Networking analysis platform. MSHub/GNPS performs auto-deconvolution of compound fragmentation patterns via unsupervised non-negative matrix factorization and quantifies the reproducibility of fragmentation patterns across samples.

Auto-deconvolution and molecular networking of gas chromatography-mass spectrometry data

We engineered a machine learning approach, MSHub, to enable auto-deconvolution of gas chromatography-mass spectrometry (GC-MS) data. We then designed workflows to enable the community to store, process, share, annotate, compare and perform molecular networking of GC-MS data within the Global Natural Product Social (GNPS) Molecular Networking analysis platform. MSHub/GNPS performs auto-deconvolution of compound fragmentation patterns via unsupervised non-negative matrix factorization and quantifies the reproducibility of fragmentation patterns across samples.

A comparison of PTI defense profiles induced in Solanum tuberosum by PAMP and non-PAMP elicitors shows distinct, elicitor-specific responses

The induction of general plant defense responses following the perception of external elicitors is now regarded as the first level of the plant immune response. Depending on the involvement or not of these molecules in pathogenicity, this induction of defense is called either Pathogen-Associated Molecular Pattern (PAMP) Triggered Immunity or Pattern Triggered Immunity-both abbreviated to PTI. Because PTI is assumed to be a widespread and stable form of resistance to infection, understanding the mechanisms driving it becomes a major goal for the sustainable management of plant-pathogen interactions. However, the induction of PTI is complex. Our hypotheses are that (i) the recognition by the plant of PAMPs vs non-PAMP elicitors leads to specific defense profiles and (ii) the responses specifically induced by PAMPs target critical life history traits of the pathogen that produced them. We thus analyzed, using a metabolomic approach coupled with transcriptomic and hormonal analyses, the defense profiles induced in potato foliage treated with either a Concentrated Culture Filtrate (CCF) from Phytophthora infestans or two non-PAMP preparations, β-aminobutyric acid (BABA) and an Ulva spp. Extract, used separately. Each elicitor induced specific defense profiles. CCF up-regulated sesquiterpenes but down-regulated sterols and phenols, notably α-chaconine, caffeoyl quinic acid and rutin, which decreased spore production of P. infestans in vitro. CCF thus induces both defense and counter-defense responses. By contrast, the Ulva extract triggered the synthesis of a large-spectrum of antimicrobial compounds through the phenylpropanoid/flavonoid pathways, while BABA targeted the primary metabolism. Hence, PTI can be regarded as a heterogeneous set of general and pathogen-specific responses triggered by the molecular signatures of each elicitor, rather than as a uniform, non-specific and broad-spectrum set of general defense reactions.

Pivotal roles of environmental sensing and signaling mechanisms in plant responses to climate change

Climate change reshapes the physiology and development of organisms through phenotypic plasticity, epigenetic modifications, and genetic adaptation. Under evolutionary pressures of the sessile lifestyle, plants possess efficient systems of phenotypic plasticity and acclimation to environmental conditions. Molecular analysis, especially through omics approaches, of these primary lines of environmental adjustment in the context of climate change has revealed the underlying biochemical and physiological mechanisms, thus characterizing the links between phenotypic plasticity and climate change responses. The efficiency of adaptive plasticity under climate change indeed depends on the realization of such biochemical and physiological mechanisms, but the importance of sensing and signaling mechanisms that can integrate perception of environmental cues and transduction into physiological responses is often overlooked. Recent progress opens the possibility of considering plant phenotypic plasticity and responses to climate change through the perspective of environmental sensing and signaling. This review aims to analyze present knowledge on plant sensing and signaling mechanisms and discuss how their structural and functional characteristics lead to resilience or hypersensitivity under conditions of climate change. Plant cells are endowed with arrays of environmental and stress sensors and with internal signals that act as molecular integrators of the multiple constraints of climate change, thus giving rise to potential mechanisms of climate change sensing. Moreover, mechanisms of stress-related information propagation lead to stress memory and acquired stress tolerance that could withstand different scenarios of modifications of stress frequency and intensity. However, optimal functioning of existing sensors, optimal integration of additive constraints and signals, or memory processes can be hampered by conflicting interferences between novel combinations and novel changes in intensity and duration of climate change-related factors. Analysis of these contrasted situations emphasizes the need for future research on the diversity and robustness of plant signaling mechanisms under climate change conditions.