TY - JOUR A1 - Omolaoye, Temidayo S. A1 - Omolaoye, Victor Adelakun A1 - Kandasamy, Richard K. A1 - Hachim, Mahmood Yaseen A1 - Du Plessis, Stefan S. T1 - Omics and male infertility BT - highlighting the application of transcriptomic data JF - Life : open access journal N2 - 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. KW - male infertility KW - omics KW - genomics KW - transcriptomics KW - proteomics KW - metabolomics Y1 - 2022 U6 - https://doi.org/10.3390/life12020280 SN - 2075-1729 VL - 12 IS - 2 PB - MDPI CY - Basel ER - TY - JOUR A1 - Zwaag, Jelle A1 - Horst, Rob ter A1 - Blaženović, Ivana A1 - Stößel, Daniel A1 - Ratter, Jacqueline A1 - Worseck, Josephine M. A1 - Schauer, Nicolas A1 - Stienstra, Rinke A1 - Netea, Mihai G. A1 - Jahn, Dieter A1 - Pickkers, Peter A1 - Kox, Matthijs T1 - Involvement of lactate and pyruvate in the anti-inflammatory effects exerted by voluntary activation of the sympathetic nervous system JF - Metabolites N2 - 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. KW - metabolomics KW - LPS KW - endotoxin KW - pyruvate KW - lactate KW - cytokines KW - inflammation KW - human endotoxemia KW - cori cycle KW - warburg effect Y1 - 2020 U6 - https://doi.org/10.3390/metabo10040148 SN - 2218-1989 VL - 10 IS - 4 SP - 1 EP - 18 PB - MDPI CY - Basel ER - TY - JOUR A1 - Schwahn, Kevin A1 - Nikoloski, Zoran T1 - Data reduction approaches for dissecting transcriptional effects on metabolism JF - Frontiers in plant science N2 - 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. KW - E. coil KW - S. cerevisiae KW - A. thaliana KW - partial correlation KW - principal component analysis KW - metabolomics KW - data reduction KW - regulation Y1 - 2018 U6 - https://doi.org/10.3389/fpls.2018.00538 SN - 1664-462X VL - 9 PB - Frontiers Research Foundation CY - Lausanne ER - TY - JOUR A1 - Steuer, Ralf A1 - Gross, Thilo A1 - Selbig, Joachim A1 - Blasius, Bernd T1 - Structural kinetic modeling of metabolic networks JF - Proceedings of the National Academy of Sciences of the United States of America N2 - 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. KW - systems biology KW - computational biochemistry KW - metabolomics KW - metabolic regulation KW - biological robustness Y1 - 2006 U6 - https://doi.org/10.1073/pnas.0600013103 SN - 0027-8424 SN - 1091-6490 VL - 103 IS - 32 SP - 11868 EP - 11873 PB - National Academy of Sciences CY - Washington ER - TY - JOUR A1 - Stobiecki, Maciej A1 - Skirycz, Aleksandra A1 - Kerhoas, L. A1 - Kachlicki, P. A1 - Muth, D. A1 - Einhorn, J. A1 - Mueller-Roeber, Bernd T1 - Profiling of phenolic glycosidic conjugates in leaves of Arabidopsis thaliana using LC/MS JF - Metabolomics : the official journal of the Metabolomics Society N2 - 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. KW - liquid chromatography-mass spectrometry KW - metabolite profiling KW - metabolomics KW - flavonoid glycosides Y1 - 2006 U6 - https://doi.org/10.1007/s11306-006-0031-5 SN - 1573-3882 VL - 2 SP - 197 EP - 219 PB - Springer CY - New York ER - TY - JOUR A1 - Jüppner, Jessica A1 - Mubeen, Umarah A1 - Leisse, Andrea A1 - Caldana, Camila A1 - Brust, Henrike A1 - Steup, Martin A1 - Herrmann, Marion A1 - Steinhauser, Dirk A1 - Giavalisco, Patrick T1 - Dynamics of lipids and metabolites during the cell cycle of Chlamydomonas reinhardtii JF - The plant journal N2 - 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. KW - Chlamydomonas reinhardtii KW - synchronized cell cultures KW - photoautotrophic growth KW - cell cycle KW - metabolomics KW - lipidomics KW - systems biology KW - two-phase extraction KW - diurnal cycle KW - technical advance Y1 - 2017 U6 - https://doi.org/10.1111/tpj.13642 SN - 0960-7412 SN - 1365-313X VL - 92 SP - 331 EP - 343 PB - Wiley CY - Hoboken ER - TY - JOUR A1 - Balazadeh, Salma A1 - Schildhauer, Joerg A1 - Araujo, Wagner L. A1 - Munne-Bosch, Sergi A1 - Fernie, Alisdair R. A1 - Proost, Sebastian A1 - Humbeck, Klaus A1 - Müller-Röber, Bernd T1 - Reversal of senescence by N resupply to N-starved Arabidopsis thaliana: transcriptomic and metabolomic consequences JF - Journal of experimental botany N2 - 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. KW - Arabidopsis KW - gene expression KW - metabolomics KW - nitrogen limitation KW - senescence KW - transcriptome Y1 - 2014 U6 - https://doi.org/10.1093/jxb/eru119 SN - 0022-0957 SN - 1460-2431 VL - 65 IS - 14 SP - 3975 EP - 3992 PB - Oxford Univ. Press CY - Oxford ER - TY - JOUR A1 - Catchpole, Gareth A1 - Platzer, Alexander A1 - Weikert, Cornelia A1 - Kempkensteffen, Carsten A1 - Johannsen, Manfred A1 - Krause, Hans A1 - Jung, Klaus A1 - Miller, Kurt A1 - Willmitzer, Lothar A1 - Selbig, Joachim A1 - Weikert, Steffen T1 - Metabolic profiling reveals key metabolic features of renal cell carcinoma JF - Journal of cellular and molecular medicine : a journal of translational medicine N2 - 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. KW - kidney cancer KW - metabolism KW - metabolomics KW - metastasis Y1 - 2011 U6 - https://doi.org/10.1111/j.1582-4934.2009.00939.x SN - 1582-1838 VL - 15 IS - 1 SP - 109 EP - 118 PB - Wiley-Blackwell CY - Malden ER - TY - JOUR A1 - Lisec, Jan A1 - Römisch-Margl, Lilla A1 - Nikoloski, Zoran A1 - Piepho, Hans-Peter A1 - Giavalisco, Patrick A1 - Selbig, Joachim A1 - Gierl, Alfons A1 - Willmitzer, Lothar T1 - Corn hybrids display lower metabolite variability and complex metabolite inheritance patterns JF - The plant journal N2 - 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. KW - heterosis KW - Zea mays KW - metabolomics Y1 - 2011 U6 - https://doi.org/10.1111/j.1365-313X.2011.04689.x SN - 0960-7412 VL - 68 IS - 2 SP - 326 EP - 336 PB - Wiley-Blackwell CY - Malden ER - TY - JOUR A1 - Rohrmann, Johannes A1 - Tohge, Takayuki A1 - Alba, Rob A1 - Osorio, Sonia A1 - Caldana, Camila A1 - McQuinn, Ryan A1 - Arvidsson, Samuel Janne A1 - van der Merwe, Margaretha J. A1 - Riano-Pachon, Diego Mauricio A1 - Müller-Röber, Bernd A1 - Fei, Zhangjun A1 - Nesi, Adriano Nunes A1 - Giovannoni, James J. A1 - Fernie, Alisdair R. T1 - Combined transcription factor profiling, microarray analysis and metabolite profiling reveals the transcriptional control of metabolic shifts occurring during tomato fruit development JF - The plant journal N2 - 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. KW - transcription factor KW - Solanum lycopersicum KW - quantitative RT-PCR KW - microarray KW - metabolomics KW - fleshy fruit ripening Y1 - 2011 U6 - https://doi.org/10.1111/j.1365-313X.2011.04750.x SN - 0960-7412 VL - 68 IS - 6 SP - 999 EP - 1013 PB - Wiley-Blackwell CY - Malden ER -