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Downscaling of microfluidic cell culture and detection devices for electrochemical monitoring has mostly focused on miniaturization of the microfluidic chips which are often designed for specific applications and therefore lack functional flexibility. We present a compact microfluidic cell culture and electrochemical analysis platform with in-built fluid handling and detection, enabling complete cell based assays comprising on-line electrode cleaning, sterilization, surface functionalization, cell seeding, cultivation and electrochemical real-time monitoring of cellular dynamics. To demonstrate the versatility and multifunctionality of the platform, we explored amperometric monitoring of intracellular redox activity in yeast (Saccharomyces cerevisiae) and detection of exocytotically released dopamine from rat pheochromocytoma cells (PC12). Electrochemical impedance spectroscopy was used in both applications for monitoring cell sedimentation and adhesion as well as proliferation in the case of PC12 cells. The influence of flow rate on the signal amplitude in the detection of redox metabolism as well as the effect of mechanical stimulation on dopamine release were demonstrated using the programmable fluid handling capability. The here presented platform is aimed at applications utilizing cell based assays, ranging from e.g. monitoring of drug effects in pharmacological studies, characterization of neural stem cell differentiation, and screening of genetically modified microorganisms to environmental monitoring.
Metabolic systems tend to exhibit steady states that can be measured in terms of their concentrations and fluxes. These measurements can be regarded as a phenotypic representation of all the complex interactions and regulatory mechanisms taking place in the underlying metabolic network. Such interactions determine the system's response to external perturbations and are responsible, for example, for its asymptotic stability or for oscillatory trajectories around the steady state. However, determining these perturbation responses in the absence of fully specified kinetic models remains an important challenge of computational systems biology. Structural kinetic modeling (SKM) is a framework to analyse whether a metabolic steady state remains stable under perturbation, without requiring detailed knowledge about individual rate equations. It provides a parameterised representation of the system's Jacobian matrix in which the model parameters encode information about the enzyme-metabolite interactions. Stability criteria can be derived by generating a large number of structural kinetic models (SK-models) with randomly sampled parameter sets and evaluating the resulting Jacobian matrices. The parameter space can be analysed statistically in order to detect network positions that contribute significantly to the perturbation response. Because the sampled parameters are equivalent to the elasticities used in metabolic control analysis (MCA), the results are easy to interpret biologically. In this project, the SKM framework was extended by several novel methodological improvements. These improvements were evaluated in a simulation study using a set of small example pathways with simple Michaelis Menten rate laws. Afterwards, a detailed analysis of the dynamic properties of the neuronal TCA cycle was performed in order to demonstrate how the new insights obtained in this work could be used for the study of complex metabolic systems. The first improvement was achieved by examining the biological feasibility of the elasticity combinations created during Monte Carlo sampling. Using a set of small example systems, the findings showed that the majority of sampled SK-models would yield negative kinetic parameters if they were translated back into kinetic models. To overcome this problem, a simple criterion was formulated that mitigates such infeasible models and the application of this criterion changed the conclusions of the SKM experiment. The second improvement of this work was the application of supervised machine-learning approaches in order to analyse SKM experiments. So far, SKM experiments have focused on the detection of individual enzymes to identify single reactions important for maintaining the stability or oscillatory trajectories. In this work, this approach was extended by demonstrating how SKM enables the detection of ensembles of enzymes or metabolites that act together in an orchestrated manner to coordinate the pathways response to perturbations. In doing so, stable and unstable states served as class labels, and classifiers were trained to detect elasticity regions associated with stability and instability. Classification was performed using decision trees and relevance vector machines (RVMs). The decision trees produced good classification accuracy in terms of model bias and generalizability. RVMs outperformed decision trees when applied to small models, but encountered severe problems when applied to larger systems because of their high runtime requirements. The decision tree rulesets were analysed statistically and individually in order to explore the role of individual enzymes or metabolites in controlling the system's trajectories around steady states. The third improvement of this work was the establishment of a relationship between the SKM framework and the related field of MCA. In particular, it was shown how the sampled elasticities could be converted to flux control coefficients, which were then investigated for their predictive information content in classifier training. After evaluation on the small example pathways, the methodology was used to study two steady states of the neuronal TCA cycle with respect to their intrinsic mechanisms responsible for stability or instability. The findings showed that several elasticities were jointly coordinated to control stability and that the main source for potential instabilities were mutations in the enzyme alpha-ketoglutarate dehydrogenase.
Catalytic bio–chemo and bio–bio tandem oxidation reactions for amide and carboxylic acid synthesis
(2014)
A catalytic toolbox for three different water-based one-pot cascades to convert aryl alcohols to amides and acids and cyclic amines to lactams, involving combination of oxidative enzymes (monoamine oxidase, xanthine dehydrogenase, galactose oxidase and laccase) and chemical oxidants (TBHP or CuI(cat)/H2O2) at mild temperatures, is presented. Mutually compatible conditions were found to afford products in good to excellent yields.
The contractile vacuole (CV) is an osmoregulatory organelle found exclusively in algae and protists. In addition to expelling excessive water out of the cell, it also expels ions and other metabolites and thereby contributes to the cell's metabolic homeostasis. The interest in the CV reaches beyond its immediate cellular roles. The CV's function is tightly related to basic cellular processes such as membrane dynamics and vesicle budding and fusion; several physiological processes in animals, such as synaptic neurotransmission and blood filtration in the kidney, are related to the CV's function; and several pathogens, such as the causative agents of sleeping sickness, possess CVs, which may serve as pharmacological targets. The green alga Chlamydomonas reinhardtii has two CVs. They are the smallest known CVs in nature, and they remain relatively untouched in the CV-related literature. Many genes that have been shown to be related to the CV in other organisms have close homologues in C. reinhardtii. We attempted to silence some of these genes and observe the effect on the CV. One of our genes, VMP1, caused striking, severe phenotypes when silenced. Cells exhibited defective cytokinesis and aberrant morphologies. The CV, incidentally, remained unscathed. In addition, mutant cells showed some evidence of disrupted autophagy. Several important regulators of the cell cycle as well as autophagy were found to be underexpressed in the mutant. Lipidomic analysis revealed many meaningful changes between wild-type and mutant cells, reinforcing the compromised-autophagy observation. VMP1 is a singular protein, with homologues in numerous eukaryotic organisms (aside from fungi), but usually with no relatives in each particular genome. Since its first characterization in 2002 it has been associated with several cellular processes and functions, namely autophagy, programmed cell-death, secretion, cell adhesion, and organelle biogenesis. It has been implicated in several human diseases: pancreatitis, diabetes, and several types of cancer. Our results reiterate some of the observations in VMP1's six reported homologues, but, importantly, show for the first time an involvement of this protein in cell division. The mechanisms underlying this involvement in Chlamydomonas, as well as other key aspects, such as VMP1's subcellular localization and interaction partners, still await elucidation.
The adaptation of cell growth and proliferation to environmental changes is essential for the surviving of biological systems. The evolutionary conserved Ser/Thr protein kinase “Target of Rapamycin” (TOR) has emerged as a major signaling node that integrates the sensing of numerous growth signals to the coordinated regulation of cellular metabolism and growth. Although the TOR signaling pathway has been widely studied in heterotrophic organisms, the research on TOR in photosynthetic eukaryotes has been hampered by the reported land plant resistance to rapamycin. Thus, the finding that Chlamydomonas reinhardtii is sensitive to rapamycin, establish this unicellular green alga as a useful model system to investigate TOR signaling in photosynthetic eukaryotes.
The observation that rapamycin does not fully arrest Chlamydomonas growth, which is different from observations made in other organisms, prompted us to investigate the regulatory function of TOR in Chlamydomonas in context of the cell cycle. Therefore, a growth system that allowed synchronously growth under widely unperturbed cultivation in a fermenter system was set up and the synchronized cells were characterized in detail. In a highly resolved kinetic study, the synchronized cells were analyzed for their changes in cytological parameters as cell number and size distribution and their starch content. Furthermore, we applied mass spectrometric analysis for profiling of primary and lipid metabolism. This system was then used to analyze the response dynamics of the Chlamydomonas metabolome and lipidome to TOR-inhibition by rapamycin
The results show that TOR inhibition reduces cell growth, delays cell division and daughter cell release and results in a 50% reduced cell number at the end of the cell cycle. Consistent with the growth phenotype we observed strong changes in carbon and nitrogen partitioning in the direction of rapid conversion into carbon and nitrogen storage through an accumulation of starch, triacylglycerol and arginine. Interestingly, it seems that the conversion of carbon into triacylglycerol occurred faster than into starch after TOR inhibition, which may indicate a more dominant role of TOR in the regulation of TAG biosynthesis than in the regulation of starch.
This study clearly shows, for the first time, a complex picture of metabolic and lipidomic dynamically changes during the cell cycle of Chlamydomonas reinhardtii and furthermore reveals a complex regulation and adjustment of metabolite pools and lipid composition in response to TOR inhibition.
Background
The Amazon molly, Poecilia formosa (Teleostei: Poeciliinae) is an unisexual, all-female species. It evolved through the hybridisation of two closely related sexual species and exhibits clonal reproduction by sperm dependent parthenogenesis (or gynogenesis) where the sperm of a parental species is only used to activate embryogenesis of the apomictic, diploid eggs but does not contribute genetic material to the offspring.
Here we provide and describe the first de novo assembled transcriptome of the Amazon molly in comparison with its maternal ancestor, the Atlantic molly Poecilia mexicana. The transcriptome data were produced through sequencing of single end libraries (100 bp) with the Illumina sequencing technique.
Results
83,504,382 reads for the Amazon molly and 81,625,840 for the Atlantic molly were assembled into 127,283 and 78,961 contigs for the Amazon molly and the Atlantic molly, respectively. 63% resp. 57% of the contigs could be annotated with gene ontology terms after sequence similarity comparisons. Furthermore, we were able to identify genes normally involved in reproduction and especially in meiosis also in the transcriptome dataset of the apomictic reproducing Amazon molly.
Conclusions
We assembled and annotated the transcriptome of a non-model organism, the Amazon molly, without a reference genome (de novo). The obtained dataset is a fundamental resource for future research in functional and expression analysis. Also, the presence of 30 meiosis-specific genes within a species where no meiosis is known to take place is remarkable and raises new questions for future research.
Background: Development of eukaryotic organisms is controlled by transcription factors that trigger specific and global changes in gene expression programs. In plants, MADS-domain transcription factors act as master regulators of developmental switches and organ specification. However, the mechanisms by which these factors dynamically regulate the expression of their target genes at different developmental stages are still poorly understood.
Results: We characterized the relationship of chromatin accessibility, gene expression, and DNA binding of two MADS-domain proteins at different stages of Arabidopsis flower development. Dynamic changes in APETALA1 and SEPALLATA3 DNA binding correlated with changes in gene expression, and many of the target genes could be associated with the developmental stage in which they are transcriptionally controlled. We also observe dynamic changes in chromatin accessibility during flower development. Remarkably, DNA binding of APETALA1 and SEPALLATA3 is largely independent of the accessibility status of their binding regions and it can precede increases in DNA accessibility. These results suggest that APETALA1 and SEPALLATA3 may modulate chromatin accessibility, thereby facilitating access of other transcriptional regulators to their target genes.
Conclusions: Our findings indicate that different homeotic factors regulate partly overlapping, yet also distinctive sets of target genes in a partly stage-specific fashion. By combining the information from DNA-binding and gene expression data, we are able to propose models of stage-specific regulatory interactions, thereby addressing dynamics of regulatory networks throughout flower development. Furthermore, MADS-domain TFs may regulate gene expression by alternative strategies, one of which is modulation of chromatin accessibility.
Biosensors for the detection of benzaldehyde and g-aminobutyric acid (GABA) are reported using aldehyde oxidoreductase PaoABC from Escherichia coli immobilized in a polymer containing bound low potential osmium redox complexes. The electrically connected enzyme already electrooxidizes benzaldehyde at potentials below −0.15 V (vs. Ag|AgCl, 1 M KCl). The pH-dependence of benzaldehyde oxidation can be strongly influenced by the ionic strength. The effect is similar with the soluble osmium redox complex and therefore indicates a clear electrostatic effect on the bioelectrocatalytic efficiency of PaoABC in the osmium containing redox polymer. At lower ionic strength, the pH-optimum is high and can be switched to low pH-values at high ionic strength. This offers biosensing at high and low pH-values. A “reagentless” biosensor has been formed with enzyme wired onto a screen-printed electrode in a flow cell device. The response time to addition of benzaldehyde is 30 s, and the measuring range is between 10–150 µM and the detection limit of 5 µM (signal to noise ratio 3:1) of benzaldehyde. The relative standard deviation in a series (n = 13) for 200 µM benzaldehyde is 1.9%. For the biosensor, a response to succinic semialdehyde was also identified. Based on this response and the ability to work at high pH a biosensor for GABA is proposed by coimmobilizing GABA-aminotransferase (GABA-T) and PaoABC in the osmium containing redox polymer.
Transcription factors (TFs) are ubiquitous gene expression regulators and play essential roles in almost all biological processes. This Ph.D. project is primarily focused on the functional characterisation of MYB112 - a member of the R2R3-MYB TF family from the model plant Arabidopsis thaliana. This gene was selected due to its increased expression during senescence based on previous qRT-PCR expression profiling experiments of 1880 TFs in Arabidopsis leaves at three developmental stages (15 mm leaf, 30 mm leaf and 20% yellowing leaf). MYB112 promoter GUS fusion lines were generated to further investigate the expression pattern of MYB112. Employing transgenic approaches in combination with metabolomics and transcriptomics we demonstrate that MYB112 exerts a major role in regulation of plant flavonoid metabolism. We report enhanced and impaired anthocyanin accumulation in MYB112 overexpressors and MYB112-deficient mutants, respectively. Expression profiling reveals that MYB112 acts as a positive regulator of the transcription factor PAP1 leading to increased anthocyanin biosynthesis, and as a negative regulator of MYB12 and MYB111, which both control flavonol biosynthesis. We also identify MYB112 early responsive genes using a combination of several approaches. These include gene expression profiling (Affymetrix ATH1 micro-arrays and qRT-PCR) and transactivation assays in leaf mesophyll cell protoplasts. We show that MYB112 binds to an 8-bp DNA fragment containing the core sequence (A/T/G)(A/C)CC(A/T)(A/G/T)(A/C)(T/C). By electrophoretic mobility shift assay (EMSA) and chromatin immunoprecipitation coupled to qPCR (ChIP-qPCR) we demonstrate that MYB112 binds in vitro and in vivo to MYB7 and MYB32 promoters revealing them as direct downstream target genes. MYB TFs were previously reported to play an important role in controlling flavonoid biosynthesis in plants. Many factors acting upstream of the anthocyanin biosynthesis pathway show enhanced expression levels during nitrogen limitation, or elevated sucrose content. In addition to the mentioned conditions, other environmental parameters including salinity or high light stress may trigger anthocyanin accumulation. In contrast to several other MYB TFs affecting anthocyanin biosynthesis pathway genes, MYB112 expression is not controlled by nitrogen limitation, or carbon excess, but rather is stimulated by salinity and high light stress. Thus, MYB112 constitutes a previously uncharacterised regulatory factor that modifies anthocyanin accumulation under conditions of abiotic stress.