570 Biowissenschaften; Biologie
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Determining the relationship between genotype and phenotype is the key to understand the plasticity and robustness of phenotypes in nature. While the directly observable plant phenotypes (e.g. agronomic, yield and stress resistance traits) have been well-investigated, there is still a lack in our knowledge about the genetic basis of intermediate phenotypes, such as metabolic phenotypes. Dissecting the links between genotype and phenotype depends on suitable statistical models. The state-of-the-art models are developed for directly observable phenotypes, regardless the characteristics of intermediate phenotypes. This thesis aims to fill the gaps in understanding genetic architecture of intermediate phenotypes, and how they tie to composite traits, namely plant growth. The metabolite levels and reaction fluxes, as two aspects of metabolic phenotypes, are shaped by the interrelated chemical reactions formed in genome-scale metabolic network. Here, I attempt to answer the question: Can the knowledge of underlying genome-scale metabolic network improve the model performance for prediction of metabolic phenotypes and associated plant growth? To this end, two projects are investigated in this thesis. Firstly, we propose an approach that couples genomic selection with genome-scale metabolic network and metabolic profiles in Arabidopsis thaliana to predict growth. This project is the first integration of genomic data with fluxes predicted based on constraint-based modeling framework and data on biomass composition. We demonstrate that our approach leads to a considerable increase of prediction accuracy in comparison to the state-of-the-art methods in both within and across environment predictions. Therefore, our work paves the way for combining knowledge on metabolic mechanisms in the statistical approach underlying genomic selection to increase the efficiency of future plant breeding approaches. Secondly, we investigate how reliable is genomic selection for metabolite levels, and which single nucleotide polymorphisms (SNPs), obtained from different neighborhoods of a given metabolic network, contribute most to the accuracy of prediction. The results show that the local structure of first and second neighborhoods are not sufficient for predicting the genetic basis of metabolite levels in Zea mays. Furthermore, we find that the enzymatic SNPs can capture most the genetic variance and the contribution of non-enzymatic SNPs is in fact small. To comprehensively understand the genetic architecture of metabolic phenotypes, I extend my study to a local Arabidopsis thaliana population and their hybrids. We analyze the genetic architecture in primary and secondary metabolism as well as in growth. In comparison to primary metabolites, compounds from secondary metabolism were more variable and show more non-additive inheritance patterns which could be attributed to epistasis. Therefore, our study demonstrates that heterozygosity in local Arabidopsis thaliana population generates metabolic variation and may impact several tasks directly linked to metabolism. The studies in this thesis improve the knowledge of genetic architecture of metabolic phenotypes in both inbreed and hybrid population. The approaches I proposed to integrate genome-scale metabolic network with genomic data provide the opportunity to obtain mechanistic insights about the determinants of agronomically important polygenic traits.
How much do we really lose?
(2019)
Natural landscape elements (NLEs) in agricultural landscapes contribute to biodiversity and ecosystem services, but are also regarded as an obstacle for large‐scale agricultural production. However, the effects of NLEs on crop yield have rarely been measured. Here, we investigated how different bordering structures, such as agricultural roads, field‐to‐field borders, forests, hedgerows, and kettle holes, influence agricultural yields. We hypothesized that (a) yield values at field borders differ from mid‐field yields and that (b) the extent of this change in yields depends on the bordering structure.
We measured winter wheat yields along transects with log‐scaled distances from the border into the agricultural field within two intensively managed agricultural landscapes in Germany (2014 near Göttingen, and 2015–2017 in the Uckermark).
We observed a yield loss adjacent to every investigated bordering structure of 11%–38% in comparison with mid‐field yields. However, depending on the bordering structure, this yield loss disappeared at different distances. While the proximity of kettle holes did not affect yields more than neighboring agricultural fields, woody landscape elements had strong effects on winter wheat yields. Notably, 95% of mid‐field yields could already be reached at a distance of 11.3 m from a kettle hole and at a distance of 17.8 m from hedgerows as well as forest borders.
Our findings suggest that yield losses are especially relevant directly adjacent to woody landscape elements, but not adjacent to in‐field water bodies. This highlights the potential to simultaneously counteract yield losses close to the field border and enhance biodiversity by combining different NLEs in agricultural landscapes such as creating strips of extensive grassland vegetation between woody landscape elements and agricultural fields. In conclusion, our results can be used to quantify ecocompensations to find optimal solutions for the delivery of productive and regulative ecosystem services in heterogeneous agricultural landscapes.
Global change threatens the maintenance of ecosystem functions that are shaped by the persistence and dynamics of populations. It has been shown that the persistence of species increases if they possess larger trait adaptability. Here, we investigate whether trait adaptability also affects the robustness of population dynamics of interacting species and thereby shapes the reliability of ecosystem functions that are driven by these dynamics. We model co‐adaptation in a predator–prey system as changes to predator offense and prey defense due to evolution or phenotypic plasticity. We investigate how trait adaptation affects the robustness of population dynamics against press perturbations to environmental parameters and against pulse perturbations targeting species abundances and their trait values. Robustness of population dynamics is characterized by resilience, elasticity, and resistance. In addition to employing established measures for resilience and elasticity against pulse perturbations (extinction probability and return time), we propose the warping distance as a new measure for resistance against press perturbations, which compares the shapes and amplitudes of pre‐ and post‐perturbation population dynamics. As expected, we find that the robustness of population dynamics depends on the speed of adaptation, but in nontrivial ways. Elasticity increases with speed of adaptation as the system returns more rapidly to the pre‐perturbation state. Resilience, in turn, is enhanced by intermediate speeds of adaptation, as here trait adaptation dampens biomass oscillations. The resistance of population dynamics strongly depends on the target of the press perturbation, preventing a simple relationship with the adaptation speed. In general, we find that low robustness often coincides with high amplitudes of population dynamics. Hence, amplitudes may indicate the robustness against perturbations also in other natural systems with similar dynamics. Our findings show that besides counteracting extinctions, trait adaptation indeed strongly affects the robustness of population dynamics against press and pulse perturbations.
Hormonal regulation of neuronal mitochondrial unfolded protein response and its impact on metabolism
(2019)
The hypothalamus is the main brain area of central regulation of whole body metabolism through impacting food intake and energy expenditure. For the complex regulation, high amounts of energy are needed and mainly provided by mitochondria. Hence, mitochondrial function is crucial for cell homeostasis and modulates central insulin sensitivity. Thus, mitochondrial dysfunction is associated with insulin resistance in the brain and therefore is involved in the pathogenesis of type-2 diabetes (T2D). Mitochondrial health and protein homeostasis is propagated by mitochondrial stress responses like e.g. mitochondrial unfolded protein response (UPRmt). Therefore, studies regarding the regulation of mitochondrial homeostasis are crucial for understanding its effects on the central nervous system (CNS) for the progression of metabolic and nutrition-dependent disorders.
One main aim of this thesis was to investigate the metabolic regulation of mitochondrial stress responsiveness in the hypothalamus. The observed results showed that functional ERK-dependent insulin signaling is needed for regulation of mitochondrial stress response (MSR) genes and positively impacted the metabolism by controlling mitochondrial proteostasis without affecting mitochondrial biogenesis.
To further explore the role of MSR genes for brain cell homeostasis and its consequences for the metabolism, one of the key players - the mitochondrial chaperone heat shock protein 10 (Hsp10) – was studied in detail. Hsp10 expression was decreased in insulin-resistant, hyperglycemic db/db mice brains along with increased protein oxidation. Leptin, another key hormone in regulating metabolism, was able to induce Hsp10 in neurons. Appropriately, lentiviral-mediated knock down (KD) of Hsp10 introduced into hypothalamic CLU-183 cells induced mitochondrial dysfunction, altered mitochondrial dynamics and increased contact sites between mitochondria and endoplasmic reticulum (ER). In addition, Hsp10 KD caused cellular insulin resistance along with increasing oxidative stress specifically in mitochondrial fraction.
Interestingly, acute Hsp10 KD in the arcuate nucleus of the hypothalamus in C57BL/6N male mice did not change body weight or food intake, but it increased plasma leptin concentrations suggesting an effect on global leptin signaling. It increased hepatic markers of gluconeogenesis and hepatic insulin resistance along with features of low-grade inflammation.
Long-term studies of hypothalamic Hsp10 KD mice revealed unaltered systemic insulin sensitivity. The demonstrated increase in markers of hepatic gluconeogenesis of acute Hsp10 KD was still exhibited after 13 weeks, but insulin resistance in the liver was no longer observed.
In conclusion, hypothalamic insulin action regulates MSR and ensures proper mitochondrial function which positively affects metabolism. In addition, hypothalamic Hsp10 acts as a modulator of both insulin and leptin signaling and is identified as pivotal for the regulation of central mitochondrial function as well as insulin sensitivity in the brain and it impacts liver function. It may present a regulator of brain-liver crosstalk influencing hepatic gluconeogenesis and insulin sensitivity through a novel regulatory signaling mechanism.
STERILE APETALA (SAP) is known to be an essential regulator of flower development for over 20 years. Loss of SAP function in the model plant Arabidopsis thaliana is associated with a reduction of floral organ number, size and fertility. In accordance with the function of SAP during early flower development, its spatial expression in flowers is confined to meristematic stages and to developing ovules. However, to date, despite extensive research, the molecular function of SAP and the regulation of its spatio-temporal expression still remain elusive.
In this work, amino acid sequence analysis and homology modeling revealed that SAP belongs to the rare class of plant F-box proteins with C-terminal WD40 repeats. In opisthokonts, this type of F-box proteins constitutes the substrate binding subunit of SCF complexes, which catalyze the ubiquitination of proteins to initiate their proteasomal degradation. With LC-MS/MS-based protein complex isolation, the interaction of SAP with major SCF complex subunits was confirmed. Additionally, candidate substrate proteins, such as the growth repressor PEAPOD 1 and 2 (PPD1/2), could be revealed during early stages of flower development. Also INDOLE-3-BUTYRIC ACID RESPONSE 5 (IBR5) was identified among putative interactors. Genetic analyses indicated that, different from substrate proteins, IBR5 is required for SAP function. Protein complex isolation together with transcriptome profiling emphasized that the SCFSAP complex integrates multiple biological processes, such as proliferative growth, vascular development, hormonal signaling and reproduction. Phenotypic analysis of sap mutant and SAP overexpressing plants positively correlated SAP function with plant growth during reproductive and vegetative development.
Furthermore, to elaborate on the transcriptional regulation of SAP, publicly available ChIP-seq data of key floral homeotic proteins were reanalyzed. Here, it was shown that the MADS-domain transcription factors APETALA 1 (AP1), APETALA 3 (AP3), PISTILLATA (PI), AGAMOUS (AG) and SEPALLATA 3 (SEP3) bind to the SAP locus, which indicates that SAP is expressed in a floral organ-specific manner. Reporter gene analyses in combination with CRISPR/Cas9-mediated deletion of putative regulatory regions further demonstrated that the intron contains major regulatory elements of SAP in Arabidopsis thaliana.
In conclusion, these data indicate that SAP is a pleiotropic developmental regulator that acts through tissue-specific destabilization of proteins. The presumed transcriptional regulation of SAP by the floral MADS-domain transcription factors could provide a missing link between the specification of floral organ identity and floral organ growth pathways.