@misc{KuekenSommerYanevaRoderetal.2018, author = {K{\"u}ken, Anika and Sommer, Frederik and Yaneva-Roder, Liliya and Mackinder, Luke C.M. and H{\"o}hne, Melanie and Geimer, Stefan and Jonikas, Martin C. and Schroda, Michael and Stitt, Mark and Nikoloski, Zoran and Mettler-Altmann, Tabea}, title = {Effects of microcompartmentation on flux distribution and metabolic pools in Chlamydomonas reinhardtii chloroplasts}, series = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, journal = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, number = {1122}, issn = {1866-8372}, doi = {10.25932/publishup-44635}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-446358}, pages = {25}, year = {2018}, abstract = {Cells and organelles are not homogeneous but include microcompartments that alter the spatiotemporal characteristics of cellular processes. The effects of microcompartmentation on metabolic pathways are however difficult to study experimentally. The pyrenoid is a microcompartment that is essential for a carbon concentrating mechanism (CCM) that improves the photosynthetic performance of eukaryotic algae. Using Chlamydomonas reinhardtii, we obtained experimental data on photosynthesis, metabolites, and proteins in CCM-induced and CCM-suppressed cells. We then employed a computational strategy to estimate how fluxes through the Calvin-Benson cycle are compartmented between the pyrenoid and the stroma. Our model predicts that ribulose-1,5-bisphosphate (RuBP), the substrate of Rubisco, and 3-phosphoglycerate (3PGA), its product, diffuse in and out of the pyrenoid, respectively, with higher fluxes in CCM-induced cells. It also indicates that there is no major diffusional barrier to metabolic flux between the pyrenoid and stroma. Our computational approach represents a stepping stone to understanding microcompartmentalized CCM in other organisms.}, language = {en} } @article{deAbreueLimaWillmitzerNikoloski2018, author = {de Abreu e Lima, Francisco Anastacio and Willmitzer, Lothar and Nikoloski, Zoran}, title = {Classification-driven framework to predict maize hybrid field performance from metabolic profiles of young parental roots}, series = {PLoS one}, volume = {13}, journal = {PLoS one}, number = {4}, publisher = {PLoS}, address = {San Fransisco}, issn = {1932-6203}, doi = {10.1371/journal.pone.0196038}, pages = {16}, year = {2018}, abstract = {Maize (Zea mays L.) is a staple food whose production relies on seed stocks that largely comprise hybrid varieties. Therefore, knowledge about the molecular determinants of hybrid performance (HP) in the field can be used to devise better performing hybrids to address the demands for sustainable increase in yield. Here, we propose and test a classification-driven framework that uses metabolic profiles from in vitro grown young roots of parental lines from the Dent x Flint maize heterotic pattern to predict field HP. We identify parental analytes that best predict the metabolic inheritance patterns in 328 hybrids. We then demonstrate that these analytes are also predictive of field HP (0.64 >= r >= 0.79) and discriminate hybrids of good performance (accuracy of 87.50\%). Therefore, our approach provides a cost-effective solution for hybrid selection programs.}, language = {en} } @misc{LaitinenNikoloski2018, author = {Laitinen, Roosa A. E. and Nikoloski, Zoran}, title = {Genetic basis of plasticity in plants}, series = {Journal of experimental botany}, volume = {70}, journal = {Journal of experimental botany}, number = {3}, publisher = {Oxford Univ. Press}, address = {Oxford}, issn = {0022-0957}, doi = {10.1093/jxb/ery404}, pages = {739 -- 745}, year = {2018}, abstract = {The ability of an organism to change its phenotype in response to different environments, termed plasticity, is a particularly important characteristic to enable sessile plants to adapt to rapid changes in their surroundings. Plasticity is a quantitative trait that can provide a fitness advantage and mitigate negative effects due to environmental perturbations. Yet, its genetic basis is not fully understood. Alongside technological limitations, the main challenge in studying plasticity has been the selection of suitable approaches for quantification of phenotypic plasticity. Here, we propose a categorization of the existing quantitative measures of phenotypic plasticity into nominal and relative approaches. Moreover, we highlight the recent advances in the understanding of the genetic architecture underlying phenotypic plasticity in plants. We identify four pillars for future research to uncover the genetic basis of phenotypic plasticity, with emphasis on development of computational approaches and theories. These developments will allow us to perform specific experiments to validate the causal genes for plasticity and to discover their role in plant fitness and evolution.}, language = {en} } @article{deAbreueLimaLiWenetal.2018, author = {de Abreu e Lima, Francisco Anastacio and Li, Kun and Wen, Weiwei and Yan, Jianbing and Nikoloski, Zoran and Willmitzer, Lothar and Brotman, Yariv}, title = {Unraveling lipid metabolism in maize with time-resolved multi-omics data}, series = {The plant journal}, volume = {93}, journal = {The plant journal}, number = {6}, publisher = {Wiley}, address = {Hoboken}, issn = {0960-7412}, doi = {10.1111/tpj.13833}, pages = {1102 -- 1115}, year = {2018}, abstract = {Maize is the cereal crop with the highest production worldwide, and its oil is a key energy resource. Improving the quantity and quality of maize oil requires a better understanding of lipid metabolism. To predict the function of maize genes involved in lipid biosynthesis, we assembled transcriptomic and lipidomic data sets from leaves of B73 and the high-oil line By804 in two distinct time-series experiments. The integrative analysis based on high-dimensional regularized regression yielded lipid-transcript associations indirectly validated by Gene Ontology and promoter motif enrichment analyses. The co-localization of lipid-transcript associations using the genetic mapping of lipid traits in leaves and seedlings of a B73 x By804 recombinant inbred line population uncovered 323 genes involved in the metabolism of phospholipids, galactolipids, sulfolipids and glycerolipids. The resulting association network further supported the involvement of 50 gene candidates in modulating levels of representatives from multiple acyl-lipid classes. Therefore, the proposed approach provides high-confidence candidates for experimental testing in maize and model plant species.}, language = {en} } @article{RodriguezCubillosTongAlseekhetal.2018, author = {Rodriguez Cubillos, Andres Eduardo and Tong, Hao and Alseekh, Saleh and de Abreu e Lima, Francisco Anastacio and Yu, Jing and Fernie, Alisdair R. and Nikoloski, Zoran and Laitinen, Roosa A. E.}, title = {Inheritance patterns in metabolism and growth in diallel crosses of Arabidopsis thaliana from a single growth habitat}, series = {Heredity}, volume = {120}, journal = {Heredity}, number = {5}, publisher = {Nature Publ. Group}, address = {London}, issn = {0018-067X}, doi = {10.1038/s41437-017-0030-5}, pages = {463 -- 473}, year = {2018}, abstract = {Metabolism is a key determinant of plant growth and modulates plant adaptive responses. Increased metabolic variation due to heterozygosity may be beneficial for highly homozygous plants if their progeny is to respond to sudden changes in the habitat. Here, we investigate the extent to which heterozygosity contributes to the variation in metabolism and size of hybrids of Arabidopsis thaliana whose parents are from a single growth habitat. We created full diallel crosses among seven parents, originating from Southern Germany, and analysed the inheritance patterns in primary and secondary metabolism as well as in rosette size in situ. In comparison to primary metabolites, compounds from secondary metabolism were more variable and showed more pronounced non-additive inheritance patterns which could be attributed to epistasis. In addition, we showed that glucosinolates, among other secondary metabolites, were positively correlated with a proxy for plant size. Therefore, our study demonstrates that heterozygosity in local A. thaliana population generates metabolic variation and may impact several tasks directly linked to metabolism.}, language = {en} } @article{SchwahnNikoloski2018, author = {Schwahn, Kevin and Nikoloski, Zoran}, title = {Data reduction approaches for dissecting transcriptional effects on metabolism}, series = {Frontiers in plant science}, volume = {9}, journal = {Frontiers in plant science}, publisher = {Frontiers Research Foundation}, address = {Lausanne}, issn = {1664-462X}, doi = {10.3389/fpls.2018.00538}, pages = {12}, year = {2018}, abstract = {The availability of high-throughput data from transcriptomics and metabolomics technologies provides the opportunity to characterize the transcriptional effects on metabolism. Here we propose and evaluate two computational approaches rooted in data reduction techniques to identify and categorize transcriptional effects on metabolism by combining data on gene expression and metabolite levels. The approaches determine the partial correlation between two metabolite data profiles upon control of given principal components extracted from transcriptomics data profiles. Therefore, they allow us to investigate both data types with all features simultaneously without doing preselection of genes. The proposed approaches allow us to categorize the relation between pairs of metabolites as being under transcriptional or post-transcriptional regulation. The resulting classification is compared to existing literature and accumulated evidence about regulatory mechanism of reactions and pathways in the cases of Escherichia coil, Saccharomycies cerevisiae, and Arabidopsis thaliana.}, language = {en} } @article{deAbreueLimaLeifelsNikoloski2018, author = {de Abreu e Lima, Francisco Anastacio and Leifels, Lydia and Nikoloski, Zoran}, title = {Regression-based modeling of complex plant traits based on metabolomics data}, series = {Plant Metabolomics}, volume = {1778}, journal = {Plant Metabolomics}, publisher = {Humana Press Inc.}, address = {New York}, isbn = {978-1-4939-7819-9}, issn = {1064-3745}, doi = {10.1007/978-1-4939-7819-9_23}, pages = {321 -- 327}, year = {2018}, abstract = {Bridging metabolomics with plant phenotypic responses is challenging. Multivariate analyses account for the existing dependencies among metabolites, and regression models in particular capture such dependencies in search for association with a given trait. However, special care should be undertaken with metabolomics data. Here we propose a modeling workflow that considers all caveats imposed by such large data sets.}, language = {en} } @article{JanowskiZoschkeScharffetal.2018, author = {Janowski, Marcin Andrzej and Zoschke, Reimo and Scharff, Lars B. and Jaime, Silvia Martinez and Ferrari, Camilla and Proost, Sebastian and Xiong, Jonathan Ng Wei and Omranian, Nooshin and Musialak-Lange, Magdalena and Nikoloski, Zoran and Graf, Alexander and Schoettler, Mark Aurel and Sampathkumar, Arun and Vaid, Neha and Mutwil, Marek}, title = {AtRsgA from Arabidopsis thaliana is important for maturation of the small subunit of the chloroplast ribosome}, series = {The plant journal}, volume = {96}, journal = {The plant journal}, number = {2}, publisher = {Wiley}, address = {Hoboken}, issn = {0960-7412}, doi = {10.1111/tpj.14040}, pages = {404 -- 420}, year = {2018}, abstract = {Plastid ribosomes are very similar in structure and function to the ribosomes of their bacterial ancestors. Since ribosome biogenesis is not thermodynamically favorable under biological conditions it requires the activity of many assembly factors. Here we have characterized a homolog of bacterial RsgA in Arabidopsis thaliana and show that it can complement the bacterial homolog. Functional characterization of a strong mutant in Arabidopsis revealed that the protein is essential for plant viability, while a weak mutant produced dwarf, chlorotic plants that incorporated immature pre-16S ribosomal RNA into translating ribosomes. Physiological analysis of the mutant plants revealed smaller, but more numerous, chloroplasts in the mesophyll cells, reduction of chlorophyll a and b, depletion of proplastids from the rib meristem and decreased photosynthetic electron transport rate and efficiency. Comparative RNA sequencing and proteomic analysis of the weak mutant and wild-type plants revealed that various biotic stress-related, transcriptional regulation and post-transcriptional modification pathways were repressed in the mutant. Intriguingly, while nuclear- and chloroplast-encoded photosynthesis-related proteins were less abundant in the mutant, the corresponding transcripts were increased, suggesting an elaborate compensatory mechanism, potentially via differentially active retrograde signaling pathways. To conclude, this study reveals a chloroplast ribosome assembly factor and outlines the transcriptomic and proteomic responses of the compensatory mechanism activated during decreased chloroplast function. Significance Statement AtRsgA is an assembly factor necessary for maturation of the small subunit of the chloroplast ribosome. Depletion of AtRsgA leads to dwarfed, chlorotic plants, a decrease of mature 16S rRNA and smaller, but more numerous, chloroplasts. Large-scale transcriptomic and proteomic analysis revealed that chloroplast-encoded and -targeted proteins were less abundant, while the corresponding transcripts were increased in the mutant. We analyze the transcriptional responses of several retrograde signaling pathways to suggest the mechanism underlying this compensatory response.}, language = {en} } @article{KuekenSommerYanevaRoderetal.2018, author = {K{\"u}ken, Anika and Sommer, Frederik and Yaneva-Roder, Liliya and Mackinder, Luke C. M. and Hoehne, Melanie and Geimer, Stefan and Jonikas, Martin C. and Schroda, Michael and Stitt, Mark and Nikoloski, Zoran and Mettler-Altmann, Tabea}, title = {Effects of microcompartmentation on flux distribution and metabolic pools in Chlamydomonas reinhardtii chloroplasts}, series = {eLife}, volume = {7}, journal = {eLife}, publisher = {eLife Sciences Publications}, address = {Cambridge}, issn = {2050-084X}, doi = {10.7554/eLife.37960}, pages = {23}, year = {2018}, abstract = {Cells and organelles are not homogeneous but include microcompartments that alter the spatiotemporal characteristics of cellular processes. The effects of microcompartmentation on metabolic pathways are however difficult to study experimentally. The pyrenoid is a microcompartment that is essential for a carbon concentrating mechanism (CCM) that improves the photosynthetic performance of eukaryotic algae. Using Chlamydomonas reinhardtii, we obtained experimental data on photosynthesis, metabolites, and proteins in CCM-induced and CCM-suppressed cells. We then employed a computational strategy to estimate how fluxes through the Calvin-Benson cycle are compartmented between the pyrenoid and the stroma. Our model predicts that ribulose-1,5-bisphosphate (RuBP), the substrate of Rubisco, and 3-phosphoglycerate (3PGA), its product, diffuse in and out of the pyrenoid, respectively, with higher fluxes in CCM-induced cells. It also indicates that there is no major diffusional barrier to metabolic flux between the pyrenoid and stroma. Our computational approach represents a stepping stone to understanding microcompartmentalized CCM in other organisms.}, language = {en} } @article{ScheunemannBradyNikoloski2018, author = {Scheunemann, Michael and Brady, Siobhan M. and Nikoloski, Zoran}, title = {Integration of large-scale data for extraction of integrated Arabidopsis root cell-type specific models}, series = {Scientific reports}, volume = {8}, journal = {Scientific reports}, publisher = {Nature Publ. Group}, address = {London}, issn = {2045-2322}, doi = {10.1038/s41598-018-26232-8}, pages = {15}, year = {2018}, abstract = {Plant organs consist of multiple cell types that do not operate in isolation, but communicate with each other to maintain proper functions. Here, we extract models specific to three developmental stages of eight root cell types or tissue layers in Arabidopsis thaliana based on a state-of-the-art constraint-based modeling approach with all publicly available transcriptomics and metabolomics data from this system to date. We integrate these models into a multi-cell root model which we investigate with respect to network structure, distribution of fluxes, and concordance to transcriptomics and proteomics data. From a methodological point, we show that the coupling of tissue-specific models in a multi-tissue model yields a higher specificity of the interconnected models with respect to network structure and flux distributions. We use the extracted models to predict and investigate the flux of the growth hormone indole-3-actetate and its antagonist, trans-Zeatin, through the root. While some of predictions are in line with experimental evidence, constraints other than those coming from the metabolic level may be necessary to replicate the flow of indole-3-actetate from other simulation studies. Therefore, our work provides the means for data-driven multi-tissue metabolic model extraction of other Arabidopsis organs in the constraint-based modeling framework.}, language = {en} } @misc{BaslerFernieNikoloski2018, author = {Basler, Georg and Fernie, Alisdair R. and Nikoloski, Zoran}, title = {Advances in metabolic flux analysis toward genome-scale profiling of higher organisms}, series = {Bioscience reports : communications and reviews in molecular and cellular biology}, volume = {38}, journal = {Bioscience reports : communications and reviews in molecular and cellular biology}, publisher = {Portland Press (London)}, address = {London}, issn = {0144-8463}, doi = {10.1042/BSR20170224}, pages = {11}, year = {2018}, abstract = {Methodological and technological advances have recently paved the way for metabolic flux profiling in higher organisms, like plants. However, in comparison with omics technologies, flux profiling has yet to provide comprehensive differential flux maps at a genome-scale and in different cell types, tissues, and organs. Here we highlight the recent advances in technologies to gather metabolic labeling patterns and flux profiling approaches. We provide an opinion of how recent local flux profiling approaches can be used in conjunction with the constraint-based modeling framework to arrive at genome-scale flux maps. In addition, we point at approaches which use metabolomics data without introduction of label to predict either non-steady state fluxes in a time-series experiment or flux changes in different experimental scenarios. The combination of these developments allows an experimentally feasible approach for flux-based large-scale systems biology studies.}, language = {en} }