Group of mathematical modelling

Detailed mapping of single-cell auxin transport

Present models, which focus mainly on the level of whole tissues, depend to a great extent on the accuracy of the representation of individual cells as their building blocks. In order to provide such information, we have focused on construction of a detailed model of auxin transport mechanisms in isolated plant cells. Using a combination of measurements of accumulation of radiolabeled auxins in cell suspensions and HPLC analysis of radiolabeled auxin metabolism to feed the mathematical model, we have succeeded to prove the ability of tobacco auxin efflux carrier to transport synthetic auxin 2,4-D out of the cells and also to define some of the crucial parameters of cellular auxin transport (Hošek & Kubeš et al., Journal of Experimental Botany, 2012). Based on the analysis of the model and performed simulations, the model seems to have a considerable potential for further development in order to contribute to the studies of regulatory mechanisms of active auxin transport.

High-accuracy auxin influx kinetics assays helped define the rules of AUX1 transporter specificity

Building on our previously developed auxin transport model, we have managed to substantially improve on the method developed by Delbarre et al. (1996) for measuring the affinity of AUX/LAX1 auxin importer towards various substrates. Using this new accurate setup, we performed a screening of a number of auxinic compouns, obtaining estimates of their kinetic parameters (VMAX and kM). These data were then used in collaboration with our colleagues from the University of Warwick, UK, to define the rules a molecule must conform to in order to be efficiently transported by the AUX/LAX1 carrier. The findings of the study (Hoyerová, Hošek, Quareshy et al., New Phytologist, 2017) might help to design more efficient and safer herbicides in future.

Predictions of a mathematical model pointed out a complex mechanism of auxin homeostasis maintenance

Change in auxin transport parameters after auxin starvation and schematic depiction of observed auxin transport processes at the PM of tobacco BY-2 cells. (taken from Müller et al., 2019, Fig. 6b)

When we used our auxin transport model to quantify auxin flows through individual transport mechanisms in tobacco cells overexpressing the NtPIN11 efflux carrier, we were surprised to see active auxin influx increase as well. After observing that the transcript levels of a specific auxin importer (NtLAX1c) have, indeed, decreased, we understood this as an indication of a specific regulatory mechanism at the level of auxin carrier transcription. A similar phenomenon concerning the same influx carrier was then observed in auxin-starved cells using again both transport modelling and transcriptional analysis, thus confirming the NtLAX1c carrier transcription to be triggered by changes in cellular auxin levels as a part of a homeostasis-maintaining mechanism (Müller et al., The Plant Journal, 2019).

Mathematical modelling of the dynamics of metabolic conversions of cytokinins

Metabolic conversions of cytokinins are a dynamical process used by the plant to respond to internal and external stimuli in order to maintain hormonal homeostasis. The first mathematical model of cytokinin metabolic conversions (Lexa et al., Annals of Botany 2003) is now seriously outdated, which has motivated us to start building a new model from the ground up. Over several years of incremental model updates and specifically designed cytokinin metabolic assays, we have obtained a model providing estimates of crucial metabolic reaction rates as well as “wet lab” data showing several interesting phenomena on their own. One of the most important observations is the fact that differences in the metabolism of isopentenyladenine N-glucosides and trans-zeatine N-glucosides are likely to be the determining factor of the native cytokinin metabolic spectrum in Arabidopsis plants (Hošek, Hoyerová et al., New Phytologist, 2019).


We cooperate with Assoc. Prof. Marcel Jiřina, Ph.D. (department of biomedical informatics, Faculty of Biomedical Engineering, Czech Technical University in Prague).