Bootstrapping and Pinning down the Root Meristem; the Auxin–PLT–ARR Network Unites Robustness and Sensitivity in Meristem Growth Control

Abstract

After germination, the meristem of the embryonic plant root becomes activated, expands in size and subsequently stabilizes to support post-embryonic root growth. The plant hormones auxin and cytokinin, together with master transcription factors of the PLETHORA (PLT) family have been shown to form a regulatory network that governs the patterning of this root meristem. Still, which functional constraints contributed to shaping the dynamics and architecture of this network, has largely remained unanswered. Using a combination of modeling approaches we reveal how the interplay between auxin and PLTs enables meristem activation in response to above-threshold stimulation, while its embedding in a PIN-mediated auxin reflux loop ensures localized PLT transcription and thereby, a finite meristem size. We furthermore demonstrate how this constrained PLT transcriptional domain enables independent control of meristem size and division rates, further supporting a division of labor between auxin and PLT. We subsequently reveal how the weaker auxin antagonism of the earlier active Arabidopsis response regulator 12 (ARR12) may arise from the absence of a DELLA protein interaction domain. Our model indicates that this reduced strength is essential to prevent collapse in the early stages of meristem expansion while at later stages the enhanced strength of Arabidopsis response regulator 1 (ARR1) is required for sufficient meristem size control. Summarizing, our work indicates that functional constraints significantly contribute to shaping the auxin–cytokinin–PLT regulatory network.

Computational modeling and quantitative physiology reveal central parameters for brassinosteroid-regulated early cell physiological processes linked to elongation growth of theArabidopsisroot

“…This approach can in principle be applied for the analysis of every signal perception and transduction process as long as a minimal set of elements and quantitative data are available or experimentally accessible, as has been demonstrated e.g. in the in-depth analysis of the PLT-auxin network during root zonation development in Arabidopsis thaliana ( Salvi et al, 2020 ; Rutten and Ten Tusscher, 2021 ).…”

“…While computational modeling has been used frequently in biomedical research since the early 2000s, its application to the plant field has started more recently ( Hübner et al, 2011 ; Holzheu and Kummer, 2020 ). Here, the growth and development of the root tip has been of particular interest ( Bruex et al, 2012 ; Muraro et al, 2016 ; Di Mambro et al, 2017 ; Rutten and Ten Tusscher, 2019 ; Salvi et al, 2020 ; Rutten and Ten Tusscher, 2021 ). Further computational studies in plants include the modeling of auxin signaling ( Vernoux et al, 2011 ) and transport pattern ( Band et al, 2014 ), and parts of the BR signaling ( Sankar et al, 2011 ; van Esse et al, 2012, 2013a ,b; Allen and Ptashnyk, 2017 ).…”

Complementary roles for auxin and auxin signalling revealed by reverse engineering lateral root stable prebranch site formation

“…Values of parameters involved in baseline auxin production ( p auxin , baseline ) and degradation ( d auxin ), additional cell type-dependent auxin production ( celltypefactor ), gene expression-mediated upregulation of auxin production ( yucca 4 factor ) and auxin transport rates and directions (intracellular and intra-apoplastic diffusion D cell , D wall , PIN-mediated export p PIN , ABC-mediated export eff basal , AUX1-mediated import p AUX / LAX , baseline import inf pas ) are taken as equal or close to values from previous well-established model studies, dating back as far as the seminal study by Grieneisen et al (2007) . For these parameter settings, models were shown to produce qualitatively realistic and robust auxin patterns ( van den Berg et al, 2016 , 2021; Grieneisen et al, 2007 ; Mähönen et al, 2014 ; Rutten and Ten Tusscher, 2021 ; Salvi et al, 2020 ) consistent with shoot cut experiments ( Grieneisen et al, 2007 ), capable of simulating tropic responses ( van den Berg et al, 2016 ; Mähönen et al, 2014 ) consistent with more recent insights on the importance of root localized auxin production ( van den Berg et al, 2021 ; Rutten and Ten Tusscher, 2021 ; Salvi et al, 2020 ), and consistent with experimentally observed changes in auxin and meristem dynamics in response to mutations ( van den Berg et al, 2021 ; Salvi et al, 2020 ) . Under these parameter settings, the basic priming dynamics shown in Fig.…”