@phdthesis{Schlossarek2023, author = {Schlossarek, Dennis}, title = {Identification of dynamic protein-metabolite complexes in saccharomyces cerevisiae using co-fractionation mass spectrometry}, doi = {10.25932/publishup-58282}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-582826}, school = {Universit{\"a}t Potsdam}, pages = {123}, year = {2023}, abstract = {Cells are built from a variety of macromolecules and metabolites. Both, the proteome and the metabolome are highly dynamic and responsive to environmental cues and developmental processes. But it is not their bare numbers, but their interactions that enable life. The protein-protein (PPI) and protein-metabolite interactions (PMI) facilitate and regulate all aspects of cell biology, from metabolism to mitosis. Therefore, the study of PPIs and PMIs and their dynamics in a cell-wide context is of great scientific interest. In this dissertation, I aim to chart a map of the dynamic PPIs and PMIs across metabolic and cellular transitions. As a model system, I study the shift from the fermentative to the respiratory growth, known as the diauxic shift, in the budding yeast Saccharomyces cerevisiae. To do so, I am applying a co-fractionation mass spectrometry (CF-MS) based method, dubbed protein metabolite interactions using size separation (PROMIS). PROMIS, as well as comparable methods, will be discussed in detail in chapter 1. Since PROMIS was developed originally for Arabidopsis thaliana, in chapter 2, I will describe the adaptation of PROMIS to S. cerevisiae. Here, the obtained results demonstrated a wealth of protein-metabolite interactions, and experimentally validated 225 previously predicted PMIs. Applying orthogonal, targeted approaches to validate the interactions of a proteogenic dipeptide, Ser-Leu, five novel protein-interactors were found. One of those proteins, phosphoglycerate kinase, is inhibited by Ser-Leu, placing the dipeptide at the regulation of glycolysis. In chapter 3, I am presenting PROMISed, a novel web-tool designed for the analysis of PROMIS- and other CF-MS-datasets. Starting with raw fractionation profiles, PROMISed enables data pre-processing, profile deconvolution, scores differences in fractionation profiles between experimental conditions, and ultimately charts interaction networks. PROMISed comes with a user-friendly graphic interface, and thus enables the routine analysis of CF-MS data by non-computational biologists. Finally, in chapter 4, I applied PROMIS in combination with the isothermal shift assay to the diauxic shift in S. cerevisiae to study changes in the PPI and PMI landscape across this metabolic transition. I found a major rewiring of protein-protein-metabolite complexes, exemplified by the disassembly of the proteasome in the respiratory phase, the loss of interaction of an enzyme involved in amino acid biosynthesis and its cofactor, as well as phase and structure specific interactions between dipeptides and enzymes of central carbon metabolism. In chapter 5, I am summarizing the presented results, and discuss a strategy to unravel the potential patterns of dipeptide accumulation and binding specificities. Lastly, I recapitulate recently postulated guidelines for CF-MS experiments, and give an outlook of protein interaction studies in the near future.}, language = {en} } @phdthesis{Bulut2023, author = {Bulut, Mustafa}, title = {Assessing the genetic architecture underlying systemic responses to variable environments in crops using multi-omics}, school = {Universit{\"a}t Potsdam}, pages = {180, IV}, year = {2023}, abstract = {Plant metabolism serves as the primary mechanism for converting assimilated carbon into essential compounds crucial for plant growth and ultimately, crop yield. This renders it a focal point of research with significant implications. Despite notable strides in comprehending the genetic principles underpinning metabolism and yield, there remains a dearth of knowledge regarding the genetic factors responsible for trait variation under varying environmental conditions. Given the burgeoning global population and the advancing challenges posed by climate change, unraveling the intricacies of metabolic and yield responses to water scarcity became increasingly important in safeguarding food security. Our research group has recently started to work on the genetic resources of legume species. To this end, the study presented here investigates the metabolic diversity across five different legume species at a tissue level, identifying species-specific biosynthesis of alkaloids as well as iso-/flavonoids with diverse functional groups, namely prenylation, phenylacylation as well as methoxylation, to create a resource for follow up studies investigation the metabolic diversity in natural diverse populations of legume species. Following this, the second study investigates the genetic architecture of drought-induced changes in a global common bean population. Here, a plethora of quantitative trait loci (QTL) associated with various traits are identified by performing genome-wide association studies (GWAS), including for lipid signaling. On this site, overexpression of candidates highlighted the induction of several oxylipins reported to be pivotal in coping with harsh environmental conditions such as water scarcity. Diverging from the common bean and GWAS, the following study focuses on identifying drought-related QTL in tomato using a bi-parental breeding population. This descriptive study highlights novel multi-omic QTL, including metabolism, photosynthesis as well as fruit setting, some of which are uniquely assigned under drought. Compared to conventional approaches using the bi-parental IL population, the study presented improves the resolution by assessing further backcrossed ILs, named sub-ILs. In the final study, a photosynthetic gene, namely a PetM subunit of the cytochrome b6f complex encoding gene, involved in electron flow is characterized in an horticultural important crop. While several advances have been made in model organisms, this study highlights the transition of this fundamental knowledge to horticultural important crops, such as tomato, and investigates its function under differing light conditions. Overall, the presented thesis combines different strategies in unveiling the genetic components in multi-omic traits under drought using conventional breeding populations as well as a diverse global population. To this end, it allows a comparison of either approach and highlights their strengths and weaknesses.}, language = {en} } @phdthesis{LopesFernando2023, author = {Lopes Fernando, Raquel Sofia}, title = {The impact of aging on proteolytic systems, transcriptome and metabolome of slow and fast muscle fiber types}, doi = {10.25932/publishup-60579}, school = {Universit{\"a}t Potsdam}, pages = {XI, 125}, year = {2023}, abstract = {Aging is a complex process characterized by several factors, including loss of genetic and epigenetic information, accumulation of chronic oxidative stress, protein damage and aggregates and it is becoming an emergent drug target. Therefore, it is the utmost importance to study aging and agerelated diseases, to provide treatments to develop a healthy aging process. Skeletal muscle is one of the earliest tissues affected by age-related changes with progressive loss of muscle mass and function from 30 years old, effect known as sarcopenia. Several studies have shown the accumulation of protein aggregates in different animal models, as well as in humans, suggesting impaired proteostasis, a hallmark of aging, especially regarding degradation systems. Thus, different publications have explored the role of the main proteolytic systems in skeletal muscle from rodents and humans, like ubiquitin proteasomal system (UPS) and autophagy lysosomal system (ALS), however with contradictory results. Yet, most of the published studies are performed in muscles that comprise more than one fiber type, that means, muscles composed by slow and fast fibers. These fiber types, exhibit different metabolism and contraction speed; the slow fibers or type I display an oxidative metabolism, while fast fibers function towards a glycolytic metabolism ranging from fast oxidative to fast glycolytic fibers. To this extent, the aim of this thesis sought to understand on how aging impacts both fiber types not only regarding proteostasis but also at a metabolome and transcriptome network levels. Therefore, the first part of this thesis, presents the differences between slow oxidative (from Soleus muscle) and fast glycolytic fibers (Extensor digitorum longus, EDL) in terms of degradation systems and how they cope with oxidative stress during aging, while the second part explores the differences between young and old EDL muscle transcriptome and metabolome, unraveling molecular features. More specifically, the results from the present work show that slow oxidative muscle performs better at maintaining the function of UPS and ALS during aging than EDL muscle, which is clearly affected, accounting for the decline in the catalytic activity rates and accumulation of autophagy-related proteins. Strinkingly, transcriptome and metabolome analyses reveal that fast glycolytic muscle evidences significant downregulation of mitochondrial related processes and damaged mitochondria morphology during aging, despite of having a lower oxidative metabolism compared to oxidative fibers. Moreover, predictive analyses reveal a negative association between aged EDL gene signature and lifespan extending interventions such as caloric restriction (CR). Although, CR intervention does not alter the levels of mitochondrial markers in aged EDL muscle, it can reverse the higher mRNA levels of muscle damage markers. Together, the results from this thesis give new insights about how different metabolic muscle fibers cope with age-related changes and why fast glycolytic fibers are more susceptible to aging than slow oxidative fibers.}, language = {en} } @article{OmolaoyeOmolaoyeKandasamyetal.2022, author = {Omolaoye, Temidayo S. and Omolaoye, Victor Adelakun and Kandasamy, Richard K. and Hachim, Mahmood Yaseen and Du Plessis, Stefan S.}, title = {Omics and male infertility}, series = {Life : open access journal}, volume = {12}, journal = {Life : open access journal}, number = {2}, publisher = {MDPI}, address = {Basel}, issn = {2075-1729}, doi = {10.3390/life12020280}, pages = {21}, year = {2022}, abstract = {Male infertility is a multifaceted disorder affecting approximately 50\% of male partners in infertile couples. Over the years, male infertility has been diagnosed mainly through semen analysis, hormone evaluations, medical records and physical examinations, which of course are fundamental, but yet inefficient, because 30\% of male infertility cases remain idiopathic. This dilemmatic status of the unknown needs to be addressed with more sophisticated and result-driven technologies and/or techniques. Genetic alterations have been linked with male infertility, thereby unveiling the practicality of investigating this disorder from the "omics" perspective. Omics aims at analyzing the structure and functions of a whole constituent of a given biological function at different levels, including the molecular gene level (genomics), transcript level (transcriptomics), protein level (proteomics) and metabolites level (metabolomics). In the current study, an overview of the four branches of omics and their roles in male infertility are briefly discussed; the potential usefulness of assessing transcriptomic data to understand this pathology is also elucidated. After assessing the publicly obtainable transcriptomic data for datasets on male infertility, a total of 1385 datasets were retrieved, of which 10 datasets met the inclusion criteria and were used for further analysis. These datasets were classified into groups according to the disease or cause of male infertility. The groups include non-obstructive azoospermia (NOA), obstructive azoospermia (OA), non-obstructive and obstructive azoospermia (NOA and OA), spermatogenic dysfunction, sperm dysfunction, and Y chromosome microdeletion. Findings revealed that 8 genes (LDHC, PDHA2, TNP1, TNP2, ODF1, ODF2, SPINK2, PCDHB3) were commonly differentially expressed between all disease groups. Likewise, 56 genes were common between NOA versus NOA and OA (ADAD1, BANF2, BCL2L14, C12orf50, C20orf173, C22orf23, C6orf99, C9orf131, C9orf24, CABS1, CAPZA3, CCDC187, CCDC54, CDKN3, CEP170, CFAP206, CRISP2, CT83, CXorf65, FAM209A, FAM71F1, FAM81B, GALNTL5, GTSF1, H1FNT, HEMGN, HMGB4, KIF2B, LDHC, LOC441601, LYZL2, ODF1, ODF2, PCDHB3, PDHA2, PGK2, PIH1D2, PLCZ1, PROCA1, RIMBP3, ROPN1L, SHCBP1L, SMCP, SPATA16, SPATA19, SPINK2, TEX33, TKTL2, TMCO2, TMCO5A, TNP1, TNP2, TSPAN16, TSSK1B, TTLL2, UBQLN3). These genes, particularly the above-mentioned 8 genes, are involved in diverse biological processes such as germ cell development, spermatid development, spermatid differentiation, regulation of proteolysis, spermatogenesis and metabolic processes. Owing to the stage-specific expression of these genes, any mal-expression can ultimately lead to male infertility. Therefore, currently available data on all branches of omics relating to male fertility can be used to identify biomarkers for diagnosing male infertility, which can potentially help in unravelling some idiopathic cases.}, language = {en} } @phdthesis{Schaarschmidt2021, author = {Schaarschmidt, Stephanie}, title = {Evaluation and application of omics approaches to characterize molecular responses to abiotic stresses in plants}, doi = {10.25932/publishup-50963}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-509630}, school = {Universit{\"a}t Potsdam}, pages = {viii, 117}, year = {2021}, abstract = {Aufgrund des globalen Klimawandels ist die Gew{\"a}hrleistung der Ern{\"a}hrungssicherheit f{\"u}r eine wachsende Weltbev{\"o}lkerung eine große Herausforderung. Insbesondere abiotische Stressoren wirken sich negativ auf Ernteertr{\"a}ge aus. Um klimaangepasste Nutzpflanzen zu entwickeln, ist ein umfassendes Verst{\"a}ndnis molekularer Ver{\"a}nderungen in der Reaktion auf unterschiedlich starke Umweltbelastungen erforderlich. Hochdurchsatz- oder "Omics"-Technologien k{\"o}nnen dazu beitragen, Schl{\"u}sselregulatoren und Wege abiotischer Stressreaktionen zu identifizieren. Zus{\"a}tzlich zur Gewinnung von Omics-Daten m{\"u}ssen auch Programme und statistische Analysen entwickelt und evaluiert werden, um zuverl{\"a}ssige biologische Ergebnisse zu erhalten. Ich habe diese Problemstellung in drei verschiedenen Studien behandelt und daf{\"u}r zwei Omics-Technologien benutzt. In der ersten Studie wurden Transkript-Daten von den beiden polymorphen Arabidopsis thaliana Akzessionen Col-0 und N14 verwendet, um sieben Programme hinsichtlich ihrer F{\"a}higkeit zur Positionierung und Quantifizierung von Illumina RNA Sequenz-Fragmenten („Reads") zu evaluieren. Zwischen 92\% und 99\% der Reads konnten an die Referenzsequenz positioniert werden und die ermittelten Verteilungen waren hoch korreliert f{\"u}r alle Programme. Bei der Durchf{\"u}hrung einer differentiellen Genexpressionsanalyse zwischen Pflanzen, die bei 20 °C oder 4 °C (K{\"a}lteakklimatisierung) exponiert wurden, ergab sich eine große paarweise {\"U}berlappung zwischen den Programmen. In der zweiten Studie habe ich die Transkriptome von zehn verschiedenen Oryza sativa (Reis) Kultivaren sequenziert. Daf{\"u}r wurde die PacBio Isoform Sequenzierungstechnologie benutzt. Die de novo Referenztranskriptome hatten zwischen 38.900 bis 54.500 hoch qualitative Isoformen pro Sorte. Die Isoformen wurden kollabiert, um die Sequenzredundanz zu verringern und danach evaluiert z.B. hinsichtlich des Vollst{\"a}ndigkeitsgrades (BUSCO), der Transkriptl{\"a}nge und der Anzahl einzigartiger Transkripte pro Genloci. F{\"u}r die hitze- und trockenheitstolerante Sorte N22 wurden ca. 650 einzigartige und neue Transkripte identifiziert, von denen 56 signifikant unterschiedlich in sich entwickelnden Samen unter kombiniertem Trocken- und Hitzestress exprimiert wurden. In der letzten Studie habe ich die Ver{\"a}nderungen in Metabolitprofilen von acht Reissorten gemessen und analysiert, die dem Stress hoher Nachttemperaturen (HNT) ausgesetzt waren und w{\"a}hrend der Trocken- und Regenzeit im Feld auf den Philippinen angebaut wurden. Es wurden jahreszeitlich bedingte Ver{\"a}nderungen im Metabolitspiegel sowie f{\"u}r agronomische Parameter identifiziert und m{\"o}gliche Stoffwechselwege, die einen Ertragsr{\"u}ckgang unter HNT-Bedingungen verursachen, vorgeschlagen. Zusammenfassend konnte ich zeigen, dass der Vergleich der RNA-seq Programme den Pflanzenwissenschaftler*innen helfen kann, sich f{\"u}r das richtige Werkzeug f{\"u}r ihre Daten zu entscheiden. Die de novo Transkriptom-Rekonstruktion von Reissorten ohne Genomsequenz bietet einen gezielten, kosteneffizienten Ansatz zur Identifizierung neuer Gene, die durch verschiedene Stressbedingungen reguliert werden unabh{\"a}ngig vom Organismus. Mit dem Metabolomik-Ansatz f{\"u}r HNT-Stress in Reis habe ich stress- und jahreszeitenspezifische Metabolite identifiziert, die in Zukunft als molekulare Marker f{\"u}r die Verbesserung von Nutzpflanzen verwendet werden k{\"o}nnten.}, language = {en} } @misc{ZwaagHorstBlaženovićetal.2020, author = {Zwaag, Jelle and Horst, Rob ter and Blaženović, Ivana and St{\"o}ßel, Daniel and Ratter, Jacqueline and Worseck, Josephine M. and Schauer, Nicolas and Stienstra, Rinke and Netea, Mihai G. and Jahn, Dieter and Pickkers, Peter and Kox, Matthijs}, title = {Involvement of lactate and pyruvate in the anti-inflammatory effects exerted by voluntary activation of the sympathetic nervous system}, series = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, journal = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, number = {4}, issn = {1866-8372}, doi = {10.25932/publishup-51778}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-517784}, pages = {20}, year = {2020}, abstract = {We recently demonstrated that the sympathetic nervous system can be voluntarily activated following a training program consisting of cold exposure, breathing exercises, and meditation. This resulted in profound attenuation of the systemic inflammatory response elicited by lipopolysaccharide (LPS) administration. Herein, we assessed whether this training program affects the plasma metabolome and if these changes are linked to the immunomodulatory effects observed. A total of 224 metabolites were identified in plasma obtained from 24 healthy male volunteers at six timepoints, of which 98 were significantly altered following LPS administration. Effects of the training program were most prominent shortly after initiation of the acquired breathing exercises but prior to LPS administration, and point towards increased activation of the Cori cycle. Elevated concentrations of lactate and pyruvate in trained individuals correlated with enhanced levels of anti-inflammatory interleukin (IL)-10. In vitro validation experiments revealed that co-incubation with lactate and pyruvate enhances IL-10 production and attenuates the release of pro-inflammatory IL-1 beta and IL-6 by LPS-stimulated leukocytes. Our results demonstrate that practicing the breathing exercises acquired during the training program results in increased activity of the Cori cycle. Furthermore, this work uncovers an important role of lactate and pyruvate in the anti-inflammatory phenotype observed in trained subjects.}, language = {en} } @article{ZwaagHorstBlaženovićetal.2020, author = {Zwaag, Jelle and Horst, Rob ter and Blaženović, Ivana and St{\"o}ßel, Daniel and Ratter, Jacqueline and Worseck, Josephine M. and Schauer, Nicolas and Stienstra, Rinke and Netea, Mihai G. and Jahn, Dieter and Pickkers, Peter and Kox, Matthijs}, title = {Involvement of lactate and pyruvate in the anti-inflammatory effects exerted by voluntary activation of the sympathetic nervous system}, series = {Metabolites}, volume = {10}, journal = {Metabolites}, number = {4}, publisher = {MDPI}, address = {Basel}, issn = {2218-1989}, doi = {10.3390/metabo10040148}, pages = {1 -- 18}, year = {2020}, abstract = {We recently demonstrated that the sympathetic nervous system can be voluntarily activated following a training program consisting of cold exposure, breathing exercises, and meditation. This resulted in profound attenuation of the systemic inflammatory response elicited by lipopolysaccharide (LPS) administration. Herein, we assessed whether this training program affects the plasma metabolome and if these changes are linked to the immunomodulatory effects observed. A total of 224 metabolites were identified in plasma obtained from 24 healthy male volunteers at six timepoints, of which 98 were significantly altered following LPS administration. Effects of the training program were most prominent shortly after initiation of the acquired breathing exercises but prior to LPS administration, and point towards increased activation of the Cori cycle. Elevated concentrations of lactate and pyruvate in trained individuals correlated with enhanced levels of anti-inflammatory interleukin (IL)-10. In vitro validation experiments revealed that co-incubation with lactate and pyruvate enhances IL-10 production and attenuates the release of pro-inflammatory IL-1 beta and IL-6 by LPS-stimulated leukocytes. Our results demonstrate that practicing the breathing exercises acquired during the training program results in increased activity of the Cori cycle. Furthermore, this work uncovers an important role of lactate and pyruvate in the anti-inflammatory phenotype observed in trained subjects.}, language = {en} } @misc{LuReichetzederPrehnetal.2018, author = {Lu, Yong-Ping and Reichetzeder, Christoph and Prehn, Cornelia and von Websky, Karoline and Slowinski, Torsten and Chen, You-Peng and Yin, Liang-Hong and Kleuser, Burkhard and Yang, Xue-Song and Adamski, Jerzy and Hocher, Berthold}, title = {Fetal serum metabolites are independently associated with Gestational diabetes mellitus}, series = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, journal = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, number = {637}, issn = {1866-8372}, doi = {10.25932/publishup-42458}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-424585}, pages = {14}, year = {2018}, abstract = {Background/Aims: Gestational diabetes (GDM) might be associated with alterations in the metabolomic profile of affected mothers and their offspring. Until now, there is a paucity of studies that investigated both, the maternal and the fetal serum metabolome in the setting of GDM. Mounting evidence suggests that the fetus is not just passively affected by gestational disease but might play an active role in it. Metabolomic studies performed in maternal blood and fetal cord blood could help to better discern distinct fetal from maternal disease interactions. Methods: At the time of birth, serum samples from mothers and newborns (cord blood samples) were collected and screened for 163 metabolites utilizing tandem mass spectrometry. The cohort consisted of 412 mother/child pairs, including 31 cases of maternal GDM. Results: An initial non-adjusted analysis showed that eight metabolites in the maternal blood and 54 metabolites in the cord blood were associated with GDM. After Benjamini-Hochberg (BH) procedure and adjustment for confounding factors for GDM, fetal phosphatidylcholine acyl-alkyl C 32:1 and proline still showed an independent association with GDM. Conclusions: This study found metabolites in cord blood which were associated with GDM, even after adjustment for established risk factors of GDM. To the best of our knowledge, this is the first study demonstrating an independent association between fetal serum metabolites and maternal GDM. Our findings might suggest a potential effect of the fetal metabolome on maternal GDM. (c) 2018 The Author(s) Published by S. Karger AG, Basel}, language = {en} } @phdthesis{Stoessel2018, author = {St{\"o}ßel, Daniel}, title = {Biomarker Discovery in Multiple Sclerosis and Parkinson's disease}, school = {Universit{\"a}t Potsdam}, pages = {135}, year = {2018}, abstract = {Neuroinflammatory and neurodegenerative diseases such as Parkinson's (PD) and multiple sclerosis (MS) often result in a severe impairment of the patient´s quality of life. Effective therapies for the treatment are currently not available, which results in a high socio-economic burden. Due to the heterogeneity of the disease subtypes, stratification is particularly difficult in the early phase of the disease and is mainly based on clinical parameters such as neurophysiological tests and central nervous imaging. Due to good accessibility and stability, blood and cerebrospinal fluid metabolite markers could serve as surrogates for neurodegenerative processes. This can lead to an improved mechanistic understanding of these diseases and further be used as "treatment response" biomarkers in preclinical and clinical development programs. Therefore, plasma and CSF metabolite profiles will be identified that allow differentiation of PD from healthy controls, association of PD with dementia (PDD) and differentiation of PD subtypes such as akinetic rigid and tremor dominant PD patients. In addition, plasma metabolites for the diagnosis of primary progressive MS (PPMS) should be investigated and tested for their specificity to relapsing-remitting MS (RRMS) and their development during PPMS progression. By applying untargeted high-resolution metabolomics of PD patient samples and in using random forest and partial least square machine learning algorithms, this study identified 20 plasma metabolites and 14 CSF metabolite biomarkers. These differentiate against healthy individuals with an AUC of 0.8 and 0.9 in PD, respectively. We also identify ten PDD specific serum metabolites, which differentiate against healthy individuals and PD patients without dementia with an AUC of 1.0, respectively. Furthermore, 23 akinetic-rigid specific plasma markers were identified, which differentiate against tremor-dominant PD patients with an AUC of 0.94 and against healthy individuals with an AUC of 0.98. These findings also suggest more severe disease pathology in the akinetic-rigid PD than in tremor dominant PD. In the analysis of MS patient samples a partial least square analysis yielded predictive models for the classification of PPMS and resulted in 20 PPMS specific metabolites. In another MS study unknown changes in human metabolism were identified after administration of the multiple sclerosis drug dimethylfumarate, which is used for the treatment of RRMS. These results allow to describe and understand the hitherto completely unknown mechanism of action of this new drug and to use these findings for the further development of new drugs and targets against RRMS. In conclusion, these results have the potential for improved diagnosis of these diseases and improvement of mechanistic understandings, as multiple deregulated pathways were identified. Moreover, novel Dimethylfumarate targets can be used to aid drug development and treatment efficiency. Overall, metabolite profiling in combination with machine learning identified as a promising approach for biomarker discovery and mode of action elucidation.}, language = {en} } @misc{LuReichetzederPrehnetal.2018, author = {Lu, Yong-Ping and Reichetzeder, Christoph and Prehn, Cornelia and Yin, Liang-Hong and Yun, Chen and Zeng, Shufei and Chu, Chang and Adamski, Jerzy and Hocher, Berthold}, title = {Cord blood Lysophosphatidylcholine 16:1 is positively associated with birth weight}, series = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, journal = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, number = {631}, issn = {1866-8372}, doi = {10.25932/publishup-42456}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-424566}, pages = {11}, year = {2018}, abstract = {Background/Aims: Impaired birth outcomes, like low birth weight, have consistently been associated with increased disease susceptibility to hypertension in later life. Alterations in the maternal or fetal metabolism might impact on fetal growth and influence birth outcomes. Discerning associations between the maternal and fetal metabolome and surrogate parameters of fetal growth could give new insight into the complex relationship between intrauterine conditions, birth outcomes, and later life disease susceptibility. Methods: Using flow injection tandem mass spectrometry, targeted metabolomics was performed in serum samples obtained from 226 mother/child pairs at delivery. Associations between neonatal birth weight and concentrations of 163 maternal and fetal metabolites were analyzed. Results: After FDR adjustment using the Benjamini-Hochberg procedure lysophosphatidylcholines (LPC) 14:0, 16:1, and 18:1 were strongly positively correlated with birth weight. In a stepwise linear regression model corrected for established confounding factors of birth weight, LPC 16: 1 showed the strongest independent association with birth weight (CI: 93.63 - 168.94; P = 6.94x10(-11)). The association with birth weight was stronger than classical confounding factors such as offspring sex (CI: - 258.81- -61.32; P = 0.002) and maternal smoking during pregnancy (CI: -298.74 - -29.51; P = 0.017). Conclusions: After correction for multiple testing and adjustment for potential confounders, LPC 16:1 showed a very strong and independent association with birth weight. The underlying molecular mechanisms linking fetal LPCs with birth weight need to be addressed in future studies. (c) 2018 The Author(s) Published by S. Karger AG, Basel}, language = {en} } @phdthesis{Schwahn2018, author = {Schwahn, Kevin}, title = {Data driven approaches to infer the regulatory mechanism shaping and constraining levels of metabolites in metabolic networks}, doi = {10.25932/publishup-42324}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-423240}, school = {Universit{\"a}t Potsdam}, pages = {109}, year = {2018}, abstract = {Systems biology aims at investigating biological systems in its entirety by gathering and analyzing large-scale data sets about the underlying components. Computational systems biology approaches use these large-scale data sets to create models at different scales and cellular levels. In addition, it is concerned with generating and testing hypotheses about biological processes. However, such approaches are inevitably leading to computational challenges due to the high dimensionality of the data and the differences in the dimension of data from different cellular layers. This thesis focuses on the investigation and development of computational approaches to analyze metabolite profiles in the context of cellular networks. This leads to determining what aspects of the network functionality are reflected in the metabolite levels. With these methods at hand, this thesis aims to answer three questions: (1) how observability of biological systems is manifested in metabolite profiles and if it can be used for phenotypical comparisons; (2) how to identify couplings of reaction rates from metabolic profiles alone; and (3) which regulatory mechanism that affect metabolite levels can be distinguished by integrating transcriptomics and metabolomics read-outs. I showed that sensor metabolites, identified by an approach from observability theory, are more correlated to each other than non-sensors. The greater correlations between sensor metabolites were detected both with publicly available metabolite profiles and synthetic data simulated from a medium-scale kinetic model. I demonstrated through robustness analysis that correlation was due to the position of the sensor metabolites in the network and persisted irrespectively of the experimental conditions. Sensor metabolites are therefore potential candidates for phenotypical comparisons between conditions through targeted metabolic analysis. Furthermore, I demonstrated that the coupling of metabolic reaction rates can be investigated from a purely data-driven perspective, assuming that metabolic reactions can be described by mass action kinetics. Employing metabolite profiles from domesticated and wild wheat and tomato species, I showed that the process of domestication is associated with a loss of regulatory control on the level of reaction rate coupling. I also found that the same metabolic pathways in Arabidopsis thaliana and Escherichia coli exhibit differences in the number of reaction rate couplings. I designed a novel method for the identification and categorization of transcriptional effects on metabolism by combining data on gene expression and metabolite levels. The approach determines the partial correlation of metabolites with control by the principal components of the transcript levels. The principle components contain the majority of the transcriptomic information allowing to partial out the effect of the transcriptional layer from the metabolite profiles. Depending whether the correlation between metabolites persists upon controlling for the effect of the transcriptional layer, the approach allows us to group metabolite pairs into being associated due to post-transcriptional or transcriptional regulation, respectively. I showed that the classification of metabolite pairs into those that are associated due to transcriptional or post-transcriptional regulation are in agreement with existing literature and findings from a Bayesian inference approach. The approaches developed, implemented, and investigated in this thesis open novel ways to jointly study metabolomics and transcriptomics data as well as to place metabolic profiles in the network context. The results from these approaches have the potential to provide further insights into the regulatory machinery in a biological system.}, 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} } @phdthesis{Wittenbecher2017, author = {Wittenbecher, Clemens}, title = {Linking whole-grain bread, coffee, and red meat to the risk of type 2 diabetes}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-404592}, school = {Universit{\"a}t Potsdam}, pages = {XII, 194, ii}, year = {2017}, abstract = {Background: Consumption of whole-grain, coffee, and red meat were consistently related to the risk of developing type 2 diabetes in prospective cohort studies, but potentially underlying biological mechanisms are not well understood. Metabolomics profiles were shown to be sensitive to these dietary exposures, and at the same time to be informative with respect to the risk of type 2 diabetes. Moreover, graphical network-models were demonstrated to reflect the biological processes underlying high-dimensional metabolomics profiles. Aim: The aim of this study was to infer hypotheses on the biological mechanisms that link consumption of whole-grain bread, coffee, and red meat, respectively, to the risk of developing type 2 diabetes. More specifically, it was aimed to consider network models of amino acid and lipid profiles as potential mediators of these risk-relations. Study population: Analyses were conducted in the prospective EPIC-Potsdam cohort (n = 27,548), applying a nested case-cohort design (n = 2731, including 692 incident diabetes cases). Habitual diet was assessed with validated semiquantitative food-frequency questionnaires. Concentrations of 126 metabolites (acylcarnitines, phosphatidylcholines, sphingomyelins, amino acids) were determined in baseline-serum samples. Incident type 2 diabetes cases were assed and validated in an active follow-up procedure. The median follow-up time was 6.6 years. Analytical design: The methodological approach was conceptually based on counterfactual causal inference theory. Observations on the network-encoded conditional independence structure restricted the space of possible causal explanations of observed metabolomics-data patterns. Given basic directionality assumptions (diet affects metabolism; metabolism affects future diabetes incidence), adjustment for a subset of direct neighbours was sufficient to consistently estimate network-independent direct effects. Further model-specification, however, was limited due to missing directionality information on the links between metabolites. Therefore, a multi-model approach was applied to infer the bounds of possible direct effects. All metabolite-exposure links and metabolite-outcome links, respectively, were classified into one of three categories: direct effect, ambiguous (some models indicated an effect others not), and no-effect. Cross-sectional and longitudinal relations were evaluated in multivariable-adjusted linear regression and Cox proportional hazard regression models, respectively. Models were comprehensively adjusted for age, sex, body mass index, prevalence of hypertension, dietary and lifestyle factors, and medication. Results: Consumption of whole-grain bread was related to lower levels of several lipid metabolites with saturated and monounsaturated fatty acids. Coffee was related to lower aromatic and branched-chain amino acids, and had potential effects on the fatty acid profile within lipid classes. Red meat was linked to lower glycine levels and was related to higher circulating concentrations of branched-chain amino acids. In addition, potential marked effects of red meat consumption on the fatty acid composition within the investigated lipid classes were identified. Moreover, potential beneficial and adverse direct effects of metabolites on type 2 diabetes risk were detected. Aromatic amino acids and lipid metabolites with even-chain saturated (C14-C18) and with specific polyunsaturated fatty acids had adverse effects on type 2 diabetes risk. Glycine, glutamine, and lipid metabolites with monounsaturated fatty acids and with other species of polyunsaturated fatty acids were classified as having direct beneficial effects on type 2 diabetes risk. Potential mediators of the diet-diabetes links were identified by graphically overlaying this information in network models. Mediation analyses revealed that effects on lipid metabolites could potentially explain about one fourth of the whole-grain bread effect on type 2 diabetes risk; and that effects of coffee and red meat consumption on amino acid and lipid profiles could potentially explain about two thirds of the altered type 2 diabetes risk linked to these dietary exposures. Conclusion: An algorithm was developed that is capable to integrate single external variables (continuous exposures, survival time) and high-dimensional metabolomics-data in a joint graphical model. Application to the EPIC-Potsdam cohort study revealed that the observed conditional independence patterns were consistent with the a priori mediation hypothesis: Early effects on lipid and amino acid metabolism had the potential to explain large parts of the link between three of the most widely discussed diabetes-related dietary exposures and the risk of developing type 2 diabetes.}, 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} } @misc{KuehnFloegelSookthaietal.2016, author = {K{\"u}hn, Tilman and Floegel, Anna and Sookthai, Disorn and Johnson, Theron and Rolle-Kampczyk, Ulrike and Otto, Wolfgang and von Bergen, Martin and Boeing, Heiner and Kaaks, Rudolf}, title = {Higher plasma levels of lysophosphatidylcholine 18:0 are related to a lower risk of common cancers in a prospective metabolomics study}, series = {BMC medicine}, journal = {BMC medicine}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-407258}, pages = {9}, year = {2016}, abstract = {Background: First metabolomics studies have indicated that metabolic fingerprints from accessible tissues might be useful to better understand the etiological links between metabolism and cancer. However, there is still a lack of prospective metabolomics studies on pre-diagnostic metabolic alterations and cancer risk. Methods: Associations between pre-diagnostic levels of 120 circulating metabolites (acylcarnitines, amino acids, biogenic amines, phosphatidylcholines, sphingolipids, and hexoses) and the risks of breast, prostate, and colorectal cancer were evaluated by Cox regression analyses using data of a prospective case-cohort study including 835 incident cancer cases. Results: The median follow-up duration was 8.3 years among non-cases and 6.5 years among incident cases of cancer. Higher levels of lysophosphatidylcholines (lysoPCs), and especially lysoPC a C18:0, were consistently related to lower risks of breast, prostate, and colorectal cancer, independent of background factors. In contrast, higher levels of phosphatidylcholine PC ae C30:0 were associated with increased cancer risk. There was no heterogeneity in the observed associations by lag time between blood draw and cancer diagnosis. Conclusion: Changes in blood lipid composition precede the diagnosis of common malignancies by several years. Considering the consistency of the present results across three cancer types the observed alterations point to a global metabolic shift in phosphatidylcholine metabolism that may drive tumorigenesis.}, language = {en} } @misc{WitzelNeugartRuppeletal.2015, author = {Witzel, Katja and Neugart, Susanne and Ruppel, Silke and Schreiner, Monika and Wiesner, Melanie and Baldermann, Susanne}, title = {Recent progress in the use of 'omics technologies in brassicaceous vegetables}, series = {Frontiers in plant science}, journal = {Frontiers in plant science}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-406479}, pages = {14}, year = {2015}, abstract = {Continuing advances in 'omics methodologies and instrumentation is enhancing the understanding of how plants cope with the dynamic nature of their growing environment. 'Omics platforms have been only recently extended to cover horticultural crop species. Many of the most widely cultivated vegetable crops belong to the genus Brassica: these include plants grown for their root (turnip, rutabaga/swede), their swollen stem base (kohlrabi), their leaves (cabbage, kale, pak choi) and their inflorescence (cauliflower, broccoli). Characterization at the genome, transcript, protein and metabolite levels has illustrated the complexity of the cellular response to a whole series of environmental stresses, including nutrient deficiency, pathogen attack, heavy metal toxicity, cold acclimation, and excessive and sub optimal irradiation. This review covers recent applications of omics technologies to the brassicaceous vegetables, and discusses future scenarios in achieving improvements in crop end-use quality.}, language = {en} } @misc{WitzelNeugartRuppeletal.2015, author = {Witzel, Katja and Neugart, Susanne and Ruppel, Silke and Schreiner, Monika and Wiesner, Melanie and Baldermann, Susanne}, title = {Recent progress in the use of 'omics technologies in brassicaceous vegetables}, series = {Frontiers in plant science}, volume = {6}, journal = {Frontiers in plant science}, publisher = {Frontiers Research Foundation}, address = {Lausanne}, issn = {1664-462X}, doi = {10.3389/fpls.2015.00244}, pages = {14}, year = {2015}, abstract = {Continuing advances in 'omics methodologies and instrumentation is enhancing the understanding of how plants cope with the dynamic nature of their growing environment. 'Omics platforms have been only recently extended to cover horticultural crop species. Many of the most widely cultivated vegetable crops belong to the genus Brassica: these include plants grown for their root (turnip, rutabaga/swede), their swollen stem base (kohlrabi), their leaves (cabbage, kale, pak choi) and their inflorescence (cauliflower, broccoli). Characterization at the genome, transcript, protein and metabolite levels has illustrated the complexity of the cellular response to a whole series of environmental stresses, including nutrient deficiency, pathogen attack, heavy metal toxicity, cold acclimation, and excessive and sub optimal irradiation. This review covers recent applications of omics technologies to the brassicaceous vegetables, and discusses future scenarios in achieving improvements in crop end-use quality.}, language = {en} } @article{BalazadehSchildhauerAraujoetal.2014, author = {Balazadeh, Salma and Schildhauer, Joerg and Araujo, Wagner L. and Munne-Bosch, Sergi and Fernie, Alisdair R. and Proost, Sebastian and Humbeck, Klaus and M{\"u}ller-R{\"o}ber, Bernd}, title = {Reversal of senescence by N resupply to N-starved Arabidopsis thaliana: transcriptomic and metabolomic consequences}, series = {Journal of experimental botany}, volume = {65}, journal = {Journal of experimental botany}, number = {14}, publisher = {Oxford Univ. Press}, address = {Oxford}, issn = {0022-0957}, doi = {10.1093/jxb/eru119}, pages = {3975 -- 3992}, year = {2014}, abstract = {Leaf senescence is a developmentally controlled process, which is additionally modulated by a number of adverse environmental conditions. Nitrogen shortage is a well-known trigger of precocious senescence in many plant species including crops, generally limiting biomass and seed yield. However, leaf senescence induced by nitrogen starvation may be reversed when nitrogen is resupplied at the onset of senescence. Here, the transcriptomic, hormonal, and global metabolic rearrangements occurring during nitrogen resupply-induced reversal of senescence in Arabidopsis thaliana were analysed. The changes induced by senescence were essentially in keeping with those previously described; however, these could, by and large, be reversed. The data thus indicate that plants undergoing senescence retain the capacity to sense and respond to the availability of nitrogen nutrition. The combined data are discussed in the context of the reversibility of the senescence programme and the evolutionary benefit afforded thereby. Future prospects for understanding and manipulating this process in both Arabidopsis and crop plants are postulated.}, language = {en} } @misc{HischeLarhlimiSchwarzetal.2012, author = {Hische, Manuela and Larhlimi, Abdelhalim and Schwarz, Franziska and Fischer-Rosinsk{\´y}, Antje and Bobbert, Thomas and Assmann, Anke and Catchpole, Gareth S. and Pfeiffer, Andreas F. H. and Willmitzer, Lothar and Selbig, Joachim and Spranger, Joachim}, title = {A distinct metabolic signature predictsdevelopment of fasting plasma glucose}, series = {Postprints der Universit{\"a}t Potsdam : Mathematisch Naturwissenschaftliche Reihe}, journal = {Postprints der Universit{\"a}t Potsdam : Mathematisch Naturwissenschaftliche Reihe}, number = {850}, issn = {1866-8372}, doi = {10.25932/publishup-42740}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-427400}, pages = {12}, year = {2012}, abstract = {Background High blood glucose and diabetes are amongst the conditions causing the greatest losses in years of healthy life worldwide. Therefore, numerous studies aim to identify reliable risk markers for development of impaired glucose metabolism and type 2 diabetes. However, the molecular basis of impaired glucose metabolism is so far insufficiently understood. The development of so called 'omics' approaches in the recent years promises to identify molecular markers and to further understand the molecular basis of impaired glucose metabolism and type 2 diabetes. Although univariate statistical approaches are often applied, we demonstrate here that the application of multivariate statistical approaches is highly recommended to fully capture the complexity of data gained using high-throughput methods. Methods We took blood plasma samples from 172 subjects who participated in the prospective Metabolic Syndrome Berlin Potsdam follow-up study (MESY-BEPO Follow-up). We analysed these samples using Gas Chromatography coupled with Mass Spectrometry (GC-MS), and measured 286 metabolites. Furthermore, fasting glucose levels were measured using standard methods at baseline, and after an average of six years. We did correlation analysis and built linear regression models as well as Random Forest regression models to identify metabolites that predict the development of fasting glucose in our cohort. Results We found a metabolic pattern consisting of nine metabolites that predicted fasting glucose development with an accuracy of 0.47 in tenfold cross-validation using Random Forest regression. We also showed that adding established risk markers did not improve the model accuracy. However, external validation is eventually desirable. Although not all metabolites belonging to the final pattern are identified yet, the pattern directs attention to amino acid metabolism, energy metabolism and redox homeostasis. Conclusions We demonstrate that metabolites identified using a high-throughput method (GC-MS) perform well in predicting the development of fasting plasma glucose over several years. Notably, not single, but a complex pattern of metabolites propels the prediction and therefore reflects the complexity of the underlying molecular mechanisms. This result could only be captured by application of multivariate statistical approaches. Therefore, we highly recommend the usage of statistical methods that seize the complexity of the information given by high-throughput methods.}, language = {en} } @article{CatchpolePlatzerWeikertetal.2011, author = {Catchpole, Gareth and Platzer, Alexander and Weikert, Cornelia and Kempkensteffen, Carsten and Johannsen, Manfred and Krause, Hans and Jung, Klaus and Miller, Kurt and Willmitzer, Lothar and Selbig, Joachim and Weikert, Steffen}, title = {Metabolic profiling reveals key metabolic features of renal cell carcinoma}, series = {Journal of cellular and molecular medicine : a journal of translational medicine}, volume = {15}, journal = {Journal of cellular and molecular medicine : a journal of translational medicine}, number = {1}, publisher = {Wiley-Blackwell}, address = {Malden}, issn = {1582-1838}, doi = {10.1111/j.1582-4934.2009.00939.x}, pages = {109 -- 118}, year = {2011}, abstract = {Recent evidence suggests that metabolic changes play a pivotal role in the biology of cancer and in particular renal cell carcinoma (RCC). Here, a global metabolite profiling approach was applied to characterize the metabolite pool of RCC and normal renal tissue. Advanced decision tree models were applied to characterize the metabolic signature of RCC and to explore features of metastasized tumours. The findings were validated in a second independent dataset. Vitamin E derivates and metabolites of glucose, fatty acid, and inositol phosphate metabolism determined the metabolic profile of RCC. alpha-tocopherol, hippuric acid, myoinositol, fructose-1-phosphate and glucose-1-phosphate contributed most to the tumour/normal discrimination and all showed pronounced concentration changes in RCC. The identified metabolic profile was characterized by a low recognition error of only 5\% for tumour versus normal samples. Data on metastasized tumours suggested a key role for metabolic pathways involving arachidonic acid, free fatty acids, proline, uracil and the tricarboxylic acid cycle. These results illustrate the potential of mass spectroscopy based metabolomics in conjunction with sophisticated data analysis methods to uncover the metabolic phenotype of cancer. Differentially regulated metabolites, such as vitamin E compounds, hippuric acid and myoinositol, provide leads for the characterization of novel pathways in RCC.}, language = {en} } @article{RohrmannTohgeAlbaetal.2011, author = {Rohrmann, Johannes and Tohge, Takayuki and Alba, Rob and Osorio, Sonia and Caldana, Camila and McQuinn, Ryan and Arvidsson, Samuel Janne and van der Merwe, Margaretha J. and Riano-Pachon, Diego Mauricio and M{\"u}ller-R{\"o}ber, Bernd and Fei, Zhangjun and Nesi, Adriano Nunes and Giovannoni, James J. and Fernie, Alisdair R.}, title = {Combined transcription factor profiling, microarray analysis and metabolite profiling reveals the transcriptional control of metabolic shifts occurring during tomato fruit development}, series = {The plant journal}, volume = {68}, journal = {The plant journal}, number = {6}, publisher = {Wiley-Blackwell}, address = {Malden}, issn = {0960-7412}, doi = {10.1111/j.1365-313X.2011.04750.x}, pages = {999 -- 1013}, year = {2011}, abstract = {Maturation of fleshy fruits such as tomato (Solanum lycopersicum) is subject to tight genetic control. Here we describe the development of a quantitative real-time PCR platform that allows accurate quantification of the expression level of approximately 1000 tomato transcription factors. In addition to utilizing this novel approach, we performed cDNA microarray analysis and metabolite profiling of primary and secondary metabolites using GC-MS and LC-MS, respectively. We applied these platforms to pericarp material harvested throughout fruit development, studying both wild-type Solanum lycopersicum cv. Ailsa Craig and the hp1 mutant. This mutant is functionally deficient in the tomato homologue of the negative regulator of the light signal transduction gene DDB1 from Arabidopsis, and is furthermore characterized by dramatically increased pigment and phenolic contents. We choose this particular mutant as it had previously been shown to have dramatic alterations in the content of several important fruit metabolites but relatively little impact on other ripening phenotypes. The combined dataset was mined in order to identify metabolites that were under the control of these transcription factors, and, where possible, the respective transcriptional regulation underlying this control. The results are discussed in terms of both programmed fruit ripening and development and the transcriptional and metabolic shifts that occur in parallel during these processes.}, language = {en} } @article{LisecRoemischMarglNikoloskietal.2011, author = {Lisec, Jan and R{\"o}misch-Margl, Lilla and Nikoloski, Zoran and Piepho, Hans-Peter and Giavalisco, Patrick and Selbig, Joachim and Gierl, Alfons and Willmitzer, Lothar}, title = {Corn hybrids display lower metabolite variability and complex metabolite inheritance patterns}, series = {The plant journal}, volume = {68}, journal = {The plant journal}, number = {2}, publisher = {Wiley-Blackwell}, address = {Malden}, issn = {0960-7412}, doi = {10.1111/j.1365-313X.2011.04689.x}, pages = {326 -- 336}, year = {2011}, abstract = {We conducted a comparative analysis of the root metabolome of six parental maize inbred lines and their 14 corresponding hybrids showing fresh weight heterosis. We demonstrated that the metabolic profiles not only exhibit distinct features for each hybrid line compared with its parental lines, but also separate reciprocal hybrids. Reconstructed metabolic networks, based on robust correlations between metabolic profiles, display a higher network density in most hybrids as compared with the corresponding inbred lines. With respect to metabolite level inheritance, additive, dominant and overdominant patterns are observed with no specific overrepresentation. Despite the observed complexity of the inheritance pattern, for the majority of metabolites the variance observed in all 14 hybrids is lower compared with inbred lines. Deviations of metabolite levels from the average levels of the hybrids correlate negatively with biomass, which could be applied for developing predictors of hybrid performance based on characteristics of metabolite patterns.}, language = {en} } @phdthesis{Boelling2006, author = {B{\"o}lling, Christian}, title = {Comprehensive metabolite analysis in Chlamydomonas reinhardtii : method development and application to the study of environmental and genetic perturbations}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-11329}, school = {Universit{\"a}t Potsdam}, year = {2006}, abstract = {This study introduces a method for multiparallel analysis of small organic compounds in the unicellular green alga Chlamydomonas reinhardtii, one of the premier model organisms in cell biology. The comprehensive study of the changes of metabolite composition, or metabolomics, in response to environmental, genetic or developmental signals is an important complement of other functional genomic techniques in the effort to develop an understanding of how genes, proteins and metabolites are all integrated into a seamless and dynamic network to sustain cellular functions. The sample preparation protocol was optimized to quickly inactivate enzymatic activity, achieve maximum extraction capacity and process large sample quantities. As a result of the rapid sampling, extraction and analysis by gas chromatography coupled to time-of-flight mass spectrometry (GC-TOF) more than 800 analytes from a single sample can be measured, of which over a 100 could be positively identified. As part of the analysis of GC-TOF raw data, aliquot ratio analysis to systematically remove artifact signals and tools for the use of principal component analysis (PCA) on metabolomic datasets are proposed. Cells subjected to nitrogen (N), phosphorus (P), sulfur (S) or iron (Fe) depleted growth conditions develop highly distinctive metabolite profiles with metabolites implicated in many different processes being affected in their concentration during adaptation to nutrient deprivation. Metabolite profiling allowed characterization of both specific and general responses to nutrient deprivation at the metabolite level. Modulation of the substrates for N-assimilation and the oxidative pentose phosphate pathway indicated a priority for maintaining the capability for immediate activation of N assimilation even under conditions of decreased metabolic activity and arrested growth, while the rise in 4-hydroxyproline in S deprived cells could be related to enhanced degradation of proteins of the cell wall. The adaptation to sulfur deficiency was analyzed with greater temporal resolution and responses of wild-type cells were compared with mutant cells deficient in SAC1, an important regulator of the sulfur deficiency response. Whereas concurrent metabolite depletion and accumulation occurs during adaptation to S deprivation in wild-type cells, the sac1 mutant strain is characterized by a massive incapability to sustain many processes that normally lead to transient or permanent accumulation of the levels of certain metabolites or recovery of metabolite levels after initial down-regulation. For most of the steps in arginine biosynthesis in Chlamydomonas mutants have been isolated that are deficient in the respective enzyme activities. Three strains deficient in the activities of N-acetylglutamate-5-phosphate reductase (arg1), N2 acetylornithine-aminotransferase (arg9), and argininosuccinate lyase (arg2), respectively, were analyzed with regard to activation of endogenous arginine biosynthesis after withdrawal of externally supplied arginine. Enzymatic blocks in the arginine biosynthetic pathway could be characterized by precursor accumulation, like the amassment of argininosuccinate in arg2 cells, and depletion of intermediates occurring downstream of the enzymatic block, e.g. N2-acetylornithine, ornithine, and argininosuccinate depletion in arg9 cells. The unexpected finding of substantial levels of the arginine pathway intermediates N-acetylornithine, citrulline, and argininosuccinate downstream the enzymatic block in arg1 cells provided an explanation for the residual growth capacity of these cells in the absence of external arginine sources. The presence of these compounds, together with the unusual accumulation of N-Acetylglutamate, the first intermediate that commits the glutamate backbone to ornithine and arginine biosynthesis, in arg1 cells suggests that alternative pathways, possibly involving the activity of ornithine aminotransferase, may be active when the default reaction sequence to produce ornithine via acetylation of glutamate is disabled.}, language = {en} } @article{StobieckiSkiryczKerhoasetal.2006, author = {Stobiecki, Maciej and Skirycz, Aleksandra and Kerhoas, L. and Kachlicki, P. and Muth, D. and Einhorn, J. and Mueller-Roeber, Bernd}, title = {Profiling of phenolic glycosidic conjugates in leaves of Arabidopsis thaliana using LC/MS}, series = {Metabolomics : the official journal of the Metabolomics Society}, volume = {2}, journal = {Metabolomics : the official journal of the Metabolomics Society}, publisher = {Springer}, address = {New York}, issn = {1573-3882}, doi = {10.1007/s11306-006-0031-5}, pages = {197 -- 219}, year = {2006}, abstract = {Profiling of plant secondary metabolites is still a very difficult task. Liquid chromatography (LC) or capillary electrophoresis hyphenated with different kinds of detectors are methods of choice for analysis of polar, thermo labile compounds with high molecular masses. We demonstrate the applicability of LC combined with UV diode array or/and mass spectrometric detectors for the unambiguous identification and quantification of flavonoid conjugates isolated from Arahidopsis thaliana leaves of different genotypes and grown in different environmental conditions. During LC/UV/MS/MS analyses we were able to identify tetra-, tri, and di-glycosides of kaempferol, quercetin and isorhamnetin. Based on our results we can conclude that due to the co-elution of different chemical compounds in reversed phase H PLC systems the application of UV detectors does not allow to precisely profile all flavonoid conjugates existing in A. thaliana genotypes. Using MS detection it was possible to unambiguously recognize the glycosylation patterns of the aglycones. However, from the mass spectra we could not conclude neither the anomeric form of the C-1 carbon atoms of sugar moieties in glycosidic bonds between sugars or sugar and aglycone nor the position of the second carbon involved in disaccharides. The applicability of collision induced dissociation techniques (CID MS/MS) for structural analyses of the studied group of plant secondary metabolites with two types of analyzers (triple quadrupole or ion trap) was demonstrated.}, language = {en} } @article{SteuerGrossSelbigetal.2006, author = {Steuer, Ralf and Gross, Thilo and Selbig, Joachim and Blasius, Bernd}, title = {Structural kinetic modeling of metabolic networks}, series = {Proceedings of the National Academy of Sciences of the United States of America}, volume = {103}, journal = {Proceedings of the National Academy of Sciences of the United States of America}, number = {32}, publisher = {National Academy of Sciences}, address = {Washington}, issn = {0027-8424}, doi = {10.1073/pnas.0600013103}, pages = {11868 -- 11873}, year = {2006}, abstract = {To develop and investigate detailed mathematical models of metabolic processes is one of the primary challenges in systems biology. However, despite considerable advance in the topological analysis of metabolic networks, kinetic modeling is still often severely hampered by inadequate knowledge of the enzyme-kinetic rate laws and their associated parameter values. Here we propose a method that aims to give a quantitative account of the dynamical capabilities of a metabolic system, without requiring any explicit information about the functional form of the rate equations. Our approach is based on constructing a local linear model at each point in parameter space, such that each element of the model is either directly experimentally accessible or amenable to a straightforward biochemical interpretation. This ensemble of local linear models, encompassing all possible explicit kinetic models, then allows for a statistical exploration of the comprehensive parameter space. The method is exemplified on two paradigmatic metabolic systems: the glycolytic pathway of yeast and a realistic-scale representation of the photosynthetic Calvin cycle.}, language = {en} } @phdthesis{Zhang2005, author = {Zhang, Baichen}, title = {Dissection of phloem transport in cucurbitaceae by metabolomic analysis}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-6644}, school = {Universit{\"a}t Potsdam}, year = {2005}, abstract = {This thesis aimed to investigate several fundamental and perplexing questions relating to the phloem loading and transport mechanisms of Cucurbita maxima, by combining metabolomic analysis with cell biological techniques. This putative symplastic loading species has long been used for experiments on phloem anatomy, phloem biochemistry, phloem transport physiology and phloem signalling. Symplastic loading species have been proposed to use a polymer trapping mechanism to accumulate RFO (raffinose family oligosaccharides) sugars to build up high osmotic pressure in minor veins which sustains a concentration gradient that drives mass flow. However, extensive evidence indicating a low sugar concentration in their phloem exudates is a long-known problem that conflicts with this hypothesis. Previous metabolomic analysis shows the concentration of many small molecules in phloem exudates is higher than that of leaf tissues, which indicates an active apoplastic loading step. Therefore, in the view of the phloem metabolome, a symplastic loading mechanism cannot explain how small molecules other than RFO sugars are loaded into phloem. Most studies of phloem physiology using cucurbits have neglected the possible functions of vascular architecture in phloem transport. It is well known that there are two phloem systems in cucurbits with distinctly different anatomical features: central phloem and extrafascicular phloem. However, mistaken conclusions on sources of cucurbit phloem exudation from previous reports have hindered consideration of the idea that there may be important differences between these two phloem systems. The major results are summarized as below: 1) O-linked glycans in C.maxima were structurally identified as beta-1,3 linked glucose polymers, and the composition of glycans in cucurbits was found to be species-specific. Inter-species grafting experiments proved that these glycans are phloem mobile and transported uni-directionally from scion to stock. 2) As indicated by stable isotopic labelling experiments, a considerable amount of carbon is incorporated into small metabolites in phloem exudates. However, the incorporation of carbon into RFO sugars is much faster than for other metabolites. 3) Both CO2 labelling experiments and comparative metabolomic analysis of phloem exudates and leaf tissues indicated that metabolic processes other than RFO sugar metabolism play an important role in cucurbit phloem physiology. 4) The underlying assumption that the central phloem of cucurbits continuously releases exudates after physical incision was proved wrong by rigorous experiments including direct observation by normal microscopy and combined multiple-microscopic methods. Errors in previous experimental confirmation of phloem exudation in cucurbits are critically discussed. 5) Extrafascicular phloem was proved to be functional, as indicated by phloem-mobile carboxyfluorescein tracer studies. Commissural sieve tubes interconnect phloem bundles into a complete super-symplastic network. 6) Extrafascicular phloem represents the main source of exudates following physical incision. The major transported metabolites by these extrafacicular phloem are non-sugar compounds including amino acids, O-glycans, amines. 7) Central phloem contains almost exclusively RFO sugars, the estimated amount of which is up to 1 to 2 molar. The major RFO sugar present in central phloem is stachyose. 8) Cucurbits utilize two structurally different phloem systems for transporting different group of metabolites (RFO sugars and non-RFO sugar compounds). This implies that cucurbits may use spatially separated loading mechanisms (apoplastic loading for extrafascicular phloem and symplastic loading for central phloem) for supply of nutrients to sinks. 9) Along the transport systems, RFO sugars were mainly distributed within central phloem tissues. There were only small amounts of RFO sugars present in xylem tissues (millimolar range) and trace amounts of RFO sugars in cortex and pith. The composition of small molecules in external central phloem is very different from that in internal central phloem. 10) Aggregated P-proteins were manually dissected from central phloem and analysed by both SDS-PAGE and mass spectrometry. Partial sequences of peptides were obtained by QTOF de novo sequencing from trypsin digests of three SDS-PAGE bands. None of these partial sequences shows significant homology to known cucurbit phloem proteins or other plant proteins. This proves that these central phloem proteins are a completely new group of proteins different from those in extrafascicular phloem. The extensively analysed P-proteins reported in literature to date are therefore now shown to arise from extrafascicular phloem and not central phloem, and therefore do not appear to be involved in the occlusion processes in central phloem.}, subject = {phloem}, language = {en} }