Cited by 12Plant Stress Responses and ToleranceSeed Germination and PhysiologyPlant Molecular Biology Research

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Abscisic acid (ABA) signaling: finding novel components off the beaten track

Open access

Published version of a preprint

Abstract

The sesquiterpene abscisic acid (ABA) is an ancient stress response molecule. In plants, many ABA-dependent processes operate via PYR/PYL/RCAR receptor complexes, but results from several studies have suggested that not all plant responses function through this mechanism. Since the ABA-dependent processes of animals and humans also operate in the absence of such receptors, we hypothesize that plant and animal proteomes harbour proteins with undiscovered ABA-binding sites. We propose that carefully curated amino acid search motifs deduced from the binding sites of experimentally confirmed ABA-binding proteins can identify many more candidates in plant and animal proteomes. Some of these candidates show structural folds that are compatible with ABA-binding. This approach identifies plant candidates including annotated ABA downstream signaling components SnRK2.2 and SnRK2.6, and proteins involved in protein folding and RNA polyadenylation. The identified ABA-binding candidates in the human proteome affect among other processes, immune responses and tumor progression. If these candidates are eventually validated experimentally, it will imply that the regulation and tuning of ABA-dependent processes is considerably more complex than hitherto suspected. It will also help to clarify the role of this conserved signaling molecule in mammals.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1007/s10725-022-00823-y

Cites

1 of 1 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Flagged first, then by citations

Show all 1 references

Research works printed but not linked: 37

  1. Ali A, Pardo JM, Yun DJ (2020) Desensitization of ABA-signaling: the swing from activation to degradation. Front Plant Sci 11:1–7. https://doi.org/10.3389/fpls.2020.00379 · DOI
  2. Anabuki T, Ohashi K, Takasuka TE et al (2022) AtTrxh3, a thioredoxin, is identified as an abscisic acid binding protein in Arabidopsis thaliana. Molecules 27:161. https://doi.org/10.3390/molecules27010161 · DOI
  3. Bassaganya-Riera J, Guri AJ, Lu P et al (2011) Abscisic acid regulates inflammation via ligand-binding domain-independent activation of peroxisome proliferator-activated receptor γ. J Biol Chem 286:2504–2516. https://doi.org/10.1074/jbc.M110.160077 · DOI
  4. Bauer H, Mayer H, Marchler-Bauer A et al (2000) Characterization of p40/GPR69A as a peripheral membrane protein related to the lantibiotic synthetase component C. Biochem Biophys Res Commun 275:69–74. https://doi.org/10.1006/bbrc.2000.3260 · DOI
  5. Chen K, Li GJ, Bressan RA et al (2020) Abscisic acid dynamics, signaling, and functions in plants. J Integr Plant Biol 62:25–54. https://doi.org/10.1111/jipb.12899 · DOI
  6. Chong GL, Foo MH, Lin WD et al (2019) Highly ABA-induced 1 (HAI1)-interacting protein HIN1 and drought acclimation-enhanced splicing efficiency at intron retention sites. Proc Natl Acad Sci USA 116:22376–22385. https://doi.org/10.1073/pnas.1906244116 · DOI
  7. Cornforth JW, Milborrow BV, Ryback G (1965) Synthesis of (±)—abscisin II. Nature 206:715. https://doi.org/10.1038/206715a0 · DOI
  8. Cornforth JW, Milborrow BV, Ryback G, Wareing PF (1965) Chemistry and physiology of ‘Dormins’ in sycamore: identity of sycamore ‘Dormin’ with abscisin II. Nature 205:1269–1270. https://doi.org/10.1038/2051269b0 · DOI
  9. Galka MM, Rajagopalan N, Buhrow LM et al (2015) Identification of interactions between abscisic acid and ribulose-1,5-bisphosphate carboxylase/oxygenase. PLoS ONE 10:1–21. https://doi.org/10.1371/journal.pone.0133033 · DOI
  10. Jung Y, Cackowski FC, Yumoto K et al (2021) Abscisic acid regulates dormancy of prostate cancer disseminated tumor cells in the bone marrow. Neoplasia 23:102–111. https://doi.org/10.1016/j.neo.2020.11.009 · DOI
  11. Kharenko OA, Boyd J, Nelson KM et al (2011) Identification and characterization of interactions between abscisic acid and mitochondrial adenine nucleotide translocators. Biochem J 437:117–123. https://doi.org/10.1042/BJ20101898 · DOI
  12. Kwiatkowski M, Wong A, Kozakiewicz A et al (2021) A tandem motif-based and structural approach can identify hidden functional phosphodiesterases. Comput Struct Biotechnol J 19:970–975. https://doi.org/10.1016/j.csbj.2021.01.036 · DOI
  13. Kwiatkowski M, Wong A, Kozakiewicz-Piekarz A et al (2021) In search of monocot phosphodiesterases: identification of a calmodulin stimulated phosphodiesterase from Brachypodium distachyon. Int J Mol Sci 22(17):9654. https://doi.org/10.3390/ijms22179654 · DOI
  14. Le Page-Degivry M-T, Bidard JN, Rouvier E et al (1986) Presence of abscisic acid, a phytohormone, in the mammalian brain. Proc Natl Acad Sci USA 83:1155–1158. https://doi.org/10.1073/pnas.83.4.1155 · DOI
  15. Lee SY, Park SK, Jung YJ et al (2009) Heat-shock and redox-dependent functional switching of an h-type arabidopsis thioredoxin from a disulfide reductase to a molecular chaperone. Plant Physiol 150:552–561. https://doi.org/10.1104/pp.109.135426 · DOI
  16. Li YC, Ren JP, Cho MJ et al (2009) The level of expression of thioredoxin is linked to fundamental properties and applications of wheat seeds. Mol Plant 2:430–441. https://doi.org/10.1093/mp/ssp025 · DOI
  17. Lievens L, Pollier J, Goossens A et al (2017) Abscisic acid as pathogen effector and immune regulator. Front Plant Sci 8:1–15. https://doi.org/10.3389/fpls.2017.00587 · DOI
  18. Lin Z, Li Y, Wang Y et al (2021) Initiation and amplification of SnRK2 activation in abscisic acid signaling. Nat Commun. https://doi.org/10.1038/s41467-021-22812-x · DOI
  19. Lipp J (1990) Nachweis und Herkunft von Abscisinsäure und Prolin in Honig. Apidologie 21:249–259. https://doi.org/10.1051/apido:19900310 · DOI
  20. Ludidi N, Gehring C (2003) Identification of a novel protein with guanylyl cyclase activity in Arabidopsis thaliana. J Biol Chem 278:6490–6494. https://doi.org/10.1074/jbc.M210983200 · DOI
  21. Mittelheuser CJ, van Steveningk RFM (1969) Stomatal closure and inhibition of transpiration induced by (RS)—abscisic acid. Nature 221:281–282. https://doi.org/10.1038/221281a0 · DOI
  22. Nakashima K, Yamaguchi-Shinozaki K (2013) ABA signaling in stress-response and seed development. Plant Cell Rep 32:959–970. https://doi.org/10.1007/s00299-013-1418-1 · DOI
  23. Negri P, Maggi MD, Ramirez L et al (2015) Abscisic acid enhances the immune response in Apis mellifera and contributes to the colony fitness. Apidologie 46:542–557. https://doi.org/10.1007/s13592-014-0345-7 · DOI
  24. Ooi A, Lemtiri-Chlieh F, Wong A, Gehring C (2017) Direct modulation of the guard cell outward-rectifying potassium channel (GORK) by abscisic acid. Mol Plant 10:1469–1472. https://doi.org/10.1016/j.molp.2017.08.010 · DOI
  25. Pettersen EF, Goddard TD, Huang CC et al (2004) UCSF Chimera—a visualization system for exploratory research and analysis. J Comput Chem 25:1605–1612. https://doi.org/10.1002/jcc.20084 · DOI
  26. Sturla L, Fresia C, Guida L et al (2009) LANCL2 is necessary for abscisic acid binding and signaling in human granulocytes and in rat insulinoma cells. J Biol Chem 284:28045–28057. https://doi.org/10.1074/jbc.M109.035329 · DOI
  27. Suzuki Y, Fujimori T, Kanno K et al (2012) Metabolome analysis of photosynthesis and the related primary metabolites in the leaves of transgenic rice plants with increased or decreased Rubisco content. Plant Cell Environ 35:1369–1379. https://doi.org/10.1111/j.1365-3040.2012.02494.x · DOI
  28. Takahashi Y, Zhang J, Hsu PK et al (2020) MAP3Kinase-dependent SnRK2-kinase activation is required for abscisic acid signal transduction and rapid osmotic stress response. Nat Commun 11(1):12. https://doi.org/10.1038/s41467-019-13875-y · DOI
  29. Takezawa D, Komatsu K, Sakata Y (2011) ABA in bryophytes: how a universal growth regulator in life became a plant hormone? J Plant Res 124:437–453. https://doi.org/10.1007/s10265-011-0410-5 · DOI
  30. Trott O, Olson AJ (2010) Autodock vina. J Comput Chem 31:2967–2970. https://doi.org/10.1002/jcc · DOI
  31. Vigliarolo T, Guida L, Millo E et al (2015) Abscisic acid transport in human erythrocytes. J Biol Chem 290:13042–13052. https://doi.org/10.1074/jbc.M114.629501 · DOI
  32. Wang ZY, Gehring C, Zhu J et al (2015) The arabidopsis vacuolar sorting receptor1 is required for osmotic stress-induced abscisic acid biosynthesis. Plant Physiol 167:137–152. https://doi.org/10.1104/pp.114.249268 · DOI
  33. Wong A, Tian X, Gehring C et al (2018) Discovery of novel functional centers with rationally designed amino acid motifs. Comput Struct Biotechnol J 16:70–76. https://doi.org/10.1016/j.csbj.2018.02.007 · DOI
  34. Wong A, Hu N, Tian X et al (2021) Nitric oxide sensing revisited. Trends Plant Sci 26:885–897. https://doi.org/10.1016/j.tplants.2021.03.009 · DOI
  35. Wong A, Tian X, Yang Y et al (2021) Identification of potential nitric oxide-sensing proteins using the H-NOX motif. Mol Plant 14:195–197. https://doi.org/10.1016/j.molp.2020.11.015 · DOI
  36. Zhou W, Chi W, Shen W et al (2021) Computational identification of functional centers in complex proteins: a step-by-step guide with examples. Front Bioinform 1:652286. https://doi.org/10.3389/fbinf.2021.652286 · DOI
  37. Zocchi E, Carpaneto A, Cerrano C et al (2001) The temperature-signaling cascade in sponges involves a heat-gated cation channel, abscisic acid, and cyclic ADP-ribose. Proc Natl Acad Sci USA 98:14859–14864. https://doi.org/10.1073/pnas.261448698 · DOI

Metadata

Authors
Wong, A., Bi, C., Pasqualini, S., & Gehring, C.
Affiliations
  • Wenzhou-Kean University (CN)
  • University of Perugia (IT)
Corresponding author
Gehring, Chris
Venue
Plant Growth Regulation
Published
2022-04-15
Volume
97
Issue
3
Pages
585-592
ISSN
  • 0167-6903 (ISSN-L)
  • 1573-5087
OpenAlex
W4226324762
Cited by
12
References
1
Citations by year
2026: 2 · 2025: 5 · 2024: 3 · 2022: 2
FWCI
1.38
Type
journal article
Language
en
Open access
Locations
  • Plant Growth Regulation (publishedVersion, cc-by)
  • Research Square (acceptedVersion, cc-by)
Funders
  • National Natural Science Foundation of China (32100581)
  • International Collaborative Research Program of Wenzhou-Kean University (ICRP202202)
  • MUR–PRIN 2017 (2017N5LBZK_004)
Topics
  • Life Sciences › Agricultural and Biological Sciences › Plant Science › Plant Stress Responses and Tolerance
  • Life Sciences › Agricultural and Biological Sciences › Plant Science › Seed Germination and Physiology
  • Life Sciences › Agricultural and Biological Sciences › Plant Science › Plant Molecular Biology Research
Keywords
abscisic acid signaling, ABA receptors, PYR/PYL/RCAR receptors, SnRK2.6, protein folding, polyadenylation, immune response, tumor progression, plant stress response

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review