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Record W2998994512 · doi:10.1101/2020.01.15.907899

Target of Rapamycin: function in abiotic stress tolerance in Arabidopsis and its involvement in a possible cross-talk with ribosomal proteins

2020· preprint· en· W2998994512 on OpenAlexaff
Achala Bakshi, Mazahar Moin, M. Sheshu Madhav, Meher B. Gayatri, Aramati B. M. Reddy, Raju Datla, Pulugurtha Bharadwaja Kirti

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2020
Typepreprint
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Stress Responses and Tolerance
Canadian institutionsGlobal Institute for Water Security
FundersChristopher S. Bond Life Sciences Center, University of MissouriIndian Council of Agricultural ResearchUniversity of Missouri
KeywordsArabidopsisBiologyAbiotic stressRibosomal proteinOsmotic shockCell biologyDownregulation and upregulationArabidopsis thalianaTransgeneGeneBiochemistryRibosomeMutantRNA

Abstract

fetched live from OpenAlex

Abstract The Target of Rapamycin (TOR) protein kinase reprograms cellular metabolism under various environmental stresses. The overexpression of TOR in Arabidopsis resulted in increased plant growth including yield and biomass when compared with the wild type under both controlled and limited water conditions. In the present investigation, we report that Arabidopsis plants overexpressing TOR exhibited enhanced tolerance to the osmotic and salt stress treatments. Further to determine the role of TOR in abiotic stresses other than water limiting conditions, which were observed earlier in rice, we have treated high and medium TOR expressing Arabidopsis plants, ATR-1.4.27 and ATR-3.7.32 respectively, with stress-inducing chemical agents such as Mannitol (100 mM), NaCl (150 mM), Sorbitol (200 mM) and PEG (7%). Both the lines, ATR-1.4.27 and ATR-3.7.32 exhibited enhanced tolerance to these stresses. These lines also had increased proline and total chlorophyll contents under stress conditions compared with their corresponding WT counterparts. The upregulation of several osmotic stress inducible genes in Arabidopsis transgenic lines indicated the role of TOR in modulating multi-stress tolerance. In the present investigation, we have also analyzed the transcriptional upregulation of ribosomal protein large and small subunit (RPL and RPS) genes in AtTOR overexpressing rice transgenic lines, TR-2.24 and TR-15.1 generated earlier (Bakshi et al., 2017a), which indicated that TOR also positively regulates the transcription of ribosomal proteins (RP) along with the synthesis of rRNAs. Also, the observations from phosphoproteomic analysis in SALK lines of various Arabidopsis T-DNA insertion mutants of ribosomal proteins showed differential regulation in phosphorylation of p70kDa ribosomal protein S6K1 and comparative analysis of phosphorylation sites for RSK (Ribosomal S6 Kinases) in RPL6, RPL18, RPL23, RPL24 and RPS28C proteins of Arabidopsis, Interestingly, rice showed similarity in their peptide sequences and Ser/Thr positions. These results suggest that the phosphorylation of S6K1 is controlled by loss/ inhibition of ribosomal protein function to switch ‘on’/ ‘off’ the translational regulation for balanced growth and the pathways of both RPs and TOR are interlinked in a cyclic manner via phosphorylation of S6K1 as a modulatory step.

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)0.000
metaresearch head score (Gemma)0.000
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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

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 head0.016
GPT teacher head0.205
Teacher spread0.189 · 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".

Quick stats

Citations4
Published2020
Admission routes1
Has abstractyes

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