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Record W3211870610 · doi:10.1093/plcell/koab271

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

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

Bibliographic record

VenueThe Plant Cell · 2021
Typeletter
Languageen
FieldAgricultural and Biological Sciences
TopicPlant nutrient uptake and metabolism
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsBiologyStarvationPhotosynthesisResource (disambiguation)BotanyHorticultureEndocrinology

Abstract

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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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0100.007
Insufficient payload (model declined to judge)0.0050.004

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.046
GPT teacher head0.201
Teacher spread0.155 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations1
Published2021
Admission routes1
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