Chemical biology and digital image processing to unravel complex molecular mechanisms in Arabidopsis

The sessile life of plant directed their evolution toward multiple adaptive strategies. Rapid protein turn over has been described to be a key regulatory mechanism for plant adaptation. Ubiquitin-modified proteins are targeted for degradation by the 26S-proteasome. A class of ubiquitin-ligases, the Cullin Ring Ligases (CRLs) have been shown to be involved in most Arabidopsis developmental processes. CRLs are stabilized by the covalent binding of the small peptide RELATED TO UBIQUITIN (RUB). The CRLs modification is required for the activity of plant hormones as exemplified by mutants deficient in the RUB-activating enzyme subunit AUXIN-RESISTANT 1 (AXR1). The perception of auxin results in the ubiquitin-mediated degradation of the AUXIN/INDOL-3-ACETIC ACID (Aux/IAA) transcriptional repressors. Aux/IAA proteins control the auxin-mediated transcriptional response. In this work, a forward chemical genomic strategy has been used to identify small synthetic molecules affecting plant development. We used the resistance of the axr1-30 mutants in order to select compounds requiring RUB activation. Among the molecules isolated to alter specific plant developmental processes, three Developmental Regulators (DRs) have been shown to directly interfere with the degradation of the Aux/IAA proteins promoting a rapid induction of specific auxin-related transcriptional responses. Furthermore, we used the molecule DR4, abolishing specifically apical hook formation, to investigate the functional selectivity of auxin perception during apical hook development. A forward genetic screen has been performed to isolate dr4-resistant mutants. Several viable mutants were isolated with different sensitivity to auxin but all resistant to DR4. The isolation of mutants preferentially resistant to the differential growth defect induced by DR4 demonstrates the potential to determine the molecular process mediating the developmental features induced by the selective agonists of auxin. Since the first digital image 60 years ago, imaging techniques are constantly evolving generating more and more digital images. The conversion of images into biologically relevant quantitative data is an essential process to overcome and understand biological variability. In this work, we describe two digital images processing approaches which have been used to semi-automatically describe intracellular structure density and colocalization; the complex shape of the Arabidopsis pavement cells