Professor Henrik Jönsson is Director of the Sainsbury Laboratory and Professor of Computational Morphodynamics.
Henrik received his masters (1997) and PhD (2002) degrees in Theoretical Physics from Lund University, Sweden, where he worked in the Complex Systems group, supervised by Bo Söderberg. He continued with post-doctoral work at Division of Biology, California Institute of Technology in the Barbara Wold Laboratory under guidance of Eric Mjolsness. He became Assistant Professor in 2008 at the Computational Biology and Biological Physics group at Lund University, and joined SLCU as a group leader in September 2011. In 2014, Henrik was appointed Professor of Computational Morphodynamics and Associate Director at SLCU and then SLCU Director in 2020. Henrik is on the Editorial Advisory Board of in silico Plants (isP) and academic editor for PLoS ONE and Journal of Theoretical Biology.
Research Interests
The focus of my research is to develop Computational Morphodynamics models at the cellular level describing multicellular tissues such as the shoot apical meristem. The models are developed in close collaboration with experimental groups and describe the dynamics of gene regulatory networks, hormone transport and signalling, cell growth and division, and mechanical properties. Integral for the research is the iterative evaluation of the models and their parameters to new experimental data, mainly in the form of live microscopy data.
One focus is on the understanding of the development of new primordia at the periphery of the shoot apex, where the phytohormone auxin is focused to the sites where new organs form, and this is accomplished via an intricate feedback to its own transport. At the same time physical stresses can provide the required intercellular connection for the regulated transport. We also suggest that stresses are sensed when creating new fibers, such that primordia growth becomes regulated and correlated with the positioning. The models we develop hence require a mechanistic description of molecular reactions transport and signalling, physical stresses and growth, and the possibility of interactions in between.
Another problem we are studying is the regulation and plasticity of the cells in the shoot apical meristem, which keeps its general cell differentiation pattern throughout the life of a plant, even if the cells are replaced during the symplastic growth where cells are moving out of the meristem tissue. We have focused on developing models for gene regulation and intercellular signalling, where the experimentally known CLAVATA-WUSCHEL negative feedback provides the core of the network. We develop models and optimise and evaluate model parameters towards large sets of perturbation experiments, where our approach focus on regions of parameters to describe the model network behavior. Also of interest is the receptor cross-talk that is part of this regulatory system.
Publications List on Google Scholar
Publications from Elements
2024 (No publication date)
2022 (No publication date)
2020 (No publication date)
2019 (No publication date)
2018 (No publication date)
2017 (No publication date)
2024
Doi: http://doi.org/10.1016/j.cub.2024.04.016
2023
Doi: 10.1073/pnas.2302985120
Doi: 10.1103/PhysRevE.108.064414
2022
Doi: 10.1038/s41467-022-30177-y
Doi: 10.1016/j.pbi.2022.102262
Doi: 10.3389/fpls.2022.827147
2021 (Accepted for publication)
2021
Doi: http://doi.org/10.1126/science.abe2305
Doi: 10.1016/j.cub.2021.05.019
2020 (Accepted for publication)
Doi: 10.1073/pnas.2003184117
2020
Doi: 10.1371/journal.pcbi.1007982
2019
Doi: http://doi.org/10.7554/eLife.39298
Doi: 10.1101/781708
Doi: 10.1098/rspa.2019.0015
Doi: 10.1038/s41580-019-0144-0
Doi: 10.1016/j.devcel.2019.06.002
Doi: 10.7554/eLife.39298
2018 (Accepted for publication)
Doi: 10.1038/s41540-018-0072-1
2018
Doi: 10.1073/pnas.1718670115
Doi: 10.7554/eLife.38161
2017 (Accepted for publication)
Doi: 10.7554/eLife.19131
2017
Doi: 10.1101/210138
Doi: 10.1101/200303
Doi: http://doi.org/10.7554/elife.19131
Doi: 10.1371/journal.pone.0175251
Doi: 10.7554/eLife.27421
2016
Doi: 10.1016/j.pbi.2015.12.009
Doi: 10.1126/sciadv.1500989
Doi: 10.1038/ng.3567
Doi: 10.1016/j.cub.2016.09.044
Doi: 10.3389/fpls.2016.01560
Doi: 10.1088/1478-3975/13/6/065002
Doi: 10.1073/pnas.1616768113
2014
Doi: 10.7554/eLife.01967
2013
Doi: 10.1038/msb.2013.8
Doi: 10.1104/pp.113.214023
2012
Doi: 10.1016/j.pbi.2011.09.007
2011
Doi: 10.1101/gad.17258511
Doi: 10.1016/j.pbi.2011.09.007
Doi: http://doi.org/10.1186/1752-0509-5-2
2010
Doi: 10.1371/journal.pbio.1000516
Doi: 10.1371/journal.pcbi.1000819
Doi: 10.1016/j.pbi.2009.10.002
Doi: 10.1371/journal.pbio.1000516
Doi: 10.1371/journal.pcbi.1000819
Doi: 10.1371/journal.pone.0011750
Doi: 10.1101/cshperspect.a001560
2009
Doi: 10.1016/j.jtbi.2009.01.019
Doi: 10.1007/978-3-642-02466-5_97
2008
Doi: 10.1126/science.1165594
2007
Doi: 10.1016/j.pbi.2006.11.005
Doi: 10.1371/journal.pbio.0050302
Doi: 10.1371/journal.pbio.0050302
2006
Doi: 10.1007/s00344-006-0080-z
Doi: 10.1073/pnas.0509839103
Doi: 10.1529/biophysj.105.080408
Doi: 10.1007/s00344-006-0066-x
2005
Doi: 10.1137/040603255
Doi: 10.1093/bioinformatics/bti1036
2003
Doi: 10.1089/106652703322539060
2002
Doi: 10.1016/S0004-3702(02)00291-6
2001
Doi: 10.1162/08997660152469369
2018 (Accepted for publication)
Doi: http://doi.org/10.1007/978-3-319-99070-5_6
2003
Doi: 10.1016/b978-012428765-5/50041-4
2017
Doi: http://doi.org/10.1016/j.mod.2017.04.182
2016
Doi: http://doi.org/10.1109/ISBI.2016.7493464