570 Biowissenschaften; Biologie
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- total internal reflection fluorescence microscopy (2)
- Biogenic amine (1)
- Donovani (1)
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Background: Leishmania tarentolae, a unicellular eukaryotic protozoan, has been established as a novel host for recombinant protein production in recent years. Current protocols for protein expression in Leishmania are, however, time consuming and require extensive lab work in order to identify well-expressing cell lines. Here we established an alternative protein expression work-flow that employs recently engineered infrared fluorescence protein (IFP) as a suitable and easy-to-handle reporter protein for recombinant protein expression in Leishmania. As model proteins we tested three proteins from the plant Arabidopsis thaliana, including a NAC and a type-B ARR transcription factor. Results: IFP and IFP fusion proteins were expressed in Leishmania and rapidly detected in cells by deconvolution microscopy and in culture by infrared imaging of 96-well microtiter plates using small cell culture volumes (2 μL - 100 μL). Motility, shape and growth of Leishmania cells were not impaired by intracellular accumulation of IFP. In-cell detection of IFP and IFP fusion proteins was straightforward already at the beginning of the expression pipeline and thus allowed early pre-selection of well-expressing Leishmania clones. Furthermore, IFP fusion proteins retained infrared fluorescence after electrophoresis in denaturing SDS-polyacrylamide gels, allowing direct in-gel detection without the need to disassemble cast protein gels. Thus, parameters for scaling up protein production and streamlining purification routes can be easily optimized when employing IFP as reporter. Conclusions: Using IFP as biosensor we devised a protocol for rapid and convenient protein expression in Leishmania tarentolae. Our expression pipeline is superior to previously established methods in that it significantly reduces the hands-on-time and work load required for identifying well-expressing clones, refining protein production parameters and establishing purification protocols. The facile in-cell and in-gel detection tools built on IFP make Leishmania amenable for high-throughput expression of proteins from plant and animal sources.
Background: For heterogeneous tissues, such as blood, measurements of gene expression are confounded by relative proportions of cell types involved. Conclusions have to rely on estimation of gene expression signals for homogeneous cell populations, e.g. by applying micro-dissection, fluorescence activated cell sorting, or in-silico deconfounding. We studied feasibility and validity of a non-negative matrix decomposition algorithm using experimental gene expression data for blood and sorted cells from the same donor samples. Our objective was to optimize the algorithm regarding detection of differentially expressed genes and to enable its use for classification in the difficult scenario of reversely regulated genes. This would be of importance for the identification of candidate biomarkers in heterogeneous tissues.
Results: Experimental data and simulation studies involving noise parameters estimated from these data revealed that for valid detection of differential gene expression, quantile normalization and use of non-log data are optimal. We demonstrate the feasibility of predicting proportions of constituting cell types from gene expression data of single samples, as a prerequisite for a deconfounding-based classification approach. Classification cross-validation errors with and without using deconfounding results are reported as well as sample-size dependencies. Implementation of the algorithm, simulation and analysis scripts are available.
Conclusions: The deconfounding algorithm without decorrelation using quantile normalization on non-log data is proposed for biomarkers that are difficult to detect, and for cases where confounding by varying proportions of cell types is the suspected reason. In this case, a deconfounding ranking approach can be used as a powerful alternative to, or complement of, other statistical learning approaches to define candidate biomarkers for molecular diagnosis and prediction in biomedicine, in realistically noisy conditions and with moderate sample sizes.
Multi-color fluorescence imaging experiments of wave forming Dictyostelium cells have revealed that actin waves separate two domains of the cell cortex that differ in their actin structure and phosphoinositide composition. We propose a bistable model of actin dynamics to account for these experimental observation. The model is based on the simplifying assumption that the actin cytoskeleton is composed of two distinct network types, a dendritic and a bundled network. The two structurally different states that were observed in experiments correspond to the stable fixed points in the bistable regime of this model. Each fixed point is dominated by one of the two network types. The experimentally observed actin waves can be considered as trigger waves that propagate transitions between the two stable fixed points.
A large number and wide variety of lake ecosystem models have been developed and published during the past four decades. We identify two challenges for making further progress in this field. One such challenge is to avoid developing more models largely following the concept of others ('reinventing the wheel'). The other challenge is to avoid focusing on only one type of model, while ignoring new and diverse approaches that have become available ('having tunnel vision'). In this paper, we aim at improving the awareness of existing models and knowledge of concurrent approaches in lake ecosystem modelling, without covering all possible model tools and avenues. First, we present a broad variety of modelling approaches. To illustrate these approaches, we give brief descriptions of rather arbitrarily selected sets of specific models. We deal with static models (steady state and regression models), complex dynamic models (CAEDYM, CE-QUAL-W2, Delft 3D-ECO, LakeMab, LakeWeb, MyLake, PCLake, PROTECH, SALMO), structurally dynamic models and minimal dynamic models. We also discuss a group of approaches that could all be classified as individual based: super-individual models (Piscator, Charisma), physiologically structured models, stage-structured models and traitbased models. We briefly mention genetic algorithms, neural networks, Kalman filters and fuzzy logic. Thereafter, we zoom in, as an in-depth example, on the multi-decadal development and application of the lake ecosystem model PCLake and related models (PCLake Metamodel, Lake Shira Model, IPH-TRIM3D-PCLake). In the discussion, we argue that while the historical development of each approach and model is understandable given its 'leading principle', there are many opportunities for combining approaches. We take the point of view that a single 'right' approach does not exist and should not be strived for. Instead, multiple modelling approaches, applied concurrently to a given problem, can help develop an integrative view on the functioning of lake ecosystems. We end with a set of specific recommendations that may be of help in the further development of lake ecosystem models.
How much is too much?
(2010)
Although dietary nutrient intake is often adequate, nutritional supplement use is common among elite athletes. However, high-dose supplements or the use of multiple supplements may exceed the recommended daily allowance (RDA) of particular nutrients or even result in a daily intake above tolerable upper limits (UL). The present case report presents nutritional intake data and supplement use of a highly trained male swimmer competing at international level. Habitual energy and micronutrient intake were analysed by 3 d dietary reports. Supplement use and dosage were assessed, and total amount of nutrient supply was calculated. Micronutrient intake was evaluated based on RDA and UL as presented by the European Scientific Committee on Food, and maximum permitted levels in supplements (MPL) are given. The athlete’s diet provided adequate micronutrient content well above RDA except for vitamin D. Simultaneous use of ten different supplements was reported, resulting in excess intake above tolerable UL for folate, vitamin E and Zn. Additionally, daily supplement dosage was considerably above MPL for nine micronutrients consumed as artificial products. Risks and possible side effects of exceeding UL by the athlete are discussed. Athletes with high energy intake may be at risk of exceeding UL of particular nutrients if multiple supplements are added. Therefore, dietary counselling of athletes should include assessment of habitual diet and nutritional supplement intake. Educating athletes to balance their diets instead of taking supplements might be prudent to prevent health risks
that may occur with long-term excess nutrient intake.
Inverse agonist and neutral antagonist actions of synthetic compounds at an insect 5-HT1 receptor
(2010)
Background and purpose: 5-Hydroxytryptamine (5-HT) has been shown to control and modulate many physiological and behavioural functions in insects. In this study, we report the cloning and pharmacological properties of a 5-HT1 receptor of an insect model for neurobiology, physiology and pharmacology. Experimental approach: A cDNA encoding for the Periplaneta americana 5-HT1 receptor was amplified from brain cDNA. The receptor was stably expressed in HEK 293 cells, and the functional and pharmacological properties were determined in cAMP assays. Receptor distribution was investigated by RT-PCR and by immunocytochemistry using an affinity-purified polyclonal antiserum. Key results: The P. americana 5-HT1 receptor (Pea5-HT1) shares pronounced sequence and functional similarity with mammalian 5-HT1 receptors. Activation with 5-HT reduced adenylyl cyclase activity in a dose-dependent manner. Pea5-HT1 was expressed as a constitutively active receptor with methiothepin acting as a neutral antagonist, and WAY 100635 as an inverse agonist. Receptor mRNA was present in various tissues including brain, salivary glands and midgut. Receptor-specific antibodies showed that the native protein was expressed in a glycosylated form in membrane samples of brain and salivary glands. Conclusions and implications: This study marks the first pharmacological identification of an inverse agonist and a neutral antagonist at an insect 5-HT1 receptor. The results presented here should facilitate further analyses of 5-HT1 receptors in mediating central and peripheral effects of 5-HT in insects.
Live cell flattening
(2010)
Eukaryotic cell flattening is valuable for improving microscopic observations, ranging from bright field (BF) to total internal reflection fluorescence (TIRF) microscopy. Fundamental processes, such as mitosis and in vivo actin polymerization, have been investigated using these techniques. Here, we review the well known agar overlayer protocol and the oil overlay method. In addition, we present more elaborate microfluidics-based techniques that provide us with a greater level of control. We demonstrate these techniques on the social amoebae Dictyostelium discoideum, comparing the advantages and disadvantages of each method.
Background: Local adaptation to divergent environmental conditions can promote population genetic differentiation even in the absence of geographic barriers and hence, lead to speciation. Perturbations by catastrophic events, however, can distort such parapatric ecological speciation processes. Here, we asked whether an exceptionally strong flood led to homogenization of gene pools among locally adapted populations of the Atlantic molly (Poecilia mexicana, Poeciliidae) in the Cueva del Azufre system in southern Mexico, where two strong environmental selection factors (darkness within caves and/or presence of toxic H2S in sulfidic springs) drive the diversification of P. mexicana. Nine nuclear microsatellites as well as heritable female life history traits (both as a proxy for quantitative genetics and for trait divergence) were used as markers to compare genetic differentiation, genetic diversity, and especially population mixing (immigration and emigration) before and after the flood. Results: Habitat type (i.e., non-sulfidic surface, sulfidic surface, or sulfidic cave), but not geographic distance was the major predictor of genetic differentiation. Before and after the flood, each habitat type harbored a genetically distinct population. Only a weak signal of individual dislocation among ecologically divergent habitat types was uncovered (with the exception of slightly increased dislocation from the Cueva del Azufre into the sulfidic creek, El Azufre). By contrast, several lines of evidence are indicative of increased flood-induced dislocation within the same habitat type, e.g., between different cave chambers of the Cueva del Azufre. Conclusions: The virtual absence of individual dislocation among ecologically different habitat types indicates strong natural selection against migrants. Thus, our current study exemplifies that ecological speciation in this and other systems, in which extreme environmental factors drive speciation, may be little affected by temporary perturbations, as adaptations to physico-chemical stressors may directly affect the survival probability in divergent habitat types.
Quantifying uncertainty, variability and likelihood for ordinary differential equation models
(2010)
Background
In many applications, ordinary differential equation (ODE) models are subject to uncertainty or variability in initial conditions and parameters. Both, uncertainty and variability can be quantified in terms of a probability density function on the state and parameter space.
Results
The partial differential equation that describes the evolution of this probability density function has a form that is particularly amenable to application of the well-known method of characteristics. The value of the density at some point in time is directly accessible by the solution of the original ODE extended by a single extra dimension (for the value of the density). This leads to simple methods for studying uncertainty, variability and likelihood, with significant advantages over more traditional Monte Carlo and related approaches especially when studying regions with low probability.
Conclusions
While such approaches based on the method of characteristics are common practice in other disciplines, their advantages for the study of biological systems have so far remained unrecognized. Several examples illustrate performance and accuracy of the approach and its limitations.