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Enregistrement W3211870610 · doi:10.1093/plcell/koab271

Survival or starvation: SnRK1 controls rate of resource use in pre-photosynthetic seedlings

2021· letter· en· W3211870610 sur OpenAlexaff
Brendan M. O’Leary

Notice bibliographique

RevueThe Plant Cell · 2021
Typeletter
Langueen
DomaineAgricultural and Biological Sciences
ThématiquePlant nutrient uptake and metabolism
Établissements canadiensAgriculture and Agri-Food Canada
Organismes subventionnairesnon disponible
Mots-clésBiologyStarvationPhotosynthesisResource (disambiguation)BotanyHorticultureEndocrinology

Résumé

récupéré en direct d'OpenAlex

In the most perilous part of a green plant’s life cycle, newly germinated seedlings must risk everything to establish photosynthesis and energetic independence. All seeds are stocked with finite nutrient resources in the forms of starch, sugars, storage oils, and storage proteins, but in a small seed like Arabidopsis (Arabidopsis thaliana), these precious resources (∼30 µg) can run out after just 4–5 d (Kircher and Schopfer, 2012). Facing uncertain conditions, seedlings must invest these few resources toward shoot and root growth in a strategic and timely fashion in order to optimize their chance of survival. It follows that multiple regulatory mechanisms have evolved to coordinate environmental and cellular cues with the mobilization of carbon, nitrogen, and energy reserves in seedlings. Throughout eukaryotes, many aspects of cellular energy status are signaled via a group of conserved regulatory kinases, which in plants are called Sucrose nonfermenting-Related protein Kinases (SnRKs). Activation of SnRK1 activity in several plant tissues signals imminent stress and carbon starvation, leading to massive transcriptional and post-translational changes that suppress growth and conserve energy (Baena-Gonzalez and Sheen, 2008). The period between germination and seedling establishment involves rapid changes in metabolism and energy status, and the likely prospect of starvation. In their recent Plant Cell paper, Markus Henninger et al. combined genetic, transcriptomic, and metabolomic approaches to elucidate a role for the master energy regulator SnRK1 at this crucial phase of plant metabolism. To assess SnRK1 function in developing seedlings, the authors established an effective inducible loss-of-function method targeting the catalytic subunits of SnRK1: SnRK1α1 and SnRK1α2. In snrk1α1/α2 seedlings, growth ceased 3 d after germination, and chlorophyll content and chlorophyll fluorescence only accumulated transiently thereafter. These observations indicated that SnRK1 activity is essential for effective seedling establishment. The establishment phenotype of snrk1α1/α2 was largely rescued by addition of easily metabolizable carbohydrates like glucose to the growth medium. Furthermore, the transcriptional differences between wild-type and snrk1α1/α2 seedlings, which were substantial under control conditions, were greatly diminished by the presence of glucose. This sugar-rescue seedling phenotype is characteristic of mutants deficient in the metabolism of storage compounds to glucose (gluconeogenesis), which is a necessary metabolic process prior to establishment of photosynthesis. Sure enough, when the author’s detailed resource mobilization in seedlings post-germination, loss of Snrk1α1/α2 led to lower rates of storage lipid and storage protein drawdown and consequently lower levels of metabolically available sugars and amino acids (Figure). Reduced sugar and amino acid availability in germinated snrk1α1/α2 seedlings. Sugar content (A) or free amino acid content (B) were measured in wild type (col-0) and snrk1α1/α2 seedlings post-germination in the dark, with or without transfer to light after 3 days. Adapted from Henninger et al. (2021), Figure 4. Reduced sugar and amino acid availability in germinated snrk1α1/α2 seedlings. Sugar content (A) or free amino acid content (B) were measured in wild type (col-0) and snrk1α1/α2 seedlings post-germination in the dark, with or without transfer to light after 3 days. Adapted from Henninger et al. (2021), Figure 4. The mechanisms behind Snrk1α1/α2 control of reserve mobilization were pursued through a post-germination RNA-seq time course. In line with metabolite level analysis, snrk1α1/α2 seedlings displayed reduced expression of transcripts for certain enzymes in lipid β-oxidation and amino acid catabolism, along with the key initial enzymes of gluconeogenesis: phosphoenolpyruvate carboxykinase and cytosolic pyruvate, phosphate dikinase (cyPPDK). The transcriptional profile of snrk1α1/α2 seedlings was similar to that of known targets of the transcription factor bZIP63 (Pedrotti et al., 2018), which itself is a subject to SnRK1 regulatory phosphorylation. Promoter reporter assays in leaf protoplasts revealed that exogenous bZIP63 expression increased ProcyPPDK activation but only in the presence of co-expressed SnRK1. Subsequent multi-pronged cyPPDK promoter analyses discovered that bZIP63 bound to specific locations on the PPDK gene. These results illustrate a clear SnRKα1/α2 regulatory mechanism in seedlings, where phosphorylation and activation of the bZIP63 lead to enhanced expression of the key gluconeogenic enzyme PPDK. Taken together, the results of this study indicate that SnRK1 plays a major role in orchestrating seed resource mobilization. Whether this role for SnRK1 differs between oilseeds (as described here) and other types of plant seeds will be an important area of future research.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,004
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,010
Score d'incertitude au seuil0,017

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,004
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0010,001
Communication savante0,0010,001
Science ouverte0,0010,000
Intégrité de la recherche0,0100,007
Charge utile insuffisante (le modèle a refusé de juger)0,0050,004

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,046
Tête enseignante GPT0,201
Écart entre enseignants0,155 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeExpérimental (laboratoire)
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations1
Publié2021
Routes d'admission1
Résumé présentnon

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