Multi-dimensional demarcation of phylogenetic groups of plant 14-3-3 isoforms using biochemical signatures
Sedlov, I. A.; Sluchanko, N. N.
Show abstract
Interaction of dimeric 14-3-3 proteins with numerous phosphotargets regulates various physiological processes in plants, from flowering to transpiration and salt tolerance. Several genes express distinct 14-3-3 isoforms, particularly numerous in plants, but comparative studies of all 14-3-3 isoforms for a given organism have not been undertaken. Here we systematically investigated twelve 14-3-3 isoforms from the model plant Arabidopsis thaliana, uniformly capable of homodimerization at high protein concentration. We unexpectedly discovered that, at physiological protein concentrations, four isoforms representing a seemingly more ancestral, epsilon phylogenetic group (iota, mu, omicron, epsilon) demonstrate an outstanding monomerization propensity and enhanced surface hydrophobicity, which is uncharacteristic for eight non-epsilon isoforms (omega, phi, chi, psi, upsilon, nu, kappa, lambda). Further analysis revealed that dramatically lowered thermodynamic stabilities entail aggregation of the epsilon-group isoforms at near-physiological temperatures and provoke their proteolytic degradation. Structure-inspired single mutations in 14-3-3 iota could rescue non-epsilon behavior, thereby pinpointing key positions responsible for the phylogenetic demarcation. Combining two major demarcating positions (namely, 27th and 51st in omega) and multi-dimensional differences in biochemical properties identified here, we developed a predictor strongly supporting categorization of abundant 14-3-3 isoforms widely across plant groups, from Eudicots to Monocots, Gymnosperms and Lycophytes. In particular, our approach fully recapitulates the phylogenetic epsilon/non-epsilon demarcation in Eudicots and supports the presence of isoforms of both types in more primitive plant groups such as Selaginella, thereby refining solely sequence-based analysis in evolutionarily distant species and providing novel insights into the evolutionary history of the epsilon phylogenetic group. SignificanceDespite over 30 years of research, systematic comparative studies on the regulatory plant 14-3-3 proteins have not been undertaken, making phylogenetic classification of numerous plant 14-3-3 isoforms in different species unreliable. Working on twelve purified Arabidopsis 14-3-3 isoforms, we have discovered a set of biochemical signatures that can be used to robustly and widely categorize epsilon and non-epsilon plant 14-3-3 isoforms, also identifying at least two amino acid positions responsible for such multi-dimensional demarcation.
Matching journals
The top 11 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Localization of four class I glutaredoxins in the cytosol and the secretory pathway and characterization of their biochemical diversification 95%
- Catch & Release - rapid cost-effective protein purification from plants using a DIY GFP-Trap-protease approach 95%
- D27-LIKE1 carotenoid isomerase has a preference towards trans/cis and cis/cis conversions in Arabidopsis 94%
Similar papers in this journal
Similar papers in this journal
- The nuts and bolts of SARS-CoV-2 Spike Receptor Binding Domain heterologous expression 92%
- YidC from Escherichia coli forms an ion-conducting pore upon activation by ribosomes. 92%
- Integrative modelling of the full-length human dehydrodolichyl diphosphate synthase using a hybrid computational and experimental approach 91%
Similar papers in this journal
- Structural basis for variable IgE reactivities of Cor a 1 hazelnut allergens 94%
- Structural genomic applied on the rust fungus Melampsora larici-populina reveals two candidate effector proteins adopting cystine-knot and nuclear transport factor 2-like protein folds 94%
- A new perspective on the evolution of the interaction between the Vg/VGLL1-3 proteins and the TEAD transcription factors 94%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.