@article{ApeltBreuerNikoloskietal.2015, author = {Apelt, Federico and Breuer, David and Nikoloski, Zoran and Stitt, Mark and Kragler, Friedrich}, title = {Phytotyping(4D): a light-field imaging system for non-invasive and accurate monitoring of spatio-temporal plant growth}, series = {The plant journal}, volume = {82}, journal = {The plant journal}, number = {4}, publisher = {Wiley-Blackwell}, address = {Hoboken}, issn = {0960-7412}, doi = {10.1111/tpj.12833}, pages = {693 -- 706}, year = {2015}, abstract = {Integrative studies of plant growth require spatially and temporally resolved information from high-throughput imaging systems. However, analysis and interpretation of conventional two-dimensional images is complicated by the three-dimensional nature of shoot architecture and by changes in leaf position over time, termed hyponasty. To solve this problem, Phytotyping(4D) uses a light-field camera that simultaneously provides a focus image and a depth image, which contains distance information about the object surface. Our automated pipeline segments the focus images, integrates depth information to reconstruct the three-dimensional architecture, and analyses time series to provide information about the relative expansion rate, the timing of leaf appearance, hyponastic movement, and shape for individual leaves and the whole rosette. Phytotyping(4D) was calibrated and validated using discs of known sizes, and plants tilted at various orientations. Information from this analysis was integrated into the pipeline to allow error assessment during routine operation. To illustrate the utility of Phytotyping(4D), we compare diurnal changes in Arabidopsis thaliana wild-type Col-0 and the starchless pgm mutant. Compared to Col-0, pgm showed very low relative expansion rate in the second half of the night, a transiently increased relative expansion rate at the onset of light period, and smaller hyponastic movement including delayed movement after dusk, both at the level of the rosette and individual leaves. Our study introduces light-field camera systems as a tool to accurately measure morphological and growth-related features in plants. Significance Statement Phytotyping(4D) is a non-invasive and accurate imaging system that combines a 3D light-field camera with an automated pipeline, which provides validated measurements of growth, movement, and other morphological features at the rosette and single-leaf level. In a case study in which we investigated the link between starch and growth, we demonstrated that Phytotyping(4D) is a key step towards bridging the gap between phenotypic observations and the rich genetic and metabolic knowledge.}, language = {en} } @article{HussJuddKoperetal.2022, author = {Huß, Sebastian and Judd, Rika Siedah and Koper, Kaan and Maeda, Hiroshi A. and Nikoloski, Zoran}, title = {An automated workflow that generates atom mappings for large-scale metabolic models and its application to Arabidopsis thaliana}, series = {The plant journal}, volume = {111}, journal = {The plant journal}, number = {5}, publisher = {Wiley-Blackwell}, address = {Oxford [u.a.]}, issn = {0960-7412}, doi = {10.1111/tpj.15903}, pages = {1486 -- 1500}, year = {2022}, abstract = {Quantification of reaction fluxes of metabolic networks can help us understand how the integration of different metabolic pathways determines cellular functions. Yet, intracellular fluxes cannot be measured directly but are estimated with metabolic flux analysis (MFA), which relies on the patterns of isotope labeling of metabolites in the network. The application of MFA also requires a stoichiometric model with atom mappings that are currently not available for the majority of large-scale metabolic network models, particularly of plants. While automated approaches such as the Reaction Decoder Toolkit (RDT) can produce atom mappings for individual reactions, tracing the flow of individual atoms of the entire reactions across a metabolic model remains challenging. Here we establish an automated workflow to obtain reliable atom mappings for large-scale metabolic models by refining the outcome of RDT, and apply the workflow to metabolic models of Arabidopsis thaliana. We demonstrate the accuracy of RDT through a comparative analysis with atom mappings from a large database of biochemical reactions, MetaCyc. We further show the utility of our automated workflow by simulating N-15 isotope enrichment and identifying nitrogen (N)-containing metabolites which show enrichment patterns that are informative for flux estimation in future N-15-MFA studies of A. thaliana. The automated workflow established in this study can be readily expanded to other species for which metabolic models have been established and the resulting atom mappings will facilitate MFA and graph-theoretic structural analyses with large-scale metabolic networks.}, language = {en} } @article{JueppnerMubeenLeisseetal.2017, author = {J{\"u}ppner, Jessica and Mubeen, Umarah and Leisse, Andrea and Caldana, Camila and Brust, Henrike and Steup, Martin and Herrmann, Marion and Steinhauser, Dirk and Giavalisco, Patrick}, title = {Dynamics of lipids and metabolites during the cell cycle of Chlamydomonas reinhardtii}, series = {The plant journal}, volume = {92}, journal = {The plant journal}, publisher = {Wiley}, address = {Hoboken}, issn = {0960-7412}, doi = {10.1111/tpj.13642}, pages = {331 -- 343}, year = {2017}, abstract = {Metabolites and lipids are the final products of enzymatic processes, distinguishing the different cellular functions and activities of single cells or whole tissues. Understanding these cellular functions within a well-established model system requires a systemic collection of molecular and physiological information. In the current report, the green alga Chlamydomonas reinhardtii was selected to establish a comprehensive workflow for the detailed multi-omics analysis of a synchronously growing cell culture system. After implementation and benchmarking of the synchronous cell culture, a two-phase extraction method was adopted for the analysis of proteins, lipids, metabolites and starch from a single sample aliquot of as little as 10-15million Chlamydomonas cells. In a proof of concept study, primary metabolites and lipids were sampled throughout the diurnal cell cycle. The results of these time-resolved measurements showed that single compounds were not only coordinated with each other in different pathways, but that these complex metabolic signatures have the potential to be used as biomarkers of various cellular processes. Taken together, the developed workflow, including the synchronized growth of the photoautotrophic cell culture, in combination with comprehensive extraction methods and detailed metabolic phenotyping has the potential for use in in-depth analysis of complex cellular processes, providing essential information for the understanding of complex biological systems.}, language = {en} }